Baike Xi

Interests

Research

Cloud microphysics retrieval from ground base measurements, atmospheric radiative transfer, cloud and radiation parameterizations in climate model, ground and satellite remote sensing of clouds and radiation, heterogeneous reaction in clouds, Asian dust/pollution transport.

Courses

Scholarly Contributions

Journals/Publications

• Xi, B., Dong, X., Zheng, X., & Xie, S. (2023). A Climatology of Midlatitude Maritime Cloud Fraction and Radiative Effect Derived from the ARM ENA Ground-Based Observations. Journal of Climate, 36(2), 531-546. doi:10.1175/jcli-d-22-0290.1
• Xi, B., Dong, X., Brendecke, J., & Zheng, X. (2022). Maritime Aerosol and CCN Profiles Derived From Ship‐Based Measurements Over Eastern North Pacific During MAGIC. Earth and Space Science, 9(4). doi:10.1029/2022ea002319
• Xi, B., Dong, X., Brendecke, J., & Zheng, X. (2022). Maritime Aerosol and CCN profiles derived from ship-based measurements over Eastern North Pacific during MAGIC 2. Earth and Space Science. doi:https://doi.org/10.1029/2022EA002319.
• Zheng, X., Xi, B., Wu, P., Wang, Y., Logan, T., & Dong, X. (2022). Environmental effects on aerosol–cloud interaction in non-precipitating marine boundary layer (MBL) clouds over the eastern North Atlantic. Atmospheric Chemistry and Physics, 22(1), 335-354. doi:10.5194/acp-22-335-2022
  More info

  Abstract. Over the eastern North Atlantic (ENA) ocean, a total of 20 non-precipitating single-layer marine boundary layer (MBL) stratus and stratocumulus cloud cases are selected to investigate the impacts of the environmental variables on the aerosol–cloud interaction (ACIr) using the ground-based measurements from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the ENA site during 2016–2018. The ACIr represents the relative change in cloud droplet effective radius re with respect to the relative change in cloud condensation nuclei (CCN) number concentration at 0.2 % supersaturation (NCCN,0.2 %) in the stratified water vapor environment. The ACIr values vary from −0.01 to 0.22 with increasing sub-cloud boundary layer precipitable water vapor (PWVBL) conditions, indicating that re is more sensitive to the CCN loading under sufficient water vapor supply, owing to the combined effect of enhanced condensational growth and coalescence processes associated with higher Nc and PWVBL. The principal component analysis shows that the most pronounced pattern during the selected cases is the co-variations in the MBL conditions characterized by the vertical component of turbulence kinetic energy (TKEw), the decoupling index (Di), and PWVBL. The environmental effects on ACIr emerge after the data are stratified into different TKEw regimes. The ACIr values, under both lower and higher PWVBL conditions, more than double from the low-TKEw to high-TKEw regime. This can be explained by the fact that stronger boundary layer turbulence maintains a well-mixed MBL, strengthening the connection between cloud microphysical properties and the below-cloud CCN and moisture sources. With sufficient water vapor and low CCN loading, the active coalescence process broadens the cloud droplet size spectra and consequently results in an enlargement of re. The enhanced activation of CCN and the cloud droplet condensational growth induced by the higher below-cloud CCN loading can effectively decrease re, which jointly presents as the increased ACIr. This study examines the importance of environmental effects on the ACIr assessments and provides observational constraints to future model evaluations of aerosol–cloud interactions.
• Huang, Y., Xi, B., Marcovecchio, A., Behrangi, A., & Dong, X. (2021). Precipitation influence on and response to early and late Arctic sea ice melt onset during melt season. International Journal of Climatology, 42(1), 81-96. doi:10.1002/joc.7233
• Huang, Y., Xi, B., Wu, P., Dong, X., & Wang, Y. (2021). New Observational Constraints on Warm Rain Processes and Their Climate Implications. Geophysical Research Letters, 48(6). doi:10.1029/2020gl091836
• Wu, P., Xi, B., Dong, X., & Brendecke, J. (2021). Maritime Cloud and Drizzle Microphysical Properties Retrieved From Ship‐Based Observations During MAGIC. Earth and Space Science, 8(5). doi:10.1029/2020ea001588
• Xi, B., Dong, X., Cui, W., & Feng, Z. (2021). Climatology of Linear Mesoscale Convective System Morphology in the United States based on Random Forests Method. Journal of Climate, 1-52. doi:10.1175/jcli-d-20-0862.1
• Xi, B., Huang, Y., Dong, X., Ding, Q., & Baxter, I. (2021). Summertime low clouds mediate the impact of the large-scale circulation on Arctic sea ice. Communications Earth & Environment, 2(1), 1-10. doi:10.1038/s43247-021-00114-w
  More info

  The rapid Arctic sea ice retreat in the early 21st century is believed to be driven by several dynamic and thermodynamic feedbacks, such as ice-albedo feedback and water vapor feedback. However, the role of clouds in these feedbacks remains unclear since the causality between clouds and these processes is complex. Here, we use NASA CERES satellite products and NCAR CESM model simulations to suggest that summertime low clouds have played an important role in driving sea ice melt by amplifying the adiabatic warming induced by a stronger anticyclonic circulation aloft. The upper-level high pressure regulates low clouds through stronger downward motion and increasing lower troposphere relative humidity. The increased low clouds favor more sea ice melt via emitting stronger longwave radiation. Then decreased surface albedo triggers a positive ice-albedo feedback, which further enhances sea ice melt. Considering the importance of summertime low clouds, accurate simulation of this process is a prerequisite for climate models to produce reliable future projections of Arctic sea ice. Summertime low clouds in the Arctic play an important role in inducing sea ice melt as they amplify warming from high pressure systems aloft through radiative effects and feedbacks, according to analyses of observations and model simulations.
• Baike, X. i. (2020). Cloud and Precipitation Properties of MCSs Along the Meiyu Frontal Zone in Central and Southern China and Their Associated Large‐Scale Environments. Journal of Geophysical Research: Atmospheres.
• Baike, X. i. (2020). Investigation of aerosol–cloud interactions under different absorptive aerosol regimes using Atmospheric Radiation Measurement (ARM) southern Great Plains (SGP) ground-based measurements. Atmospheric Chemistry and Physics.
• Baike, X. i. (2020). Spatial Distribution and Impacts of Aerosols on Clouds Under Meiyu Frontal Weather Background Over Central China Based on Aircraft Observations. Journal of Geophysical Research: Atmospheres.
• Baike, X. i. (2020). Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China During the Meiyu Seasons. Journal of Geophysical Research: Atmospheres.
• Dong, X., & Xi, B. (2020). Statistical Characteristics of the Raindrop Size Distributions in Central China During Meiyu Season. JGR. doi:https://doi.org/ 10.1029/2019JD031954
• Wu, P., Xi, B., Dong, X., Logan, T., Zheng, X., Wang, Y., Marlow, E., & Maddux, J. (2020). Quantifying Long‐Term Seasonal and Regional Impacts of North American Fire Activity on Continental Boundary Layer Aerosols and Cloud Condensation Nuclei. Earth and Space Science, 7(12). doi:10.1029/2020ea001113
• Xi, B., Dong, X., & Wu, P. (2020). A Climatology of Marine Boundary Layer Cloud and Drizzle Properties Derived from Ground-Based Observations over the Azores. Journal of Climate, 33(23), 10133-10148. doi:10.1175/jcli-d-20-0272.1
• Xi, B., Dong, X., Cui, W., Feng, Z., & Fan, J. (2020). Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?. Journal of Hydrometeorology, 21(1), 39-57. doi:10.1175/jhm-d-19-0123.1
• Xi, B., Xi, B., Tian, J., Feng, Z., & Dong, X. (2020). Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains. Journal of Hydrometeorology, 21(2), 317-334. doi:10.1175/jhm-d-19-0176.1
  More info

  AbstractIn this study, the mesoscale convective systems (MCSs) are tracked using high-resolution radar and satellite observations over the U.S. Great Plains during April–August from 2010 to 2012. T...
• Xi, B., Zhang, W., Xu, G., Ren, J., Wan, X., Zhou, L., Cui, C., & Wu, D. (2020). Comparative Study of Cloud Liquid Water and Rain Liquid Water Obtained From Microwave Radiometer and Micro Rain Radar Observations Over Central China During the Monsoon. Journal of Geophysical Research: Atmospheres, 125(20). doi:10.1029/2020jd032456
• Cui, W., Dong, X., Xi, B., & Feng, Z. (2020). Climatology of linear mesoscale convective system morphology based on random forests method. Journal of Climate.
• McHardy, T. M., Wang, J., Tian, J., Xi, B., Dong, X., Cui, W., & Fan, J. (2019). Understanding Ice Cloud‐Precipitation Properties of Three Modes of Mesoscale Convective Systems During PECAN. Journal of Geophysical Research: Atmospheres, 124(7), 4121-4140. doi:10.1029/2019jd030330
• Tian, J., Dong, X., Xi, B., Williams, C. R., & Wu, P. (2019). Estimation of liquid water path below the melting layer in stratiform precipitation systems using radar measurements during MC3E. ATMOSPHERIC MEASUREMENT TECHNIQUES, 12(7), 3743-3759.
• Wang, J., Dong, X., Kennedy, A., Hagenhoff, B., & Xi, B. (2019). A Regime-Based Evaluation of Southern and Northern Great Plains Warm-Season Precipitation Events in WRF. WEATHER AND FORECASTING, 34(4), 805-831.
• Xi, B., Dong, X., Huang, Y., Bailey, D. A., Holland, M. M., DuVivier, A. K., Kay, J. E., Landrum, L. L., & Deng, Y. (2019). Thicker Clouds and Accelerated Arctic Sea Ice Decline: The Atmosphere‐Sea Ice Interactions in Spring. Geophysical Research Letters, 46(12), 6980-6989. doi:10.1029/2019gl082791
• Xi, B., Dong, X., Zheng, X., Xi, B., Wu, P., Ward, D. M., & Dong, X. (2019). Impacts of aerosols on MBL Cloud Microphysical and Drizzle Properties using Aircraft in-Situ Measurements during ACE-ENA. JGR.
• Chen, X., Huang, X., Dong, X., Xi, B., Dolinar, E. K., Loeb, N. G., Kato, S., Stackhouse, P. W., & Bosilovich, M. G. (2018). Using AIRS and ARM SGP Clear-Sky Observations to Evaluate Meteorological Reanalyses: A Hyperspectral Radiance Closure Approach. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 123(20), 11720-11734.
• Logan, T., Dong, X., & Xi, B. (2018). Aerosol properties and their impacts on surface CCN at the ARM Southern Great Plains site during the 2011 Midlatitude Continental Convective Clouds Experiment. ADVANCES IN ATMOSPHERIC SCIENCES, 35(2), 224-233.
• McHardy, T. M., Dong, X., Xi, B., Thieman, M. M., Minnis, P., & Palikonda, R. (2018). Comparison of Daytime Low-Level Cloud Properties Derived From GOES and ARM SGP Measurements. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 123(15), 8221-8237.
• Wang, J., Dong, X., & Xi, B. (2018). Investigation of Liquid Cloud Microphysical Properties of Deep Convective Systems: 2. Parameterization of Raindrop Size Distribution and its Application for Convective Rain Estimation. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 123(20), 11637-11651.
• Wu, P., Xi, B., Dong, X., & Zhang, Z. (2018). Evaluation of autoconversion and accretion enhancement factors in general circulation model warm-rain parameterizations using ground-based measurements over the Azores. ATMOSPHERIC CHEMISTRY AND PHYSICS, 18(23).
• Xi, B., Qiu, S., & Dong, X. (2018). Influence of Wind Direction on Thermodynamic Properties and Arctic Mixed-Phase Clouds in Autumn at Utqiaġvik, Alaska. Journal of Geophysical Research: Atmospheres, 123(17), 9589-9603. doi:10.1029/2018jd028631
• Cui, W., Dong, X., Xi, B., & Kennedy, A. (2017). Evaluation of Reanalyzed Precipitation Variability and Trends Using the Gridded Gauge-Based Analysis over the CONUS. JOURNAL OF HYDROMETEOROLOGY, 18(8), 2227-2248.
• Huang, Y., Dong, X., Xi, B., Dolinar, E. K., & Stanfield, R. E. (2017). The footprints of 16 year trends of Arctic springtime cloud and radiation properties on September sea ice retreat. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 122(4), 2179-2193.
• Huang, Y., Dong, X., Xi, B., Dolinar, E. K., Stanfield, R. E., & Qiu, S. (2017). Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations. JOURNAL OF CLIMATE, 30(19), 8007-8029.
• Tian, J., Dong, X., Xi, B., Minnis, P., Smith Jr., W. L., Sun-Mack, S., Thieman, M., & Wang, J. (2018). Comparisons of Ice Water Path in Deep Convective Systems Among Ground-Based, GOES, and CERES-MODIS Retrievals. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 123(3), 1708-1723.
• Wu, P., Dong, X., Xi, B., Liu, Y., Thieman, M., & Minnis, P. (2017). Effects of environment forcing on marine boundary layer cloud-drizzle processes. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 122(8), 4463-4478.
• Zhang, L., Dong, X., Kennedy, A., Xi, B., & Li, Z. (2017). Evaluation of NASA GISS Post-CMIP5 Single Column Model Simulated Clouds and Precipitation Using ARM Southern Great Plains Observations. ADVANCES IN ATMOSPHERIC SCIENCES, 34(3), 306-320.
• Zhang, Z., Dong, X., Xi, B., Song, H., Ma, P., Ghan, S. J., Platnick, S., & Minnis, P. (2017). Intercomparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 122(4), 2351-2365.
• Carletta, N. D., Mullendore, G. L., Starzec, M., Xi, B., Feng, Z., & Dong, X. (2016). Determining the Best Method for Estimating the Observed Level of Maximum Detrainment Based on Radar Reflectivity. MONTHLY WEATHER REVIEW, 144(8), 2915-2926.
• Cui, W., Dong, X., Xi, B., & Stenz, R. (2016). Comparison of the GPCP 1DD Precipitation Product and NEXRAD Q2 Precipitation Estimates over the Continental United States. JOURNAL OF HYDROMETEOROLOGY, 17(6), 1837-1853.
• Dolinar, E. K., Dong, X., & Xi, B. (2016). Evaluation and intercomparison of clouds, precipitation, and radiation budgets in recent reanalyses using satellite-surface observations. CLIMATE DYNAMICS, 46(7-8), 2123-2144.
• Dolinar, E. K., Dong, X., Xi, B., Jiang, J. H., & Loeb, N. G. (2016). A clear-sky radiation closure study using a one-dimensional radiative transfer model and collocated satellite-surface-reanalysis data sets. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 121(22), 13698-13714.
• Dong, X., Xi, B., Qiu, S., Minnis, P., Sun-Mack, S., & Rose, F. (2016). A radiation closure study of Arctic stratus cloud microphysical properties using the collocated satellite-surface data and Fu-Liou radiative transfer model. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 121(17), 10175-10198.
• Kennedy, A. D., Dong, X., & Xi, B. (2016). Cloud fraction at the ARM SGP site: reducing uncertainty with self-organizing maps. THEORETICAL AND APPLIED CLIMATOLOGY, 124(1-2), 43-54.
• Logan, T., Dong, X., Xi, B., Wang, J., & Tian, J. (2016). Biomass burning smoke and deep convection during the 2011 midlatitude continental convective louds experiment (MC3E). ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 252.
• Stanfield, R. E., Jiang, J. H., Dong, X., Xi, B., Su, H., Donner, L., Rotstayn, L., Wu, T., Cole, J., & Shindo, E. (2016). A quantitative assessment of precipitation associated with the ITCZ in the CMIP5 GCM simulations. CLIMATE DYNAMICS, 47(5-6), 1863-1880.
• Stenz, R., Dong, X., Xi, B., Feng, Z., & Kuligowski, R. J. (2016). Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth. JOURNAL OF HYDROMETEOROLOGY, 17(2), 557-570.
• Tian, J., Dong, X., Xi, B., Wang, J., Homeyer, C. R., McFarquhar, G. M., & Fan, J. (2016). Retrievals of ice cloud microphysical properties of deep convective systems using radar measurements. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 121(18), 10820-10839.
• Wang, J., Dong, X., Xi, B., & Heymsfield, A. J. (2016). Investigation of liquid cloud microphysical properties of deep convective systems: 1. Parameterization raindrop size distribution and its application for stratiform rain estimation. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 121(18), 10739-10760.
• Zhang, L., Dong, X., Kennedy, A., Xi, B., & Li, Z. (2016). Evaluation of NASA GISS Post-CMIP5 single column model simulated cloud and precipitation using the ARM SGP observations. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 252.
• Chenghai, W., Hongxia, S., Haolin, H., Wang, Y. i., & Baike, X. (2015). Properties of cloud and precipitation over the Tibetan Plateau. ADVANCES IN ATMOSPHERIC SCIENCES, 32(11), 1504-1516.
• Dolinar, E. K., Dong, X., Xi, B., Jiang, J. H., & Su, H. (2015). Evaluation of CMIP5 simulated clouds and TOA radiation budgets using NASA satellite observations. CLIMATE DYNAMICS, 44(7-8), 2229-2247.
• Dong, X., Schwantes, A. C., Xi, B., & Wu, P. (2015). Investigation of the marine boundary layer cloud and CCN properties under coupled and decoupled conditions over the Azores. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 120(12), 6179-6191.
• Qiu, S., Dong, X., Xi, B., & Li, J. (2015). Characterizing Arctic mixed-phase cloud structure and its relationship with humidity and temperature inversion using ARM NSA observations. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 120(15), 7737-7746.
• Stanfield, R. E., Dong, X., Xi, B., Del, G., Minnis, P., Doelling, D., & Loeb, N. (2015). Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part II: TOA Radiation Budget and CREs. JOURNAL OF CLIMATE, 28(5), 1842-1864.
• Wang, J., Dong, X., & Xi, B. (2015). Investigation of ice cloud microphysical properties of DCSs using aircraft in situ measurements during MC3E over the ARM SGP site. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 120(8), 3533-3552.
• Xu, G., Xi, B., Zhang, W., Cui, C., Dong, X., Liu, Y., & Yan, G. (2015). Comparison of atmospheric profiles between microwave radiometer retrievals and radiosonde soundings. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 120(19), 10313-10323.
• Baike, X. i. (2014). Comparison of marine boundary layer cloud properties from CERES-MODIS Edition 4 and DOE ARM AMF measurements at the Azores. Journal of Geophysical Research: Atmospheres.
• Dong, X., Xi, B., & Wu, P. (2014). Investigation of the Diurnal Variation of Marine Boundary Layer Cloud Microphysical Properties at the Azores. JOURNAL OF CLIMATE, 27(23), 8827-8835.
• Dong, X., Xi, B., Kennedy, A., Minnis, P., & Wood, R. (2014). A 19-Month Record of Marine Aerosol- Cloud-Radiation Properties Derived from DOE ARM Mobile Facility Deployment at the Azores. Part I: Cloud Fraction and Single-Layered MBL Cloud Properties. JOURNAL OF CLIMATE, 27(10), 3665-3682.
• Dong, X., Zib, B. J., Xi, B., Stanfield, R., Deng, Y. i., Zhang, X., Lin, B., & Long, C. N. (2014). Critical mechanisms for the formation of extreme arctic sea-ice extent in the summers of 2007 and 1996. CLIMATE DYNAMICS, 43(1-2), 53-70.
• Kennedy, A. D., Dong, X., & Xi, B. (2014). Cloud fraction at the ARM SGP site Instrument and sampling considerations from 14 years of ARSCL. THEORETICAL AND APPLIED CLIMATOLOGY, 115(1-2), 91-105.
• Logan, T., Xi, B., & Dong, X. (2014). Aerosol properties and their influences on marine boundary layer cloud condensation nuclei at the ARM mobile facility over the Azores. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 119(8), 4859-4872.
• Minnis, P., Xi, B., Smith, W. L., Xi, B., Yost, C. R., Trepte, Q. Z., Sun-mack, S., Spangenberg, D. A., Smith, W. L., Palikonda, R., Dong, X., Bedka, S. T., & Bedka, K. M. (2014). Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications. Geosci. Remote Sens., 49, 4401-4430.
• Stanfield, R. E., Dong, X., Xi, B., Kennedy, A., Del, G., Minnis, P., & Jiang, J. H. (2014). Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part I: Cloud Fraction and Properties. JOURNAL OF CLIMATE, 27(11), 4189-4208.
• Stenz, R., Dong, X., Xi, B., & Kuligowski, R. J. (2014). Assessment of SCaMPR and NEXRAD Q2 Precipitation Estimates Using Oklahoma Mesonet Observations. JOURNAL OF HYDROMETEOROLOGY, 15(6), 2484-2500.
• Xi, B. (2014). Validation of CERES-MODIS Edition 4 Marine Boundary Layer Cloud Properties using DOE ARM AMF Measurements at the Azores. doi: 10.1002/2014JD021813. doi:doi: 10.1002/2014JD021813.
• Xi, B., Dong, X., Minnis, P., & Sun-Mack, S. (2014). Comparison of marine boundary layer cloud properties from CERES-MODIS Edition 4 and DOE ARM AMF measurements at the Azores. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 119(15), 9509-9529.
• Logan, T., Xi, B., & Dong, X. (2013). A Comparison of the Mineral Dust Absorptive Properties between Two Asian Dust Events. ATMOSPHERE, 4(1), 1-16.
• Logan, T., Xi, B., Dong, X., Li, Z., & Cribb, M. (2013). Classification and investigation of Asian aerosol absorptive properties. ATMOSPHERIC CHEMISTRY AND PHYSICS, 13(4), 2253-2265.
• Wu, D. i., Dong, X., Xi, B., Feng, Z., Kennedy, A., Mullendore, G., Gilmore, M., & Tao, W. (2013). Impacts of microphysical scheme on convective and stratiform characteristics in two high precipitation squall line events. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 118(19), 11119-11135.
• Xi, B., Logan, T., & Dong, X. (2013). Biomass burning aerosol properties over the Northern Great Plains during the 2012 warm season. Atmospheric Chemistry and Physics, 13(12), 32269-32289. doi:10.5194/acpd-13-32269-2013
  More info

  Biomass burning aerosols can have a large impact on atmospheric processes as well as human health. During the 2012 warm season, a large outbreak of wildfires originating from the intermountain and Pacific states provided many opportunities to observe the physical and chemical properties of biomass smoke aerosols. Six biomass burning smoke plumes (26 June–15 September) have been observed by the newly installed Grand Forks, North Dakota, AERONET site (47.91° N, 97.32° W) and are selected for this study. To identify the source regions, HYSPLIT backward trajectory model data and satellite imagery are used to track these events. The volume size distribution and spectral aerosol optical depth (AOD) dependence showed the relative influences of fine and coarse mode particles. Case II (4 July) had the strongest fine mode influence as evidenced by a strong spectral AOD dependence while Case VI (15 September) had the strongest coarse mode influence with the weakest spectral dependence. The spectral dependences of absorption aerosol optical depth (AAOD) and single scattering co-albedo (ω oabs ) illustrated the varying absorption of the smoke plumes by inferring the relative contributions of strongly and weakly absorbing carbonaceous species. More specifically, the AAOD parameter is primarily influenced by aerosol particle size while ω oabs is more dependent on aerosol composition. The AAOD spectral dependences for Cases I (26 June), III (31 July), and VI were weaker than those from Cases II, IV (28 August), and V (30 August). However, the spectral ω oabs dependences were different in that the smoke particles in Cases III and VI had the strongest absorption while Cases I, II, IV, and V had moderate to weakly absorbing particles. In addition, a weak correlation was found between plume transport time and particle absorption where strongly absorbing carbon was converted to weakly absorbing carbon.
• Feng, Z., Dong, X., Xi, B., McFarlane, S. A., Kennedy, A., Lin, B., & Minnis, P. (2012). Life cycle of midlatitude deep convective systems in a Lagrangian framework. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 117.
• Xi, B., Logan, T., Li, Z., Dong, X., & Cribb, M. (2012). Classification and investigation of Asian aerosol properties. Atmospheric Chemistry and Physics Discussions, 12(8), 18927-18958. doi:10.5194/acpd-12-18927-2012
  More info

  Abstract. Ongoing urbanization and industrialization in East Asia have generated a wide variety of aerosols in the atmosphere and have consequently added more uncertainty when evaluating global climate change. To classify different types of aerosols and investigate their physical and chemical properties, four AErosol RObotic NETwork (AERONET) sites have been selected to represent aerosol properties dominated by mixed complex particle types (Xianghe and Taihu), desert-urban (SACOL), and biomass (Mukdahan) over East Asia during the 2001–2010 period. The volume size distribution, aerosol optical depth [τ (λ) and τabs(λ)], Ångström exponent (α and αabs), and the single scattering co-albedo [ωoabs(λ)] and α(ωoabs) parameters over the four selected sites have been analyzed. These parameters are used to (a) investigate the aerosol properties and their seasonal variations over the four selected sites, (b) discern the different absorptive characteristics of BC, OC, and mineral dust particles using αabs440-870 and α (ωoabs440-870), and (c) develop an aerosol clustering method involving α440-870 and ωoabs440. A strong mineral dust influence is seen at the Xianghe, Taihu, and SACOL sites during the spring months (MAM) as given by coarse mode size distribution dominance, declining α440-870, and elevated αabs440-870 and α (ωoabs440-870) values. A weakly absorbing pollution (OC and biomass) aerosol dominance is seen in the summer (JJA) and autumn (SON) months as given by a strong fine mode influence, increasing α440-870, and declining αabs440-870 and α (ωoabs440-870) values. A winter season (DJF) shift toward strongly absorbing BC particles is observed at Xianghe and Taihu (elevated α440-870, increase in αabs440-870 and α(ωoabs440-870)). At Mukdahan, a fine mode biomass particle influence is observed year round as given by the volume size distribution, elevated α440-870 (higher than the other sites), low αabs440-870 and negative α (ωoabs440-870) values indicating weakly absorbing OC particles. The α(ωoabs) parameter is also shown to have less overlap in values than αabs in discerning influences from OC, BC, biomass and mineral dust particles. The clustering method using α440-870 and ωoabs440 illustrates four groups of aerosols: Cluster I – fine mode, weakly absorbing pollution particles, Cluster II – fine mode, strongly absorbing pollution particles, Cluster III – coarse mode, strongly absorbing mineral dust particles, and Cluster IV – biomass particles with similar characteristics as Cluster II but less absorbing. This method has shown that aerosol mixtures are both seasonal and regional combinations of particles that were either locally generated or transported from other source regions and should be implemented over other AERONET sites in the future.
• Zib, B. J., Dong, X., Xi, B., & Kennedy, A. (2012). Evaluation and Intercomparison of Cloud Fraction and Radiative Fluxes in Recent Reanalyses over the Arctic Using BSRN Surface Observations. JOURNAL OF CLIMATE, 25(7), 2291-2305.
• Dong, X., Xi, B., Kennedy, A., Feng, Z., Entin, J. K., Houser, P. R., Schiffer, R. A., L'Ecuyer, T., Olson, W. S., Hsu, K., Liu, W. T., Lin, B., Deng, Y. i., & Jiang, T. (2011). Investigation of the 2006 drought and 2007 flood extremes at the Southern Great Plains through an integrative analysis of observations. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 116.
• Feng, Z., Dong, X., Xi, B., Schumacher, C., Minnis, P., & Khaiyer, M. (2011). Top-of-atmosphere radiation budget of convective core/stratiform rain and anvil clouds from deep convective systems. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 116.
• Kennedy, A. D., Dong, X., Xi, B., Xie, S., Zhang, Y., & Chen, J. (2011). A Comparison of MERRA and NARR Reanalyses with the DOE ARM SGP Data. JOURNAL OF CLIMATE, 24(17), 4541-4557.
• Minnis, P., Sun-Mack, S., Chen, Y., Khaiyer, M. M., Yi, Y., Ayers, J. K., Brown, R. R., Dong, X., Gibson, S. C., Heck, P. W., Lin, B., Nordeen, M. L., Nguyen, L., Palikonda, R., Smith Jr., W. L., Spangenberg, D. A., Trepte, Q. Z., & Xi, B. (2011). CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data-Part II: Examples of Average Results and Comparisons With Other Data. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 49(11), 4401-4430.
• Baike, X. i. (2010). Correction to “A 10 year climatology of cloud fraction and vertical distribution derived from both surface and GOES observations over the DOE ARM SPG site”. Journal of Geophysical Research.
• Dong, X., Xi, B., Crosby, K., Long, C. N., Stone, R. S., & Shupe, M. D. (2010). A 10 year climatology of Arctic cloud fraction and radiative forcing at Barrow, Alaska. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 115.
• Kennedy, A. D., Dong, X., Xi, B., Minnis, P., Del, G., Wolf, A. B., & Khaiyer, M. M. (2010). Evaluation of the NASA GISS Single-Column Model Simulated Clouds Using Combined Surface and Satellite Observations. JOURNAL OF CLIMATE, 23(19), 5175-5192.
• Logan, T., Xi, B., Dong, X., Obrecht, R., Li, Z., & Cribb, M. (2010). A study of Asian dust plumes using satellite, surface, and aircraft measurements during the INTEX-B field experiment. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 115.
• Xi, B., Dong, X., Minnis, P., & Khaiyer, M. M. (2010). A 10 year climatology of cloud fraction and vertical distribution derived from both surface and GOES observations over the DOE ARM SPG site (vol 115, D12124, 2010). JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 115.
• Feng, Z., Dong, X., & Xi, B. (2009). A Method to Merge WSR-88D Data with ARM SGP Millimeter Cloud Radar Data by Studying Deep Convective Systems. JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 26(5), 958-971.
• Dong, X., Minnis, P., Xi, B., Sun-Mack, S., & Chen, Y. (2008). Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM southern great plains site. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 113(D3).
• Dong, X., Wielicki, B. A., Xi, B., Hu, Y., Mace, G. G., Benson, S., Rose, F., Kato, S., Charlock, T., & Minnis, P. (2008). Using observations of deep convective systems to constrain atmospheric column absorption of solar radiation in the optically thick limit. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 113(D10).
• Dong, X., Xi, B., & Minnis, P. (2006). A climatology of midlatitude continental clouds from the ARM SGP central facility. Part II: Cloud fraction and surface radiative forcing. JOURNAL OF CLIMATE, 19(9), 1765-1783.
• Dong, X., Xi, B., & Minnis, P. (2006). Observational evidence of changes in water vapor, clouds, and radiation at the ARM SGP site. GEOPHYSICAL RESEARCH LETTERS, 33(19).
• Minnis, P., Heck, P. W., Sun-Mack, S., Trepte, Q. Z., Chen, Y., Brown, R. R., Gibson, S., Dong, X., & Xi, B. (2006). A Multi-Year Data Set of Cloud Properties Derived for CERES from Aqua, Terra, and TRMM. 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 1780-+.
• Xi, B., Minnis, P., & Dong, X. (2005). A climatology of midlatitude continental clouds from the ARM SGP central facility: Part I: Low-level cloud macrophysical, microphysical, and radiative properties. Journal of Climate, 18(9), 1391-1410. doi:10.1175/jcli3342.1
  More info

  Abstract A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 h of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant mixed-phase low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (re) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (τ), effective solar transmission (γ), and cloud/top-of-atmosphere albedos (Rcldy/RTOA) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations...