Xubin Zeng

Interests

Teaching

Introduction to weather and climate, dynamic meteorology, boundary layer meteorology, climate observations and modeling

Research

Land-atmosphere-ocean interface processes, climate modeling, climate change, hydrometeorology, remote sensing, nonlinear dynamics, and big data analytics (via machine learning and AI)

Courses

Scholarly Contributions

Books

• Oleson, W., Lawrence, M., Bonan, B., Flanner, G., Kluzek, E., Lawrence, J., Levis, S., Swenson, C., Thornton, E., Dai, A., Decker, M., Dickinson, R. E., Feddema, J. J., Heald, L., Hoffman, F. M., Lamarque, J., Mahowald, N. M., Niu, G., Niu, G., , Qian, T., et al. (2010). Technical Description of version 4.0 of the Community Land Model (CLM). doi:10.5065/D6FB50WZ
• Oleson, K. W., Dai, Y., Bonan, B., Bosilovichm, M., Dickinson, R. E., Dirmeyer, P. A., Hoffman, F. M., Houser, P. R., Levis, S., Niu, G., Niu, G., Thornton, P. E., Vertenstein, M., Yang, Z., Yang, Z., & Zeng, X. (2004). Technical Description of the Community Land Model (CLM). doi:10.5065/D6N877R0

Chapters

• Huxman, T. E., Sibayan, M., Abramson, N., Bugaj, A., Barron-Gafford, G. A., Van Haren, J. L., Zeng, X., Chorover, J. D., Hunt, E., Neilson, J. W., Meira, A. A., Troch, P. A., Dontsova, K. M., Volkmann, T., Pangle, L., & Sengupta, A. (2017). Advancing understanding of hydrological and biogeochemical interactions in evolving landscapes through controlled experimentation and monitoring at the Landscape Evolution Observatory. In Terrestrial Ecosystem Research Infrastructures: Challenges, New Developments and Perspectives(pp 83-118). CRC Press.
• Volkmann, T. H., Sengupta, A., Pangle, L. A., Katerinadontsova, K., Barron-gafford, G. A., Barron-gafford, G. A., Harman, C. J., Niu, G. Y., Niu, G., Meredith, L., Meredith, L. K., Abramson, N., Neto, A. A., Yadiwang, Y., Adams, J., Breshears, D. D., Bugaj, A., Jonchorover, J., Cueva, A., , Delong, S. B., et al. (2017). Controlled experiments of hillslope co-evolution at the Biosphere 2 Landscape Evolution Observatory: toward prediction of coupled hydrological, biogeochemical, and ecological change. In Hydrology of Artificial and Controlled Experiments. IntechOpen. doi:10.5772/INTECHOPEN.72325
• Yang, Z., Dominguez, F., Gupta, H. V., Zeng, X., & Norman, L. (2017). Potential impacts of the continuing urbanization on regional climate: The developing Phoenix-Tucson "Sun Corridor".. In Water Bankruptcy In The Land Of Plenty: Steps towards a transatlantic and transdisciplinary assessment of water scarcity in Southern Arizona. CRC Press.
  More info

  Yang, Z., F. Dominguez, H. Gupta, X. Zeng, and L. Norman, 2017: Potential impacts of the continuing urbanization on regional climate: The developing Phoenix-Tucson "Sun Corridor". Chapter 11 (p. 179-193) of the book "Water Bankruptcy In The Land Of Plenty: Steps towards a transatlantic and transdisciplinary assessment of water scarcity in Southern Arizona" edited by F. Poupeau, H. Gupta, A. Serrat-Capdevilla, M.A. Sans-Fuentes, S. Harris, and L. G. Hayde, CRC Press, Boca Raton, FL, p. 437.
• Poupeau, F., Gupta, H. V., Sans-Fuentes, M. A., & Serrat-Capdevilla, A. (2016). Next Steps: Collaborative research and training towards transdisciplinarity. In Water Bankruptcy In The Land Of Plenty: Steps towards a transatlantic and transdisciplinary assessment of water scarcity in Southern Arizona. CRC Press.
  More info

  F Poupeau, Gupta HV, MA Sans-Fuentes & A Serrat-Capdevilla (2016 Invited), Next Steps: Collaborative research and training towards transdisciplinarity; Chapter 22 in: Water Bankruptcy In The Land Of Plenty: Steps towards a transatlantic and transdisciplinary assessment of water scarcity in Southern Arizona, Eds: Gupta HV, F Poupeau, MA Sans-Fuentes & A Serrat-Capdevilla, CRC Press.
• Yang, Z., Dominguez, F., Gupta, H. V., Zeng, X., & Norman, L. (2016). Potential Impacts of the developing Phoenix-Tucson ‘Sun’ Corridor on Regional Climate. In Water Bankruptcy In The Land Of Plenty: Steps towards a transatlantic and transdisciplinary assessment of water scarcity in Southern Arizona. CRC Press.
  More info

  Yang Z, F Dominguez, H Gupta, X Zeng and L Norman (2016 Invited) Potential Impacts of the developing Phoenix-Tucson ‘Sun’ Corridor on Regional Climate; Chapter 11 in: Water Bankruptcy In The Land Of Plenty: Steps towards a transatlantic and transdisciplinary assessment of water scarcity in Southern Arizona, Eds: Gupta HV, F Poupeau, MA Sans-Fuentes & A Serrat-Capdevilla, CRC Press.
• Niu, G., & Zeng, X. (2012). The Earth System Model, Modeling the land component of. In Encyclopedia of Sustainability Science and Technology. doi: 10.1007/978-1-4419-0851-3.
  More info

  R.A. Meyers, Ed.
• Claussen, M., Cox, P. M., Zeng, X., Viterbo, P., Beljaars, A., Betts, R., Bolle, H., Chase, T. N., & Koster, R. (2004). The Global Climate. In Vegetation, Water, Humans and the Climate. Springer-Verlag. doi:10.1007/978-3-642-18948-7_5
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  In this chapter, we present evidence that changes in landsurface, in particular those relating to vegetation-atmos-phere interaction, affect weather and climate at the global scale. We also show that without understanding vegetation dynamics we are unable to describe long-term climate variability, nor can we fully interpret palaeodimatic reconstructions or predict global weather properly. This chapter is organised as follows (see also Table A.1): In Sect. A.4.1, we present theoretical considerations. We show how vegetation interferes with the atmosphere and the other components of the climate system at the global scale, and we explore the consequences of the nonlinear character of atmosphere-vegetation dynamics. In Sect. A.4.2, we interpret palaeoclimatic and palaeobotanic reconstructions in the light of the theory being developed in Sect. A.4.1. In Sect. A.4.3, emphasis is given to the interaction of atmosphere-vegetation dynamics and the global carbon cycle. We mainly focus on numerical sensitivity experiments which highlight potential changes in the climate system under the condition of increased emissions of CO2. In Sect. A.4.4, we discuss the memory effects which soil moisture imposes on the global climate system. This memory effect becomes important where seasonal climate variability is concerned. In Sect. A.4.5, we present evidence that improved representation of atmosphere-vegetation interaction in a model of global weather forecast has substantially improved prediction skill.
• Zeng, X., & He, Y. (2001). Observational and modeling study on the relationship between sea surface temperature and evaporation over the tropical Pacific. In Dynamics of Atmospheric and Oceanic Circulation and Climate(pp 508-520). China Meteorological Press.
• Pielke, R., Dalu, G., Eastman, J., Vidale, P., & Zeng, X. (1998). Boundary layer processes and land surface interactions on the mesoscale. In Clear and Cloudy Boundary Layers(pp 155-176). Royal Netherlands Academy of Arts and Sciences.
  More info

  A. A. M. Holtslag and P. G. Duynkerke, Eds.
• Pielke, R., Nicholls, M., Nygaard, T., Walko, R., & Zeng, X. (1997). Several unresolved issues in numerical modeling of geophysical flows. In Numerical Methods in Atmospheric and Oceanic Modeling, The Andre J. Robert Memorial Volume(pp 557-581).
  More info

  C. A. Lin, R. Laprise, and H. Ritchie, Eds.
• Pielke, R., other coauthors, s., & Zeng, X. (1996). Use of mesoscale models for simulation of seasonal weather and climate change for the Rocky Mountain States. In GIS and Environmental Modeling: Progress and Research Issues(pp 99-103).
  More info

  M.F. Goodchild, Ed., GIS World
• Pielke, R., Eastman, J., Grasso, L., Knowles, J., Nicholls, M., Walko, R., & Zeng, X. (1995). Atmospheric Vortices. In Fluid Vortices(pp 617-650). Kluwer Academic Publishing.
  More info

  S.I. Green, Ed.

Journals/Publications

• Brunke, M. A., Pielke Sr, ,., & Zeng, X. (2023). Possible self-regulation of Northern Hemisphere mid-tropospheric temperatures and its connection to upper-level winds in reanalyses and Earth system models. Theoretical and Applied Climatology, 154(3), 1395--1409.
• Dmitrovic, S., Hair, J. W., Collister, B. L., Crosbie, E., Fenn, M. A., Ferrare, R. A., Harper, D. B., Hostetler, C. A., Hu, Y., Reagan, J. A., & others, . (2023). HSRL-2 Retrievals of Ocean Surface Wind Speeds. EGUsphere, 2023, 1--33.
• Galarneau Jr, ,. T., Zeng, X., Dixon, R. D., Ouyed, A., Su, H., & Cui, W. (2023). Tropical mesoscale convective system formation environments. Atmospheric Science Letters, 24(5), e1152.
• Hu, Y., Lu, X., Zeng, X., Gatebe, C., Yang, P., Weimer, C., Stamnes, S., Creary, G., Ashraf, A., Stamnes, K., & others, . (2023). Linking lidar multiple scattering profiles to snow depth and snow density: An analytical radiative transfer analysis and the implications for remote sensing of snow. Frontiers in Remote Sensing, 4, 1202234.
• Liu, S., Zeng, X., Dai, Y., Yuan, H., Wei, N., Wei, Z., Lu, X., Zhang, S., & Li, X. (2023). Scale-Dependent Estimability of Turbulent Flux in the Unstable Surface Layer for Land Surface Modeling. Journal of Advances in Modeling Earth Systems, 15(8), e2022MS003567.
• Ouyed, A., Smith, N., Zeng, X., Galarneau Jr, ,., Su, H., & Dixon, R. D. (2023). Global Three-Dimensional Water Vapor Feature-Tracking for Horizontal Winds Using Hyperspectral Infrared Sounder Data From Overlapped Tracks of Two Satellites. Geophysical Research Letters, 50(7), e2022GL101830.
• Painemal, D., Chellappan, S., Smith Jr, ,. W., Spangenberg, D., Park, J. M., Ackerman, A., Chen, J., Crosbie, E., Ferrare, R., Hair, J., & others, . (2023). Wintertime synoptic patterns of midlatitude boundary layer clouds over the western North Atlantic: Climatology and insights from in-situ ACTIVATE observations. Journal of Geophysical Research: Atmospheres, e2022JD037725.
• Scheftic, W. D., Zeng, X., & Brunke, M. A. (2023). Seasonal forecasting of precipitation, temperature, and snow mass over the western US by combining ensemble post-processing with empirical ocean-atmosphere teleconnections. Weather and Forecasting.
• Scott, W. (2023). Reflections and Thoughts on the Future of Science From AGU Hydrology Section Fellows. Perspectives of Earth and Space Scientists, 4(1), https--doi.
• Shen, B., Pielke Sr, ,. R., & Zeng, X. (2023). The 50th anniversary of the metaphorical butterfly effect since Lorenz (1972): Multistability, multiscale predictability, and sensitivity in numerical models.
• Shen, B., Pielke Sr, ,. R., Zeng, X., & Zeng, X. (2023). Lorenz’s View on the Predictability Limit of the Atmosphere. Encyclopedia, 3(3), 887--899.
• Sorooshian, A., Alexandrov, M. D., Bell, A. D., Bennett, R., Betito, G., Burton, S. P., Buzanowicz, M. E., Cairns, B., Chemyakin, E. V., Chen, G., & others, . (2023). Spatially-coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: The NASA ACTIVATE dataset. Earth System Science Data, 15(8), 3419--3472.
• Stamnes, K., Li, W., Stamnes, S., Hu, Y., Zhou, Y., Chen, N., Fan, Y., Hamre, B., Lu, X., Huang, Y., & others, . (2023). Laser light propagation in a turbid medium: solution including multiple scattering effects. The European Physical Journal D, 77(6), 110.
• Xue, Y., Diallo, I., Boone, A. A., Zhang, Y., Zeng, X., Lau, W. K., Neelin, J. D., Yao, T., Tang, Q. i., Sato, T., & others, . (2023). Remote effects of Tibetan Plateau spring land temperature on global subseasonal to seasonal precipitation prediction and comparison with effects of sea surface temperature: the GEWEX/LS4P Phase I experiment. Climate Dynamics, 1--26.
• Zeng, X., Scarino, A. J., Sorooshian, A., Dadashazar, H., Li, X., Wang, H., Chen, J., Endo, S., Kirschler, S., Voigt, C., Crosbie, E., Ziemba, L. D., Painemal, D., Cairns, B., Hair, J. W., Corral, A. F., Robinson, C., Chen, G., Ferrare, R. A., , Kleb, M. M., et al. (2023). Large-Eddy Simulations of Marine Boundary-Layer Clouds Associated with Cold-Air Outbreaks During the ACTIVATE Campaign. Part II: Aerosol–Meteorology–Cloud Interaction. Journal of the Atmospheric Sciences. doi:10.1175/jas-d-21-0324.1
• Zeng, X., Stephens, G., Polcher, J., van Oevelen, P., Poveda, G., Bosilovich, M., Ahn, M., Balsamo, G., Duan, Q., Hegerl, G., Jakob, C., Lamptey, B., Leung, R., Piles, M., Su, Z., Dirmeyer, P., Findell, K. L., Verhoef, A., Ek, M., , L’Ecuyer, T., et al. (2023). The First 30 Years of GEWEX. Bulletin of the American Meteorological Society, 104(1), E126-E157. doi:10.1175/bams-d-22-0061.1
• Brunke, M. A., Cutler, L., Urzua, R. D., Corral, A. F., Crosbie, E., Hair, J., Hostetler, C., Kirschler, S., Larson, V., Li, X., Ma, P., Minke, A., Moore, R., Robinson, C. E., Scarino, A. J., Schlosser, J., Shook, M., Sorooshian, A., Thornhill, K. L., , Voigt, C., et al. (2022). Aircraft Observations of Turbulence in Cloudy and Cloud-Free Boundary Layers Over the Western North Atlantic Ocean From ACTIVATE and Implications for the Earth System Model Evaluation and Development. Journal of Geophysical Research: Atmospheres, 127(19).
• Cutler, L., Brunke, M. A., & Zeng, X. (2022). Re-Evaluation of Low Cloud Amount Relationships With Lower-Tropospheric Stability and Estimated Inversion Strength. Geophysical Research Letters, 49(12).
• Lu, X., Hu, Y., Zeng, X., Stamnes, S. A., Neuman, T. A., Kurtz, N. T., Yang, Y., Zhai, P., Gao, M., Sun, W., Xu, K., Liu, Z., Omar, A. H., Baize, R. R., Rogers, L. J., Mitchell, B. O., Stamnes, K., Huang, Y., Chen, N., , Weimer, C., et al. (2022). Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements: Uncertainty Analyses. Frontiers in Remote Sensing, 3.
• Reeves Eyre, J. E., Zeng, X., Brunke, M. A., Zheng, X., Golaz, J., Van Roekel, L. P., Roberts, A. F., Wolfe, J. D., Lin, W., Bradley, A. M., Tang, Q., Maltrud, M. E., Forsyth, R. M., Zhang, C., Zhou, T., Zhang, K., Zender, C. S., Wu, M., Wang, H., , Turner, A. K., et al. (2022). The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation. Journal of Advances in Modeling Earth Systems, 14(12). doi:10.1029/2022ms003156
• Shen, B., Pielke, R. A., & Zeng, X. (2022). One Saddle Point and Two Types of Sensitivities within the Lorenz 1963 and 1969 Models. Atmosphere, 13(5), 753.
• Shen, B., Pielke, R. A., Zeng, X., Cui, J., Faghih-Naini, S., Paxson, W., & Atlas, R. (2022). Three Kinds of Butterfly Effects within Lorenz Models. Encyclopedia, 2(3), 1250--1259.
• Stamnes, K., Li, W., Stamnes, S., Hu, Y., Zhou, Y., Chen, N., Fan, Y., Hamre, B., Lu, X., Huang, Y., Weimer, C., Lee, J., Zeng, X., & Stamnes, J. (2022). A novel approach to solve forward/inverse problems in remote sensing applications. Frontiers in Remote Sensing, 3.
• Wan, H., Zhang, K., Rasch, P. J., Larson, V. E., Zeng, X., Zhang, S., & Dixon, R. (2022). CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM). Geoscientific Model Development, 15(8), 3205--3231.
• Wang, Y., Gupta, H. V., Zeng, X., & Niu, G. (2022). Exploring the Potential of Long Short-Term Memory Networks for Improving Understanding of Continental- and Regional-Scale Snowpack Dynamics. Water Resources Research, 58(3).
• Xue, Y., Diallo, I., Boone, A. A., Yao, T., Zhang, Y., Zeng, X., Neelin, J. D., Lau, W., Pan, Y., Liu, Y. e., Pan, X., Tang, Q. i., Oevelen, P. J., Sato, T., Koo, M., Materia, S., Shi, C., Yang, J., Ardilouze, C., , Lin, Z., et al. (2022). Spring Land Temperature in Tibetan Plateau and Global-Scale Summer Precipitation: Initialization and Improved Prediction. Bulletin of the American Meteorological Society, 103(12), E2756--E2767.
• Zeng, X., Liu, R., Liu, S., Huang, H., Dai, Y., Yuan, H., Wei, Z., Lu, X., Wei, N., Zhang, S., & Wei, J. (2022). The Effect of Surface Heating Heterogeneity on Boundary Layer Height and Its Dependence on Background Wind Speed. Journal of Geophysical Research: Atmospheres, 127(19). doi:10.1029/2022jd037168
• Zeng, X., Liu, S., Dai, Y., Yuan, H., Wei, N., Wei, Z., Lu, X., & Zhang, S. (2022). A Surface Flux Estimation Scheme Accounting for Large‐Eddy Effects for Land Surface Modeling. Geophysical Research Letters, 49(23). doi:10.1029/2022gl101754
• Zeng, X., Reeves Eyre, J., Hsu, C., DeMott, C. A., & Branson, M. D. (2022). Ocean Surface Flux Algorithm Effects on Tropical Indo‐Pacific Intraseasonal Precipitation. Geophysical Research Letters, 49(7). doi:10.1029/2021gl096968
• Zeng, X., Sengupta, A., Singh, B., DeFlorio, M. J., Raymond, C., Robertson, A. W., Waliser, D. E., & Jones, J. (2022). Advances in Subseasonal to Seasonal Prediction Relevant to Water Management in the Western United States. Bulletin of the American Meteorological Society, 103(10), E2168-E2175. doi:10.1175/bams-d-22-0146.1
• Zeng, X., Wang, Y., Xu, X., Xie, F., & Zhao, Y. (2022). Improving the Estimate of Summer Daytime Planetary Boundary Layer Height Over Land From GPS Radio Occultation Data. Geophysical Research Letters, 49(2). doi:10.1029/2021gl096304
• Zhang, X., Niu, G., & Zeng, X. (2022). The Control of Plant and Soil Hydraulics on the Interannual Variability of Plant Carbon Uptake Over the Central US. Journal of Geophysical Research: Atmospheres, 127(9).
• Zhang, X., Zeng, X., Niu, G., Neto, A. A., Jin, J., & Hawkins, C. P. (2022). The Compensatory CO ₂ Fertilization and Stomatal Closure Effects on Runoff Projection From 2016–2099 in the Western United States. Water Resources Research, 58(1). doi:10.1029/2021wr030046
• Dadashazar, H., Painemal, D., Alipanah, M., Brunke, M., Chellappan, S., Corral, A. F., Crosbie, E., Kirschler, S., Liu, H., Moore, R. H., Robinson, C., Scarino, A. J., Shook, M., Sinclair, K., Thornhill, K. L., Voigt, C., Wang, H., Winstead, E., Zeng, X., , Ziemba, L., et al. (2021). Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors. Atmospheric chemistry and physics, 21(13), 10499-10526.
• Ma, P., Harrop, B. E., Larson, V. E., Neale, R., Gettelman, A., Morrison, H., Wang, H., Zhang, K., Klein, S. A., Zelinka, M. D., & others, . (2021). Better calibration of cloud parameterizations and subgrid effects increases the fidelity of E3SM Atmosphere Model version 1. Geoscientific Model Development Discussions, 1--57.
• Ouyed, A., Zeng, X., Wu, L., Posselt, D., & Su, H. (2021). Two-Stage Artificial Intelligence Algorithm for Calculating Moisture-Tracking Atmospheric Motion Vectors. Journal of Applied Meteorology and Climatology, 60(12), 1671--1684.
• Reeves Eyre, J. E., Zeng, X., & Zhang, K. (2021). Ocean surface flux algorithm effects on Earth system model energy and water cycles. Frontiers in Marine Science.
• Saleska, S. R., Zeng, X., Albert, L. P., Restrepo‐Coupe, N., Longo, M., Baker, I., Levine, N. M., Mercado, L. M., da Araujo, A. C., Christoffersen, B. O., Costa, M. H., Fitzjarrald, D. R., Galbraith, D., Imbuzeiro, H., Malhi, Y., von Randow, C., & Moorcroft, P. (2021). Understanding water and energy fluxes in the Amazonia: Lessons from an observation‐model intercomparison. Global Change Biology, 27(9), 1802-1819. doi:10.1111/gcb.15555
• Shen, B., Pielke Sr, ,. R., Zeng, X., Baik, J., Faghih-Naini, S., Cui, J., & Atlas, R. (2021). Is Weather Chaotic?: Coexistence of Chaos and Order within a Generalized Lorenz Model. Bulletin of the American Meteorological Society, 102(1), E148--E158.
• Wan, H., Zhang, K., Rasch, P. J., Larson, V. E., Zeng, X., Zhang, S., & Dixon, R. (2021). CondiDiag1. 0: A flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM). Geoscientific Model Development Discussions, 1--38.
• Xue, Y., Yao, T., Boone, A. A., Diallo, I., Liu, Y. e., Zeng, X., Lau, W. K., Sugimoto, S., Tang, Q. i., Pan, X., & others, . (2021). Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): Organization and Experimental design. Geoscientific Model Development Discussions, 1--58.
• Zeng, X., & Reeves Eyre, J. E. (2021). The Amazon Water Cycle: Perspectives from Water Budget Closure and Ocean Salinity. Journal of Climate, 34(4), 1439-1451. doi:10.1175/jcli-d-20-0309.1
• Zeng, X., & Welty, J. (2021). Characteristics and Causes of Extreme Snowmelt over the Conterminous United States. Bulletin of the American Meteorological Society, 102(8), E1526-E1542. doi:10.1175/bams-d-20-0182.1
• Zeng, X., Arevalo, J., Welty, J., & Fan, Y. (2021). Implementation of Snowpack Treatment in the CPC Water Balance Model and Its Impact on Drought Assessment. Journal of Hydrometeorology. doi:10.1175/jhm-d-20-0201.1
• Zeng, X., Brunke, M. A., Painemal, D., Corral, A. F., Sorooshian, A., Chellappan, S., Afzali Gorooh, V., Ham, S., O'Neill, L., Smith, W. L., Tselioudis, G., Wang, H., & Zuidema, P. (2021). An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast—Part 2: Circulation, Boundary Layer, and Clouds. Journal of Geophysical Research: Atmospheres, 126(6). doi:10.1029/2020jd033423
• Zeng, X., Neelin, J. D., Tang, S., Xie, S., Guo, Z., Hong, S., Khouider, B., Klocke, D., Köhler, M., Koo, M., Krishna, P. M., Larson, V. E., Park, S., Vaillancourt, P. A., Wang, Y., Yang, J., Daleu, C. L., Homeyer, C. R., Jones, T. R., , Malap, N., et al. (2021). Long‐term single‐column model intercomparison of diurnal cycle of precipitation over midlatitude and tropical land. Quarterly Journal of the Royal Meteorological Society, 148(743), 641-669. doi:10.1002/qj.4222
• Zeng, X., Reeves, E., Dixon, R. D., & Arevalo, J. (2021). Quantifying the occurrence of record hot years through normalized warming trends. Geophysical Research Letters, 48(10), e2020GL091626.
• Zeng, X., Sorooshian, A., Brunke, M., Seethala, C., Zuidema, P., Edson, J., Chen, G., Li, X., Painemal, D., Robinson, C., Shingler, T., Shook, M., Thornhill, L., Tornow, F., Wang, H., & Ziemba, L. (2021). On Assessing ERA5 and MERRA2 Representations of Cold‐Air Outbreaks Across the Gulf Stream. Geophysical Research Letters, 48(19). doi:10.1029/2021gl094364
• Zeng, X., Welty, J., & Brunke, M. A. (2021). Attribution of Snowpack Errors to Simulated Temperature and Precipitation in E3SMv1 Over the Contiguous United States. Journal of Advances in Modeling Earth Systems, 13(10). doi:10.1029/2021ms002640
• Arevalo, J., Zeng, X., Durcik, M., Sibayan, M., Pangle, L., Abramson, N., Bugaj, A., Ng, W., Kim, M., Barron-Gafford, G., van, H. J., Niu, G., Adams, J., Ruiz, J., & Troch, P. A. (2020). Highly sampled measurements in a controlled atmosphere at the Biosphere 2 Landscape Evolution Observatory. SCIENTIFIC DATA, 7(1).
• Dadashazar, H., Crosbie, E., Majdi, M. S., Panahi, M., Moghaddam, M. A., Behrangi, A., Brunke, M., Zeng, X., Jonsson, H. H., & Sorooshian, A. (2020). Stratocumulus cloud clearings: statistics from satellites, reanalysis models, and airborne measurements. ATMOSPHERIC CHEMISTRY AND PHYSICS, 20(8), 4637-4665.
• Niu, G., Fang, Y., Chang, L., Jin, J., Yuan, H., & Zeng, X. (2020). Enhancing the Noah‐MP Ecosystem Response to Droughts With an Explicit Representation of Plant Water Storage Supplied by Dynamic Root Water Uptake. Journal of Advances in Modeling Earth Systems. doi:10.1029/2020MS002062
• Oveisgharan, S., Esteban-Fernandez, D., Waliser, D., Friedl, R., Nghiem, S., & Zeng, X. (2020). Evaluating the Preconditions of Two Remote Sensing SWE Retrieval Algorithms over the US. REMOTE SENSING, 12(12).
• Russell, J. L., Zeng, X., Atlas, R., Birk, R. J., Carr, F. H., Carrier, M. J., Cucurull, L., Hooke, W. H., Kalnay, E., Murtugudde, R., Posselt, D. J., Tyndall, D. P., Weller, R. A., & Zhang, F. (2020). Use of Observing System Simulation Experiments in the United States. Bulletin of the American Meteorological Society, 101(8), E1427-E1438. doi:10.1175/bams-d-19-0155.1
• Wang, Y., Zeng, X., Xu, X., Welty, J., Lenschow, D., Zhou, M., & Zhao, Y. (2020). Why Are There More Summer Afternoon Low Clouds Over the Tibetan Plateau Compared to Eastern China?. Geophysical Research Letters. doi:10.1029/2020GL089665
• Xian, G. Z., Loveland, T., Munson, S. M., Vogelmann, J. E., Zeng, X., & Homer, C. J. (2020). Climate sensitivity to decadal land cover and land use change across the conterminous United States. GLOBAL AND PLANETARY CHANGE, 192.
• Zeng, X., & Galarneau, T. J. (2020). The Hurricane Harvey (2017) Texas Rainstorm: Synoptic Analysis and Sensitivity to Soil Moisture. Monthly Weather Review, 148(6), 2479-2502. doi:10.1175/mwr-d-19-0308.1
• Zeng, X., Schlosser, J., McComiskey, A., Hossein Mardi, A., Sorooshian, A., Corral, A. F., Braun, R. A., Cairns, B., Crosbie, E., Ferrare, R., Hair, J., Kleb, M. M., Maring, H., Moore, R., Painemal, D., Scarino, A. J., Shingler, T., Shook, M., Wang, H., , Ziemba, L., et al. (2020). Atmospheric Research Over the Western North Atlantic Ocean Region and North American East Coast: A Review of Past Work and Challenges Ahead. Journal of Geophysical Research: Atmospheres, 125(6). doi:10.1029/2019jd031626
• Zeng, X., Waliser, D. E., Oveisgharan, S., Nghiem, S. V., Friedl, R. R., & Esteban-fernandez, D. (2020). Correction: Oveisgharan, S., et al. Evaluating the Preconditions of Two Remote Sensing SWE Retrieval Algorithms over the US, Remote Sensing 2020, 12, 2021. Remote Sensing, 12(16), 2592. doi:10.3390/rs12162592
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  The authors would like to add Radar to the title for more clarification [...]
• Zeng, X., Wan, H., Woodward, C. S., Zhang, S., Vogl, C. J., Stinis, P., Gardner, D. J., Rasch, P. J., Larson, V. E., & Singh, B. (2020). Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling. Journal of Advances in Modeling Earth Systems, 12(10). doi:10.1029/2019ms001982
• Zeng, X., Welty, J., Stillman, S., & Santanello, J. (2020). Increased Likelihood of Appreciable Afternoon Rainfall Over Wetter or Drier Soils Dependent Upon Atmospheric Dynamic Influence. Geophysical Research Letters, 47(11). doi:10.1029/2020gl087779
• Zhang, S., Zeng, X., Yan, H., Wan, H., Rasch, P. J., & Larson, V. E. (2020). Quantifying and attributing time step sensitivities in present-dayclimate simulations conducted with EAMv1. Geoscientific Model Development Discussions, 1-36. doi:10.5194/gmd-2020-330
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  Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1-degree horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of such changes include warming in the lower troposphere, cooling in the tropical and subtropical upper troposphere, as well as decreases of relative humidity throughout the troposphere accompanied by cloud fraction decreases. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; the model would require retuning to regain optimal climate fidelity in the absence of those truncation errors. A coarse-grained attribution of the time step sensitivities is carried out by separately shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the counter-intuitive finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection and stratiform cloud macro- and microphysics parameterizations but by the step sizes used outside the subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM has a substantial impact on the marine stratocumulus decks while the deep convection parameterization has a significant impact on trade cumulus. The step size of the cloud macro- and microphysics subcycles appears to have a primary impact on cloud fraction at most latitudes in the upper troposphere as well as in the mid-latitude near-surface layers. Impacts of step sizes used by the dynamical core and radiation appear to be relatively small. These results provide useful clues to help better understand the root causes of time step sensitivities in EAM. The experimentation strategy used here can also provide a pathway for other models to identify and reduce time integration errors.
• Balsamo, G., Agusti-Panareda, A., Albergel, C., Arduini, G., Beljaars, A., Bidlot, J., Blyth, E., Bousserez, N., Boussetta, S., Brown, A., Buizza, R., Buontempo, C., Chevallier, F., Choulga, M., Cloke, H., Cronin, M. F., Dahoui, M., De, R. P., Dirmeyer, P. A., , Drusch, M., et al. (2019). Observations for Advancing Global Earth Surface Modelling: A Review (vol 10, 2038, 2018). REMOTE SENSING, 11(8).
• Brunke, M. A., Ma, P., Eyre, J., Rasch, P. J., Sorooshian, A., & Zeng, X. (2019). Subtropical Marine Low Stratiform Cloud Deck Spatial Errors in the E3SMv1 Atmosphere Model. GEOPHYSICAL RESEARCH LETTERS, 46(21), 12598-12607.
• Sorooshian, A., Anderson, B., Bauer, S. E., Braun, R. A., Cairns, B., Crosbie, E., Dadashazar, H., Diskin, G., Ferrare, R., Flagan, R. C., Hair, J., Hostetler, C., Jonsson, H. H., Kleb, M. M., Liu, H., MacDonald, A. B., McComiskey, A., Moore, R., Painemal, D., , Russell, L. M., et al. (2019). Aerosol-Cloud-Meteorology Interaction Airborne Field Investigations: Using Lessons Learned from the US West Coast in the Design of ACTIVATE off the US East Coast. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 100(8), 1511-1528.
• Yang, Z., Dominguez, F., & Zeng, X. (2019). Large and local-scale features associated with heat waves in the United States in reanalysis products and the NARCCAP model ensemble. CLIMATE DYNAMICS, 52(3-4), 1883-1901.
• Yu, L., Yang, Q., Zhou, M., Zeng, X., Lenschow, D. H., Wang, X., & Han, B. o. (2019). The Intraseasonal and Interannual Variability of Arctic Temperature and Specific Humidity Inversions. ATMOSPHERE, 10(4).
• Zeng, X., & Davis, K. (2019). Seasonal Prediction of North Atlantic Accumulated Cyclone Energy and Major Hurricane Activity. Weather and Forecasting, 34(1), 221-232. doi:10.1175/waf-d-18-0125.1
• Zeng, X., Broxton, P., Wang, Y., Fang, Y., Behrangi, A., Barlage, M., & Niu, G. (2019). A Wet‐Bulb Temperature‐Based Rain‐Snow Partitioning Scheme Improves Snowpack Prediction Over the Drier Western United States. Geophysical Research Letters, 46(23), 13825-13835. doi:10.1029/2019gl085722
• Zeng, X., Liu, S., Dai, Y., & Shao, Y. (2019). Further Improvement of Surface Flux Estimation in the Unstable Surface Layer Based on Large‐Eddy Simulation Data. Journal of Geophysical Research: Atmospheres, 124(17-18), 9839-9854. doi:10.1029/2018jd030222
• Zeng, X., Perket, J., Pelletier, J. D., Gentine, P., Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C., Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., Kennedy, D., Kluzek, E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., , Riley, W. J., et al. (2019). The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty. Journal of Advances in Modeling Earth Systems, 11(12), 4245-4287. doi:10.1029/2018ms001583
• Zeng, X., Perket, J., Pelletier, J., Hazenberg, P., Brooks, P. D., Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W., Mackay, D. S., McDonnell, J. J., Milly, P. C., Sullivan, P. L., , Tague, C., et al. (2019). Hillslope Hydrology in Global Change Research and Earth System Modeling. Water Resources Research, 55(2), 1737-1772. doi:10.1029/2018wr023903
• Zeng, X., Reeves Eyre, J. E., Van Roekel, L., Brunke, M. A., & Golaz, J. (2019). Ocean Barrier Layers in the Energy Exascale Earth System Model. Geophysical Research Letters, 46(14), 8234-8243. doi:10.1029/2019gl083591
• Zheng, X., Reeves Eyre, J. E., Zeng, X., Brunke, M. A., Branstetter, M., Golaz, J., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q., Wolfe, J. D., Abeshu, G., Anantharaj, V., Asay‐Davis, X. S., Bader, D. C., Baldwin, S. A., Bisht, G., Bogenschutz, P. A., Brus, S. R., , Burrows, S. M., et al. (2019). The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution. Journal of Advances in Modeling Earth Systems, 11(7), 2089-2129. doi:10.1029/2018ms001603
• Balsamo, G., Coauthors, ., & Zeng, X. (2018). Satellite and in-situ observations for advancing global Earth surface modelling: a review. Remote Sens.. doi:10.3390/rs10122038
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  Balsamo, G., and coauthors, 2018: Satellite and in-situ observations for advancing global Earth surface modelling: a review, Remote Sens., 10(12), 2038; https://doi.org/10.3390/rs10122038.
• Brunke, M. A., Cassano, J. J., Dawson, N., DuVivier, A. K., Gutowski, Jr., W. J., Hamman, J., Maslowski, W., Nijssen, B., Renteria, J. C., Roberts, A., & Zeng, X. (2018). Evaluation of Atmosphere-Land-Ocean-Sea Ice Interface Processes in the Regional Arctic System Model Version 1.0 (RASM1.0). JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 11. doi:10.5194/gmd-11-4817-2018
• Fan, Y., Co-authors, ., & Zeng, X. (2018). Structures and Functions of Hillslope Hydrology with Relevance to Earth System Modeling: Syntheses and Testable Hypotheses. Water Resources Research. doi:doi:10.1029/2018WR023903
• Qi, J., Zhang, X., McCarty, G. W., Sadeghi, A. M., Cosh, M. H., Zeng, X., Gao, F., Daughtry, C., Huang, C., Lang, M. W., & Arnold, J. G. (2018). Assessing the performance of a physically-based soil moisture module integrated within the Soil and Water Assessment Tool. ENVIRONMENTAL MODELLING & SOFTWARE, 109, 329-341.
• Stillman, S., & Zeng, X. (2018). Evaluation of SMAP Soil Moisture Relative to Five Other Satellite Products Using the Climate Reference Network Measurements Over USA. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 56(11), 6296-6305.
• Wang, A., & Zeng, X. (2018). 10.3390/rs10122038. Atmospheric and Oceanic Science Letters. doi:10.1080/16742834.2017.1379865
• Welty, J., & Zeng, X. (2018). Does Soil Moisture Affect Warm Season Precipitation Over the Southern Great Plains?. GEOPHYSICAL RESEARCH LETTERS, 45(15), 7866-7873.
• Yang, Z., Dominguez, F., & Zeng, X. (2018). Large and Local Scale Features Associated with Heat Waves in the United States in MERRA-2 and the NARCCAP model Ensemble. Climate Dynamics. doi:10.1007/s00382-018-4414-x
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  Yang, Z., F. Dominguez, and X. Zeng, 2018: Large and Local Scale Features Associated with Heat Waves in the United States in MERRA-2 and the NARCCAP model Ensemble, Climate Dynamics, doi: 10.1007/s00382-018-4414-x.
• Zeng, X., Broxton, P., & Dawson, N. (2018). Evaluation of Remotely Sensed Snow Water Equivalent and Snow Cover Extent over the Contiguous United States. Journal of Hydrometeorology, 19(11), 1777-1791. doi:10.1175/jhm-d-18-0007.1
• Zeng, X., Broxton, P., & Dawson, N. (2018). Snowpack Change From 1982 to 2016 Over Conterminous United States. Geophysical Research Letters, 45(23), 7866-7873. doi:10.1029/2018gl079621
• Zhang, Y., Zeng, X., Singh, M. S., Shipway, B. J., Sandu, I., Rio, C., Pritchard, M. S., Morrison, H., Klocke, D., Hannah, W. M., & Bogenschutz, P. A. (2018). Future Community Efforts in Understanding and Modeling Atmospheric Processes. Bulletin of the American Meteorological Society, 99(9), ES159-ES162. doi:10.1175/bams-d-18-0139.1
• Bashir, F., Zeng, X., Gupta, H. V., & Hazenberg, P. (2017). A Hydro-meteorological Perspective on the Karakoram Anomaly using Unique Valley-based Synoptic Weather Observations. Geophysical Research Letters.
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  Bashir F, X Zeng, H Gupta and P Hazenberg (2017), A Hydro-meteorological Perspective on the Karakoram Anomaly using Unique Valley-based Synoptic Weather Observations, Geophysical Research Letters, Article ID: GRL56536, DOI: 10.1002/2017GL075284
• Dawson, N., Broxton, P., & Zeng, X. (2017). A New Snow Density Parameterization for Land Data Initialization. JOURNAL OF HYDROMETEOROLOGY, 18(1), 197-207.
• Eyre, J., & Zeng, X. (2017). Evaluation of Greenland near surface air temperature datasets. CRYOSPHERE, 11(4), 1591-1605.
• Gupta, H., Zeng, X., Yang, Z., Dominguez, F., Hu, H., & Yang, B. (2017). Impact of Irrigation over the California Central Valley on Regional Climate. Journal of Hydrometeorology, 18(5), 1341-1357. doi:10.1175/jhm-d-16-0158.1
• Hazenberg, P., Gupta, H., Zeng, X., & Bashir, F. (2017). A Hydrometeorological Perspective on the Karakoram Anomaly Using Unique Valley‐Based Synoptic Weather Observations. Geophysical Research Letters, 44(20). doi:10.1002/2017gl075284
• Restrepo-Coupe, N., Levine, N. M., Christoffersen, B. O., Albert, L. P., Wu, J., Costa, M. H., Galbraith, D., Imbuzeiro, H., Martins, G., da, A., Malhi, Y. S., Zeng, X., Moorcroft, P., & Saleska, S. R. (2017). Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison. GLOBAL CHANGE BIOLOGY, 23(1), 191-208.
• Yang, Z., Dominguez, F., Zeng, X., Hu, H., Gupta, H., & Yang, B. (2017). Impact of Irrigation over the California Central Valley on Regional Climate. JOURNAL OF HYDROMETEOROLOGY, 18(5), 1341-1357.
• Zeng, X., & Wang, A. (2017). Impacts of internal climate variability on meteorological drought changes in China. Atmospheric and Oceanic Science Letters, 11(1), 78-85. doi:10.1080/16742834.2017.1379865
• Zeng, X., Broxton, P. D., & Dawson, N. (2017). The Impact of a Low Bias in Snow Water Equivalent Initialization on CFS Seasonal Forecasts. Journal of Climate, 30(21), 8657-8671. doi:10.1175/jcli-d-17-0072.1
• Zeng, X., Brunke, M., Cassano, J. J., DuVivier, A., Roberts, A., Hughes, M., Seefeldt, M., Craig, A., Fisel, B., Gutowski, W., Hamman, J., Higgins, M., Maslowski, W., Nijssen, B., & Osinski, R. (2017). Development of the Regional Arctic System Model (RASM): Near-Surface Atmospheric Climate Sensitivity. Journal of Climate, 30(15), 5729-5753. doi:10.1175/jcli-d-15-0775.1
• Zeng, X., Brunke, M., Wang, Z., Dadashazar, H., Crosbie, E., Jonsson, H., Woods, R. K., Flagan, R. C., Seinfeld, J. H., & Sorooshian, A. (2017). Relationships between giant sea salt particles and clouds inferred from aircraft physicochemical data. Journal of Geophysical Research: Atmospheres, 122(6), 3421-3434. doi:10.1002/2016jd026019
• van, H. J., Dontsova, K., Barron-Gafford, G. A., Troch, P. A., Chorover, J., Delong, S. B., Breshears, D. D., Huxman, T. E., Pelletier, J. D., Saleska, S. R., Zeng, X., & Ruiz, J. (2017). CO2 diffusion into pore spaces limits weathering rate of an experimental basalt landscape. GEOLOGY, 45(3), 203-206.
• Broxton, P. D., Zeng, X., & Dawson, N. (2016). Why Do Global Reanalyses and Land Data Assimilation Products Underestimate Snow Water Equivalent?. JOURNAL OF HYDROMETEOROLOGY, 17(11), 2743-2761.
• Hamman, J., Nijssen, B., Brunke, M., Cassano, J., Craig, A., DuVivier, A., Hughes, M., Lettenmaier, D. P., Maslowski, W., Osinski, R., Roberts, A., & Zeng, X. (2016). Land Surface Climate in the Regional Arctic System Model. JOURNAL OF CLIMATE, 29(18), 6543-6562.
• Hazenberg, P., Broxton, P., Gochis, D., Niu, G. -., Pangle, L. A., Pelletier, J. D., Troch, P. A., & Zeng, X. (2016). Testing the hybrid-3-D hillslope hydrological model in a controlled environment. WATER RESOURCES RESEARCH, 52(2), 1089-1107.
• Lytle, W., & Zeng, X. (2016). Coupled Evaluation of Below-and Aboveground Energy and Water Cycle Variables from Reanalysis Products over Five Flux Tower Sites in the United States. JOURNAL OF HYDROMETEOROLOGY, 17(7), 2105-2119.
• Sakaguchi, K., Zeng, X., Leung, R. B., & Shao, P. (2016). Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4). Environ. Res. Lett., 11. doi:10.1088/1748-9326/aa51d9
• Sengupta, A., Wang, Y., Meira, A. A., Matos, K., Dontsova, K. M., Root, R., Neilson, J. W., Chorover, J. D., Maier, R. M., & Troch, P. A. (2016). Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations. JoVE, e54536. doi:10.3791/54536
• Stillman, S., Zeng, X., & Bosilovich, M. G. (2016). Evaluation of 22 Precipitation and 23 Soil Moisture Products over a Semiarid Area in Southeastern Arizona. JOURNAL OF HYDROMETEOROLOGY, 17(1), 211-230.
• Wang, A., Zeng, X., & Guo, D. (2016). Estimates of Global Surface Hydrology and Heat Fluxes from the Community Land Model (CLM4.5) with Four Atmospheric Forcing Datasets. JOURNAL OF HYDROMETEOROLOGY, 17(9), 2493-2510.
• Williams, Z., Troch, P. A., Zeng, X., Hazenberg, P., Pelletier, J. D., Broxton, P. D., Niu, G., Brunke, M. A., & Gochis, D. (2016). A gridded global data set of soil, intact regolith, and sedimentary deposit thicknesses for regional and global land surface modeling. Journal of Advances in Modeling Earth Systems, 8(1), 41-65. doi:10.1002/2015ms000526
• Yang, Z., Dominguez, F., Gupta, H., Zeng, X., & Norman, L. (2016). Urban Effects on Regional Climate: A Case Study in the Phoenix and Tucson "Sun Corridor''. EARTH INTERACTIONS, 20.
• Zeng, X., & Geil, K. (2016). Global warming projection in the 21st century based on an observational data-driven model: Global Warming Projection. Geophysical Research Letters, 43(20), 10,947-10,954. doi:10.1002/2016gl071035
• Zeng, X., & Stillman, S. (2016). Development of a 0.5° global monthly raining day product from 1901 to 2010. Geophysical Research Letters, 43(18), 9704-9711. doi:10.1002/2016gl070244
• Zeng, X., Ackerman, S., Ferraro, R. D., Lee, T. J., Murray, J. J., Pawson, S., Reynolds, C., & Teixeira, J. (2016). Challenges and opportunities in NASA weather research. Bull. Amer. Meteor. Soc, 97, ES137-140. doi:10.1175/BAMS-D-15-00195
• Zeng, X., Broxton, P. D., & Dawson, N. (2016). Linking snowfall and snow accumulation to generate spatial maps of SWE and snow depth. Earth and Space Science, 3(6), 246-256. doi:10.1002/2016ea000174
• Zeng, X., Brunke, M., Sorooshian, A., Wang, Z., Crosbie, E., Chuang, P. Y., Craven, J. S., Coggon, M. M., Jonsson, H., Woods, R. K., Flagan, R. C., & Seinfeld, J. H. (2016). Stratocumulus Cloud Clearings and Notable Thermodynamic and Aerosol Contrasts across the Clear–Cloudy Interface. Journal of the Atmospheric Sciences, 73(3), 1083-1099. doi:10.1175/jas-d-15-0137.1
• Zeng, X., Dawson, N., Broxton, P., Leuthold, M., Barlage, M., & Holbrook, P. (2016). An Evaluation of Snow Initializations in NCEP Global and Regional Forecasting Models. Journal of Hydrometeorology, 17(6), 1885-1901. doi:10.1175/jhm-d-15-0227.1
• Zeng, X., Gupta, H., Yang, Z., Dominguez, F., & Norman, L. (2016). Urban Effects on Regional Climate: A Case Study in the Phoenix and Tucson “Sun Corridor”. Earth Interactions, 20(20), 1-25. doi:10.1175/ei-d-15-0027.1
• Zeng, X., Troch, P. A., Hazenberg, P., Pelletier, J., Brunke, M. A., Broxton, P., Gochis, D., Lawrence, D. M., Leung, L. R., & Niu, G. (2016). Implementing and Evaluating Variable Soil Thickness in the Community Land Model, Version 4.5 (CLM4.5). Journal of Climate, 29(9), 3441-3461. doi:10.1175/jcli-d-15-0307.1
• Zeng, X., Troch, P. A., Pelletier, J. D., Hazenberg, P., Broxton, P., Gochis, D., Niu, G., & Pangle, L. A. (2016). Testing the hybrid-3-D hillslope hydrological model in a controlled environment: CONTROLLED TESTING OF THE h3D HILLSLOPE MODEL. Water Resources Research, 52(2), 1089-1107. doi:10.1002/2015wr018106
• Brunke, M., Stegall, S., & Zeng, X. (2015). A climatology of tropospheric humidity inversions in five reanalyses. Atmos. Res, 153, 165-187. doi:10.1016/j.atmosres.2014.08.005
• Geil, K. L., & Zeng, X. (2015). Quantitative characterization of spurious numerical oscillations in 48 CMIP5 models. GEOPHYSICAL RESEARCH LETTERS, 42(12), 5066-5073.
• Pangle, L. A., Delong, S. B., Abramson, N., Adams, J., Barron-Gafford, G. A., Breshears, D. D., Brooks, P. D., Chorover, J. D., Dietrich, W. E., Dontsova, K. M., Durcik, M., Espleta, J., Ferre, P. A., Ferriere, R. H., Henderson, W., Hunt, E. A., Huxman, T. E., Millar, D., Murphy, B., , Niu, G., et al. (2015). The Landscape Evolution Observatory: A large-scale controllable infrastructure to study Earth-surface processes.. Geomorphology, 244, 190-203. doi:10.1016/j.geomorph.2015.01.020
• Ritchie, E. A., Zeng, X., & Davis, K. (2015). A New Statistical Model for Predicting Seasonal North Atlantic Hurricane Activity. Weather and Forecasting, 30(3), 730-741. doi:10.1175/waf-d-14-00156.1
• Zeng, X., & Geil, K. L. (2015). Quantitative characterization of spurious numerical oscillations in 48 CMIP5 models. Geophysical Research Letters, 42(12), 5066-5073. doi:10.1002/2015gl063931
• Zeng, X., & Wang, A. (2015). Global hourly land surface air temperature datasets: inter‐comparison and climate change. International Journal of Climatology, 35(13), 3959-3968. doi:10.1002/joc.4257
• Zeng, X., Swenson, S. C., Shen, C., Maxwell, R. M., Mackay, D. S., Leung, L. R., Lawrence, D. M., Kumar, M., Hooper, R. P., Gochis, D. J., Fan, Y., Clark, M. P., Bolster, D., & Adam, J. C. (2015). Improving the representation of hydrologic processes in Earth System Models. Water Resources Research, 51(8), 5929-5956. doi:10.1002/2015wr017096
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  Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale models, such as the land components of Earth System Models (ESMs), do not yet represent the terrestrial water cycle in a fully integrated manner or resolve the finer-scale processes that can dominate large-scale water budgets. This paper reviews the current representation of hydrologic processes in ESMs and identifies the key opportunities for improvement. This review suggests that (1) the development of ESMs has not kept pace with modeling advances in hydrology, both through neglecting key processes (e.g., groundwater) and neglecting key aspects of spatial variability and hydrologic connectivity; and (2) many modeling advances in hydrology can readily be incorporated into ESMs and substantially improve predictions of the water cycle. Accelerating modeling advances in ESMs requires comprehensive hydrologic benchmarking activities, in order to systematically evaluate competing modeling alternatives, understand model weaknesses, and prioritize model development needs. This demands stronger collaboration, both through greater engagement of hydrologists in ESM development and through more detailed evaluation of ESM processes in research watersheds. Advances in themore » representation of hydrologic process in ESMs can substantially improve energy, carbon and nutrient cycle prediction capabilities through the fundamental role the water cycle plays in regulating these cycles.« less
• Zeng, X., Troch, P. A., Pelletier, J. D., Hazenberg, P., Fang, Y., Broxton, P., Gochis, D., & Niu, G. (2015). A hybrid‐3D hillslope hydrological model for use in E arth system models. Water Resources Research, 51(10), 8218-8239. doi:10.1002/2014wr016842
• Broxton, P. D., Zeng, X., Scheftic, W., & Troch, P. A. (2014). A MODIS-Based Global 1-km Maximum Green Vegetation Fraction Dataset. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 53(8), 1996-2004.
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  Global land-cover data are widely used in regional and global models because land cover influences land atmosphere exchanges of water, energy, momentum, and carbon. Many models use data of maximum green vegetation fraction (MGVF) to describe vegetation abundance. MGVF products have been created in the past using different methods, but their validation with ground sites is difficult. Furthermore, uncertainty is introduced because many products use a single year of satellite data. In this study, a global 1-km MGVF product is developed on the basis of a "climatology" of data of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index and land-cover type, which removes biases associated with unusual greenness and inaccurate land-cover classification for individual years. MGVF shows maximum annual variability from 2001 to 2012 for intermediate values of average MGVF, and the standard deviation of MGVF normalized by its mean value decreases nearly monotonically as MGVF increases. In addition, there are substantial differences between this climatology and MGVF data from the MODIS Continuous Fields (CF) Collection 3, which is currently used in the Community Land Model. Although the CF data only use 2001 MODIS data, many of these differences cannot be explained by usage of different years of data. In particular, MGVF as based on CF data is usually higher than that based on the MODIS climatology from this paper. It is difficult to judge which product is more realistic because of a lack of ground truth, but this new MGVF product is more consistent than the CF data with the MODIS leaf area index product (which is also used to describe vegetation abundance in models).
• Brunke, M. A., Stegall, S. T., & Zeng, X. (2014). A climatology of tropospheric humidity inversions in five reanalyses. ATMOSPHERIC RESEARCH, 153, 165-187.
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  Specific humidity is generally thought to decrease with height in the troposphere. However, here we document the existence of specific humidity inversions in five reanalyses: the National Centers for Environmental Prediction (NCEP) second reanalysis (NCEP-2), the European Centre for Medium-Range Forecasts (ECMWF) 40-year reanalysis (ERA-40), the Modem Era Retrospective Analysis for Research Applications (MERRA), NCEP's Climate Forecast System Reanalysis (CFSR), and the ECMWF interim reanalysis (ERA-Interim). These inversions are most frequent in the polar regions. Inversions do occur elsewhere, most notably over the subtropical stratus regions, but are less frequent and likely overproduced depending on the location. Polar inversions are the most persistent in winter and the strongest (as defined by the humidity difference divided by the pressure-difference across the inversion) in summer or autumn with low bases (at pressures > 900 hPa). Winter humidity inversions are lower, being near-surface, due to the persistence of low-level temperature inversions associated with these humidity inversions, while summer humidity inversions tend to be located near cloud top providing moisture to prevent the melt season stratus from evaporating. The most important contributions to affect humidity inversions in MERRA are dynamics, turbulence, and moist physics. However, local advection may not play as much of a role as regional humidity convergence. The subtropical stratus inversions are as thick as polar humidity inversions but with higher bases generally at pressures
• Chorover, J. D., Gavaert, A., Tueling, A. J., Uijlenhoet, R., DeLong, S. B., Huxman, T. E., Pangle, L., Brashears, D. D., Pelletier, J. D., Saleska, S. R., Zeng, X., & Troch, P. A. (2014). Hillslope-scale experiment demonstrates the role of convergence during two-step saturation. Hydrol. Earth Syst. Sci., 18, 1-12.
• Christoffersen, B. O., Restrepo-Coupe, N., Arain, M. A., Baker, I. T., Cestaro, B. P., Ciais, P., Fisher, J. B., Galbraith, D., Guan, X., Gulden, L., van den Hurk, B., Ichii, K., Imbuzeiro, H., Jain, A., Levine, N., Miguez-Machor, G., Poulter, B., Roberti, D. R., Sakaguchi, K., , Sahoo, A., et al. (2014). Mechanisms of water supply and vegetation demand govern the seasonality and magnitude of evapotranspiration in Amazonia and Cerrado. AGRICULTURAL AND FOREST METEOROLOGY, 191, 33-50.
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  Evapotranspiration (E) in the Amazon connects forest function and regional climate via its role in precipitation recycling However, the mechanisms regulating water supply to vegetation and its demand for water remain poorly understood, especially during periods of seasonal water deficits In this study, we address two main questions: First, how do mechanisms of water supply (indicated by rooting depth and groundwater) and vegetation water demand (indicated by stomatal conductance and intrinsic water use efficiency) control evapotranspiration (E) along broad gradients of climate and vegetation from equatorial Amazonia to Cerrado, and second, how do these inferred mechanisms of supply and demand compare to those employed by a suite of ecosystem models? We used a network of eddy covariance towers in Brazil coupled with ancillary measurements to address these questions With respect to the magnitude and seasonality of E, models have much improved in equatorial tropical forests by eliminating most dry season water limitation, diverge in performance in transitional forests where seasonal water deficits are greater, and mostly capture the observed seasonal depressions in E at Cerrado However, many models depended universally on either deep roots or groundwater to mitigate dry season water deficits, the relative importance of which we found does not vary as a simple function of climate or vegetation In addition, canopy stomatal conductance (g's) regulates dry season vegetation demand for water at all except the wettest sites even as the seasonal cycle of E follows that of net radiation In contrast, some models simulated no seasonality in gs, even while matching the observed seasonal cycle of E. We suggest that canopy dynamics mediated by leaf phenology may play a significant role in such seasonality, a process poorly represented in models Model bias in gs and E, in turn, was related to biases arising from the simulated light response (gross primary productivity, GPP) or the intringic water use efficiency of photosynthesis (iWUE). We identified deficiencies in models which would not otherwise be apparent based on a simple comparison of simulated and observed rates of E. While some deficiencies can be remedied by parameter tuning, in most models they highlight the need for continued process development of belowground hydrology and in particular, the biological processes of root dynamics and leaf phenology, which via their controls on E, mediate vegetation-climate feedbacks in the tropics. (C) 2014 Elsevier B.V. All rights reserved.
• Cummins, K., Shuttleworth, W. J., Zeng, X., Stillman, S., Ninneman, J., Franz, T., & Scott, R. L. (2014). Summer Soil Moisture Spatiotemporal Variability in Southeastern Arizona. Journal of Hydrometeorology, 15(4), 1473-1485. doi:10.1175/jhm-d-13-0173.1
• Niu, G., Troch, P. A., Paniconi, C., Scott, R. L., Durcik, M., Zeng, X., Huxman, T., Goodrich, D., & Pelletier, J. (2014). An integrated modelling framework of catchment- scale ecohydrological processes: 2. The role of water subsidy by overland flow on vegetation dynamics in a semi- arid catchment. ECOHYDROLOGY, 7(2), 815-827.
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  In water-limited regions, surface water and carbon fluxes are strongly controlled by soil water availability, which may be highly variable at very small spatial scales (e.g. metres) because of variations in terrain, soils, and vegetation conditions and to processes of water redistribution along hillslopes. This second of a two-part paper first evaluates the performance of a newly developed ecohydrological model over a small semi-arid experimental catchment (792ha) in southeastern Arizona. Secondly, it investigates the effects of soil properties on water subsidy resulting from lateral overland flow re-infiltration and on overall ecohydrological response. With optimized parameters, the model shows a higher ability to simulate surface energy and water fluxes than CO2 fluxes at all temporal scales. The model simulates observed CO2 fluxes fairly well at diurnal scales during the main growing seasons and the interannual variability of these fluxes in response to soil moisture variations from drought years to wet years. However, the model reproduces less well carbon assimilation in spring and positive CO2 flux pulses following early monsoon rain events, suggesting a need for further development of the model's representations of multiple plant species and soil carbon decomposition. The model simulates soil moisture at 5cm much better than at 15cm mainly because of heterogeneous soil properties. Through five numerical experiments with varying saturated hydraulic conductivity values, it is revealed that the discharge at the outlet of this semi-arid catchment is essentially attributed to lateral overland flow that is generated mainly by infiltration-excess runoff. Subsurface flow plays a minor role in this semi-arid catchment with a very deep groundwater table (>100m). The model produces wetter soils in lowland areas along stream rills and channels through re-infiltration of lateral overland flow. This water subsidy provides plants with favourable conditions to produce more leaves, CO2, and ET fluxes in lowland areas. Re-infiltration of overland flow over complex terrain may play a role in buffering climatic impacts in a warming climate with fewer but more intense rainfall events in the Southwestern United States. Copyright (c) 2013 John Wiley & Sons, Ltd.
• Niu, Y., Pasetto, D., Scudeler, C., Paniconi, C., Putti, M., Troch, P. A., DeLong, S., Dontsova, K. M., Pangle, L., Breshears, D. D., Chorover, J. D., Huxman, T. E., Pelletier, J. D., Saleska, S. R., & Zeng, X. (2014). Incipient subsurface heterogeneity and its effect on overland flow generation -- insight from a modeling study of the first experiment at the Biosphere 2 Landscape Evolution Observatory. Hydrol. Earth Syst. Sci., 18, 1873-1883.
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• Rosolem, R., Hoar, T., Arellano, A., Anderson, J. L., Shuttleworth, W. J., Zeng, X., & Franz, T. E. (2014). Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale. HYDROLOGY AND EARTH SYSTEM SCIENCES, 18(11), 4363-4379.
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  Above-ground cosmic-ray neutron measurements provide an opportunity to infer soil moisture at the sub-kilometer scale. Initial efforts to assimilate those measurements have shown promise. This study expands such analysis by investigating (1) how the information from aboveground cosmic-ray neutrons can constrain the soil moisture at distinct depths simulated by a land surface model, and (2) how changes in data availability (in terms of retrieval frequency) impact the dynamics of simulated soil moisture profiles. We employ ensemble data assimilation techniques in a "nearly-identical twin" experiment applied at semi-arid shrubland, rainfed agricultural field, and mixed forest biomes in the USA. The performance of the Noah land surface model is compared with and without assimilation of observations at hourly intervals, as well as every 2 days. Synthetic observations of aboveground cosmic-ray neutrons better constrain the soil moisture simulated by Noah in root-zone soil layers (0-100 cm), despite the limited measurement depth of the sensor (estimated to be 12-20 cm). The ability of Noah to reproduce a "true" soil moisture profile is remarkably good, regardless of the frequency of observations at the semi-arid site. However, soil moisture profiles are better constrained when assimilating synthetic cosmic-ray neutron observations hourly rather than every 2 days at the cropland and mixed forest sites. This indicates potential benefits for hydrometeorological modeling when soil moisture measurements are available at a relatively high frequency. Moreover, differences in summertime meteorological forcing between the semi-arid site and the other two sites may indicate a possible control-ling factor to soil moisture dynamics in addition to differences in soil and vegetation properties.
• Scheftic, W., Zeng, X., Broxton, P., & Brunke, M. (2014). Intercomparison of seven NDVI products over the United States and Mexico. Remote Sensing, 6(2), 1057-1084.
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  Abstract: Satellites have provided large-scale monitoring of vegetation for over three decades, and several satellite-based Normalized Difference Vegetation Index (NDVI) datasets have been produced. Here we intercompare four long-term NDVI datasets based largely on the AVHRR sensor (NDVIg, NDVI3g, STAR, VIP) and three datasets based on newer sensors (SPOT, Terra, Aqua) and evaluate the effectiveness of homogenizing the datasets using the green vegetation fraction (GVF) and the impact it has on phenology trends. Results show that all NDVI datasets are highly correlated with each other. However, there are significant differences in the regression slopes that vary spatially and temporally. There is a general trend towards higher maximum annual NDVI over much of the temperate forests of the US and a longer greening period due mostly to a delayed end of the season. These trends are less well-defined over rainfall dependent ecosystems in Mexico and the southwest US Compared with the NDVI datasets, the derived GVF datasets show more one-to-one relationships, have reduced interannual variation, preserve their relationships better over the entire time period and are characterized by weaker trends. Finally, weak agreement between the trends in the datasets stresses the importance of using multiple datasets to evaluate changes in vegetation and its phenology. © 2014 by the authors; licensee MDPI, Basel, Switzerland.
• Stillman, S., Ninneman, J., Zeng, X., Franz, T. E., Scott, R. L., Shuttleworth, W. J., & Cummins, K. (2014). Summer Soil Moisture Spatiotemporal Variability in Southeastern Arizona. JOURNAL OF HYDROMETEOROLOGY, 15(4), 1473-1485.
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  Soil moisture is important for many applications, but its measurements are lacking globally and even regionally. The Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona has measured near-surface 5-cm soil moisture with 19 in situ probes since 2002 within its 150 km(2) area. Using various criteria to identify erroneous data, it is found that in any given period from 1 July to 30 September from 2002 to 2011, 13-17 of these probes were producing reasonable data, and this is sufficient to estimate area-averaged seasonal soil moisture. A soil water balance model is then developed using rainfall as its only input to spatially extrapolate soil moisture estimates to the 88 rain gauges located within the watershed and to extend the measurement period to 56 years. The model is calibrated from 2002 to 2011 so that the daily in situ and modeled soil moisture time series have a high average correlation of 0.89 and a root-mean-square deviation of 0.032 m(3) m(-3). By interpolating modeled soil moisture from the 88 rain gauges to a 100-m gridded domain over WGEW, it is found that spatial variability often increases when 88 (rather than 13-17) estimates are taken. While no trend in the spatial average surface soil moisture is found, large variability in the spatial average soil moisture from 1 July to 30 September is observed from year to year, ranging from 0.05 to 0.09 m(3) m(-3). In addition to spatiotemporal analysis of WGEW, this gridded soil moisture product from 1956 to 2011 can be used for validation of satellite-based and reanalysis products and land surface models.
• Troch, P. A., Zeng, X., Broxton, P. D., & Sulla-Menashe, D. (2014). A Global Land Cover Climatology Using MODIS Data. Journal of Applied Meteorology and Climatology, 53(6), 1593-1605. doi:10.1175/jamc-d-13-0270.1
• Yu, Y., Xie, Z., & Zeng, X. (2014). Impacts of modified Richards equation on RegCM4 regional climate modeling over East Asia. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 119(22), 12642-12659.
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  To remove the deficiency of the numerical solution of the mass conservation-based Richards equation for soil moisture in a regional climate model (RegCM4 with its land surface component Community Land Model 3.5 (CLM3.5)), a revised numerical algorithm that is used in CLM4.5 is implemented into CLM3.5. Compared with in situ measurements, the modified numerical method improves the ground water table depth simulations in RegCM4. It also improves the temporal and spatial variability of soil moisture to some extent. Its impact on simulated summer precipitation is mixed, with improvements over three subregions in China but with increased errors in three other subregions. The impact on the simulated summer temperature is relatively small (with the mean biases changed by less than 10% over most subregions). The evapotranspiration differences between modified and control land-atmosphere coupled simulations are enhanced over the northwest subregion and Tibetan Plateau compared to offline simulations due to land surface feedbacks to the atmosphere (in coupled simulations). Similarly the soil moisture differences in coupled simulations are geographically different from those in offline simulations over the eastern monsoon area. The summer precipitation differences between modified and control coupled simulations are found to be explained by the differences of both surface evapotranspiration and large-scale water vapor flux convergence which have opposite signs over the northwest subregion and Tibetan Plateau but have the same signs over other subregions.
• Zeng, X., & Shao, P. (2014). Differences in carbon cycle and temperature projections from emission- and concentration-driven earth system model simulations. Earth System Dynamics Discussions, 5(2), 991-1012. doi:10.5194/esdd-5-991-2014
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  Abstract. The influence of prognostic and prescribed atmospheric CO2 concentrations ([CO2]) on the carbon uptake and temperature is investigated using all eight Earth System Models (ESMs) with relevant output variables from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Under the RCP8.5 scenario, the projected [CO2] differences in 2100 vary from −19.7 to +207.3 ppm in emission-driven ESMs. Incorporation of the interactive concentrations also increases the range of global warming, computed as the 20 year average difference between 2081–2100 and 1850–1869/1861–1880, by 49% from 2.36 K (i.e. ranging from 3.11 to 5.47 K) in the concentration-driven simulations to 3.51 K in the emission-driven simulations. The observed seasonal amplitude of global [CO2] from 1980–2011 is about 1.2–5.3 times as large as those from the eight emission-driven ESMs, while the [CO2] seasonality is simply neglected in concentration-driven ESMs, suggesting the urgent need of ESM improvements in this area. The temperature-concentration feedback parameter α is more sensitive to [CO2] (e.g. during 1980–2005 versus 2075–2100) than how [CO2] is handled (i.e. prognostic versus prescribed). This sensitivity can be substantially reduced by using a more appropriate parameter α' computed from the linear regression of temperature change versus that of the logarithm of [CO2]. However, the inter-model relative variations of both α and α' remain large, suggesting the need of more detailed studies to understand and hopefully reduce these discrepancies.
• Zeng, X., & Wang, A. (2014). Range of monthly mean hourly land surface air temperature diurnal cycle over high northern latitudes. Journal of Geophysical Research, 119(10), 5836-5844. doi:10.1002/2014jd021602
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  Daily maximum and minimum temperatures over global land are fundamental climate variables, and their difference represents the diurnal temperature range (DTR). While the differences between the monthly averaged DTR (MDTR) and the range of monthly averaged hourly temperature diurnal cycle (RMDT) are easy to understand qualitatively, their differences have not been quantified over global land areas. Based on our newly developed in situ data (Climatic Research Unit) reanalysis (Modern-Era Retrospective analysis for Research and Applications) merged hourly temperature data from 1979 to 2009, RMDT in January is found to be much smaller than that in July over high northern latitudes, as it is much more affected by the diurnal radiative forcing than by the horizontal advection of temperature. In contrast, MDTR in January is comparable to that in July over high northern latitudes, but it is much larger than January RMDT, as it primarily reflects the movement of lower frequency synoptic weather systems. The area-averaged RMDT trends north of 40°N are near zero in November, December, and January, while the trends of MDTR are negative. These results suggest the need to use both the traditional MDTR and RMDT suggested here in future observational and modeling studies. Furthermore, MDTR and its trend are more sensitive to the starting hour of a 24 h day used in the calculations than those for RMDT, and this factor also needs to be considered in model evaluations using observational data.
• Zeng, X., Shuttleworth, W. J., Rosolem, R., Hoar, T. J., Franz, T. E., Arellano, A. F., & Anderson, J. L. (2014). Assimilation of near-surface cosmic-ray neutrons improves summertime soil moisture profile estimates at three distinct biomes in the USA. Hydrology and Earth System Sciences Discussions, 11(5), 5515-5558. doi:10.5194/hessd-11-5515-2014
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  Abstract. Aboveground cosmic-ray neutron measurements provide an opportunity to infer soil moisture at the sub-kilometer scale. Initial efforts to assimilate those measurements have shown promise. This study expands such analysis by investigating (1) how the information from aboveground cosmic-ray neutrons can constrain the soil moisture at distinct depths simulated by a land surface model, and (2) how changes in data availability (in terms of retrieval frequency) impact the dynamics of simulated soil moisture profiles. We employ ensemble data assimilation techniques in a "nearly-identical twin" experiment applied at semi-arid shrubland, rainfed agricultural field, and mixed forest biomes in the USA The performance of the Noah land surface model is compared without and with assimilation of observations at hourly intervals and every 2 days Synthetic observations of aboveground cosmic-ray neutrons better constrain the soil moisture simulated by Noah in root zone soil layers (0–100 cm) despite the limited measurement depth of the sensor (estimated to be 12–20 cm). The ability of Noah to reproduce a "true" soil moisture profile is remarkably good regardless of the frequency of observations at the semi-arid site. However, soil moisture profiles are better constrained when assimilating synthetic cosmic-ray neutrons observations hourly rather than every 2 days at the cropland and mixed forest sites. This indicates potential benefits for hydrometeorological modeling when soil moisture measurements are available at relatively high frequency. Moreover, differences in summertime meteorological forcing between the semi-arid site and the other two sites may indicate a possible controlling factor to soil moisture dynamics in addition to differences in soil and vegetation properties.
• Zeng, X., Wang, A., Barlage, M., & Draper, C. S. (2014). Comparison of land skin temperature from a land model, remote sensing, and in situ measurement: Comparison of land skin temperature. Journal of Geophysical Research: Atmospheres, 119(6), 3093-3106. doi:10.1002/2013jd021026
• Geil, K. L., Serra, Y. L., & Zeng, X. (2013). Assessment of CMIP5 model simulations of the North American monsoon system. Journal of Climate, 26(22), 8787-8801.
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  Abstract: Precipitation, geopotential height, and wind fields from 21 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are examined to determine how well this generation of general circulation models represents the North American monsoon system (NAMS). Results show no improvement since CMIP3 in the magnitude (root-mean-square error and bias) of the mean annual cycle of monthly precipitation over a core monsoon domain, but improvement in the phasing of the seasonal cycle in precipitation is notable. Monsoon onset is early for most models but is clearly visible in daily climatological precipitation, whereas monsoon retreat is highly variable and unclear in daily climatological precipitation. Models that best capture large-scale circulation patterns at a low level usually have realistic representations of the NAMS, but even the best models poorly represent monsoon retreat. Difficulty in reproducing monsoon retreat results from an inaccurate representation of gradients in low-level geopotential height across the larger region, which causes an unrealistic flux of low-level moisture from the tropics into the NAMS region that extends well into the postmonsoon season. Composites of the models with the best and worst representations of the NAMS indicate that adequate representation of the monsoon during the early to midseason can be achieved even with a large-scale circulation pattern bias, as long as the bias is spatially consistent over the larger region influencing monsoon development; in other words, as with monsoon retreat, it is the inaccuracy of the spatial gradients in geopotential height across the larger region that prevents some models from realistic representation of the early and midseason monsoon system. © 2013 American Meteorological Society.
• Gustavo, L., Borak, J. S., Costa, M. H., Saleska, S. R., Baker, I., Restrepo-Coupe, N., Muza, M. N., Poulter, B., Verbeeck, H., Fisher, J. B., Arain, M. A., Arkin, P., Cestaro, B. P., Christoffersen, B., Galbraith, D., Guan, X., J.J.M., B., Ichii, K., M., H., , Jain, A. K., et al. (2013). Overview of the large-scale biosphere-atmosphere experiment in amazonia data model intercomparison project (LBA-DMIP). Agricultural and Forest Meteorology, 182-183, 111-127.
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  Abstract: A fundamental question connecting terrestrial ecology and global climate change is the sensitivity of key terrestrial biomes to climatic variability and change. The Amazon region is such a key biome: it contains unparalleled biological diversity, a globally significant store of organic carbon, and it is a potent engine driving global cycles of water and energy. The importance of understanding how land surface dynamics of the Amazon region respond to climatic variability and change is widely appreciated, but despite significant recent advances, large gaps in our understanding remain. Understanding of energy and carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Land surface/ecosystem models have become important tools for extrapolating local observations and understanding to much larger terrestrial regions. They are also valuable tools to test hypothesis on ecosystem functioning. Funded by NASA under the auspices of the LBA (the Large-Scale Biosphere-Atmosphere Experiment in Amazonia), the LBA Data Model Intercomparison Project (LBA-DMIP) uses a comprehensive data set from an observational network of flux towers across the Amazon, and an ecosystem modeling community engaged in ongoing studies using a suite of different land surface and terrestrial ecosystem models to understand Amazon forest function. Here an overview of this project is presented accompanied by a description of the measurement sites, data, models and protocol. © 2013 Elsevier B.V.
• Rosolem, R., Shuttleworth, W. J., Zreda, M. G., Franz, T. E., Zeng, X. -., & Kurc, S. A. (2013). The effect of atmospheric water vapor on neutron count in the cosmic-ray soil moisture observing system. Journal of Hydrometeorology, 14(5), 1659-1671.
• Shao, P., Zeng, X., J., D., & Zeng, X. (2013). Soil microbial respiration from observations and Earth System Models. Environmental Research Letters, 8(3).
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  Abstract: Soil microbial respiration (Rh) is a large but uncertain component of the terrestrial carbon cycle. Carbon-climate feedbacks associated with changes to Rh are likely, but Rh parameterization in Earth System Models (ESMs) has not been rigorously evaluated largely due to a lack of appropriate measurements. Here we assess, for the first time, Rh estimates from eight ESMs and their environmental drivers across several biomes against a comprehensive soil respiration database (SRDB-V2). Climatic, vegetation, and edaphic factors exert strong controls on annual Rh in ESMs, but these simple controls are not as apparent in the observations. This raises questions regarding the robustness of ESM projections of Rh in response to future climate change. Since there are many more soil respiration (Rs) observations than Rh data, two 'reality checks' for ESMs are also created using the Rs data. Guidance is also provided on the Rh improvement in ESMs. © 2013 IOP Publishing Ltd.
• Shao, P., Zeng, X., Sakaguchi, K., Monson, R. K., & Zeng, X. (2013). Terrestrial carbon cycle: Climate relations in eight CMIP5 earth system models. Journal of Climate, 26(22), 8744-8764.
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  Abstract: Eight Earth System Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated, focusing on both the net carbon dioxide flux and its components and their relation with climatic variables (temperature, precipitation, and soil moisture) in the historical (1850-2005) and representative concentration pathway 4.5 (RCP4.5; 2006-2100) simulations. While model results differ, their median globally averaged production and respiration terms from 1976 to 2005 agree reasonably with available observation-based products. Disturbances such as land use change are roughly represented but crucial in determining whether the land is a carbon source or sink over many regions in both simulations. While carbon fluxes vary with latitude and between the two simulations, the ratio of net to gross primary production, representing the ecosystem carbon use efficiency, is less dependent on latitude and does not differ significantly in the historical and RCP4.5 simulations. The linear trend of increased land carbon fluxes (except net ecosystem production) is accelerated in the twenty-first century. The cumulative net ecosystem production by 2100 is positive (i.e., carbon sink) in all models and the tropical and boreal latitudes become major carbon sinks in most models. The temporal correlations between annual-mean carbon cycle and climate variables vary substantially (including the change of sign) among the eight models in both the historical and twenty-first-century simulations. The ranges of correlations of carbon cycle variables with precipitation and soil moisture are also quite different, reflecting the important impact of the model treatment of the hydrological cycle on the carbon cycle. © 2013 American Meteorological Society.
• Zeng, X., & Wang, A. (2013). Development of Global Hourly 0.5° Land Surface Air Temperature Datasets. Journal of Climate, 26(19), 7676-7691. doi:10.1175/jcli-d-12-00682.1
• Zeng, X., Niu, G., Paniconi, C., Troch, P. A., Scott, R. L., Durcik, M., Huxman, T., & Goodrich, D. C. (2013). An integrated modelling framework of catchment-scale ecohydrological processes: 1. Model description and tests over an energy-limited watershed: A CATCHMENT-SCALE ECOHYDROLOGICAL MODEL. Ecohydrology, 7(2), 427-439. doi:10.1002/eco.1362
• Zreda, M., Zeng, X., Stillman, S., Shuttleworth, W. J., Goodrich, D. C., & Unkrich, C. L. (2013). Spatiotemporal Variability of Summer Precipitation in Southeastern Arizona. Journal of Hydrometeorology, 14(6), 1944-1951. doi:10.1175/jhm-d-13-017.1
• Brunke, M. A., Zeng, X., & Sakaguchi, K. (2012). Temporal- and Spatial-Scale Dependence of Three CMIP3 Climate Models in Simulating the Surface Temperature Trend in the Twentieth Century. Journal of Climate, 25(7), 2456-2470. doi:10.1175/jcli-d-11-00106.1
• Decker, M., Brunke, M. A., Wang, Z., Sakaguchi, K., Zeng, X., & Bosilovich, M. G. (2012). Evaluation of the reanalysis products from GSFC, NCEP, and ECMWF using flux tower observations. Journal of Climate, 25(6), 1916-1944.
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  Abstract: Reanalysis products produced at the various centers around the globe are utilized formany different scientific endeavors, including forcing land surface models and creating surface flux estimates. Here, flux tower observations of temperature, wind speed, precipitation, downward shortwave radiation, net surface radiation, and latent and sensible heat fluxes are used to evaluate the performance of various reanalysis products [NCEP-NCAR reanalysis and Climate Forecast System Reanalysis (CFSR) from NCEP; 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and ECMWF Interim Re-Analysis (ERA-Interim) from ECMWF; and Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Global Land Data Assimilation System (GLDAS) from the Goddard Space Flight Center (GSFC)]. To combine the biases and standard deviation of errors from the separate stations, a ranking systemis utilized. It is found thatERA-Interimhas the lowest overall bias in 6-hourly air temperature, followed closely by MERRA and GLDAS. The variability in 6-hourly air temperature is again most accurate in ERA-Interim. ERA-40 is found to have the lowest overall bias in latent heat flux, followed closely by CFSR, while ERA-40 also has the lowest 6-hourly sensible heat bias. MERRA has the second lowest and is close to ERA-40. The variability in 6-hourly precipitation is best captured byGLDAS and ERA-Interim, and ERA-40 has the lowest precipitation bias. It is also found that at monthly time scales, the bias term in the reanalysis products are the dominant cause of the mean square errors, while at 6-hourly and daily time scales the dominant contributor to the mean square errors is the correlation term. Also, it is found that the hourly CFSR data have discontinuities present due to the assimilation cycle, while the hourly MERRA data do not contain these jumps. © 2012 American Meteorological Society.
• Franz, T. E., Zreda, M., Ferre, T. P., Rosolem, R., Zweck, C., Stillman, S., Zeng, X., & Shuttleworth, W. J. (2012). Measurement depth of the cosmic ray soil moisture probe affected by hydrogen from various sources. WATER RESOURCES RESEARCH, 48.
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  We present here a simple and robust framework for quantifying the effective sensor depth of cosmic ray soil moisture neutron probes such that reliable water fluxes may be computed from a time series of cosmic ray soil moisture. In particular, we describe how the neutron signal depends on three near-surface hydrogen sources: surface water, soil moisture, and lattice water (water in minerals present in soil solids) and also their vertical variations. Through a combined modeling study of one-dimensional water flow in soil and neutron transport in the atmosphere and subsurface, we compare average water content between the simulated soil moisture profiles and the universal calibration equation which is used to estimate water content from neutron counts. By using a linear sensitivity weighting function, we find that during evaporation and drainage periods the RMSE of the two average water contents is 0.0070 m(3) m(-3) with a maximum deviation of 0.010 m(3) m(-3) for a range of soil types. During infiltration, the RMSE is 0.011 m(3) m(-3) with a maximum deviation of 0.020 m(3) m(-3), where piston like flow conditions exists for the homogeneous isotropic media. Because piston flow is unlikely during natural conditions at the horizontal scale of hundreds of meters that is measured by the cosmic ray probe, this modeled deviation of 0.020 m(3) m(-3) represents the worst case scenario for cosmic ray sensing of soil moisture. Comparison of cosmic ray soil moisture data and a distributed sensor soil moisture network in Southern Arizona indicates an RMSE of 0.011 m(3) m(-3) over a 6 month study period.
• Rosolem, R., Gupta, H. V., Shuttleworth, W. J., Zeng, X., & Gustavo, L. (2012). A fully multiple-criteria implementation of the Sobol' method for parameter sensitivity analysis. Journal of Geophysical Research D: Atmospheres, 117(7).
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  Abstract: We present a novel rank-based fully multiple-criteria implementation of the Sobol variance-based sensitivity analysis approach that implements an objective strategy to evaluate parameter sensitivity when model evaluation involves several metrics of performance. The method is superior to single-criterion approaches while avoiding the subjectivity observed in "pseudo" multiple-criteria methods. Further, it contributes to our understanding of structural characteristics of a model and simplifies parameter estimation by identifying insensitive parameters that can be fixed to default values during model calibration studies. We illustrate the approach by applying it to the problem of identifying the most influential parameters in the Simple Biosphere 3 (SiB3) model using a network of flux towers in Brazil. We find 27-31 (out of 42) parameters to be influential, most (∼78%) of which are primarily associated with physiology, soil, and carbon properties, and that uncertainties in the physiological properties of the model contribute most to total model uncertainty in regard to energy and carbon fluxes. We also find that the second most important model component contributing to the total output uncertainty varies according to the flux analyzed; whereas morphological properties play an important role in sensible heat flux, soil properties are important for latent heat flux, and carbon properties (mainly associated with the soil respiration submodel) are important for carbon flux (as expected). These distinct sensitivities emphasize the need to account for the multioutput nature of land surface models during sensitivity analysis and parameter estimation. Applied to other similar models, our approach can help to establish which soil-plant-atmosphere processes matter most in land surface models of Amazonia and thereby aid in the design of field campaigns to characterize and measure the associated parameters. The approach can also be used with other sensitivity analysis procedures that compute at least two model performance metrics.
• Sakaguchi, K., Zeng, X., & Brunke, M. A. (2012). The hindcast skill of the CMIP ensembles for the surface air temperature trend. Journal of Geophysical Research D: Atmospheres, 117(16).
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  Abstract: Linear trends of the surface air temperature (SAT) simulated by selected models from the Coupled Model Intercomparison Project (CMIP3 and CMIP5) historical experiments are evaluated using observations to document (1) the expected range and characteristics of the errors in hindcasting the change in SAT at different spatiotemporal scales, (2) if there are threshold spatiotemporal scales across which the models show substantially improved performance, and (3) how they differ between CMIP3 and CMIP5. Root Mean Square Error, linear correlation, and Brier score show better agreement with the observations as spatiotemporal scale increases but the skill for the regional (5 × 5 - 20 × 20 grid) and decadal (10 - ∼30-year trends) scales is rather limited. Rapid improvements are seen across 30 × 30 grid to zonal average and around 30 years, although they depend on the performance statistics. Rather abrupt change in the performance from 30 × 30 grid to zonal average implies that averaging out longitudinal features, such as land-ocean contrast, might significantly improve the reliability of the simulated SAT trend. The mean bias and ensemble spread relative to the observed variability, which are crucial to the reliability of the ensemble distribution, are not necessarily improved with increasing scales and may impact probabilistic predictions more at longer temporal scales. No significant differences are found in the performance of CMIP3 and CMIP5 at the large spatiotemporal scales, but at smaller scales the CMIP5 ensemble often shows better correlation and Brier score, indicating improvements in the CMIP5 on the temporal dynamics of SAT at regional and decadal scales. © 2012. American Geophysical Union. All Rights Reserved.
• Wang, A., & Zeng, X. (2012). Evaluation of multireanalysis products with in situ observations over the Tibetan Plateau. Journal of Geophysical Research D: Atmospheres, 117(5).
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  Abstract: As the highest plateau in the world, the Tibetan Plateau (TP) strongly affects regional weather and climate as well as global atmospheric circulations. Here six reanalysis products (i.e., MERRA, NCEP/NCAR-1, CFSR, ERA-40, ERA-Interim, and GLDAS) are evaluated using in situ measurements at 63 weather stations over the TP from the Chinese Meteorological Administration (CMA) for 1992-2001 and at nine stations from field campaigns (CAMP/Tibet) for 2002-2004. The measurement variables include daily and monthly precipitation and air temperature at all CMA and CAMP/Tibet stations as well as radiation (downward and upward shortwave and longwave), wind speed, humidity, and surface pressure at CAMP stations. Four statistical quantities (correlation coefficient, ratio of standard deviations, standard deviation of differences, and bias) are computed, and a ranking approach is also utilized to quantify the relative performance of reanalyses with respect to each variable and each statistical quantity. Compared with measurements at the 63 CMA stations, ERA-Interim has the best overall performance in both daily and monthly air temperatures, while MERRA has a high correlation with observations. GLDAS has the best overall performance in both daily and monthly precipitation because it is primarily based on the merged precipitation product from surface measurements and satellite remote sensing, while ERA-40 and MERRA have the highest correlation coefficients for daily and monthly precipitation, respectively. Compared with measurements at the nine CAMP stations, CFSR shows the best overall performance, followed by GLDAS, although the best ranking scores are different for different variables. It is also found that NCEP/NCAR-1 reanalysis shows the worst overall performance compared with both CMA and CAMP data. Since no reanalysis product is superior to others in all variables at both daily and monthly time scales, various reanalysis products should be combined for the study of weather and climate over the TP. Copyright 2012 by the American Geophysical Union.
• Zeng, X., & Wang, A. (2012). What is monthly mean land surface air temperature?. Eos, 93(15), 156-.
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  Abstract: Land surface air temperature is one of the fundamental variables in weather and climate observations, modeling, and applications. Its monthly mean has been computed as the average of daily maximum and minimum temperatures [Jones et al., 1999]. This is different from the true monthly mean temperature, which is defined as the integral of the continuous temperature measurements in a month divided by the integration period and can be very accurately represented using hourly data, as has long been recognized [e.g., Brooks, 1921]. We argue, from scientific, technological, and historical perspectives, that it is time to compute the true monthly mean using hourly data for the national and international climate data record. © 2012 by the American Geophysical Union.
• Zeng, X., Brunke, M. A., Decker, M., Wang, Z., Sakaguchi, K., & Bosilovich, M. G. (2012). Evaluation of the Reanalysis Products from GSFC, NCEP, and ECMWF Using Flux Tower Observations. Journal of Climate, 25(6), 1916-1944. doi:10.1175/jcli-d-11-00004.1
• Zeng, X., Kiviat, K. L., Sakaguchi, K., & Mahmoud, A. M. (2012). A toy model for monthly river flow forecasting. Journal of Hydrology, 452-453, 226-231.
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  Abstract: River flow forecasting depends on land-atmosphere coupled processes, and is relevant to hydrological applications and land-ocean coupling. A toy model is developed here for monthly river flow forecasting using the river flow and river basin averaged precipitation in prior month. Model coefficients are calibrated for each month using historical data. The toy model is based on water balance, easy to use and reproduce, and robust to calibrate with a short period of data. For five major rivers in the world, its results agree with observations very well. Its prediction uncertainty can be quantified using the model's error statistics or using a dynamic approach, but not by the dispersion of 10,000 ensemble members with different sets of coefficients in the model. Its results are much better than those from a physically based land model even after the mean bias correction. The toy model and a standard neural network available from the MATLAB give similar results, but the latter is more sensitive to the length of calibration period. For the monthly prediction of river flow with a strong seasonal cycle, a modified Nash-Sutcliffe coefficient of efficiency is introduced and is found to be more reliable in model evaluations than the original coefficient of efficiency or the correlation coefficient. © 2012 Elsevier B.V.
• Zeng, X., Shuttleworth, W. J., Gupta, H. V., Rosolem, R., & de Gonçalves, L. G. (2012). Towards a comprehensive approach to parameter estimation in land surface parameterization schemes: COMPREHENSIVE APPROACH TO PARAMETER ESTIMATION IN LAND SURFACE MODELS. Hydrological Processes, 27(14), 2075-2097. doi:10.1002/hyp.9362
• Zeng, X., Wang, Z., & Wang, A. (2012). Surface Skin Temperature and the Interplay between Sensible and Ground Heat Fluxes over Arid Regions. Journal of Hydrometeorology, 13(4), 1359-1370. doi:10.1175/jhm-d-11-0117.1
• Zheng, W., Wei, H., Wang, Z., Zeng, X., Meng, J., Michael, E. k., Mitchell, K., & Derber, J. (2012). Improvement of daytime land surface skin temperature over arid regions in the NCEP GFS model and its impact on satellite data assimilation. Journal of Geophysical Research D: Atmospheres, 117(6).
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  Abstract: Comparison of the land surface skin temperature (LST) from the National Centers for Environmental Prediction (NCEP) operational Global Forecast System (GFS) against satellite and in situ data in summer 2007 indicates that the GFS has a large and cold bias in LST over the arid western continental United States (CONUS) during daytime. This LST bias contributes to large errors in simulated satellite brightness temperatures over land by the Community Radiative Transfer Model (CRTM) and hence the rejection of satellite data in the NCEP Gridpoint Statistical Interpolation (GSI) system, especially for surface-sensitive satellite channels. The new vegetation-dependent formulations of momentum and thermal roughness lengths are tested in the GFS. They substantially reduce the large cold bias of daytime LST over the arid western CONUS in the warm season. This, in turn, significantly reduces the large biases of calculated satellite brightness temperatures found for infrared and microwave sensors in window or near-window channels, so that many more satellite data can be assimilated in the GSI system. In the arid western CONUS, the calculation of surface emissivity for microwave sensors in the CRTM can be further improved, and the new microwave land emissivity model together with increased LST via changes in surface roughness length formulations reduces biases and root-mean-square errors in the calculated brightness temperature. © 2012 by the American Geophysical Union.
• Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T. E., & Rosolem, R. (2012). COSMOS: the COsmic-ray Soil Moisture Observing System. HYDROLOGY AND EARTH SYSTEM SCIENCES, 16(11), 4079-4099.
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  The newly-developed cosmic-ray method for measuring area-average soil moisture at the hectometer horizontal scale is being implemented in the COsmic-ray Soil Moisture Observing System (or the COSMOS). The stationary cosmic-ray soil moisture probe measures the neutrons that are generated by cosmic rays within air and soil and other materials, moderated by mainly hydrogen atoms located primarily in soil water, and emitted to the atmosphere where they mix instantaneously at a scale of hundreds of meters and whose density is inversely correlated with soil moisture. The COSMOS has already deployed more than 50 of the eventual 500 cosmic-ray probes, distributed mainly in the USA, each generating a time series of average soil moisture over its horizontal footprint, with similar networks coming into existence around the world. This paper is written to serve a community need to better understand this novel method and the COSMOS project. We describe the cosmic-ray soil moisture measurement method, the instrument and its calibration, the design, data processing and dissemination used in the COSMOS project, and give example time series of soil moisture obtained from COSMOS probes.
• Sakaguchi, K., Zeng, X., Christoffersen, B. J., Restrepo-Coupe, N., Saleska, S. R., & Brando, P. M. (2011). Natural and drought scenarios in an east central Amazon forest: Fidelity of the Community Land Model 3.5 with three biogeochemical models. Journal of Geophysical Research G: Biogeosciences, 116(1).
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  Abstract: Recent development of general circulation models involves biogeochemical cycles: flows of carbon and other chemical species that circulate through the Earth system. Such models are valuable tools for future projections of climate, but still bear large uncertainties in the model simulations. One of the regions with especially high uncertainty is the Amazon forest where large-scale dieback associated with the changing climate is predicted by several models. In order to better understand the capability and weakness of global-scale land-biogeochemical models in simulating a tropical ecosystem under the present day as well as significantly drier climates, we analyzed the off-line simulations for an east central Amazon forest by the Community Land Model version 3.5 of the National Center for Atmospheric Research and its three independent biogeochemical submodels (CASA', CN, and DGVM). Intense field measurements carried out under Large Scale Biosphere-Atmosphere Experiment in Amazonia, including forest response to drought from a throughfall exclusion experiment, are utilized to evaluate the whole spectrum of biogeophysical and biogeochemical aspects of the models. Our analysis shows reasonable correspondence in momentum and energy turbulent fluxes, but it highlights three processes that are not in agreement with observations: (1) inconsistent seasonality in carbon fluxes, (2) biased biomass size and allocation, and (3) overestimation of vegetation stress to short-term drought but underestimation of biomass loss from long-term drought. Without resolving these issues the modeled feedbacks from the biosphere in future climate projections would be questionable. We suggest possible directions for model improvements and also emphasize the necessity of more studies using a variety of in situ data for both driving and evaluating land-biogeochemical models. Copyright 2011 by the American Geophysical Union.
• Wang, A., & Zeng, X. (2011). Sensitivities of terrestrial water cycle simulations to the variations of precipitation and air temperature in China. Journal of Geophysical Research D: Atmospheres, 116(2).
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  Abstract: The quality of simulated soil hydrological variables (i.e., soil moisture, evapotranspiration, and runoff) is largely dependent on the accuracy of meteorological forcing data, especially precipitation and air temperature. This issue is quantitatively addressed here by running the Community Land Model (CLM3.5) over China from 1993 to 2002 using the reanalysis-based precipitation and air temperature and in situ observations in the meteorological forcing data set. Compared to the in situ measured soil moisture data, the CLM3.5 simulation can generally capture the spatial and seasonal variations of soil moisture but produces too-wet soil in northeastern and eastern China and too-dry soil in northwestern China. This deficiency is significantly reduced when the in situ measured precipitation data are used to drive the model. An index is also constructed to quantify the sensitivities of soil hydrological variables to variations of precipitation and air temperature. The highest sensitivity of surface hydrological variables to precipitation appears over semiarid regions, while the sensitivity to air temperature for different variables varies regionally (semiarid regions for runoff and soil moisture and humid regions for evapotranspiration (ET)). Over semiarid regions, precipitation and air temperature are equally important to the simulations of soil hydrological variables. Over humid regions, in contrast, ET is more dependent on air temperature than on precipitation, while soil moisture and runoff are less affected by air temperature. Copyright 2011 by the American Geophysical Union.
• Zeng, X., Brunke, M. A., Wang, Z., Bosilovich, M., & Shie, C. (2011). An Assessment of the Uncertainties in Ocean Surface Turbulent Fluxes in 11 Reanalysis, Satellite-Derived, and Combined Global Datasets. Journal of Climate, 24(21), 5469-5493. doi:10.1175/2011jcli4223.1
• Zeng, X., Yang, Z., Thornton, P. E., Swenson, S. C., Slater, A. G., Sakaguchi, K., Oleson, K. W., Levis, S., Lawrence, P. J., Lawrence, D. M., Flanner, M. G., & Bonan, G. B. (2011). Parameterization improvements and functional and structural advances in version 4 of the Community Land Model. Journal of Advances in Modeling Earth Systems, 3(1), n/a-n/a. doi:10.1029/2011ms00045
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  [1] The Community Land Model is the land component of the Community Climate System Model. Here, we describe a broad set of model improvements and additions that have been provided through the CLM development community to create CLM4. The model is extended with a carbon-nitrogen (CN) biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states and vegetation phenology. An urban canyon model is added and a transient land cover and land use change (LCLUC) capability, including wood harvest, is introduced, enabling study of historic and future LCLUC on energy, water, momentum, carbon, and nitrogen fluxes. The hydrology scheme is modified with a revised numerical solution of the Richards equation and a revised ground evaporation parameterization that accounts for litter and within-canopy stability. The new snow model incorporates the SNow and Ice Aerosol Radiation model (SNICAR) - which includes aerosol deposition, grain-size dependent snow aging, and vertically-resolved snowpack heating – as well as new snow cover and snow burial fraction parameterizations. The thermal and hydrologic properties of organic soil are accounted for and the ground column is extended to ∼50-m depth. Several other minor modifications to the land surface types dataset, grass and crop optical properties, surface layer thickness, roughness length and displacement height, and the disposition of snow-capped runoff are also incorporated. The new model exhibits higher snow cover, cooler soil temperatures in organic-rich soils, greater global river discharge, and lower albedos over forests and grasslands, all of which are improvements compared to CLM3.5. When CLM4 is run with CN, the mean biogeophysical simulation is degraded because the vegetation structure is prognostic rather than prescribed, though running in this mode also allows more complex terrestrial interactions with climate and climate change.
• Zreda, M., Zeng, X., & other coauthors, e. (2011). Cosmic-Ray Neutrons, An Innovative Method for Measuring Area-Average Soil Moisture. GEWEX News, 21(3), 6-10.
• Brunke, M. A., Szoeke, S. D., Zuidema, P., & Zeng, X. (2010). A comparison of ship and satellite measurements of cloud properties with global climate model simulations in the southeast Pacific stratus deck. Atmospheric Chemistry and Physics, 10(14), 6527-6536.
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  Abstract: Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003-2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that Cloud-Sat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP∼h9) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP∼h2) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Zmax>-15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h∼LWP1/2). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20° S, 85°W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20deg; S, 75deg; W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface. © 2010 Author(s).
• Rosolem, R., Shuttleworth, W. J., Zeng, X., Saleska, S. R., & Huxman, T. E. (2010). Land surface modeling inside the Biosphere 2 tropical rain forest biome. Journal of Geophysical Research G: Biogeosciences, 115(4).
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  Abstract: Tropical rain forests contribute substantially to regional and global energy, water, and carbon exchanges between the land surface and the atmosphere, and better understanding of the mechanisms of vegetation response to different environmental stresses is needed. The Biosphere 2 facility provides an opportunity to link laboratory-scale and plot-scale studies in a controllable environment. We compiled a consistent quality-controlled time series of climate data from Biosphere 2 and used it to drive the Simple Biosphere model (SiB3) to test how well it represented the behavior of soils and vegetation inside the tropical rain forest biome of Biosphere 2 (B2-TRF). We found that soil respiration parameterization in SiB3 was not suitable for use in B2-TRF, so several alternative parameterizations were tested. None gave outstanding results, but a modified version of the parameterization originally proposed for SiB3 gave the best results. With this modification, SiB3 well simulated the observed net ecosystem exchange in B2-TRF but, significantly, only after additionally modifying parameters describing the thermal tolerance of plants so that photosynthetic capacity was reduced on average but maintained to higher temperatures. This implies either that tropical rain forest species can acclimate to higher temperatures than allowed for by vegetation models or that the plant community assembly in B2-TRF has shifted to allow continued functioning at higher temperatures, and plants in natural ecosystems could also. In either case, this suggests that the Amazon rain forest may be more resilient to climate change than hitherto thought. Copyright 2010 by the American Geophysical Union.
• Wang, Z., Zeng, X., & Decker, M. (2010). Improving snow processes in the Noah land model. Journal of Geophysical Research D: Atmospheres, 115(20).
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  Abstract: Snow is one of the most crucial land surface processes over middle and high latitudes. A widely known deficiency of the Noah land model as used in the National Centers for Environmental Prediction (NCEP) operational models and the Weather Research and Forecasting model (WRF) at the National Center for Atmospheric Research is that snowmelt occurs much too early. Through detailed diagnostics of the Noah output over the high-altitude Niwot Ridge forest site (40.03°N, 105.55°W) and a boreal forest site (53.9°N, 104.7°W), six deficiencies in Noah model physics are identified along with improved formulations that (1) consider the vegetation shading effect on snow sublimation and snowmelt; (2) consider under-canopy resistance; (3) revise the ground heat flux computation when snow is deep; (4) revise the momentum roughness length computation when snow is present; (5) revise the snow density computation near 0°C; and (6) increase the maximum iteration number from five to 30 in the turbulence computation. These revisions significantly improve Noah simulations of all snow processes such as snow water equivalent (SWE), snow depth, and sensible and latent heat fluxes over these two forest sites. The revisions were also evaluated (without tunings) with an independent forest site and a grassland site, further confirming the robust and positive impacts of these revisions on Noah snow simulations. These modifications maintain the Noah model structure and do not introduce new prognostic variables, allowing easy implementation into NCEP operational models and into WRF. Furthermore, they are found to be as good as, or slightly better than, a much more complicated land model in the snow simulation over the three forest sites. Copyright 2010 by the American Geophysical Union.
• Zeng, X. (2010). Reply to comments on "what is the atmosphere's effect on earth's surface temperature?". Eos, 91(46), 432-.
• Zeng, X. (2010). What is the atmospheres effect on Earth's surface temperature?. Eos, 91(15), 134-135.
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  Abstract: It is frequently stated in textbooks and scholarly articles that the surface temperature of Earth is 33C warmer than it would be without the atmosphere and that this difference is due to the greenhouse effect. This Forum shows that the atmosphere effect leads to warming of only 20C. This new conclusion requires a revision to all of the relevant literature in K-12, undergraduate, and graduate education material and to science papers and reports. The greenhouse effect on Earth's surface temperature is well understood qualitatively and is regarded as basic knowledge about Earth's climate and climate change. The 33C warming has been used to quantify the greenhouse effect of greenhouse gases, or of greenhouse gases and clouds, in K-12 educational material (e.g., http://epa.gov/climatechange/kids/greenhouse.html), undergraduate freshman introductory textbooks on weather and climate [e.g., Ahrens, 2008], and graduate textbooks on climate [e.g., Peixoto and Oort, 1992]. Some textbooks and various other publications have less stringently attributed the warming to the greenhouse effect [e.g., Wallace and Hobbs, 2006; Le Treut et al., 2007; American Meteorological Society, 2000].
• Zeng, X., & Decker, M. (2010). Reply. Journal of Hydrometeorology, 11(4), 1051-1054. doi:10.1175/2010jhm1199.1
• Zeng, X., & Wang, Z. (2010). Evaluation of Snow Albedo in Land Models for Weather and Climate Studies. Journal of Applied Meteorology and Climatology, 49(3), 363-380. doi:10.1175/2009jamc2134.1
• Zeng, X., Barlage, M., Castro, C., & Fling, K. (2010). Comparison of Land–Precipitation Coupling Strength Using Observations and Models. Journal of Hydrometeorology, 11(4), 979-994. doi:10.1175/2010jhm1226.1
• Zhang, S., Zeng, X., Zhang, W., & Barlage, M. (2010). Revising the ensemble-based kalman filter covariance for the retrieval of deep-layer soil moisture. Journal of Hydrometeorology, 11(1), 219-227.
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  Abstract: Previous studies have demonstrated that soil moisture in the top layers (e.g., within the top 1-m depth) can be retrieved by assimilating near-surface soil moisture observations into a land surface model using ensemblebased data assimilation algorithms. However, it remains a challenging issue to provide good estimates of soil moisture in the deep layers, because the error correlation between the surface and deep layers is low and hence is easily influenced by the physically limited range of soil moisture, probably resulting in a large noiseto-signal ratio. Furthermore, the temporally correlated errors between the surface and deep layers and the nonlinearity of the system make the retrieval even more difficult. To tackle these problems, a revised ensemble-based Kalman filter covariance method is proposed by constraining error covariance estimates in deep layers in two ways: 1) explicitly using the error covariance at the previous time step and 2) limiting the increase of the soil moisture error correlation with the increase of the vertical distance between the two layers. This method is then tested at three separate point locations representing different precipitation regimes. It is found that the proposed method can effectively control the abrupt changes of error covariance estimates between the surface layer and two deep layers. It significantly improves the estimates of soil moisture in the two deep layers with daily updating. For example, relative to the initial background error, after 150 daily updates, the error in the deepest layer reduces to 11.4%, 32.3%, and 27.1% at the wet, dry, and medium wetness locations, only reducing to 62.3%, 80.8%, and 47.5% with the original method, respectively. However, the improvement of deep-layer soil moisture retrieval is very slight when the updating frequency is reduced to once every three days. © 2010 American Meteorological Society.
• Er, L. u., Zeng, X., Jiang, Z., Wang, Y., & Zhang, Q. (2009). Precipitation and precipitable water: Their temporal-spatial behaviors and use in determining monsoon onset/retreat and monsoon regions. Journal of Geophysical Research D: Atmospheres, 114(23).
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  Abstract: Precipitation (P) is conventionally used for determining monsoon onset/retreat. It can roughly separate monsoon regions from nonmonsoon regions, Zeng and Lu (2004) found that precipitable water (W) can also determine the monsoon onset/retreat but cannot determine the monsoon regions. Temporal-spatial behaviors of P and W are compared in this article with observed data and results of previous theoretical analyses, and the comparison is used to understand the performances of P and W in determining the monsoon onset/retreat and monsoon regions. It is shown that W increases everywhere from winter to summer, dominated by the large seasonal change of temperature. P increases from winter to summer mainly in monsoon regions; it decreases or does not change much in most of the nonmonsoon regions. Whether P increases or not from winter to summer depends on whether the increase of W is greater than the increase of temperature. Synoptic variations of P and W have positive correlations everywhere. The increases of P and W from winter to summer in monsoon regions make both able to determine the climatic monsoon onset and retreat. The positive correlations of daily P and W in monsoon onset and retreat seasons make the interannual variations of the monsoon onset and retreat determined from P able to be determined from W. The decrease or small change of P from winter to summer in most of the nonmonsoon regions and the increase of W in nonmonsoon regions make P able to roughly determine the monsoon regions while W fails to. Copyright 2009 by the American Geophysical Union.
• Huxman, T., Troch, P., Chorover, J., Breshears, D. D., Saleska, S., Pelletier, J., Zeng, X., & Espeleta, J. (2009). The hills are alive: Earth science in a controlled environment. Eos, 90(14), 120-.
• Wang, A., & Zeng, X. (2009). Improving the treatment of the vertical snow burial fraction over short vegetation in the NCAR CLM3. Advances in Atmospheric Sciences, 26(5), 877-886.
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  Abstract: One deficiency of the NCAR Community Land Model (CLM3) is the disappearance of the simulated snow even in the middle of winter over a boreal grassland site due to unrealistically modeled high downward turbulent fluxes. This is caused by the inappropriate treatment of the vertical snow burial fraction for short vegetation. A new snow burial fraction formulation for short vegetation is then proposed and validated using in situ observations. This modification in the CLM3 largely removes the unrealistic surface turbulent fluxes, leading to a more reasonable snowmelt process, and improves the snow water equivalent (SWE) simulation. Moreover, global offline simulations show that the proposed formulation decreases sensible and latent heat fluxes as well as the ground temperature during the snowmelt season over short vegetation dominant regions. Correspondingly, the SWE is enhanced, leading to the increase in snowmelt-induced runoff during the same period. Furthermore, sensitivity tests indicate that these improvements are insensitive to the exact functional form or parameter values in the proposed formulation. © 2009 Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer Berlin Heidelberg.
• Zeng, X., & Decker, M. (2009). Impact of Modified Richards Equation on Global Soil Moisture Simulation in the Community Land Model (CLM3.5). Journal of Advances in Modeling Earth Systems, 1(3), n/a-n/a. doi:10.3894/james.2009.1.5
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  [1] A fundamental deficiency has been found in the numerical solution of the soil moisture-based Richards equation using the mass-conservative scheme in the Community Land Model (CLM) in the first part of our efforts (Zeng and Decker 2009). This study implements the revised form of the Richards equation from that study (which doesn't change the property of the differential equation but does remove the deficiency of the numerical solution) along with a new bottom boundary condition into the current version of CLM (CLM3.5) for global offline modeling evaluations. CLM3.5 represents a significant improvement over its earlier version (CLM3.0), but it also introduces a new deficiency in the vertical distribution of the soil moisture variability. Mean soil moisture in CLM3.5 is also too wet. It is found that the new treatments (primarily a numerically correct solution of Richards equation with a new bottom boundary condition) with minimal tuning are able to maintain the improvements of the CLM3.5 over CLM3.0 and, at the same time, remove the new deficiencies of CLM3.5 based on in situ and satellite data analysis. Because the deficiency in the numerical solution of the soil moisture-based Richards equation is also expected in other land models, implementation details are provided to facilitate similar tests using other land models in the future.
• Zeng, X., & Decker, M. (2009). Improving the Numerical Solution of Soil Moisture–Based Richards Equation for Land Models with a Deep or Shallow Water Table. Journal of Hydrometeorology, 10(1), 308-319. doi:10.1175/2008jhm1011.1
• Zeng, X., & Sakaguchi, K. (2009). Effects of soil wetness, plant litter, and under-canopy atmospheric stability on ground evaporation in the Community Land Model (CLM3.5): NEW SCHEMES FOR CLM3.5 SOIL EVAPORATION. Journal of Geophysical Research: Atmospheres, 114(D1). doi:10.1029/2008jd010834
• Brunke, M. A., Zeng, X., Misra, V., & Beljaars, A. (2008). Integration of a prognostic sea surface skin temperature scheme into weather and climate models. Journal of Geophysical Research D: Atmospheres, 113(21).
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  Abstract: A prognostic skin sea surface temperature (SST) algorithm is included in the Community Atmosphere Model (CAM3.1). With this algorithm, the model produces a mean diurnal cycle of 0.5 K primarily in tropical and subtropical oceans of the summer hemisphere with isolated areas of >2 K. The diurnal cycle in air temperature is substantially increased over regions with large skin SST diurnal cycles, and the enhanced diurnal cycle agrees better with the TAO buoy data over the equatorial Pacific. There is also a significant effect on the diurnal cycle in precipitation particularly in the increased hourly maximum precipitation over the Bay of Bengal and the western Pacific in boreal summer. These changes to the diurnal cycle in SST affect the seasonal climatologies in the model with improved seasonal mean precipitation mainly in the tropics following similar patterns to the hourly maximum precipitation rates. The near-surface flow across the Indian subcontinent is also increased during the summer monsoon resulting in higher seasonal precipitation over the Bay of Bengal. Copyright 2008 by the American Geophysical Union.
• Wang, Z., & Zeng, X. (2008). Snow albedo's dependence on solar zenith angle from in situ and MODIS data. Atmos. Oceanic Sci. Lett., 1, 45-50.
• Zeng, X., & Wang, Z. (2008). Snow Albedo’s Dependence on Solar Zenith Angle from In Situ and MODIS Data. Atmospheric and Oceanic Science Letters, 1(1), 45-50. doi:10.1080/16742834.2008.11446763
• Zeng, X., Brunke, M., Misra, V., & Marx, L. (2008). The Equatorial Pacific Cold Tongue Bias in a Coupled Climate Model. Journal of Climate, 21(22), 5852-5869. doi:10.1175/2008jcli2205.1
• Zeng, X., Yang, F., Mitchell, K., Hou, Y., Dai, Y., Wang, Z., & Liang, X. (2008). Dependence of Land Surface Albedo on Solar Zenith Angle: Observations and Model Parameterization. Journal of Applied Meteorology and Climatology, 47(11), 2963-2982. doi:10.1175/2008jamc1843.1
• Zeng, X., Zeng, X., & Barlage, M. (2008). Growing temperate shrubs over arid and semiarid regions in the Community Land Model-Dynamic Global Vegetation Model: GROWING TEMPERATE SHRUBS IN CLM-DGVM. Global Biogeochemical Cycles, 22(3), n/a-n/a. doi:10.1029/2007gb003014
• Wang, Z., Zeng, X., & Barlage, M. (2007). Moderate resolution imaging spectroradiometer bidirectional reflectance distribution function-based albedo parameterization for weather and climate models. Journal of Geophysical Research D: Atmospheres, 112(2).
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  Abstract: The albedo of land surfaces is an important parameter for surface energy balance and is dependent on the solar zenith angle and the three-dimensional structure of the canopies. The Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) algorithm is reformulated to derive a new two-parameter scheme for the computation of land surface albedo and its solar zenith angle (SZA) dependence for use in weather and climate models as well as in the remote sensing retrieval of surface solar fluxes. In this formulation the season- and pixel- dependent black-sky albedo at 60° SZA can be directly prescribed using the MODIS BRDF data while the two parameters are taken as a function of vegetation type only. Comparison of this formulation with those used in weather, climate, and data assimilation models (at NCAR, NCEP, and NASA) reveals the deficiencies in the treatment of SZA dependence and white-sky albedo in these models. Similarly, comparison of this formulation with those computed using the remotely sensed solar flux data from three groups (International Satellite Cloud Climatology Project (ISCCP)-FD, NASA's Clouds and the Earth's Radiant Energy System Tropical Rainfall Measuring Mission (CERES/ TRMM), and University of Maryland) shows that surface albedos from these data sets are at times unrealistic, and suggestions are made regarding how to better treat the surface albedo and its SZA dependence in the retrieval of surface and atmospheric solar fluxes. Copyright 2007 by the American Geophysical Union.
• Zeng, X., & Wang, A. (2007). Consistent Parameterization of Roughness Length and Displacement Height for Sparse and Dense Canopies in Land Models. Journal of Hydrometeorology, 8(4), 730-737. doi:10.1175/jhm607.1
• Zeng, X., & Zeng, X. (2007). Transition and pattern diversity in arid and semiarid grassland: A modeling study: TRANSITION AND PATTERN OF GRASSLAND. Journal of Geophysical Research: Biogeosciences, 112(G4), n/a-n/a. doi:10.1029/2007jg000411
• Brunke, M. A., Zhou, M., Zeng, X., & Andreas, E. L. (2006). An intercomparison of bulk aerodynamic algorithms used over sea ice with data from the Surface Heat Budget for the Arctic Ocean (SHEBA) experiment. Journal of Geophysical Research C: Oceans, 111(9).
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  Abstract: The presence of sea ice fundamentally changes the energy and momentum exchange between the ocean and the atmosphere in the Arctic. Thus an accurate representation of the surface turbulent fluxes in climate models is a necessity. An intercomparison of bulk aerodynamic algorithms that calculate surface turbulent fluxes in four climate and numerical weather prediction models is undertaken using data from the Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment, which occurred on the ice in the Beaufort and Chukchi seas north of Alaska from October 1997 to October 1998. Algorithm deficiencies include the consistently higher wind stresses produced by the Arctic Regional Climate System Model (ARCSYM) algorithm; the lower sensible heat fluxes under stable conditions by the algorithms in ARCSYM, the National Center for Environmental Prediction's Global Forecasting System model, and the European Centre for Medium-Range Weather Forecasts (ECMWF) model; and the lower wind stresses by the National Center for Atmospheric Research's Community Climate System Model (CCSM) algorithm under stable conditions. Unlike the constants used in most of the four model algorithms, the roughness lengths for momentum can be fitted by an exponential function with parameters that account for the seasonality in the roughness length. The roughness lengths for heat, Zot, can be considered a constant (e.g., that used in CCSM, 0.5 mm), similar to what was found by Andreas et al. (2004). When these roughness lengths were implemented into the CCSM and ECMWF algorithms, they produced slightly better wind stresses and sensible heat fluxes most of the time. Copyright 2006 by the American Geophysical Union.
• Decker, M., & Zeng, X. (2006). An empirical formulation of soil ice fraction based on in situ observations. Geophysical Research Letters, 33(5).
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  Abstract: In situ data from around the globe are used to evaluate the parameterization of the fraction of soil ice over total moisture (fi) as used in four weather and climate models. Based on these evaluations and data analysis, an overall realistic (empirical) formulation is developed to compute fi as a function of soil temperature and the ratio of total moisture over its saturated value. This new formulation is found to reduce the winter ground temperature by up to 3 K over high latitudes in the offline Community Land Model (CLM3) simulation. Copyright 2006 by the American Geophysical Union.
• Dickinson, R. E., Zeng, X., Wang, A., Shen, S. S., & Zeng, Q. (2006). Time Scales of Land Surface Hydrology. Journal of Hydrometeorology, 7(5), 868-879. doi:10.1175/jhm527.1
• Kursinski, A. L., & Zeng, X. (2006). Areal estimation of intensity and frequency of summertime precipitation over a midlatitude region. Geophysical Research Letters, 33(22).
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  Abstract: Spatially averaged precipitation characteristics derived from observations are needed to evaluate climate model generated precipitation intensity and frequency. In this study, observations from gauges and radar datasets are used to address three issues that are related to the areal estimation of intensity and frequency of summertime precipitation over the state of Ohio, USA. First, spatial averages of intensity and frequency from point precipitation are found to be very sensitive to the averaging method (i.e., spatial averaging followed by temporal averaging versus temporal followed by spatial averaging), particularly at lower precipitation thresholds. Second, approximately 30 gauges are found to be necessary to construct average intensity for a typical climate model grid, which is much higher than the gauge number required for average precipitation amount. Finally, the fractional area receiving rainfall is found to have a fairly linear relation with the precipitation amount averaged over the grid, but the slope differs between the gauge and radar data. Copyright 2006 by the American Geophysical Union.
• Miller, J., Barlage, M., Zeng, X., Wei, H., Mitchell, K., & Tarpley, D. (2006). Sensitivity of the NCEP/Noah land surface model to the MODIS green vegetation fraction data set. Geophysical Research Letters, 33(13).
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  Abstract: Land surface processes are strongly controlled by vegetation cover. Current land surface models represent vegetation as a combination of leaf area index (LAI) and green vegetation fraction (GVF) parameters. The purpose of the study is to examine the impact of a spatially and temporally detailed Moderate Resolution Imaging Spectroradiometer (MODIS)-based GVF on surface processes in the NCEP Noah land surface model. The largest differences between the GVF data set currently used by the Noah model and the new MODIS GVF data set occur in winter and for tree-dominated vegetation classes. The greatest impact of the new GVF data on the surface energy and water balance is seen during the summer, when the transpiration is increased by more than 10 W/m2 on average for most vegetation types and the July averaged daily transpiration rate is increased by up to 50 W/m2 for evergreen needleleaf sites. Copyright 2006 by the American Geophysical Union.
• Zeng, X., Dickinson, R. E., Oleson, K. W., Bonan, G., Hoffman, F., Thornton, P., Vertenstein, M., & Yang, Z. (2006). The Community Land Model and Its Climate Statistics as a Component of the Community Climate System Model. Journal of Climate, 19(11), 2302-2324. doi:10.1175/jcli3742.1
• Zeng, X., Suyehiro, K., Stein, R. S., Penner, J. E., Freymueller, J. T., Defries, R., Costa, J. E., Collins, C., & Bougeret, J. (2006). Extending AGU's digital library. Eos, Transactions American Geophysical Union, 87(26), 255-255. doi:10.1029/2006eo260008
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  AGU has a long and proud history of publishing. The Union's most visible and stalwart publication, the Journal of Geophysical Research (JGR), traces its roots to 1896, when the journal Terrestrial Magnetism first appeared. Since then, AGU's publications have come to include more than a dozen journals, books, maps, and the venerable Eos Transactions, which you are reading now. By far, the largest amount of AGU's published output has been in the form of printed media. Print communications have served scholars for centuries, and they remain valuable. However, today's investigators expect to conduct research in the digital environment of the Internet, where material can be more easily found, accessed, and utilized. Consequently, it is common for scholarly publishers these days to convert their older, print content so that it is accessible and usable on the Internet, a process often called ‘retrospective digitization.’ AGU is embarking on such a process.
• Zeng, X., Wang, A., Zeng, Q., Dickinson, R. E., Zeng, X., & Shen, S. S. (2006). Intermediately complex models for the hydrological interactions in the atmosphere-vegetation-soil system. Advances in Atmospheric Sciences, 23(1), 127-140.
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  Abstract: This paper investigates the hydrological interactions in the atmosphere-evegetation-soil system by using the bucket model and several new simplified intermediately complex models. The results of mathematical analysis and numerical simulations show that these models, despite their simplicity, can very clearly reveal the essential features of the rather complex hydrological system of atmosphere-ecosystem-soil. For given atmospheric variables, these models clearly demonstrate multiple timescales, the "red shift" of response spectra, multi-equilibria and limit cycles, bifurcation, abrupt change, self-organization, recovery, "desertification", and chaos. Most of these agree with observations. Especially, the weakening of "shading effect" of living canopy and the wilted biomass might be a major mechanism leading to the desertification in a relatively short period due to overgrazing, and the desertification in a relatively long period or in climate of change might be due to both Charney's mechanism and the shading effect. These ideas could be validated with further numerical simulations. In the paper, some methods for improving the estimation of timescales in the soil water evolution responding to the forcing are also proposed.
• Zhou, M., Li, S., Chen, Z., Zhang, Z., & Zeng, X. (2006). Characteristics of the atmospheric surface layer and heat budget over the Arctic ice in summer. Chinese Journal of Geophysics (Acta Geophysica Sinica), 49(2), 353-359.
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  Abstract: Observational data of August 19-24, 1999 during the first Chinese arctic research exploration were analyzed and the vertical distribution of meteorological variables in the surface layer and the heat budget problem over ice in the Arctic region in summer were discussed. The results show that the humidity of surface layer is very high relative to the ice surface, and is often close to its saturated value. The ice temperature has a significant diurnal variation. The ice temperature gradient near the surface is relatively large at night, and is very small during daytime. For the top 40cm of ice, the ice temperature sometimes reaches a maximum value at 20cm depth. The heat budget analysis shows that the heat loss during night caused by the radiation cooling effect is compensated by heat transferred from the inner ice layer to the ice surface. In daytime, the inner ice heat comes mainly from penetrating shortwave radiation, and heat exchange between the ice surface and inner ice is very weak. The ice/snow thaw heat in daytime can not be neglected.
• Zhou, M., Zeng, X., Brunke, M., Zhang, Z., & Fairall, C. (2006). An analysis of statistical characteristics of stratus and stratocumulus over eastern Pacific. Geophysical Research Letters, 33(2).
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  Abstract: Observational measurements of cloud base, top, thickness, fraction, and liquid water path (LWP) are analyzed to study the macro- and micro-physical properties of stratus and stratocumulus over the eastern Pacific. It is found that the increase in liquid water content with height in cloud is significantly less than the adiabatic rate. The variations of cloud base and top both contribute to the variation of cloud thickness that approximately fits a normal distribution better than either cloud base or top. Because the distribution of LWP depends on the intervals of cloud fraction (or other environmental variables, for example, relative humidity), the determination of cloud fraction from the mean LWP alone would introduce large uncertainties particularly when LWP is large. Copyright 2006 by the American Geophysical Union.
• Dickinson, R. E., Dickinson, R. E., Zeng, X., Zeng, X., Zeng, X., Zeng, X., Shen, S. S., & Shen, S. S. (2005). Reply to comment by Dekker and Rietkerk on “Multiple equilibrium states and the abrupt transitions in a dynamical system of soil water interacting with vegetation”. Geophysical Research Letters, 32(9). doi:10.1029/2004gl022339
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  [1] Dekker and Rietkerk [2005] (hereinafter referred to as DR) raise some valid points regarding our paper ‘‘Multiple equilibrium states and the abrupt transitions in a dynamical system of soil water interacting with vegetation’’ [Zeng et al., 2004] (hereinafter referred to as XZ). We appreciate the opportunity to clarify these issues here and hope this dialogue (between scientists working on horizontal interaction and spatial patterns and those who are more interested in the area-averaged land-atmosphere interactions) will shed some new lights on the overall land modeling over arid and semiarid regions. [2] DR argued that XZ ignored well-known spatial processes, leading to spatial pattern formation, no abrupt boundaries, and dramatically changing parameter regions. As a single column model, by definition, horizontal interactions cannot be explicitly included and spatial patterns cannot be produced in XZ. However, this does not mean that the area-averaged effects of these spatial patterns are completely ignored. In fact, horizontal heterogeneity is included in XZ by separately considering processes (e.g., evaporation, transpiration, runoff) over the vegetated and non-vegetated areas in a single column. The use of average soil water over the column also implies an (instantaneous) horizontal water exchange between these two areas. In contrast, models on spatial patterns as reviewed by Rietkerk et al. [2004] would divide this single column into numerous small cells. While the horizontal interaction among different cells is considered in these models, each cell is assumed to be uniformly covered by vegetation (i.e., without considering bare soil fraction). [3] Different mechanisms have been proposed to explain the self-organized spatial patterns, as summarized byRietkerk et al. [2004]. The essence of all these mechanisms is that water is more concentrated into patches of vegetation due to spatial interactions over arid and semiarid regions. Since our single column model contains only the soil water averaged over vegetated and non-vegetated areas, the above effect can be largely represented by the increase of the exponential coefficient in the biomass growth dependence on soil water (i.e., XZ, e0 g in equation (4)). Indeed, Figure 1 shows that, as e0 g increases, the parameter regime of bistability between m1 and m2 shifts towards left, in agreement with Figure 2 of DR. Detailed discussion of the sensitivity of the parameter regime of bistability to all model parameters is given by Zeng et al. [2005]. Further, in Figure 1 vegetated states at different e0 g do not converge to the same state, in agreement with van de Koppel and Rietkerk [2004]. In contrast, it is unclear how DR draw their Figure 2 where the vegetated states with or without spatial interactions intercept with each other at a higher resource input, which is inconsistent with van de Koppel and Rietkerk [2004] and Figure 1 here. [4] We also agree with DR that, visually, vegetation boundaries are not abrupt but go through a diversity of vegetation patterns instead over arid and semiarid regions, and we regret that this point was not explicitly stated in XZ. However, the abrupt change was discussed in terms of biomass in XZ and other references cited in DR. For instance, Figure 1 shows that a small perturbation near the unstable equilibrium state or a small variation in moisture index near the critical points m1 and m2 may lead to a desert or vegetated state. Note that the vegetated state in our single column model still contains non-vegetated area and may correspond to a particular spatial pattern [e.g., see Rietkerk et al., 2004, Figure 3]. Therefore, even though our model cannot predict specific spatial patterns, it can still predict vegetation boundaries in terms of biomass. [5] In summary, while horizontal interactions and spatial patterns are not explicitly considered in XZ, their effect averaged over an area can be implicitly represented by the adjustment of model coefficients, and the results in XZ on abrupt boundaries in terms of biomass and parameter regimes remain correct. [6] While the model in XZ emphasizes vertical interactions between vegetation and soil water (e.g., inclusion of wilted biomass that is very important over temperate grassland), other models as reviewed by Rietkerk et al. [2004] GEOPHYSICAL RESEARCH LETTERS, VOL. 32, L09403, doi:10.1029/2004GL022339, 2005
• Dickinson, R. E., Zeng, X., Barlage, M., Dai, Y., Wang, G., & Oleson, K. (2005). Treatment of Undercanopy Turbulence in Land Models. Journal of Climate, 18(23), 5086-5094. doi:10.1175/jcli3595.1
• Dickinson, R. E., Zeng, X., Zeng, X., Shen, S. S., Rietkerk, M., & Dekker, S. C. (2005). Comment on: Multiple equilibrium states and the abrupt transitions in a dynamical system of soil water interacting with vegetation. Authors' replay. Geophysical Research Letters, 32(9).
• Er, L. u., & Zeng, X. (2005). Understanding different precipitation seasonality regimes from water vapor and temperature fields: Case studies. Geophysical Research Letters, 32(22), 1-5.
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  Abstract: Different precipitation seasonality regimes, although produced by different surface and atmospheric conditions, can be understood from the basic atmospheric fields. By comparing the change of water vapor from winter to summer with the change of temperature using the NARR reanalysis, three seasonality cases over the United States and Mexico are analyzed. In the western coast of the U.S., the change of temperature from winter to summer is much greater than the change of water vapor. So, relative to summer, the coldness of the winter air is much more significant than the dryness, which makes the winter have a large saturation extent and thus precipitation. In contrast, over South Mexico, the much more significant moistness of the summer air than its warmness is important to the summer monsoon precipitation. In the southeastern U.S. where precipitation occurs throughout the year, the changes of water vapor and temperature are roughly equivalent. Copyright 2005 by the American Geophysical Union.
• Wang, Z., Barlage, M., Zeng, X., Dickinson, R. E., & Schaaf, C. B. (2005). The solar zenith angle dependence of desert albedo. Geophysical Research Letters, 32(5), 1-4.
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  Abstract: Most land models assume that the bare soil albedo is a function of soil color and moisture but independent of solar zenith angle (SZA). However, analyses of the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) and albedo data over thirty desert locations indicate that bare soil albedo does vary with SZA. This is further confirmed using the in situ data. In particular, bare soil albedo normalized by its value at 60° SZA can be adequately represented by a one-parameter formulation (1 + C)/(1 + 2C * cos(SZA)) or a two-parameter formulation (1 + B1 * f1(SZA) + B2 * f2(SZA)). Using the MODIS and in situ data, the empirical parameters C, B1, and B2 are taken as 0.15, 0.346 and 0.063. The SZA dependence of soil albedo is also found to significantly affect the modeling of land surface energy balance over a desert site. Copyright 2005 by the American Geophysical Union.
• Zeng, X., & Beljaars, A. (2005). A prognostic scheme of sea surface skin temperature for modeling and data assimilation. Geophysical Research Letters, 32(14), 1-4.
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  Abstract: A prognostic scheme is derived for the computation of sea surface skin temperature in weather forecasting, four-dimensional data assimilation, and ocean-atmosphere coupled modeling. This scheme is then tested using the in situ data over tropical and midlatitude oceans. By implementing this scheme into the ECMWF model, the diurnal variation of sea surface temperature as measured by the geostationary satellite can also be reproduced. Copyright 2005 by the American Geophysical Union.
• Zeng, X., & Lu, E. (2005). Understanding different precipitation seasonality regimes from water vapor and temperature fields: Case studies: PRECIPITATION SEASONALITY. Geophysical Research Letters, 32(22), n/a-n/a. doi:10.1029/2005gl024333
• Zeng, X., Barlage, M., Wei, H., & Mitchell, K. E. (2005). A global 0.05° maximum albedo dataset of snow-covered land based on MODIS observations: MAXIMUM ALBEDO OF SNOW-COVERED LAND. Geophysical Research Letters, 32(17). doi:10.1029/2005gl022881
• Zeng, X., Dickinson, R. E., Barlage, M., Dai, Y., Wang, G., & Oleson, K. (2005). Treatment of undercanopy turbulence in land models. Journal of Climate, 18(23), 5086-5094.
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  Abstract: In arid and semiarid regions most of the solar radiation penetrates through the canopy and reaches the ground, and hence the turbulent exchange coefficient under canopy Cs becomes important. The use of a constant Cs that is only appropriate for thick canopies is found to be primarily responsible for the excessive warm bias of around 10 K in monthly mean ground temperature over these regions in version 2 of the Community Climate System Model (CCSM2). New Cs formulations are developed for the consistent treatment of undercanopy turbulence for both thick and thin canopies in land models, and provide a preliminary solution of this problem. © 2005 American Meteorological Society.
• Zeng, X., Wang, A., Zhao, G., S., S., Zeng, X., & Zeng, Q. (2005). Ecological dynamic model of grassland and its practical verification. Science in China, Series C: Life Sciences, 48(1), 41-48.
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  PMID: 15844356;Abstract: Based on the physico-biophysical considerations, mathematical analysis and some approximate formulations generally adopted in meteorology and ecology, an ecological dynamic model of grassland is developed. The model consists of three interactive variables, i.e. the biomass of living grass, the biomass of wilted grass, and the soil wetness. The major biophysical processes are represented in parameterization formulas, and the model parameters can be determined inversely by using the observational climatological and ecological data. Some major parameters are adjusted by this method to fit the data (although incomplete) in the Inner Mongolia grassland, and other secondary parameters are estimated through sensitivity studies. The model results are well agreed with reality, e.g., (i) the maintenance of grassland requires a minimum amount of annual precipitation (approximately 300 mm); (ii) there is a significant relationship between the annual precipitation and the biomass of living grass; and (iii) the overgrazing will eventually result in desertification. A specific emphasis is put on the shading effect of the wilted grass accumulated on the soil surface. It effectively reduces the soil surface temperature and the evaporation, hence benefits the maintenance of grassland and the reduction of water loss in the soil. Copyright by Science in China Press 2005.
• Zeng, X., Zeng, X., Shen, S. S., Dickinson, R. E., & Zeng, Q. (2005). Vegetation-soil water interaction within a dynamical ecosystem model of grassland in semi-arid areas. Tellus, Series B: Chemical and Physical Meteorology, 57(3), 189-202.
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  Abstract: A dynamical ecosystem model with three variables, living biomass, wilted biomass and available soil wetness, is developed to examine the vegetation-soil water interaction in semi-arid areas. The governing equations are based on the mass conservation law. The physical and biophysical processes are formulated with the parameters estimated from observational data. Both numerical results and qualitative analysis of the model as well as observational data indicate that the maintenance of a grassland requires a minimum precipitation (or equivalently, a minimum moisture index), and the grassland and desert ecosystem can coexist when precipitation is within a range above this threshold. Sensitivity studies show that these numerical results are robust with respect to model parameters and the transformation functions. It is also found that the wilted vegetation plays a very important role in shaping the transition between grassland and desert. By using the theories of an attractor basin and multiple equilibrium states, the conditions for grassland maintenance and the strategy of grazing are also analysed. Copyright © Blackwell Munksgaard, 2005.
• Barlage, M., & Zeng, X. (2004). Impact of observed vegetation root distribution on seasonal global simulations of land surface processes. Journal of Geophysical Research D: Atmospheres, 109(9), D09101 1-14.
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  Abstract: Using a global root distribution derived from observations, results from June to August ensemble simulations are presented. The new root distribution shifts the location of roots in the soil in most regions of the world. Root relocation depends on land use type with some roots located shallower (e.g., grasslands) and others deeper (e.g., tropical forests). Comparison of the boreal summer results of 1988 and 1993 for a control simulation and simulation with the new root distribution produces, in several regions of the world, statistically significant differences of up to 40 W/m2 in the components of the surface energy budget. Analysis of the eastern and western United States shows statistically significant changes of over 1 K in surface air temperature and over 25 W/m2 in surface energy components for both seasonal averages and diurnal cycles. Comparison with observations shows that the new root distribution improves the surface air temperature simulation, especially in 1993, but any precipitation improvement is statistically insignificant. Copyright 2004 by the American Geophysical Union.
• Barlage, M., & Zeng, X. (2004). The effects of observed fractional vegetation cover on the land surface climatology of the community land model. Journal of Hydrometeorology, 5(5), 823-830.
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  Abstract: Accurate modeling of surface processes requires a specification of the amount of land covered by vegetation. The National Center for Atmospheric Research Community Land Model (CLM2) does not realistically represent sparsely vegetated regions because of a lack of bare soil in the model. In this study, the existing CLM2 surface dataset is replaced by a global 1-km fractional vegetation cover dataset. This results in a doubling of global bare soil fraction in the model. It also significantly affects the fractional coverages of shrub, grass, and crop compared with only minor changes to trees. Regional changes occur most greatly in Australia, with an increase of over 0.4 in bare soil fraction. The western United States, southern South America, and southern Africa show fractional increases of more than 0.2. Simulations of CLM2 coupled with the Community Atmosphere Model (CAM2) show several regions with statistically significant decreases of up to 2 K in 2-m air temperature and up to 10 K in ground temperature, which reduces the high temperature bias in arid and semiarid regions in the model. In Australia, the vegetation changes result in an increase in net downward longwave radiation, which is balanced by an increase of latent and sensible heat fluxes and a decrease of absorbed solar radiation. © 2004 American Meteorological Society.
• Brunke, M. A., Zeng, X., Zhou, M., Fairall, C., Bond, N. A., & Lenschow, D. H. (2004). Marine Atmospheric Boundary Layer Height over the Eastern Pacific: Data Analysis and Model Evaluation. Journal of Climate, 17(21), 4159-4170. doi:10.1175/jcli3190.1
• Chase, T. N., Pielke Sr., R. A., Herman, B., & Zeng, X. (2004). Likelihood of rapidly increasing surface temperatures unaccompanied by strong warming in the free troposphere. Climate Research, 25(3), 185-190.
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  Abstract: Recent model simulations of the effects of increasing greenhouse gases combined with other anthropogenic effects predicted larger rates of warming in the mid and upper troposphere than near the Earth's surface. In multiple model comparisons we find that accelerated upper-level warming is simulated in all models for the greenhouse-gas/direct-aerosol forcing representative of 1979-2000. However, in a test of model predictive skill, a comparison with observations shows no warming of the free troposphere over this period. We assessed the likelihood that such a disparity between model projection and observations could be generated by forcing uncertainties or chance model fluctuations, by comparing all possible 22 yr temperature trends in a series of climate simulations. We find that it is extremely unlikely for near-surface air temperatures (surface temperatures) to increase at the magnitude observed since 1979 without a larger warming in the mid-troposphere. Warming of the surface relative to the mid-troposphere was also more likely in control simulations than under anthropogenic forcing. Because errors in the vertical temperature structure would be expected to create errors in water-vapor feedback, cloud cover and moisture content, these results suggest the need for great caution when applying the simulations to future climate predictions and to impact assessments. © Inter-Research 2004.
• Curry, J. A., Bentamy, A., Bourassa, M. A., Bourras, D., Bradley, E. F., Brunke, M., Castro, S., Chou, S. H., Clayson, C. A., Emery, W. J., Eymard, L., Fairall, C. W., Kubota, M., Lin, B., Perrie, W., Reeder, R. A., Renfrew, I. A., Rossow, W. B., Schulz, J., , Smith, S. R., et al. (2004). SEAFLUX. Bulletin of the American Meteorological Society, 85(3), 409-424.
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  Abstract: The SEAFLUX strategy to assess satellite flux products, and to improve the accuracy and resolution of satellite-derived sensible and latent heat fluxes, is described. Analysis shows that at present, zonal and monthly averaged flux values have significant uncertainties, based on the comparison of climatologies determined from ships, numerical weather prediction analyses, and satellite products.
• Dickinson, R. E., Zeng, X., Zeng, X., & Shen, S. S. (2004). Multiple equilibrium states and the abrupt transitions in a dynamical system of soil water interacting with vegetation: SOIL WATER INTERACTING WITH VEGETATION. Geophysical Research Letters, 31(5), n/a-n/a. doi:10.1029/2003gl018910
• Tian, Y., Dickinson, R. E., Zhou, L., Zeng, X., Dai, Y., Myneni, R. B., Knyazikhin, Y., Zhang, X., Friedl, M., Yu, H., Wu, W., & Shaikh, M. (2004). Comparison of seasonal and spatial variations of leaf area index and fraction of absorbed photosynthetically active radiation from Moderate Resolution Imaging Spectroradiometer (MODIS) and Common Land Model. Journal of Geophysical Research D: Atmospheres, 109(1), D01103 1-14.
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  Abstract: This paper compares by land cover type seasonal and spatial variations of MODIS leaf area index (LAI) and fraction of photosynthetically active radiation (0.4-0.7 μm) absorbed by vegetation (FPAR) from 2.5 years with those from the Common Land Model (CLM) and investigates possible reasons for notable differences. The FPAR value is mainly determined by LAI in MODIS and both LAI and stem area index (SAI) in CLM. On average, the model underestimates FPAR in the Southern Hemisphere and overestimates FPAR over most areas in the Northern Hemisphere compared to MODIS observations during all seasons except northern middle latitude summer. Such overestimation is most significant in winter over northern high latitudes. The MODIS LAI is generally consistent with the model during the snow-free periods but may be underestimated in the presence of snow, especially for evergreen trees. The positive FPAR bias is mainly attributed to CLM SAI of deciduous canopy and higher LAI than MODIS for evergreen canopy as well. The negative FPAR bias results from several factors, including differences in LAI and soil albedo between CLM and MODIS or limitations of the geometric optics scheme used in the model. Therefore the MODIS algorithm needs to better represent the winter LAI retrievals, while the model needs to better quantify LAI and SAI. Since stems will not have the same single-scattering albedo as green leaves, it may be inappropriate for the model to treat LAI and SAI the same in the FPAR and albedo parameterizations. If so, the role of SAI in these parameterizations needs reformulation. Copyright 2004 by the American Geophysical Union.
• Tsukernik, M., Chase, T. N., Serreze, M. C., Barry, R. G., Pielke Sr., R., Herman, B., & Zeng, X. (2004). On the regulation of minimum mid-tropospheric temperatures in the Arctic. Geophysical Research Letters, 31(6), L06112 1-4.
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  Abstract: Observations indicate a minimum mid-tropospheric Arctic winter temperature of about -45°C at 500 hPa. This minimum temperature coincides with that predicted for moist adiabatic ascent over a sea surface near its salinity-adjusted freezing point. NCAR/NCEP Reanalysis data show that convective heating maxima averaged over the 50-70°N latitude band coincide both in longitude and altitude with total horizontal energy flux maxima entering the Arctic, indicating the significance of convection over open water on the winter Arctic energy budget. NCAR CCM single column model experiments simulating convective warming of a cold airmass moving over open water and radiative cooling as it moves again over cold land/sea ice support the hypothesis that the -45°C threshold can be maintained for 10-14 days after convective warming occurs. We speculate on the implications of this regulatory mechanism on surface temperatures. Copyright 2004 by the American Geophysical Union.
• Wang, Z., Zeng, X., Barlage, M., Dickinson, R. E., Gao, F., & Schaaf, C. B. (2004). Using MODIS BRDF and albedo data to evaluate global model land surface albedo. Journal of Hydrometeorology, 5(1), 3-14.
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  Abstract: The land surface albedo in the NCAR Community Climate System Model (CCSM2) is calculated based on a two-stream approximation, which does not include the effect of three-dimensional vegetation structure on radiative transfer. The model albedo (including monthly averaged albedo, direct albedo at local noon, and the solar zenith angle dependence of albedo) is evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) and albedo data acquired during July 2001-July 2002. The model monthly averaged albedos in February and July are close to the MODIS white-sky albedos (within 0.02 or statistically insignificant) over about 40% of the global land between 60°S and 70°N. However, CCSM2 significantly underestimates albedo by 0.05 or more over deserts (e.g., the Sahara Desert) and some semiarid regions (e.g., parts of Australia). The difference between the model direct albedo at local noon and the MODIS black-sky albedo for the near-infrared (NIR) band (with wavelength > 0.7 μm) is larger than the difference for the visible band (with wavelength < 0.7 μm) for most snow-free regions. For eleven model grid cells with different dominant plant functional types, the model diffuse NIR albedo is higher by 0.05 or more than the MODIS white-sky albedo in five of these cells. Direct albedos from the model and MODIS (as computed using the BRDF parameters) increase with solar zenith angles, but model albedo increases faster than the MODIS data. These analyses and the MODIS BRDF and albedo data provide a starting point toward developing a BRDF-based treatment of radiative transfer through a canopy for land surface models that can realistically simulate the mean albedo and the solar zenith angle dependence of albedo. © 2004 American Meteorological Society.
• Zeng, X., & Er, L. u. (2004). Globally unified monsoon onset and retreat indexes. Journal of Climate, 17(11), 2241-2248.
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  Abstract: Different criteria have been used in the past to define the monsoon onset and retreat over different monsoon regions and even over different parts of the same monsoon region. Here an objective criterion is proposed to define, for the first time, globally unified summer monsoon onset (or retreat) dates using a single meteorological variable (i.e., the global daily 1× 1° normalized precipitable water data) with the threshold value being the Golden Ratio (0.618). Results are found to be consistent with those determined using long-term rainfall data over most monsoon regions. The precipitable water data have also been used to refine the definition of monsoon regions on a grid-cell-by-cell basis. The objective definitions of these basic monsoon characteristics would provide one of the necessary foundations for global monsoon research. They, along with the onset/retreat data over a 10-yr period (1988-97), would also facilitate the diagnostics and validation of global monsoon simulations. © 2004 American Meteorological Society.
• Zeng, X., Suyehiro, K., Stein, R. S., Jaumann, R., Jackson, R., Hornberger, G. M., Costa, J. E., Collins, C., Bowring, S. A., & Bougeret, J. (2004). A virtual publications forum. Eos, Transactions American Geophysical Union, 85(12), 118-118. doi:10.1029/2004eo120009
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  As part of the continuing effort to inform members about the publications program and get their input, the Publications Committee scheduled an open forum at the 2003 AGU Fall Meeting. This was to allow any members or guests the opportunity to ask questions about the AGU publications program, processes, progress, or any other publications-related concerns. Here, we are using the pages of Eos to share several “good news” messages about AGU publications and open a dialogue with the membership about the publications program. The first thing to remember about AGU publications is that historically they have supported many of the non-revenue generating activities of the Union that we hold to be important. Examples include workshops for high school teachers, career information for pre-college students and school counselors, and information for the press and for decision-makers at various levels of government. Publications are very important to the mission of AGU, both intellectually and financially (Figure 1).
• Brunke, M. A., Fairall, C. W., Zeng, X., Eymard, L., & Curry, J. A. (2003). Which bulk aerodynamic algorithms are least problematic in computing ocean surface turbulent fluxes?. Journal of Climate, 16(4), 619-635.
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  Abstract: Bulk aerodynamic algorithms are needed to compute ocean surface turbulent fluxes in weather forecasting and climate models and in the development of global surface flux datasets. Twelve such algorithms are evaluated and ranked using direct turbulent flux measurements determined from covariance and inertial-dissipation methods from 12 ship cruises over the tropical and midlatitude oceans (from about 5°S to 60°N . The four least problematic of these 12 algorithms based upon the overall ranking for this data include the Coupled Ocean-Atmosphere Response Experiment (COARE) version 3.0 and The University of Arizona (UA) schemes as well as those used at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Aeronautics and Space Administration (NASA) Data Assimilation Office for version 1 of the Goddard Earth Observing System reanalysis (GEOS-1). Furthermore, the four most problematic of these algorithms are also identified along with possible explanations. The overall ranking is not substantially affected by the use of the average of covariance and inertial-dissipation flux measurements or by taking into consideration measurement uncertainties. The differences between computed and observed fluxes are further evaluated as a function of near-surface wind speed and sea surface temperature to understand the rankings. Finally, several unresolved issues in terms of measurement and algorithm uncertainties are raised.
• Dai, Y., Zeng, X., Dickinson, R. E., Baker, I., Bonan, G. B., Bosilovich, M. G., Denning, A. S., Dirmeyer, P. A., Houser, P. R., Niu, G., Oleson, K. W., Schlosser, C. A., & Yang, Z. (2003). The common land model. Bulletin of the American Meteorological Society, 84(8), 1013-1023.
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  Abstract: Scientists from several institutions and with different research backgrounds have worked together to develop a prototype modular land model for weather forecasting and climate studies. The resultant model, called Common Land Model (CLM), is now available for public use and further development. The model includes three elements, including, the core single-column soil-snow-vegetation biophysical code, the land boundary data, and the scaling procedures within a climate model required to interface atmospheric model grid-square inputs to land single-column processes.
• Dickinson, R. E., Wang, G., Zeng, X., & Zeng, Q. (2003). How does the partitioning of evapotranspiration and runoff between different processes affect the variability and predictability of soil moisture and precipitation?. Advances in Atmospheric Sciences, 20(3), 475-478.
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  Abstract: Water stored as part of the land surface is lost to evapotranspiration and runoff on different time scales, and the partitioning between these time scales is important for modeling soil water in a climate model. Different time scales are imposed on evapotranspiration primarily because it is derived from different reservoirs with different storage capacities, from the very rapid evaporation of canopy stores to the slow removal by transpiration of rooting zone soil moisture. Runoff likewise ranges in time scale from rapid surface terms to the slower base-flow. The longest time scale losses of water determine the slow variation of soil moisture and hence the longer time scale effects of soil moisture on precipitation. This paper shows with a simple analysis how shifting the partitioning of evapotranspiration between the different reservoirs affects the variability of soil moisture and precipitation. In particular, it is concluded that a shift to shorter time scale reservoirs shifts the variance of precipitation from that which is potentially predictable to unpredictable.
• Pan, X., Zeng, X., Zhang, J., Shi, Q., Qing, H. e., Chao, Q., & Chao, J. (2003). Preliminary study on the relationship between temporal and spatial evolution of ecological landscape pattern and climate change in Xinjiang, China. Proceedings of SPIE - The International Society for Optical Engineering, 4890(1), 58-73.
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  Abstract: Fractional vegetation cover data (FVC) based on the annual maximum NOAA/AVHRR NDVI (Advanced Very High Resolution Radiometer normalized difference vegetation index) data and the ground meteorological data have been used to analyze the relationship between the temporal and spatial evolution of ecological landscape pattern and climate change in Xinjiang autonomous region, China from 1982 to 1993. It is found that during this period, the averaged oasis cropland or low-damp forest-shrub meadow area occupies 7.50% of the whole region, desert dune/barren desert 25.70%; temperate semi-arbor desert 21.70%; temperate shrub and semi-shrub desert 8.36%; alpine subalpine desert steppe 7.71%; temperate gramineous and ruderal steppe 7.63%; mountain forest steppe 2.13%; high-cold barren 8.93%; high-cold low semi-shrub desert 9.08%; water/ice 1.26%. Compared with the 30-year (1961-1990) climatology, the 12-year averaged annual surface air temperature and precipitation over the whole region increase by 0.28 °C and 23.6 mm respectively. The maximum increase of precipitation does not occur over the mountain region; instead it occurs over the region with a concentrated distribution of oases, suggesting the positive role of oases in adjusting regional climate. The area of temporal steppe also increases with the increase of precipitation and temperature. Together, these results demonstrate that, during the 12-year period, the condition of vegetation cover has been improved and large-scale desertification does not occur in Xinjiang.
• Zeng, X., Rao, P., DeFries, R. S., & Hansen, M. C. (2003). Interannual variability and decadal trend of global fractional vegetation cover from 1982 to 2000. Journal of Applied Meteorology, 42(10), 1525-1530.
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  Abstract: Fractional vegetation cover (FVC) is one of the most important variables in land surface modeling and also provides a continuous field to complement discrete land cover classification. A global 8-km FVC dataset for 1982-2000 is derived using the NOAA-NASA land Pathfinder normalized difference vegetation index data. The confidence in the dataset is provided by the insensitivity of the algorithm to the data resolution (between 1 and 8 km), the good agreement of the results with the field survey data over Germany, the consistency of the results with previous observational studies over the savannas in North Africa and the forests in Bolivia, and the robustness of the algorithm, as demonstrated by the small interannual variability of FVC over areas where anthropogenic land cover change is expected to be small, based on the 30-m Landsat data analysis. Significant interannual variability is found over shrubland, savanna, and grassland; both positive and negative trends exist over different areas of the same region in many parts of the world. In particular, the trend analysis pinpoints areas with statistically significant trends (i.e., "hotspots") for further study using higher-resolution satellite data and field-survey data.
• Zhou, L., Dickinson, R. E., Tian, Y., Zeng, X., Dai, Y., Yang, Z. -., Schaaf, C. B., Gao, F., Jin, Y., Strahler, A., Myneni, R. B., Yu, H., Wu, W., & Shaikh, M. (2003). Comparison of seasonal and spatial variations of albedos from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Common Land Model. Journal of Geophysical Research D: Atmospheres, 108(15), ACL 15-1 - ACL 15-20.
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  Abstract: This paper compares seasonal and spatial variations of Moderate Resolution Imaging Spectroradiometer (MODIS) albedos with those from the Common Land Model (CLM) by land cover type. MODIS albedo data in the year 2001 were used to determine seasonal, spatial, and land cover dependence at 1 km resolution and to investigate the biases in CLM. Albedo dependence on vegetation type is smaller than that on snow and soil. Snow causes the largest temporal and spatial variations, especially in the visible band (0.3-0.7 μm). CLM has visible albedos that are lower by up to 0.4-0.5 in winter over northern high latitudes but are globally higher by 0.02-0.04 in summer over most vegetation, mainly due to its overestimated leaf and stem area index in winter and slightly higher prescribed canopy albedos in summer, respectively. MODIS and CLM differ considerably in soil albedo over desert and semidesert regions, especially in the near-infrared band (0.7-5.0 μm), with the largest low bias of about 0.1 in the Sahara. Adjustments of the prescribed albedos in CLM based on MODIS observations could reduce such biases. Therefore the model should better represent leaf and stem area index, vegetation albedo in the presence of snow, and soil albedo. Copyright 2003 by the American Geophysical Union.
• Bonan, G. B., Oleson, K. W., Vertenstein, M., Levis, S., Zeng, X., Dai, Y., Dickinson, R. E., & Yang, Z. (2002). The land surface climatology of the community land model coupled to the NCAR community climate model. Journal of Climate, 15(22), 3123-3149.
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  Abstract: The land surface parameterization used with the community climate model (CCM3) and the climate system model (CSM 1), the National Center for Atmospheric Research land surface model (NCAR LSM 1), has been modified as part of the development of the next version of these climate models. This new model is known as the community land model (CLM2). In CLM2, the surface is represented by five primary subgrid land cover types (glacier, lake, wetland, urban, vegetated) in each grid cell. The vegetated portion of a grid cell is further divided into patches of up to 4 of 16 plant functional types, each with its own leaf and stem area index and canopy height. The relative area of each subgrid unit, the plant functional type, and leaf area index are obtained from 1-km satellite data. The soil texture dataset allows vertical profiles of sand and clay. Most of the physical parameterizations in the model were also updated. Major model differences include: 10 layers for soil temperature and soil water with explicit treatment of liquid water and ice; a multilayer snowpack; runoff based on the TOPMODEL concept; new formulation of ground and vegetation fluxes: and vertical root profiles from a global synthesis of ecological studies. Simulations with CCM3 show significant improvements in surface air temperature, snow cover, and runoff for CLM2 compared to LSM1. CLM2 generally warms surface air temperature in all seasons compared to LSM1, reducing or eliminating many cold biases. Annual precipitation over land is reduced from 2.35 mm day-1 in LSM1 to 2.14 mm day-1 in CLM2. The hydrologic cycle is also different. Transpiration and ground evaporation are reduced. Leaves and stems evaporate more intercepted water annually in CLM2 than LSM1. Global runoff from land increases from 0.75 mm day-1 in LSM1 to 0.84 mm day-1 in CLM2. The annual cycle of runoff is greatly improved in CLM2, especially in arctic and boreal regions where the model has low runoff in cold seasons when the soil is frozen and high runoff during the snowmelt season. Most of the differences between CLM2 and LSM1 are attributed to particular parameterizations rather than to different surface datasets. Important processes include: multilayer snow, frozen water, interception, soil water limitation to latent heat, and higher aerodynamic resistances to heat exchange from ground.
• Brunke, M. A., Zeng, X., & Anderson, S. (2002). Uncertainties in sea surface turbulent flux algorithms and data sets. Journal of Geophysical Research C: Oceans, 107(10), 5-1.
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  Abstract: An intercomparison of eight bulk sea surface turbulent flux algorithms used in data set generation as well as weather and climate prediction is performed for the tropical Pacific and midlatitude Atlantic. The results show some significant differences in fluxes due to differences in the way the algorithms consider wave spectrum, convective gustiness, and salinity as well as the way the algorithms parameterize roughness lengths and turbulent exchange coefficients. For instance, for sea surface temperature between 27.75°C and 28.25°C, the maximum differences in monthly latent heat flux and wind stress among algorithms over the tropical Pacific are about 23 W m-2 (or 16% relative to the algorithm-averaged flux) and 0.013 N m-2 (or 19% relative to the algorithm-averaged value) respectively. Evaluation of these algorithms using 270 hourly samples of observed turbulent flux data over the midlatitude Pacific shows that algorithms are largely consistent with observations. However, some algorithms show significant deviations from observations under certain conditions (e.g., weak wind conditions). Insights from the above intercomparison are then used to evaluate ocean surface turbulent fluxes from two global data sets, one is derived from satellite remote sensing while the other is a reanalysis. Over two buoy sites in the eastern and western tropical Pacific, the mean heat flux differences between the two data sets are primarily caused by differences in bulk variables (e.g., wind speed) rather than by differences in bulk algorithms. However, bulk algorithm differences could contribute up to 17 W m-2 to the long-term averaged latent heat flux over the tropical Pacific if different algorithms were used. This suggests that both bulk algorithms and the deviation of environmental variables need to be further improved in order to produce ocean surface turbulent fluxes with an accuracy of 10 W m-2.
• Buermann, W., Wang, Y., Dong, J., Zhou, L., Zeng, X., Dickinson, R. E., Potter, C. S., & Myneni, R. B. (2002). Analysis of a multiyear global vegetation leaf area index data set. Journal of Geophysical Research D: Atmospheres, 107(22), 14-1-14-16.
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  Abstract: The analysis of a global data set of monthly leaf area index (LAI), derived from satellite observations of normalized difference vegetation index (NDVI) for the period July 1981 to September 1994, is discussed in this paper. Validation of this retroactive, coarse resolution (8 km) global multiyear data set is a challenging task because repetitive ground measurements from all representative vegetation types are not available. Therefore the magnitudes and interannual variations in the derived LAI fields were assessed as follows. First, the use of a NDVI-based algorithm, as opposed to a more physically based approach, is estimated to result in relative errors in LAI of about 10-20%, which is comparable to the mean uncertainty of AVHRR NDVI data. Second, the satellite LAI values compared reasonably well to ground measurements from three field campaigns. Third, comparison with an existing multiyear LAI data set showed qualitative agreement with regards to interannual variability, although the LAI values of the earlier data were consistently larger than those derived here. Fourth, interannual variations in LAI were evaluated through correlations with climate data sets, e.g., sea surface temperatures and precipitation in tropical semiarid regions known for ENSO impacts, temperature dependence of vegetation growth, and therefore LAI, in the northern latitudes. The general consistency between these independent data sets imbues confidence in the LAI data set, at least for use in large-scale modeling studies. Finally, improvements in near-surface climate simulation are documented in a companion article when satellite LAI values were used in a global climate model. The data set is available to the community via our Web server (http://cybele.bu.edu). Copyright 2002 by the American Geophysical Union.
• Chase, T. N., Herman, B., Pielke Sr., R. A., Zeng, X., & Leuthold, M. (2002). A proposed mechanism for the regulation of minimum midtropospheric temperatures in the Arctic. Journal of Geophysical Research D: Atmospheres, 107(14), 2-1-2-7.
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  Abstract: This paper documents an observed lower extreme of midtropospheric (500 mbar) temperatures in the Arctic of approximately -45°C during the winter season in several data sets. Each data set shows that the coldest air masses in the Arctic reach -45°C during the fall months but seldom get much colder even into late winter despite a continued net radiative loss. We demonstrate that midtropospheric temperatures are significantly skewed toward warmer temperatures, indicating a regulatory mechanism at work. We further provide evidence that minimum Arctic midtropospheric temperatures are regulated by moist convective processes and that minimum 500 mbar temperatures are controlled to a large extent by high-latitude sea surface temperatures. The temperature -45°C is the expected 500 mbar temperature in an atmosphere regulated by moist adiabatic ascent from a surface temperature of l°-2° below 0°C, the approximate freezing point of seawater. This implies that Arctic air masses are regularly in contact with unfrozen seawater to the south, an easily verified observation. Climate model simulations of the effects of increased greenhouse gasses hypothesize that high, northern latitude regions should warm at a faster rate than the globe as a whole, a hypothesis which does not appear to have strong observational support. We discuss the implications of this result for the accelerated Arctic warming hypothesis. Copyright 2002 by the American Geophysical Union.
• Jin, Y., Schaaf, C. B., Gao, F., Xiaowen, L. i., Strahler, A. H., Zeng, X., & Dickinson, R. E. (2002). How does snow impact the albedo of vegetated land surfaces as analyzed with MODIS data?. Geophysical Research Letters, 29(10), 12-1 - 12-4.
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  Abstract: Albedo derived from MODIS observations is found to be very stable during November 2000-January 2001. We analyze shortwave albedo under snow and snow-free conditions by IGBP land cover types. Snow changes the spectral property of the surface reflectivity and causes high heterogeneity in the surface albedo between and within land types. The mean black sky (or direct beam) albedo at local solar noon for snow-covered forests is less than 0.30 in the shortwave (0.3-5.0 μm), but it reaches 0.57 for snow-covered grassland and barren. Although we are unable to further separate within-class albedos with fractional tree cover, we find that the normalized difference snow index (NDSI) is highly correlated with surface albedo and hence can be taken as a measure of snow, soil and canopy fraction.
• Tsvetsinskaya, E. A., Schaaf, C. B., Gao, F., Strahler, A. H., Dickinson, R. E., Zeng, X., & Lucht, W. (2002). Relating MODIS-derived surface albedo to soils and rock types over Northern Africa and the Arabian peninsula. Geophysical Research Letters, 29(9), 67-1 - 67-4.
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  Abstract: We use the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra spacecraft to derive surface albedo for the arid areas of Northern Africa and the Arabian peninsula. Albedo in seven MODIS spectral bands for land and three broad bands (for shortwave, near infrared, and visible portions of the spectrum) is produced. Surface albedo is derived from MODIS observations during a sixteen-day period and is analyzed at 1 km spatial resolution. MODIS data show considerable spatial variability of surface albedo in the study region that is related to soil and geological characteristics of the surface. For example, solar shortwave white-sky albedo varies by a factor of about 2.5 from the darkest volcanic terrains to the brightest sand sheets. Vegetation contribution to surface reflectance is essentially negligible since we only considered pixels with under ten percent fractional canopy cover. Few, if any, coupled land- atmosphere global or regional models capture this observed spatial variability in surface reflectance or albedo. Here we suggest a scheme that relates soil groups (based on the United Nations Food and Agriculture Organization, FAO, soil classification) and rock types (based on the United States Geological Survey, USGS, geological maps) to MODIS derived surface albedo statistics. This approach is a first step towards the incorporation of the observed spatial variability in surface reflective properties into climate models.
• Zeng, X., Dickinson, R. E., Tsvetsinskaya, E. A., Schaaf, C. B., Gao, F., Strahler, A. H., & Lucht, W. (2002). Relating MODIS-derived surface albedo to soils and rock types over Northern Africa and the Arabian peninsula: RELATING MODIS-DERIVED SURFACE ALBEDO TO SOILS AND ROCK TYPES. Geophysical Research Letters, 29(9), 67-1-67-4. doi:10.1029/2001gl014096
• Zeng, X., Pielke, R. A., Herman, B. M., & Chase, T. N. (2002). More Heat Over Greenhouse Gases. Physics Today, 55(5), 14-14. doi:10.1063/1.1485563
• Zeng, X., Shajkh, M., Dai, Y., Dickinson, R. E., & Myneni, R. (2002). Coupling of the Common Land Model to the NCAR Community Climate Model. Journal of Climate, 15(14), 1832-1854.
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  Abstract: The Common Land Model (CLM), which results from a 3-yr joint effort among seven land modeling groups, has been coupled with the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3). Two 15-yr simulations of CCM3 coupled with CLM and the NCAR Land Surface Model (LSM), respectively, are used to document the relative impact of CLM versus LSM on land surface climate. It is found that CLM significantly reduces the summer cold bias of surface air temperature in LSM, which is associated with higher sensible heat fluxes and lower latent heat fluxes in CLM, and the winter warm bias over seasonally snow-covered regions, especially in Eurasia. CLM also significantly improves the simulation of the annual cycle of runoff in LSM. In addition, CLM simulates the snow mass better than LSM during the snow accumulation stage. These improvements are primarily caused by the improved parameterizations in runoff, snow, and other processes (e.g., turbulence) in CLM. The new land boundary data (e.g., leaf-area index, fractional vegetation cover, albedo) also contribute to the improvement in surface air temperature simulation over some regions. Overall, CLM has little impact on precipitation and surface net radiative fluxes.
• Zeng, X., Zhang, Q., Johnson, D., & Tao, W. -. (2002). Parameterization of wind gustiness for the computation of ocean surface fluxes at different spatial scales. Monthly Weather Review, 130(8), 2125-2133.
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  Abstract: Analysis of the Goddard cloud-ensemble (GCE) model output forced by observational data over the tropical western Pacific and eastern tropical North Atlantic has shown that ocean surface latent and sensible heat fluxes averaged in a typical global-model grid box are reproduced well using bulk algorithms with grid-box-average scalar wind speed but could be significantly underestimated under weak wind conditions using average vector wind speed. This is consistent with previous observational and modeling studies. The difference between scalar and vector wind speeds represents the subgrid wind variability (or wind gustiness) that is contributed by boundary layer large eddies, convective precipitation, and cloudiness. Based on the GCE data analysis for a case over the tropical western Pacific, a simple parameterization for wind gustiness has been developed that considers the above three factors. This scheme is found to fit well the GCE data for two other cases over the tropical western Pacific and eastern tropical North Atlantic. Its fit is also much better than that of the traditional approach that considers the contribution to wind gustiness by boundary layer large eddies alone. A simple formulation has also been developed to account for the dependence of the author's parameterization on spatial scales (or model grid size). Together, the preliminary parameterization and formulation can be easily implemented into weather and climate models with various horizontal resolution.
• Buermann, W., Dong, J., Zeng, X., Myneni, R. B., & Dickinson, R. E. (2001). Evaluation of the utility of satellite-based vegetation leaf area index data for climate simulations. Journal of Climate, 14(17), 3536-3550.
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  Abstract: In this study the utility of satellite-based leaf area index (LAI) data in improving the simulation of near-surface climate with the NCAR Community Climate Model, version 3 (CCM3), GCM is evaluated. The use of mean LAI values, obtained from the Advanced Very High Resolution Radiometer Pathfinder data for the 1980s, leads to notable warming and decreased precipitation over large parts of the Northern Hemisphere lands during the boreal summer. Such warming and decreased rainfall reduces discrepancies between the simulated and observed near-surface temperature and precipitation fields. The impact of interannual vegetation extremes observed served during the 1980s on near-surface climate is also investigated by utilizing the maximum and minimum LAI values from the 10-yr LAI record. Surface energy budget analysis indicates that the dominant impact of interannual LAI variations is modification of the partitioning of net radiant energy between latent and sensible heat fluxes brought about through changes in the proportion of energy absorbed by the vegetation canopy and the underlying ground and not from surface albedo changes. The enhanced latent heat activity in the greener scenario leads to an annual cooling of the earth land surface of about 0.3°C, accompanied by an increase in precipitation of 0.04 mm day-1. The tropical evergreen forests and temperature grasslands contribute most to this cooling and increased rainfall. These results illustrate the importance and utility of satellite-based vegetation LAI data in simulations of near-surface climate variability.
• Wei, X., Hahmann, A. N., Dickinson, R. E., Yang, Z., Zeng, X., Schaudt, K. J., Schaaf, C. B., & Strugnell, N. (2001). Comparison of albedos computed by land surface models and evaluation against remotely sensed data. Journal of Geophysical Research D: Atmospheres, 106(D18), 20687-20702.
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  Abstract: The albedos of two land surface models, the Biosphere-Atmosphere Transfer Scheme (BATS) and the NCAR Land Surface Model (LSM), are compared with remotely sensed data and each other. The model albedos differ primarily because of their assumptions about and model differences in soil moisture content, soil color, snow albedo, shading of snow by canopy, and prescribed parameters for each land cover type. Global albedo maps for February and July 1995, developed from the advanced very high resolution radiometer (AVHRR) data, are used to evaluate model albedos. The models display a high bias as compared to the remotely sensed values in desert and semidesert regions. Over North Africa, LSM, whose albedos were previously tuned to data from the Earth Radiation Budget Experiment (ERBE), has the highest albedos. Elsewhere, and overall, BATS has the highest bias for desert and semidesert regions. Both models demonstrate a high bias over regions of winter snow, where the AVHRR data are expected to have a negative bias. LSM has especially high winter albedos, apparently because of intercepted snow increasing its canopy albedo. Copyright 2001 by the American Geophysical Union.
• Zeng, X. (2001). Global vegetation root distribution for land modeling. JOURNAL OF HYDROMETEOROLOGY, 2(5), 525-530.
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  Vegetation root distribution is one of the factors that determine the overall water holding capacity of the land surface and the relative rates of water extraction from different soil layers for vegetation transpiration. Despite its importance, significantly different root distributions are used by different land surface models. Using a comprehensive global field survey dataset, vegetation root distribution (including rooting depth) has been developed here for three of the most widely used land cover classifications [i.e., the Biosphere-Atmosphere Transfer Scheme (BATS), International Geosphere-Biosphere Program (IGBP), and version 2 of the Simple Biosphere Model (SiB2)] for direct use by any land model with any number of soil layers.
• Zhang, Q., Zeng, X., Dickinson, R., Johnson, D., & Tao, W. (2001). Progress in the parameterization of mesoscale enhancement of ocean surface fluxes in large-scale models. Chinese J. Oceanogr., 23, 132-142.
• Lenschow, D. H., Zhou, M., Zeng, X., Chen, L., & Xiangde, X. u. (2000). Measurements of fine-scale structure at the top of marine stratocumulus. Boundary-Layer Meteorology, 97(2), 331-357.
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  Abstract: During the Dynamics and Chemistry of the Marine Stratocumulus (DYCOMS) experiment in July-August 1985, the NCAR Electra aircraft flew a series of flight legs just at the top of the marine stratocumulus cloud decks that cap the mixed layer off the coast of southern California. Because of the corrugated structure of the cloud-top, the aircraft, which was flown at a nearly constant level and adjusted only to maintain its altitude at the average cloud-top height, was alternately within and above the clouds - roughly half the time in each domain. These legs were used to examine the structure of the cloud-top by compositing the segments on either side of the cloud/clear-air interface, which was identified by the transitions of liquid water measured by the Forward Scattering Spectrometer Probe (either increasing or decreasing) through a threshold of 0.04 x 10-3 kg m-3. An equivalent vertical distance (EVD) from the cloud-top was obtained from the horizontal flight legs by estimating the average slope of the cloud-top from the cloud-top radiation temperature. The results show that a near discontinuity occurs in variables across cloud top over an EVD of 0.3 m, but that above this, the air has already been modified by boundary-layer air. Thus, cloud-top is not the limit of mixing of boundary-layer air. This mixing may extend to tens of metres or more. The bulk Richardson number in the vicinity of cloud-top increases from near zero within the cloud to about 1.2 at an EVD of 3-6 m above cloud. Fluctuations of the three velocity components within cloud are nearly equal; above cloud the vertical component structure function is about half the horizontal components. The scalar structure functions are about an order of magnitude higher above cloud than in cloud. The structure parameters of temperature and humidity measured just below cloud-top agree reasonably well with predicted values based on a previously-developed model for the clear convective boundary layer. Above cloud, the scalar structure parameters are much larger, but their interpretation is questionable, since this region does not contain isotropic turbulence.
• Zeng, X., Dickinson, R. E., Walker, A., Shaikh, M., Defries, R. S., & Jiaguo, Q. i. (2000). Derivation and evaluation of global 1-km fractional vegetation cover data for land modeling. Journal of Applied Meteorology, 39(6), 826-839.
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  Abstract: Fractional vegetation cover (σv) is needed in the modeling of the land-atmosphere exchanges of momentum, energy, water, and trace gases. From global 1-km, 10-day composite Advanced Very High Resolution Radiometer normalized difference vegetation index (NDVI) data from April 1992 to March 1993, global 1-km σv is derived based on the annual maximum NDVI value for each pixel in comparison with the NDVI value that corresponds to 100% vegetation cover for each International Geosphere-Biosphere Program land cover type. This dataset is pixel dependent but season independent, with the seasonal variation of vegetation greenness in a pixel accounted for by the leaf area index. The authors' algorithm is found to be insensitive to the use of a specific land cover classification. In comparison with an independent dataset derived by DeFries et al. by using a more sophisticated statistical approach, the current dataset has a similar spatial distribution but systematically smaller σv (particularly over shrublands and barren land cover). It also gives σv values that overall are consistent with those derived from higher-resolution aircraft and satellite data over Arizona and field-survey data over Germany.
• Zhao, M., & Zeng, X. (2000). Some problems in the computation of ocean surface moisture and heat fluxes in atmospheric models. Chinese J. Meteor., 58, 340-346.
• Zeng, X. (1999). The relationship among precipitation, cloud-top temperature, and precipitable water over the tropics. Journal of Climate, 12(8 PART 2), 2503-2514.
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  Abstract: The relationship of monthly precipitation P to precipitable water w and cloud-top temperature as represented by the Geostationary Operational Environmental Satellite (GOES) Precipitation Index (GPI) is obtained over tropical land, coast, and ocean: P = exp[a1(w - a2)] GPI, where coefficients a1 and a2 are determined using one year of the Global Precipitation Climatology Project (GPCP) monthly rain gauge data and then independently tested using four other years of gauge data. This algorithm, over land, gives more accurate precipitation estimates than are obtained using the cloud-top temperature alone (i.e., GPI) and is as accurate as the state-of-the-art multisatellite algorithm (MS) from GPCP. Over coastal and oceanic regions, this algorithm has a smaller bias in precipitation estimation than GPI but has the same correlation coefficient with gauge data as GPI. Compared with MS, it has a much smaller bias but larger mean absolute deviation. Evaluation using the Pacific atoll-island gauge data also shows that this algorithm can reproduce well the observed meridional distribution of precipitation across the ITCZ and SPCZ near the date line. This algorithm is then used to produce a five-year (January 1988-December 1992) 2.5°X 2.5°integrated dataset of precipitation and precipitable water between 40°N and 40°S for climate model evaluation. The small bias of this algorithm (particularly over ocean) also suggests that it would be a good data source for precipitation merging algorithms.
• Zeng, X., Zhao, M., Dickinson, R. E., & Yanping, H. e. (1999). A multiyear hourly sea surface skin temperature data set derived from the TOGA TAO bulk temperature and wind speed over the tropical Pacific. Journal of Geophysical Research C: Oceans, 104(C1), 1525-1536.
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  Abstract: A theoretical relationship is derived to estimate the sea surface skin temperature from near-surface wind speed and the diurnal variation of sea surface bulk (or bucket) temperature. Coefficients in the relation are determined using the R/V Franklin data during the Tropical Ocean-Global Atmosphere (TOGA) Coupled Ocean-Atmosphere Response Experiment (COARE). In contrast to previous methods, surface energy flux data are not explicitly required but rather are implied by the temporal variation of bulk temperature. A multiyear hourly skin temperature data set is obtained using data of bulk temperature at 1-m depth and wind speed from the TOGA Tropical Atmosphere-Ocean (TAO) moored buoys spanning the tropical Pacific Ocean from 95°W in the eastern Pacific to 137°E in the western Pacific between 9°N and 8°S. The diurnal amplitude of skin temperature reaches its maximum of about 2.8 K for daily averaged wind speed between 1-2 m s -1 and skin temperature between 20°-21°C and decreases with greater wind speeds. The most frequent amplitude is about 0.5 K, the average amplitude is 0.65 K, and the accumulated frequency for amplitudes greater than 1 K is 10% within the parameter space of daily averaged wind speed between 1 and 15 m s -1 and daily averaged skin temperature between 18° and 34°C. Copyright 1999 by the American Geophysical Union.
• Zhao, M., & Zeng, X. (1999). A diagnostic study of the relationship between surface fluxes and environmental variables over the tropical western Pacific. J. Tropical Meteor., 5, 214-224.
• Chen, M., Zeng, X., & Dickinson, R. E. (1998). Adjustment of GCM precipitation intensity over the United States. Journal of Applied Meteorology, 37(9), 876-887.
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  Abstract: A regression equation is developed to adjust the simulated monthly averaged intensity of hourly precipitation over the continental United States using air temperature at the first model level (about 80 m above ground) simulated by a revised version of NCAR's Community Climate Model version 2 coupled with the Biosphere-Atmosphere Transfer Scheme. The adjusted precipitation intensity is in much closer agreement with the locally observed precipitation intensity, both in pattern and magnitude, than is the simulated intensity produced by climate models The multiresponse randomised block permutation analysis shows that the authors' adjustment method is statistically significant The equation is robust with respect to seasonal and interannual variations, as demonstrated by applying it to independent months of different years. The relationship between precipitation intensity and near-surface air temperature likely reflects a linkage among precipitation, precipitable water, and vertical velocity. It can be applied to estimate fractional precipitation coverage with temporal and spatial variability over the continental United States, and to help statistically construct a time series of local precipitation events both for the present climate and for the studies of climate change.
• Pielke Sr., R. A., Avissar, R., Raupach, M., Dolman, A. J., Zeng, X., & Denning, A. S. (1998). Interactions between the atmosphere and terrestrial ecosystems: influence on weather and climate. Global Change Biology, 4(5), 461-475.
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  Abstract: This paper overviews the short-term (biophysical) and long-term (out to around 100 year timescales; biogeochemical and biogeographical) influences of the land surface on weather and climate. From our review of the literature, the evidence is convincing that terrestrial ecosystem dynamics on these timescales significantly influence atmospheric processes. In studies of past and possible future climate change, terrestrial ecosystem dynamics are as important as changes in atmospheric dynamics and composition, ocean circulation, ice sheet extent, and orbit perturbations.
• Zeng, X., & Dickinson, R. E. (1998). Effect of surface sublayer on surface skin temperature and fluxes. Journal of Climate, 11(4), 537-550.
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  Abstract: The surface sublayer is the layer of air adjacent to the surface where the transfer of momentum and heat by molecular motion becomes important. Equations are derived to incorporate this surface sublayer (or the variable ratio of the roughness length for momentum over that for heat, Zo/Zoh) over bare soil into a commonly used formulation for aerodynamic transfer coefficients. Along with the consideration of the laminar layer around vegetation leaves in the Biosphere-Atmosphere transfer Scheme (BATS), these equations provide a consistent approach for the computation of surface fluxes over bare soil or vegetated surface. Qualitative and quantitative analysis show that the surface sublayer tends to substantially increase the surface skin temperature for a given sensible heat flux and decrease the heat flux for a given surface versus air temperature difference. Using a climate model output as the atmospheric forcing data for BATS over a semiarid region, it is also found that the surface sublayer significantly increases the monthly and July-averaged hourly surface skin temperature and decreases surface sensible heat and net radiation fluxes. Comparison with limited observations of Zo/Zoh also suggests that the same (or different) exchange coefficients should be used over bare soil and vegetated portions in a grid box for dense canopies (eg grassland or forest [or sparse canopies (eg semiarid regions)].
• Zeng, X., & Dickinson, R. E. (1998). Impact of diurnally-varying skin temperature on surface fluxes over the tropical Pacific. Geophysical Research Letters, 25(9), 1411-1414.
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  Abstract: Multi-year hourly data of air temperature, wind speed, and humidity from the TOGA TAO moored buoys over the tropical Pacific along with our derived hourly sea surface skin temperature data are analyzed to show that there are substantial diurnal variations of monthly averaged surface fluxes of latent heat, sensible heat, and momentum (eg, one-third of the cases show monthly averaged latent heat diurnal amplitudes greater than 20 Wm-2). Daily or monthly average surface temperatures cannot provide such flux variations, suggesting that numerical modeling may require the inclusion of the diurnal variation of surface skin temperature.
• Zeng, X., Dai, Y., Dickinson, R. E., & Shaikh, M. (1998). The role of root distribution for climate simulation over land. Geophysical Research Letters, 25(24), 4533-4536.
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  Abstract: A comprehensive global root database is used to derive vertical root distribution and rooting depth for various vegetation categories in one of the most widely-used land models; i.e., the Biosphere-Atmosphere Transfer Scheme (BATS). Using a variety of observational datasets, observed root distribution is found to significantly improves the offline simulation of surface water and energy balance. Global climate modeling further demonstrates that observed root distribution primarily affects latent heat flux and soil wetness over tropical and midlatitude land, respectively.
• Zeng, X., Zhao, M., & Dickinson, R. E. (1998). Intercomparison of bulk aerodynamic algorithms for the computation of sea surface fluxes using TOGA COARE and TAO data. Journal of Climate, 11(10), 2628-2644.
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  Abstract: A bulk aerodynamic algorithm is developed for all stability conditions for the computation of ocean surface fluxes. It provides roughness lengths of wind, humidity, and temperature for a wind speed range from 0 to 18 m s-1: z(o) = 0.013u(*)2/g + 0.11ν/u(*) and ln(z(o)/z(ot)) = ln(z(o)/z(oq)) = 2.67Re(*)(1/4) - 2.57 as derived using the Tropical Oceans Global Atmosphere (TOGA) Coupled Ocean-Atmosphere Response Experiment (COARE) data constrained by other observations under high wind conditions. Using the TOGA COARE ship data and the multiyear hourly TOGA Tropical Atmosphere-Ocean moored buoy data, intercomparison of six different algorithms, which are widely used in research, operational forecasting, and data reanalysis, shows that algorithms differ significantly in heat and momentum fluxes under both very weak and very strong wind conditions, but agree with each other under moderate wind conditions. Algorithms agree better for wind stress than for heat fluxes. Based on past observations, probable deficiencies in roughness lengths (or neutral exchange coefficients) of some of the algorithms are identified along with possible solutions, and significant issues (particularly the trend of the neutral exchange coefficient for heat with wind speed under strong wind conditions) are raised for future experiments. The vapor pressure reduction of 2% over saline seawater has a significant impact on the computation of surface latent heat flux under strong wind conditions and should be considered in any bulk aerodynamic algorithm.
• Pielke, R. A., Zeng, X., Lee, T. J., & Dalu, G. A. (1997). Mesoscale fluxes over heterogeneous flat landscapes for use in larger scale models. Journal of Hydrology, 190(3-4), 317-336.
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  Abstract: We have developed a framework to parameterize mesoscale fluxes of heat, moisture, and momentum, in a cloud-free environment, which result from heterogeneous heating of flat land surfaces. The importance and parameterizability of these mesoscale fluxes is demonstrated using the mathematical concept of predictability. This methodology is used to estimate the relative importance of mesoscale, as contrasted with turbulent fluxes, in the Konza Prairie of Kansas during the FIFE field experiment.
• Chen, M., Dickinson, R. E., Zeng, X., & Hahmann, A. N. (1996). Comparison of precipitation observed over the continental United States to that simulated by a climate model. Journal of Climate, 9(9), 2233-2249.
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  Abstract: This study compares monthly average frequency, intensity, and amount of hourly precipitation simulated by National Center for Atmospheric Research Community Climate Model version 2/Biosphere-Atmosphere Transfer Scheme to the smoothed estimates of those observed locally over the continental United States. The observed monthly intensities vary from less than 1 to 5 mm h-1, with lowest values in the winter in northern midcontinent and highest around the Gulf Coast in summer. Model intensities are on the average 3-4 times less when drizzle is excluded and an order of magnitude less when drizzle is included. As might be anticipated, relative frequencies are much too high and intensities much too low in the model fields, compared to those observed. The spatial pattern of these quantities and the total precipitation are more realistic. The study also compares extreme events and diurnal and seasonal variations and finds that, in general, the simulated precipitation has larger spatial variability, larger diurnal variation, and longer maximum continuous wet and dry periods than those observed. These discrepancies are largely due to the different nature of model (area averaged) precipitation and observed (local) precipitation. Therefore, the use of GCM output to directly represent local values of intensities and frequencies may lead to large errors in the coupling of the land surface to the atmosphere above it.
• Dalu, G. A., Pielke, R. A., Baldi, M., & Zeng, X. (1996). Heat and momentum fluxes induced by thermal inhomogeneities with and without large-scale flow. Journal of the Atmospheric Sciences, 53(22), 3286-3302.
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  Abstract: The authors present an analytical evaluation of the vertical heat and momentum fluxes associated with mesoscale flow generated by periodic and isolated thermal inhomogeneities within the convective boundary layer (CBL). The influence of larger-scale wind flow is also included. The results show that, with little or no synoptic wind, the vertical velocity is in phase with the diabatic temperature perturbations and that the mesoscale heat flux is positive and of the same order as the diabatic heat flux within the CBL. Above the CBL, the heat flux is negative and penetrates into the free atmosphere through a depth comparable to the depth of the CBL. In the presence of synoptic flow, the mesoscale perturbation is in the form of propagating waves that penetrate deeply into the free atmosphere. As a result, there is a net downward flux of momentum, which is dissipated within the CBL by turbulence. Furthermore, mixing with the environment of the air particles displaced by the waves results in a net negative mesoscale heat flux, which contributes to the weakening of the stability of the free atmosphere. Strong synoptic advection can significantly weaken the horizontal temperature gradients in the CBL, thereby weakening the intensity of the mesoscale flow. Turbulent diffusion also weakens the temperature gradients and the intensity of the mesoscale flow at large wavenumbers when the wavelength is comparable to the CBL depth. Finally, when the synoptic wind is very strong, the mesoscale perturbation is very weak and vertically trapped.
• Zeng, N., Dickinson, R. E., & Zeng, X. (1996). Climatic impact of Amazon deforestation - A mechanistic model study. Journal of Climate, 9(4), 859-883.
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  Abstract: Recent general circulation model (GCM) experiments suggest a drastic change in the regional climate, especially the hydrological cycle, after hypothesized Amazon basinwide deforestation. To facilitate the theoretical understanding of such a change, we develop an intermediate-level model for tropical climatology, including atmosphere-land-ocean interaction. The model consists of linearized steady-state primitive equations with simplified thermodynamics. A simple hydrological cycle is also included. Special attention has been paid to land-surface processes. In comparison with previous simple modeling work on tropical climatology or anomalies, the present model is more sophisticated in predicting, with little input, most of the important meteorological variables; nevertheless, it is computationally simple. It generally better simulates tropical climatology and the ENSO anomaly than do many of the previous simple models. The climatic impact of Amazon deforestation is studied in the context of this model. Model results show a much weakened Atlantic Walker-Hadley circulation as a result of the existence of a strong positive feedback loop in the atmospheric circulation system and the hydrological cycle. The regional climate is highly sensitive to albedo change and sensitive to evapotranspiration change. The pure dynamical effect of surface roughness length on convergence is small, but the surface flow anomaly displays intriguing features. Analysis of the thermodynamic equation reveals that the balance between convective heating, adiabatic cooling, and radiation largely determines the deforestation response. Studies of the consequences of hypothetical continuous deforestation suggest that the replacement of forest by desert may be able to sustain a dry climate. Scaling analysis motivated by our modeling efforts also helps to interpret the common results of many GCM simulations. When a simple mixed-layer ocean model is coupled with the atmospheric model, the results suggest a 1°C decrease in SST gradient across the equatorial Atlantic Ocean in response to Amazon deforestation. The magnitude depends on the coupling strength.
• ZENG, X., & PIELKE, R. (1995). LANDSCAPE-INDUCED ATMOSPHERIC FLOW AND ITS PARAMETERIZATION IN LARGE-SCALE NUMERICAL-MODELS. JOURNAL OF CLIMATE, 8(5), 1156-1177.
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  Extensive numerical simulations are performed to demonstrate that the landscape-induced mesoscale sensible heat, moisture, and momentum fluxes associated with spatially heterogeneous convective boundary layers can be larger than, and have a different vertical structure from, the turbulent fluxes for a typical general circulation model grid box. The mesoscale fluxes above the convective boundary layer may also provide a natural mechanism for the strong coupling between the boundary layer and the free atmosphere above. The parameterizability of these mesoscale and turbulent fluxes is demonstrated based on their predictability.
• Zeng, X. (1995). : Stochastic aspects in estimating the probability of producing good products by a system. The Earth Observer, 7(6), 23-24.
• Zeng, X., & Pielke, R. A. (1995). Further Study on the Predictability of Landscape-Induced Atmospheric Flow.. Journal of the Atmospheric Sciences, 52(10), 1680-1698. doi:10.1175/1520-0469(1995)052<1680:fsotpo>2.0.co;2
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  Abstract The effect of the synoptic-scale wind on the predictability of landscape-induced atmospheric flow as a function of surface characteristics is studied by means of over 200 two-dimensional numerical simulations. The predictability measure is defined based on domain-averaged signal to noise ratio. The decomposition of the signal into two different parts is also used to further understand the effect of the synoptic-scale wind on the mesoscale atmospheric predictability. It is emphasized that different predictability measures should be used for different purposes, and different predictability results can be obtained based on different measures. For the cases of surface heat patches with patch sizes from L = 0 to 150 km and constant large-scale mean winds of U = 0, 3, 5, 7, and 9 m s−1, it is found that the potential temperature θ, the deviation of θ from its horizontally domain-averaged value θ′, the horizontal velocity u, and u′ are all predictable at any time during the day when L = 10 to 150 km reg...
• Zeng, X., & Pielke, R. A. (1995). Landscape-Induced Atmospheric Flow and its Parameterization in Large-Scale Numerical Models. Journal of Climate, 8(5), 1156-1177. doi:10.1175/1520-0442(1995)008<1156:liafai>2.0.co;2
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  Abstract Extensive numerical simulations are performed to demonstrate that the landscape-induced mesoscale sensible heat, moisture, and momentum fluxes associated with spatially heterogeneous convective boundary layers can be larger than, and have a different vertical structure from, the turbulent fluxes for a typical general circulation model grid box. The mesoscale fluxes above the convective boundary layer may also provide a natural mechanism for the strong coupling between the boundary layer and the free atmosphere above. The parameterizability of these memoscale and turbulent fluxes is demonstrated based on their predictability. Nine dimensionless parameters are proposed, which combine large-scale quantities with local inhomogeneities and consider both horizontal and vertical variations. Based on these parameters, parameterization schemes for the mesoscale and turbulent sensible heat, moisture, and momentum fluxes in the convective boundary layer, and for the total (i.e., mesoscale plus turbulent) se...
• Zeng, X., & Pielke, R. A. (1994). Long-Term Variability of Climate. Journal of the Atmospheric Sciences, 51(1), 155-159. doi:10.1175/1520-0469(1994)051<0155:ltvoc>2.0.co;2
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  In this research note, the authors address the following general question: In a nonlinear dynamical system (such as the climate system), can a known short-periodic variation lead to significant long-term variability It is known for chaos studies (e.g., Lorenz 1991) that any perturbations in chaotic dynamic systems can lead to a red-noise spectrum; however, whether a significant long-term variability can be induced is unknown. To perform this study, an idealized nonlinear model developed by Lorenz (1984, 1990) is used. The model and the results are presented in sections 2 and 3, respectively. Finally, the implications of this research to the understanding of the natural variability of the climate system due to internal dynamics will be discussed in section 4. 14 refs., 6 figs., 1 tab.
• Pielke, R. A., Schimel, D. S., Lee, T. J., Kittel, T. G., & Zeng, X. (1993). Atmosphere-terrestrial ecosystem interactions: implications for coupled modeling. Ecological Modelling, 67(1), 5-18.
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  Abstract: This paper overviews the important interactions between ecosystem and atmospheric dynamics. Examples of suggested procedures to model these interrelationships are introduced. The concept of equilibrium versus non-equilibrium non-linear dynamics in the context of chaos is discussed. The paper concludes with a description of a parameterization of vegetation effects on atmospheric structure, including a model sensitivity simulation of the importance of land surface processes on this structure. © 1993.
• Zeng, X., & Pielke, R. A. (1993). Error-growth dynamics and predictability of surface thermally induced atmospheric flow. Journal of the Atmospheric Sciences, 50(17), 2817-2844. doi:10.1175/1520-0469(1993)050<2817:egdapo>2.0.co;2
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  Abstract Using the CSU Regional Atmospheric Modeling System (RAMS) in its nonhydrostatic and compressible configuration, over 200 two-dimensional simulations with Δx = 2 km and Δx = 100 m are performed to study in detail the initial adjustment process and the error-growth dynamics of surface thermally induced circulations including the sensitivity to initial conditions (i.e., the traditional predictability), boundary conditions, and model parameters, and to study the predictability as a function of the size of surface heat patches under a calm mean wind. It is found that the error growth (at least at the stage when the surface forcing is strong) is not sensitive to the characteristics of the initial perturbations. The numerical smoothing has a strong impact on the initial adjustment process and on the error-growth dynamics. The predictability is variable dependent. The mesoscale flow is insensitive to lateral and top boundary conditions. Among the conclusions regarding the influence of the boundary-layer ...
• Zeng, X., & Pielke, R. A. (1993). What does a low-dimensional weather attractor mean?. Physics Letters A, 175(5), 299-304.
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  Abstract: Low-dimensional attractors are obtained reliably for a surface thermally-induced atmospheric flow. Different physical processes corresponding with these low dimensions are discussed, and a mathematical mapping of the atmospheric flow patterns from these physical processes is determined. © 1993.
• Zeng, X., Pielke, R. A., & Eykholt, R. (1993). Chaos Theory and Its Applications to the Atmosphere. Bulletin of the American Meteorological Society, 74(4), 631-644. doi:10.1175/1520-0477(1993)074<0631:ctaiat>2.0.co;2
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  A brief overview of chaos theory is presented, including bifurcations, routes to turbulence, and methods for characterizing chaos. The paper divides chaos applications in atmospheric sciences into three categories: new ideas and insights inspired by chaos, analysis of observational data, and analysis of output from numerical models. Based on the review of chaos theory and the classification of chaos applications, suggestions for future work are given.
• Zeng, X., Pielke, R. A., & Eykholt, R. (1992). EXTRACTING LYAPUNOV EXPONENTS FROM SHORT TIME SERIES OF LOW PRECISION. Modern Physics Letters B, 06(02), 55-75. doi:10.1142/s0217984992000090
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  Different methods for computing the Lyapunov-exponent spectrum from a time series are reviewed. All algorithms are based on either Gram-Schmidt orthonormalization or Householder QR decomposition, and they use either the linearized map or a higher-order polynomial approximation. They also differ in implementation details. The ability to use these methods for a short time series of low precision is investigated, with special attention being given to the practicality of these algorithms; i.e., their efficiency and accuracy and the number of adjustable free parameters.
• Zeng, X., Pielke, R. A., & Eykholt, R. (1992). Estimating the fractal dimension and the predictability of the atmosphere. Journal of the Atmospheric Sciences, 49(8), 649-659.
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  Abstract: The fractal dimension, Lyapunov-exponent spectrum, Kolmogorov entropy, and predictability are analyzed for chaotic attractors in the atmosphere by analyzing the time series of daily surface temperature and pressure over several regions of the United States and the North Atlantic Ocean with different climatic signal-to-noise ratios. Though the total number of data points (from about 13 800 to about 36 500) is larger than those used in previous studies, it is still too small to obtain a reliable estimate of the Grassberger-Procaccia correlation dimension because of the limitations discussed by Ruelle. However, it can be shown that this dimension is greater than 8. Also, it is pointed out the most, if not all, of the previous estimates of low fractal dimensions in the atmosphere are spurious. -from Authors
• Zeng, X., Pielke, R. A., & Eykholt, R. (1992). Reply to Jascourt and Raymond. Tellus B, 44(3), 247-248. doi:10.3402/tellusb.v44i3.15450
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  Jascourt and Raymond (1992; henceforth denoted by JR) raise som valid points regarding our paper "Chaos in Daisyworld" (Zeng et al., 1990; henceforth denoted by ZPE). However, much of their criticism is based on simple misunderstandings, and we welcome the opportunity to clarify these issues. DOI: 10.1034/j.1600-0889.1992.00008.x
• Zeng, X., Eykholt, R., & Pielke, R. A. (1991). Estimating the Lyapunov-exponent spectrum from short time series of low precision. Physical Review Letters, 66(25), 3229-3232.
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  Abstract: We propose a new method to compute Lyapunov exponents from limited experimental data. The method is tested on a variety of known model systems, and it is found that the algorithm can be used to obtain a reasonable Lyapunov-exponent spectrum from only 5000 data points with a precision of 10-1 or 10-2 in three- or four-dimensional phase space, or 10000 data points in five-dimensional phase space. We also apply our algorithm to the daily-averaged data of surface temperature observed at two locations in the United States to quantitatively evaluate atmospheric predictability.
• Pielke, R., & Zeng, X. (1989). Influence on severe storm development of irrigated land. Natl. Wea. Dig., 14, 16-17.
• Zeng, X., Zhao, M., & Li, X. (1989). Three-dimensional numerical simulations of the interaction between urban heat island circulation and land breeze under sloping terrains. Chinese J. Atmos. Sci., 13, 358-366.
• Zeng, X., Zhao, M., & Miao, M. (1987). A study of wind profiles below 140 M under stable conditions. Chinese J. Atmos. Sci., 11, 183-191.
• Zhao, M., Zeng, X., & Wang, Y. (1986). The computation of the wind speed in the tower layer under near-neutral atmosphere. Chinese J. Meteor. Sci., 7-16.

Proceedings Publications

• Yanovsky, I., Posselt, D., Wu, L., Hristova-Veleva, S., Nguyen, H., Lambrigtsen, B., & Zeng, X. (2023). Atmospheric motion vector retrieval using the total variation-based optical flow method. In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium.
• Shuttleworth, J., Zreda, M., Zeng, X., Zweck, C., & Ferre, T. (2010, Jul.). The COsmic-ray Soil Moisture Observing System (COSMOS): a non-invasive, intermediate scale soil moisture measurement network. In British Hydrological Society Third International Symposium: "Role of Hydrology in Managing Consequences of a Changing Global Environment",, 757-763.
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  Newcastle University, Newcastle, United Kingdom, 19-23 July 2010. ISBN: 1 903741 17 3
• Zeng, Q., Zeng, X., Wang, A., Dickinson, R., Zeng, X., & Shen, S. (2005, May). Models and numerical simulations of atmosphere-vegetaion-soil interactions and ecosystem dynamics. In Computational Physics: Proceedings of the Joint Conference of ICCP6 and CCP 2003, 98-109.
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  X.G. Zhao, S. Jiang, and X.J. Yu, Eds.

Presentations

• Niu, G., Zeng, X., Gupta, H. V., & Wang, Y. H. (2021). Developing Regional Snow Model Using Long Short-Term Memory Networks Applied to Large Pixel-Scale Datasets. El Dia Del Agua y Atmosphera, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, Mar 31/April 1. Online: Department of Hydrology and Atmospheric Sciences, The University of Arizona,.
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  Wang YH, H Gupta, X Zeng and GY Niu (2021), Developing Regional Snow Model Using Long Short-Term Memory Networks Applied to Large Pixel-Scale Datasets, presented at El Dia Del Agua y Atmosphera, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, Mar 31/April 1
• Niu, G., Zeng, X., Gupta, H. V., & Wang, Y. H. (2021). Hypothesis Testing Using Long Short-Term Memory Networks for Improving Understanding of Continental- and Regional-Scale Snowpack Dynamics. 2021 Fall Meeting of the American Geophysical Union, Online, Dec 13-17. Online: AGU.
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  Wang YH, HV Gupta , X Zeng and GY Niu (2021), Hypothesis Testing Using Long Short-Term Memory Networks for Improving Understanding of Continental- and Regional-Scale Snowpack Dynamics, Session H081: Physics-informed Machine Learning in Hydrology, presented at 2021 Fall Meeting of the American Geophysical Union, Online, Dec 13-17.
• Song, Y., Zeng, X., Smith, W. K., Biederman, J., & Hu, T. (2021, Dec). The feedback of Arizona Grassland to Longer Seasonal Droughts and its Implication for Dryland Carbon Cycling: Insights from Model-Experiment Integration. AGU2021. Online.
• Zeng, X. (2018, Spring). 10 Invited Presentations from January to December 2018 (detailed omitted here). Various conferences and institutions.
• Zeng, X. (2018, Spring). 10+ Contributed Presentations from January to December 2018 (detailed omitted here). Various Conferences.

Poster Presentations

• Song, Y., Zeng, X., Smith, W. K., Biederman, J., & Hu, T. (2021, Nov). The effect of Biological and Physical Processes on Soil Water Dynamics and its Feedback to Arizona Grassland. The 17th Annual Research Insights in Semiarid Ecosystem Symposium. Tucson AZ: USDA.

Reviews

• Zeng, X. (2004. Review of two-volume books “Large-Scale Atmosphere-Ocean Dynamics I and II”(pp 282-284).
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  Bull. Amer. Meteor. Soc., 85

Others

• Smith, R., Carbone, R., & Zeng, X. (2013, Jun.). Final Report of The Lower Atmospheric Observing Facilities Workshop - Meeting the Challenges of Climate System Science (on 18-19 June 2012, Boulder, Colorado, USA).
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  11 June 2013. 44 pp (submitted to NSF AGS).
• Snow, J., Zeng, X., Klein, P., Shepherd, M., Sarnat, S., & Stanley, Sr., E. (2012, Jun.). NRC Report on “Urban Meteorology: Forecasting, Monitoring, and Meeting End Users' Needs”.
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  National Academies Press, Washington, D.C., 190 pp.
• Dabberdt, W., Carbone, R., Chen, S., Forbes, G., Foufoula-Georgiou, E., Morss, R., Snow, J., & Zeng, X. (2010, May). NRC Report on “When Weather Matters: Science and Service to Meet Critical Societal Needs”.
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  National Academies Press, Washington, D.C., 146 pp.
• including, A. C., & Zeng, X. (2010, Mar.). The 2009 AMS member Survey – A summary of findings and response to members.
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  Bull. Amer. Meteor. Soc., 91, 657-673.
• Asner, G., other coauthors, t., & Zeng, X. (2007, Oct.). Final Report of the 2007 NASA Earth Science Senior Review.
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  36 pages, submitted to the NASA Earth Science Division
• Robinson, D., other coauthors, t., & Zeng, X. (2007, Jun.). NRC Report on Principles and Guidelines for Archiving Environmental and Geospatial Data at NOAA.
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  National Academies Press, Washington, D.C., 116 pp.
• Overpeck, J., other coauthors, s., & Zeng, X. (2004, May). Earth Sciences and Environmental Programs at the University of Arizona: A Plan for Focused Excellence.
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  32 pages, submitted to the University of Arizona Provost
• ZENG, ., PIELKE, R., & EYKHOLT, R. (1992, JUL). CHAOS IN DAISYWORLD - REPLY. TELLUS SERIES B-CHEMICAL AND PHYSICAL METEOROLOGY.