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

• Brendecke, J., Dong, X., Xi, B., Zhong, X., Li, J., Barker, H., & Pilewskie, P. (2024). Evaluation of clear-sky surface downwelling shortwave fluxes computed by three atmospheric radiative transfer models. Journal of Quantitative Spectroscopy and Radiative Transfer, 328. doi:10.1016/j.jqsrt.2024.109164
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  In this study the clear-sky total, direct, and diffuse shortwave (SW) fluxes at the surface, have been calculated by three radiation transfer models (RTMs) – MODTRAN6.0 (M6.0), Canadian Centre for Climate Modelling and Analysis (CCCma), and Langley-modified Fu-Liou (NASA CERES). These calculations have been evaluated by surface measurements collected from seven sites that represent different climatological regimes with various surface scene types including ocean, grassland/continental, desert, and snow/sea ice. For pristine atmospheric conditions, SW fluxes predicted by CCCma and M6.0 shows little variation, which lays a baseline for further analysis. Note that computing time required by CCCma is ∼1000 times smaller than M6.0. Based on all samples collected from seven sites, mean differences of total, direct, and diffuse fluxes between surface measurements and CCCma / M6.0 / Fu-Liou are [5.3 / 2.4 / 0.9], [-2.2 / -5.1 / -13.7], and [7.5 / 7.5 / 14.6] W m-2, respectively. Histograms of differences between the three RTM calculations and surface measurements show that CCCma computed direct and diffuse fluxes have the smallest biases with standard deviations similar to those for M6.0, while Fu-Liou values have the largest biases and standard deviations. While Fu-Liou outperforms for total flux, especially for desert conditions, it is hampered by large biases for direct and diffuse across all scene types. The three RTMs are consistent with showing the least error for total flux and the largest in diffuse based on bias, correlation, and root mean square error.
• Logan, T., Dong, X., Xi, B., Zheng, X., Wu, L., Abramowitz, A., Goluszka, A., & Harper, M. (2024). Assessing Radiative Impacts of African Smoke Aerosols Over the Southeastern Atlantic Ocean. Earth and Space Science, 11(4). doi:10.1029/2023ea003138
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  Biomass burning smoke aerosols are efficient at attenuating incoming solar radiation. The Layered Atlantic Smoke Interactions with Clouds campaign was conducted from June 2016 to October 2017. The U. S. Department of Energy mobile Atmospheric Radiation Measurement site located on Ascension Island (AMF-ASI) identified several instances of smoke plume intrusions. Increases in surface and column measurements of aerosol loading were directly related to increases in fine mode fraction, number concentrations of aerosols (Na), and cloud condensation nuclei (NCCN). During periods of weak lower tropospheric stability, smoke particles were more likely to be advected downward either by boundary layer turbulence or cloud top entrainment under non-overcast sky conditions. Backward trajectory analysis illustrated that smoke aerosols reaching the AMF-ASI site were fine mode, less aged, strongly absorbing, and had shorter boundary layer trajectories while longer boundary layer trajectories denoted mixtures of weakly absorbing smoke and coarse mode marine aerosols. The most polluted smoke cases of August 2016 and 2017 revealed a notable contrast in radiative forcing per unit aerosol optical depth or radiative forcing efficiency (ΔFeff) at the top of the atmosphere (TOA) and near-surface (BOA). The weakly (strongly) absorbing 2016 cases exhibited weaker (stronger) ΔFeff at the TOA and BOA suggesting a warming (cooling) effect within the boundary layer. The 2017 cases featured the strongest ΔFeff suggesting more of a cooling effect at the TOA and BOA due to mixing of fresh smoke with marine aerosols during transport.
• Zheng, X., Dong, X., Xi, B., Logan, T., & Wang, Y. (2024). Distinctive aerosol–cloud–precipitation interactions in marine boundary layer clouds from the ACE-ENA and SOCRATES aircraft field campaigns. Atmospheric Chemistry and Physics, 24(18). doi:10.5194/acp-24-10323-2024
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  The aerosol–cloud–precipitation interactions within the cloud-topped marine boundary layer (MBL) are examined using aircraft in situ measurements from Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) and Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) field campaigns. SOCRATES clouds exhibit a larger number concentration and smaller cloud droplet effective radius (148.3 cm−3 and 8.0 µm) compared to ACE-ENA summertime (89.4 cm−3 and 9.0 µm) and wintertime clouds (70.6 cm−3 and 9.8 µm). The ACE-ENA clouds, especially during the winter, feature stronger drizzle formation via droplet growth through enhanced collision–coalescence that is attributed to a relatively cleaner environment and deeper cloud layer. Furthermore, the aerosol–cloud interaction (ACI) indices from the two aircraft field campaigns exhibit distinct sensitivities, indicating different cloud microphysical responses to aerosols. The ACE-ENA winter season features relatively fewer aerosols, which are more likely activated into cloud droplets under the conditions of sufficient water vapor availability and strong turbulence. The enriched aerosol loading during ACE-ENA summer and SOCRATES generally leads to smaller cloud droplets competing for the limited water vapor and exhibiting a stronger ACI. Notably, the precipitation susceptibilities are stronger during the ACE-ENA than during the SOCRATES campaigns. The in-cloud drizzle behavior significantly alters sub-cloud cloud condensation nuclei (CCN) budgets through the coalescence-scavenging effect and, in turn, impacts the ACI assessments. The results of this study can enhance understanding and aid in future model simulation and assessment of the aerosol–cloud interaction.
• Zhong, X., Dong, X., Xi, B., Brendecke, J., & Pilewskie, P. (2024). Tracing the physical signatures among the calculated global clear-sky spectral shortwave radiative flux distribution. Journal of Quantitative Spectroscopy and Radiative Transfer, 328. doi:10.1016/j.jqsrt.2024.109167
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  This study utilized the high-spectral resolution radiative transfer model (MODerate resolution atmospheric TRANsmission, MODTRAN6.0.2.5) to compute global clear-sky shortwave (SW) radiative flux and compared it with NASA's Clouds and the Earth's Radiant Energy System (CERES) Synoptic Radiative Fluxes and Clouds (SYN1deg) product. The comparison revealed that the global distributions of clear-sky downwelling SW fluxes at the surface from the M6.0 calculations and SYN1 results are similar, with annual means of 246.51 Wm-2 and 242.42 Wm-2, respectively. Analysis further showed that most of the M6.0 calculations are slightly higher from low to mid-latitudes, particularly in the Northern Hemisphere (NH), but lower in higher latitudes compared to SYN1 results. However, these differences mostly fall within the CERES estimated uncertainty (6 Wm-2) of monthly mean clear-sky downwelling SW flux at the surface. The sensitivity of clear-sky SW/μ0 fluxes to changes in Precipitable Water Vapor (PWV), represented by the clear-sky water vapor radiative kernel, is about -0.7 Wm-2/(kgm-2) over oceans for both M6.0 and CERES SYN1 products, except for SYN1 results over the Southern Hemisphere (SH) ocean. Additionally, the zonal means of land coverage and SW/VIS/NIR albedos from M6.0 calculations indicate that VIS albedos are highest in polar regions (>60°), followed by SW and NIR albedos, while NIR albedos become highest from low to mid-latitudes (
• Logan, T., Dong, X., Xi, B., Zheng, X., Wu, L., Abramowitz, A., & Goluszka, A. (2023). Assessing Radiative Impacts of African Smoke Aerosols over the Southeastern Atlantic Ocean. Earth and Space Science. doi:10.22541/essoar.168748472.26906237/v1
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  Biomass burning smoke aerosols exhibit complex impacts on the temperature profile of the atmosphere and cloud development. Central Africa is a region where smoke aerosols are constantly being transported westward over the remote southeastern Atlantic Ocean. A dedicated measurement platform located on Ascension Island, maintained by the U. S. Department of Energy, observed several plumes of biomass burning smoke during the 2016 and 2017 austral burn season months. It was found that the smoke aerosols displayed different radiative properties while readily activating as cloud condensation nuclei. An anomalously strong African Easterly Jet was responsible for facilitating extreme fire conditions in 2016. During the 2017 burn season, an anomalously weaker jet led to more mixing of mineral dust and marine aerosols which were more efficient at cooling the atmosphere than in 2016.
• Marcovecchio, A. R., Xi, B., Zheng, X., Wu, P., Dong, X., & Behrangi, A. (2023). What Are the Similarities and Differences in Marine Boundary Layer Cloud and Drizzle Microphysical Properties During the ACE‐ENA and MARCUS Field Campaigns?. Journal of Geophysical Research: Atmospheres, 128(18). doi:10.1029/2022jd037109
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  This study compares macrophysical and microphysical properties of single-layered, liquid-dominant MBL clouds from the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) (above 60°S) and the ARM East North Atlantic (ENA) site during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) field campaign. A total of 1,136 (16.5% of clouds) and 6,034 5-min cloud samples are selected from MARCUS and ARM ENA in this study. MARCUS clouds have higher cloud-top heights, thicker cloud layers, larger liquid water path, and colder cloud temperatures than ENA. Thinner, warmer MBL clouds at ENA can contain higher layer-mean liquid water content due to higher cloud and ocean surface temperatures along with greater precipitable water vapor (PWV). MARCUS has a higher drizzle frequency rate (71.8%) than ENA (45.1%). Retrieved cloud and drizzle microphysical properties from each field campaign show key differences. MARCUS clouds feature smaller cloud droplets, whereas ENA clouds have larger cloud droplets, especially at the upper region of the cloud. From cloud top to cloud base, drizzle drop sizes increase while number concentrations decrease. Drizzle drop radius and number concentration decrease from cloud base to drizzle base due to net evaporation, and MARCUS' lower specific humidity leads to a higher drizzle base than ENA. The broader surface pressure and lower tropospheric stability (LTS) distributions during MARCUS have demonstrated that there are different synoptic patterns for selected cases during MARCUS with less PWV, while ENA is dominated by high pressure systems with nearly doubled PWV.
• Wang, Y., Zheng, X., Dong, X., Xi, B., & Yung, Y. (2023). Insights of warm-cloud biases in Community Atmospheric Model 5 and 6 from the single-column modeling framework and Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) observations. Atmospheric Chemistry and Physics, 23(15). doi:10.5194/acp-23-8591-2023
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  There has been a growing concern that most climate models predict precipitation that is too frequent, likely due to lack of reliable subgrid variability and vertical variations in microphysical processes in low-level warm clouds. In this study, the warm-cloud physics parameterizations in the singe-column configurations of NCAR Community Atmospheric Model version 6 and 5 (SCAM6 and SCAM5, respectively) are evaluated using ground-based and airborne observations from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign near the Azores islands during 2017-2018. The 8-month single-column model (SCM) simulations show that both SCAM6 and SCAM5 can generally reproduce marine boundary layer cloud structure, major macrophysical properties, and their transition. The improvement in warm-cloud properties from the Community Atmospheric Model 5 and 6 (CAM5 to CAM6) physics can be found through comparison with the observations. Meanwhile, both physical schemes underestimate cloud liquid water content, cloud droplet size, and rain liquid water content but overestimate surface rainfall. Modeled cloud condensation nuclei (CCN) concentrations are comparable with aircraft-observed ones in the summer but are overestimated by a factor of 2 in winter, largely due to the biases in the long-range transport of anthropogenic aerosols like sulfate. We also test the newly recalibrated autoconversion and accretion parameterizations that account for vertical variations in droplet size. Compared to the observations, more significant improvement is found in SCAM5 than in SCAM6. This result is likely explained by the introduction of subgrid variations in cloud properties in CAM6 cloud microphysics, which further suppresses the scheme's sensitivity to individual warm-rain microphysical parameters. The predicted cloud susceptibilities to CCN perturbations in CAM6 are within a reasonable range, indicating significant progress since CAM5 which produces an aerosol indirect effect that is too strong. The present study emphasizes the importance of understanding biases in cloud physics parameterizations by combining SCM with in situ observations.
• Wang, Y., Zheng, X., Dong, X., Xi, B., & Yung, Y. L. (2023). Insights of warm cloud biases in CAM5 and CAM6 from the single-column modeling framework and ACE-ENA observations. ACP. doi:10.5194/egusphere-2023-587
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  Abstract. There has been a growing concern that most climate models predict too frequent precipitation, likely due to lack of reliable sub-grid variability and vertical variations of microphysical processes in low-level warm clouds. In this study, the warm cloud physics parameterizations in the singe-column configurations of NCAR Community Atmospheric Model version 6 and 5 (SCAM6 and SCAM5, respectively) are evaluated using ground-based and airborne observations from the DOE ARM Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign near the Azores islands during 2017–2018. Eight-month SCM simulations show that both SCAM6 and SCAM5 can generally reproduce marine boundary-layer cloud structure, major macrophysical properties, and their transition. The improvement of warm cloud properties from CAM5 to CAM6 physics can be found compared to the observations. Meanwhile, both physical schemes underestimate cloud liquid water content, cloud droplet size, and rain liquid water content, but overestimate surface rainfall. Modeled cloud condensation nuclei (CCN) concentrations are comparable with aircraft observed ones in the summer but overestimated by a factor of two in winter, largely due to the biases in the long-range transport of anthropogenic aerosols like sulfate. We also test the newly recalibrated autoconversion and accretion parameterizations that account for vertical variations of droplet size. Compared to the observations, more significant improvement is found in SCAM5 than in SCAM6. This result is likely explained by the introduction of sub-grid variations of cloud properties in CAM6 cloud microphysics, which further suppresses the scheme sensitivity to individual warm rain microphysical parameters. The predicted cloud susceptibilities to CCN perturbations in CAM6 are within a reasonable range, indicating significant progress since CAM5 which produces too strong aerosol indirect effect. The present study emphasizes the importance of understanding biases in cloud physics parameterizations by combining SCM with in situ observations.
• Wang, Y., Zheng, X., Dong, X., Xi, B., & Yung, Y. L. (2023). Supplementary material to "Insights of warm cloud biases in CAM5 and CAM6 from the single-column modeling framework and ACE-ENA observations". Atomspheric chemistry and Physics (ACP). doi:10.5194/egusphere-2023-587-supplement
• 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
• Yang, X., Cai, Z., Xi, B., Li, J., Li, P., Yang, J., Sun, H., Wang, B., & Zhu, Y. (2023). Assessing the performance of Ka-band millimeter-wavelength cloud radar retrieval of microphysical parameters in central China Monsoon frontal clouds. ESS Open Archive. doi:10.22541/essoar.168351205.50687482/v1
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  This study investigates the microphysical properties of the Monsoon frontal cloud (MFC), which were inhomogeneous and exhibited scale differences based on observations and simulations. This research aims to better understand MFC microphysical processes, which are crucial for comprehending the precipitation mechanism during the summer of the middle and lower reaches of the Yangtze river. The results show that the Ka-band Precipitation Radar (KPR) measured reflectivity factor (dBZKPR) agrees well with the observed reflectivity (dBZobs), with a correlation coefficient of 0.78 and a mean bias of 2.45 dBZ along the aircraft flight track, indicating the reliability of KPR for detecting and retrieving cloud microphysical properties. Based on this, four approaches were conducted to create the relationships between radar reflectivity (Z) and microphysical parameters such as liquid water content (LWC) and effective diameter (De) which were then validated. Differential precipitation and non-precipitation clouds proved effective in predicting LWC using dBZKPR, while De required the further division of LWC into seven bins at 100.5 g m-3 intervals. The empirical formulas used in this study produced results closest to observation data compared to previous studies. Detailed criteria for using these formulas were quantified, including differentiating grounded echoes and the size of the retrieved LWC values. This study sheds light on the microphysical properties of the MFC and provides insights into the precipitation mechanism of the middle and lower reaches of the Yangtze river during the summer.
• Zhang, X., Dong, X., Xi, B., & Zheng, X. (2023). Aerosol Properties and Their Influences on Marine Boundary Layer Cloud Condensation Nuclei over the Southern Ocean. Atmosphere, 14(8), 1246. doi:10.3390/atmos14081246
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  Five overcast marine stratocumulus cases during the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES) aircraft field campaign were selected to examine aerosol and cloud condensation nuclei (CCN) properties with cloud influence. The Aitken- and accumulation-mode aerosols contributed approximately 70% and 30% of the total aerosols, respectively. The aerosol properties before and after periods of drizzle were investigated using in situ measurements during one case. Sub-cloud drizzle processes impacted accumulation-mode aerosols and CCN distribution. There was a nearly linear increase in CCN number concentration (NCCN) with supersaturation (S) during the ‘before drizzle’ period, but this was not true for the ‘after drizzle’ period, particularly when S > 0.4%. Using the hygroscopicity parameter (κ) to quantitatively investigate the chemical cloud-processing mechanisms, we found that higher κ values (>0.4) represent cloud-processing aerosols, while lower κ values (
• Zheng, X., Dong, X., Xi, B., Logan, T., & Wang, Y. (2023). Supplementary material to "Distinctive aerosol-cloud-precipitation interactions in marine boundary layer clouds from the ACE-ENA and SOCRATES aircraft field campaigns". ACP. doi:10.5194/egusphere-2023-2608-supplement
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  Abstract. The aerosol-cloud-precipitating interaction within the cloud-topped Marine Boundary Layer (MBL), are being examined using aircraft in-situ measurements from Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) and Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES) field campaigns. SOCRATES clouds have a larger number of smaller cloud droplets compared to ACE-ENA summertime and wintertime clouds. The ACE-ENA clouds, especially in wintertime, exhibit pronounced drizzle formation and growth, attributed to the strong in-cloud turbulence that enhances the collision-coalescence process. Furthermore, the Aerosol-Cloud Interaction (ACI) indices from the two aircraft field campaigns suggest distinct sensitivities. The aerosols during ACE-ENA winter are more likely to be activated into cloud droplets due to more larger aerosols and strong vertical turbulence. The enriched aerosol loading during SOCRATES generally leads to smaller cloud droplets competing for available water vapor and exhibiting a stronger ACI. The ACI calculated near the cloud base was noticeably larger than the layer-mean and near-cloud-top, owing to the closer connection between the cloud layer and sub-cloud aerosols. Notably, the sensitivities of cloud base precipitating rates to cloud-droplet number concentrations are more pronounced during the ACE-ENA than during the SOCRATES campaigns. The in-cloud drizzle evolutions significantly alter sub-cloud cloud condensation nuclei (CCN) budgets through the coalescence-scavenging effect, and in turn, impact the ACI assessments. The results of this study can enhance the understanding and aid in future model simulation and assessment of the aerosol-cloud interaction.
• 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.
• Xi, B., Dong, X., Zheng, X., & Wu, P. (2022). Cloud phase and macrophysical properties over the Southern Ocean during the MARCUS field campaign. Atmospheric Measurement Techniques, 15(12). doi:10.5194/amt-15-3761-2022
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  To investigate the cloud phase and macrophysical properties over the Southern Ocean (SO), the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF2) was installed on the Australian icebreaker research vessel (R/V) Aurora Australis during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign (41 to 69°S, 60 to 160°E) from October 2017 to March 2018. To examine cloud properties over the midlatitude and polar regions, the study domain is separated into the northern (NSO) and southern (SSO) parts of the SO, with a demarcation line of 60°S. The total cloud fractions (CFs) were 77.9%, 67.6%, and 90.3% for the entire domain, NSO and SSO, respectively, indicating that higher CFs were observed in the polar region. Low-level clouds and deep convective clouds are the two most common cloud types over the SO. A new method was developed to classify liquid, mixed-phase, and ice clouds in single-layered, low-level clouds (LOW), where mixed-phase clouds dominate with an occurrence frequency (Freq) of 54.5%, while the Freqs of the liquid and ice clouds were 10.1% (most drizzling) and 17.4% (least drizzling). The meridional distributions of low-level cloud boundaries are nearly independent of latitude, whereas the cloud temperatures increased by ∼1/48K, and atmospheric precipitable water vapor increased from ∼1/45mm at 69°S to ∼1/418mm at 43°S. The mean cloud liquid water paths over NSO were much larger than those over SSO. Most liquid clouds occurred over NSO, with very few over SSO, whereas more mixed-phase clouds occurred over SSO than over NSO. There were no significant differences for the ice cloud Freq between NSO and SSO. The ice particle sizes are comparable to cloud droplets and drizzle drops and well mixed in the cloud layer. These results will be valuable for advancing our understanding of the meridional and vertical distributions of clouds and can be used to improve model simulations over the SO.
• Zheng, X., Dong, X., Ward, D., Xi, B., Wu, P., & Wang, Y. (2022). Aerosol-Cloud-Precipitation Interactions in a Closed-cell and Non-homogenous MBL Stratocumulus Cloud. Advances in Atmospheric Sciences, 39(12). doi:10.1007/s00376-022-2013-6
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  A closed-cell marine stratocumulus case during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) aircraft field campaign is selected to examine the heterogeneities of cloud and drizzle microphysical properties and the aerosol-cloud-precipitation interactions. The spatial and vertical variabilities of cloud and drizzle microphysics are found in two different sets of flight legs: Leg-1 and Leg-2, which are parallel and perpendicular to the cloud propagation, respectively. The cloud along Leg-2 was close to adiabatic, where cloud-droplet effective radius and liquid water content linearly increase from cloud base to cloud top with less drizzle. The cloud along Leg-1 was sub-adiabatic with lower cloud-droplet number concentration and larger cloud-droplet effective, but higher drizzle droplet number concentration, larger drizzle droplet median diameter and drizzle liquid water content. The heavier drizzle frequency and intensity on Leg-1 were enhanced by the collision-coalescence processes within cloud due to strong turbulence. The sub-cloud precipitation rate on Leg-1 was significantly higher than that along Leg-2. As a result, the sub-cloud accumulation mode aerosols and CCN on Leg-1 were depleted, but the coarse model aerosols increased. This further leads to a counter-intuitive phenomenon that the CCN is less than cloud-droplet number concentration for Leg-1. The average CCN loss rates are −3.89 cm−3 h−1 and −0.77 cm−3 h−1 on Leg-1 and Leg-2, respectively. The cloud and drizzle heterogeneities inside the same stratocumulus can significantly alter the sub-cloud aerosols and CCN budget. Hence it should be treated with caution in the aircraft assessment of aerosol-cloud-precipitation interactions.
• 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
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  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.
• Cui, W., Dong, X., Xi, B., & Feng, Z. (2020). Climatology of linear mesoscale convective system morphology based on random forests method. Journal of Climate.
• 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
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  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.
• Zhang, H., Dong, X., Xi, B., Xin, X., Liu, Q., He, H., Xie, X., Li, L., & Yu, S. (2021). Retrieving high-resolution surface photosynthetically active radiation from the MODIS and GOES-16 ABI data. Remote Sensing of Environment. doi:10.1016/j.rse.2021.112436
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  Incident photosynthetically active radiation (PAR) is a key parameter in plant physiological, biological and physical process-based terrestrial ecosystem models. Deriving highly accurate and spatially continuous PAR from remote sensing data can fill in the gaps of insufficient ground-based measurements. In this study, we provide an efficient approach for estimating PAR by employing look-up table (LUT) method using observations from both MODIS and GOES-16. The GOES-16 is the first satellite of the new-generation US Geostationary Operational Environmental Satellite R-series (GOES-R), which can capture dynamic changes in the atmosphere every 5 min. First, the diurnal variation of surface bidirectional reflectance is characterized assuming that the surface characteristics and solar zenith angles in tropical and middle latitudes at a given time of day do not change dramatically within a month. Next, the aerosol optical depth (AOD) and cloud optical depth (COD) are retrieved from the GOES-16 visible observations under both clear-sky and cloudy conditions. Finally, PAR is estimated via the retrieved AOD and COD using the LUT method and a MODIS-based surface albedo product. The estimated PAR was compared against ground-based measurements collected from seven SURFace RADiation budget network (SURFRAD) sites and 23 National Ecological Observatory Network (NEON) sites at instantaneous, hourly and daily scales. The instantaneous PAR validation results achieved R2 values of 0.97 and 0.82, and root mean square errors (RMSEs) of 18.1 and 51.1 W m‐2, for clear and cloudy skies, respectively. The RMSEs of the hourly averaged PAR were reduced to 16.8 W m−2 and 40.4 W m−2, respectively, for clear-sky and cloudy conditions. The daily mean PAR evaluation for all sky conditions shows an overall mean bias error (MBE) of 0.97 W m−2 and an RMSE of 10.5 W m−2. Compared with other global PAR datasets, the estimated PAR values in this study have lower RMSEs and higher spatial-temporal resolution. Uncertainties in the retrieved PAR caused by topography and solar-cloud-geometry effects (SCGE) can be reduced by spatial and temporal averaging. Based on an evaluation of retrievals at different spatial-temporal scales, we recommend that a 20 × 20 km2 domain-averaged PAR be utilized for instantaneous PAR validation, whereas hourly and daily averaged PAR values are nearly independent of spatial scale.
• 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
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  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
• Huang, Y., Ding, Q., Dong, X., Baxter, I., & Xi, B. (2019). Linking large-scale atmospheric circulation variability with cloud changes during the Arctic sea ice melt season. Communications Earth and Environment.
• 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.
• Logan, T., Zheng, X., Xi, B., & Dong, X. (2018).

  Aerosol properties and their impacts on surface CCN at the

   ARM Southern Great Plains site during the 2011 Midlatitude Continental Convective Cloud Experiment. Adv. Atmos. Sci.

• 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
• Chen, X., Huang, X., Loeb, N. G., Dong, X., Xi, B., Dolinar, E. K., Bosilovich, M. G., Kato, S., Smith, W. L., & Stackhouse, P. W. (2017). A clear-sky hyperspectral closure study for MERRA-2 and ERA-interim reanalyses. JGR.
• 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.
• Dolinar, E. K., Dong, X., Xi, B., Jiang, J., & Su, H. (2014).

  Evaluation of CMIP5 simulated Clouds and TOA Radiation Budgets using NASA satellite observations

  . Climate Dynamics.
• 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.
• Dong, X., Xi, B., Kennedy, A., Minnis, P., & Wood, R. (2013). A 19-Month Climatology of Marine Aerosol-Cloud-Radiation Properties Derived From DOE ARM AMF Deployment at the Azores: Part I: Cloud Fraction and Single-Layered MBL Cloud Properties. Journal of Climate.
• 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
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  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
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  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.
• Dong, X., Xi, B., Crosby, K., Long, C. S., & Stone, R. S. (2009). A 10-yr Climatology of Arctic Cloud Fraction and Surface Radiation Budget at Barrow, Alaska. JGR.
• 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. Journal of Climate. doi:10.1175/jcli3710.1
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  Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility are analyzed for determining the variability of cloud fraction and radiative forcing at several temporal scales between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layer low (0-3 km), middle (3-6 km), and high clouds (greater than 6 km) using ARM SGP ground-based paired lidar-radar measurements. Shortwave (SW), longwave (LW), and net cloud radiative forcings (CRF) are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements. The annual averages of total, and single-layer, nonoverlapped low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Total and low cloud amounts were greatest from December through March and least during July and August. The monthly variation of high cloud amount is relatively small with a broad maximum from May to August. During winter, total cloud cover varies diurnally with a small amplitude, mid-morning maximum and early evening minimum, and during summer it changes by more than 0.14 over the daily cycle with a pronounced early evening minimum. The diurnal variations of mean single-layer cloud cover change with season and cloud height. Annual averages of all-sky, total, and single-layer high, middle, and low LW CRFs are 21.4, 40.2, 16.7, 27.2, and 55.0 Wm(sup -2), respectively; and their SW CRFs are -41.5, -77.2, -37.0, -47.0, and -90.5 Wm(sup -2). Their net CRFs range from -20 to -37 Wm(sup -2). For all-sky, total, and low clouds, the maximum negative net CRFs of -40.1, -70, and -69.5 Wm(sup -2), occur during April; while the respective minimum values of -3.9, -5.7, and -4.6 Wm(sup -2), are found during December. July is the month having maximum negative net CRF of -46.2 Wm(sup -2) for middle clouds, and May has the maximum value of -45.9 Wm(sup -2) for high clouds. An uncertainty analysis demonstrates that the calculated CRFs are not significantly affected by the difference between clear-sky and cloudy conditions. A more comprehensive cloud fraction study from both surface and satellite observations will follow.
• 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
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  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...

Proceedings Publications

• Dong, X., Wu, P., Xi, B., Tian, J., & Ward, D. (2020). Profiles of MBL cloud and drizzle microphysical properties retrieved from ground-based observations and validated by aircraft in-situ measurements over the Azores. In AGU.
• Dong, X., & Xi, B. (2013). Marine and Continental Low-level Cloud Processes and Properties. In AGU.
• Xi, B. (1999). Laboratory investigation of heterogeneous interactions involving an atmospheric trace gas and ice. In Cloud physics and chemistry.