scholarly journals Is Positive Correlation between Cloud Droplet Effective Radius and Aerosol Index over Land Due to Retrieval Artifacts or Real Physical Processes?

2019 ◽  
Author(s):  
Hailing Jia ◽  
Xiaoyan Ma ◽  
Johannes Quaas ◽  
Yan Yin ◽  
Tom Qiu
Keyword(s):  
Radiant Energy ◽  
Single Layer ◽  
Cloud Droplet ◽  
Energy System ◽  
Reanalysis Data ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Anthropogenic Aerosol ◽  
Aerosol Cloud ◽  
Aerosol Index

Abstract. The Moderate Resolution Imaging Spectroradiometer (MODIS) C6 L3, Clouds and the Earth's Radiant Energy System (CERES) Edition-4 L3 products, and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis data are employed to systematically study aerosol-cloud correlations over three anthropogenic aerosol regions and their adjacent oceans, as well as explore the effect of retrieval artifacts and underlying physical mechanisms. This study is confined to warm phase and single layer clouds without precipitation during the summertime (June, July, and August). Our analysis suggest that cloud effective radius (CER) is positively correlated with aerosol index (AI) over land (positive slopes), but negatively correlated over oceans (negative slopes) even with small ranges of liquid water path (quasi-constant). The changes in albedo at the top of atmosphere (TOA) corresponding to aerosol-induced changes in CER also lends credence to the authenticity of this opposite aerosol-cloud correlation between land and ocean. It is noted that potential artifacts, such as the retrieval biases of both cloud (partially cloudy and 3-D shaped clouds) and aerosol, can result in a serious overestimation of the slope of CER-AI. Our results show that collision-coalescence seems not to be the dominant cause for positive slope over land, but the increased CER caused by increased aerosol might further increase CER by initializing collision-coalescence, generating a positive feedback. By stratifying data according to the lower tropospheric stability and relative humidity near cloud top, it is found that the positive correlations more likely occur in case of drier cloud top and stronger turbulence in clouds, while negative correlations occur in case of moister cloud top and weaker turbulence in clouds, which implies entrainment mixing might be a possible physical interpretation for such a positive CER-AI slope.

scholarly journals Is positive correlation between cloud droplet effective radius and aerosol optical depth over land due to retrieval artifacts or real physical processes?

2019 ◽  
Vol 19 (13) ◽  
pp. 8879-8896 ◽  
Author(s):  
Hailing Jia ◽  
Xiaoyan Ma ◽  
Johannes Quaas ◽  
Yan Yin ◽  
Tom Qiu
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Radiant Energy ◽  
Single Layer ◽  
Cloud Droplet ◽  
Energy System ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Anthropogenic Aerosol ◽  
Aerosol Cloud

Abstract. The Moderate Resolution Imaging Spectroradiometer (MODIS) C6 L3, Clouds and the Earth's Radiant Energy System (CERES) Edition-4 L3 products, and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis data are employed to systematically study aerosol–cloud correlations over three anthropogenic aerosol regions and their adjacent oceans, as well as explore the effect of retrieval artifacts and underlying physical mechanisms. This study is confined to warm phase and single-layer clouds without precipitation during the summertime (June, July, and August). Our analysis suggests that cloud effective radius (CER) is positively correlated with aerosol optical depth (AOD) over land (positive slopes), but negatively correlated with aerosol index (AI) over oceans (negative slopes) even with small ranges of liquid water path (quasi-constant). The changes in albedo at the top of the atmosphere (TOA) corresponding to aerosol-induced changes in CER also lend credence to the authenticity of this opposite aerosol–cloud correlation between land and ocean. It is noted that potential artifacts, such as the retrieval biases of both cloud (partially cloudy and 3-D-shaped clouds) and aerosol, can result in a serious overestimation of the slope of CER–AOD/AI. Our results show that collision–coalescence seems not to be the dominant cause for positive slope over land, but the increased CER caused by increased aerosol might further increase CER by initializing collision–coalescence, generating a positive feedback. By stratifying data according to the lower tropospheric stability and relative humidity near cloud top, it is found that the positive correlations more likely occur in the case of drier cloud top and stronger turbulence in clouds, while negative correlations occur in the case of moister cloud top and weaker turbulence in clouds, which implies entrainment mixing might be a possible physical interpretation for such a positive CER–AOD slope.

scholarly journals Building a cloud in the Southeast Atlantic: Understanding low-cloud controls based on satellite observations with machine learning

2018 ◽  
Author(s):  
Julia Fuchs ◽  
Jan Cermak ◽  
Hendrik Andersen
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Cloud Droplet ◽  
Reanalysis Data ◽  
Cloud Fraction ◽  
Effective Radius ◽  
Gradient Boosting ◽  
Tropospheric Temperature ◽  
Aerosol Cloud ◽  
Low Cloud

Abstract. Understanding the processes that determine low-cloud properties and aerosol–cloud interactions (ACI) is crucial for the estimation of their radiative effects. However, the covariation of meteorology and aerosols complicates the determination of cloud-relevant influences and the quantification of the aerosol–cloud relation. This study identifies and analyzes sensitivities of cloud fraction and cloud droplet effective radius to their meteorological and aerosol environment in the atmospherically stable Southeast Atlantic during the biomass-burning season. The effect of geophysical parameters on clouds is investigated based on a machine learning technique, gradient boosting regression trees (GBRTs), using a combination of satellite and reanalysis data as well as trajectory modeling of air-mass origins. A comprehensive, multivariate analysis of important drivers of cloud occurrence and properties is performed and evaluated. The statistical model reveals marked subregional differences of relevant drivers and processes determining low clouds in the Southeast Atlantic. Cloud fraction is sensitive to changes of lower tropospheric stability in the oceanic, southwestern subregion, while in the northeastern subregion it is governed mostly by surface winds. In the pristine, oceanic subregion large-scale dynamics and aerosols seem to be more important for changes of cloud droplet effective radius than in the polluted, near-shore subregion, where free tropospheric temperature is more relevant. This study suggests the necessity to consider distinct ACI regimes in cloud studies in the Southeast Atlantic.

scholarly journals Ground-based remote sensing scheme for monitoring aerosol–cloud interactions

2016 ◽  
Vol 9 (3) ◽  
pp. 1039-1050 ◽  
Author(s):  
Karolina Sarna ◽  
Herman W. J. Russchenberg
Keyword(s):  
Remote Sensing ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Aerosol Concentration ◽  
Backscatter Coefficient ◽  
Liquid Water Path ◽  
Data Set ◽  
Aerosol Cloud ◽  
Microphysical Properties ◽  
Aerosol Cloud Interactions

Abstract. A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example case studies were chosen from the Atmospheric Radiation Measurement (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius (re) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m−2 wide. For every LWP bin we present the correlation coefficient between ln re and ln ATB, as well as ACIr (defined as ACIr = −d ln re∕d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACIr are in the range 0.01–0.1. We show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.

scholarly journals MBL drizzle properties and their impact on cloud property retrievals

2015 ◽  
Vol 8 (4) ◽  
pp. 4307-4323
Author(s):  
P. Wu ◽  
X. Dong ◽  
B. Xi
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Property ◽  
Annual Means ◽  
Mean Differences ◽  
The Impact

Abstract. In this study, we retrieve and document drizzle properties, and investigate the impact of drizzle on cloud property retrievals from ground-based measurements at the ARM Azores site from June 2009 to December 2010. For the selected cloud and drizzle samples, the drizzle occurrence is 42.6% with a maximum of 55.8% in winter and a minimum of 35.6% in summer. The annual means of drizzle liquid water path LWPd, effective radius rd, and number concentration Nd for the rain (virga) samples are 5.48 (1.29) g m−2, 68.7 (39.5) μm, and 0.14 (0.38) cm−3. The seasonal mean LWPd values are less than 4% of the MWR-retrieved LWP values. The annual mean differences in cloud-droplet effective radius with and without drizzle are 0.12 and 0.38 μm, respectively, for the virga and rain samples. Therefore, we conclude that the impact of drizzle on cloud property retrievals is insignificant at the ARM Azores site.

scholarly journals Constraints on interactions between aerosols and clouds on a global scale from a combination of MODIS-CERES satellite data and climate simulations

2010 ◽  
Vol 10 (20) ◽  
pp. 9851-9861 ◽  
Author(s):  
X. Ma ◽  
K. von Salzen ◽  
J. Cole
Keyword(s):  
Liquid Water ◽  
Negative Relationship ◽  
Cloud Droplet ◽  
Global Scale ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Cloud Droplets ◽  
Cloud Liquid Water ◽  
Albedo Effect ◽  
Cloud Liquid Water Path

Abstract. Satellite-based cloud top effective radius retrieved by the CERES Science Team were combined with simulated aerosol concentrations from CCCma CanAM4 to examine relationships between aerosol and cloud that underlie the first aerosol indirect (cloud albedo) effect. Evidence of a strong negative relationship between sulphate, and organic aerosols, with cloud top effective radius was found for low clouds, indicating both aerosol types are contributing to the first indirect effect on a global scale. Furthermore, effects of aerosol on the cloud droplet effective radius are more pronounced for larger cloud liquid water paths. While CanAM4 broadly reproduces the observed relationship between sulphate aerosols and cloud droplets, it does not reproduce the dependency of cloud top droplet size on organic aerosol concentrations nor the dependency on cloud liquid water path. Simulations with a modified version of the model yield a more realistic dependency of cloud droplets on organic carbon. The robustness of the methods used in the study are investigated by repeating the analysis using aerosol simulated by the GOCART model and cloud top effective radii derived from the MODIS Science Team.

scholarly journals The source of discrepancies in aerosol–cloud–precipitation interactions between GCM and A-Train retrievals

2016 ◽  
Vol 16 (23) ◽  
pp. 15413-15424 ◽  
Author(s):  
Takuro Michibata ◽  
Kentaroh Suzuki ◽  
Yousuke Sato ◽  
Toshihiko Takemura
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Cloud Droplet ◽  
Systematic Difference ◽  
Liquid Water Path ◽  
Light Rain ◽  
Aerosol Cloud ◽  
Nonlinear Complexity ◽  
Aerosol Cloud Interactions

Abstract. Aerosol–cloud interactions are one of the most uncertain processes in climate models due to their nonlinear complexity. A key complexity arises from the possibility that clouds can respond to perturbed aerosols in two opposite ways, as characterized by the traditional “cloud lifetime” hypothesis and more recent “buffered system” hypothesis. Their importance in climate simulations remains poorly understood. Here we investigate the response of the liquid water path (LWP) to aerosol perturbations for warm clouds from the perspective of general circulation model (GCM) and A-Train remote sensing, through process-oriented model evaluations. A systematic difference is found in the LWP response between the model results and observations. The model results indicate a near-global uniform increase of LWP with increasing aerosol loading, while the sign of the response of the LWP from the A-Train varies from region to region. The satellite-observed response of the LWP is closely related to meteorological and/or macrophysical factors, in addition to the microphysics. The model does not reproduce this variability of cloud susceptibility (i.e., sensitivity of LWP to perturbed aerosols) because the parameterization of the autoconversion process assumes only suppression of rain formation in response to increased cloud droplet number, and does not consider macrophysical aspects that serve as a mechanism for the negative responses of the LWP via enhancements of evaporation and precipitation. Model biases are also found in the precipitation microphysics, which suggests that the model generates rainwater readily even when little cloud water is present. This essentially causes projections of unrealistically frequent and light rain, with high cloud susceptibilities to aerosol perturbations.

scholarly journals An intercomparison of radar-based liquid cloud microphysics retrievals and implication for model evaluation studies

2011 ◽  
Vol 4 (6) ◽  
pp. 7109-7158 ◽  
Author(s):  
D. Huang ◽  
C. Zhao ◽  
M. Dunn ◽  
X. Dong ◽  
G. G. Mace ◽  
...  
Keyword(s):  
Great Plains ◽  
Liquid Water ◽  
Model Evaluation ◽  
Evaluation Studies ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Cloud Microphysics ◽  
Effective Radius ◽  
High Altitudes ◽  
Liquid Water Path

Abstract. To assess if current radar-based liquid cloud microphysical retrievals of the Atmospheric Radiation Measurement (ARM) program can provide useful constraints for modeling studies, this paper presents intercomparison results of three cloud products at the Southern Great Plains (SGP) site: the ARM MICROBASE, University of Utah (UU), and University of North Dakota (UND) products over the nine-year period from 1998 to 2006. The probability density and spatial autocorrelation functions of the three cloud Liquid Water Content (LWC) retrievals appear to be consistent with each other, while large differences are found in the droplet effective radius retrievals. The differences in the vertical distribution of both cloud LWC and droplet effective radius retrievals are found to be alarmingly large, with the relative difference between nine-year mean cloud LWC retrievals ranging from 20% at low altitudes to 100% at high altitudes. Nevertheless, the spread in LWC retrievals is much smaller than that in cloud simulations by climate and cloud resolving models. The MICROBASE effective radius ranges from 2.0 at high altitudes to 6.0 μm at low altitudes and the UU and UND droplet effective radius is 6 μm larger. Further analysis through a suite of retrieval experiments shows that the difference between MICROBASE and UU LWC retrievals stems primarily from the partition total Liquid Water path (LWP) into supercooled and warm liquid, and from the input cloud boundaries and LWP. The large differences between MICROBASE and UU droplet effective radius retrievals are mainly due to rain/drizzle contamination and the assumptions of cloud droplet concentration used in the retrieval algorithms. The large discrepancy between different products suggests caution in model evaluation with these observational products, and calls for improved retrievals in general.

scholarly journals Untangling causality in midlatitude aerosol-cloud adjustments

2019 ◽  
Author(s):  
Daniel T. McCoy ◽  
Paul Field ◽  
Hamish Gordon ◽  
Gregory S. Elsaesser ◽  
Daniel P. Grosvenor
Keyword(s):  
Radiative Forcing ◽  
Sensible Heat Flux ◽  
Cloud Droplet ◽  
Causal Link ◽  
Cloud Microphysics ◽  
Liquid Water Path ◽  
Aerosol Cloud ◽  
Causal Pathways ◽  
Model Adjustment ◽  
Aerosol Cloud Interactions

Abstract. Aerosol-cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (Nd) (the first indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of forcing associated with changes in cloud macrophysics in response to aerosol (aerosol-cloud adjustments) remain uncertain. This uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud microphysical state to cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path averaged across cloudy and clear regions (LWP, here, characterizing the macrophysical state) and Nd (characterizing the microphysical) is the sum of two causal pathways linking Nd to LWP: Nd altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting Nd. Only the former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We hypothesize that the diversity of constraints on aerosol-cloud adjustments in the literature may be partly due to not explicitly characterizing covariance flowing from cloud to aerosol, and aerosol to cloud. Here, we restrict our analysis to the regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP, and MODIS are compared to simulations in the MetOffice Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat flux enhance LWP, while increasing subsidence, and sea surface temperature decrease it. A simulation where cloud microphysics are insensitive to changes in Nd is used to characterize covariance between Nd and LWP that is induced by factors other than aerosol-cloud adjustments. By removing variability associated with meteorology and scavenging we infer the sensitivity of LWP to changes in Nd. Application of this technique to UM GA7.1 simulations reproduces the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments and observed covariability between Nd and LWP predict a 25–30 % overestimate by the UM GA7.1 in LWP change and a 30–35% overestimate in associated radiative forcing.

scholarly journals Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice-Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

2007 ◽  
Vol 46 (3) ◽  
pp. 249-272 ◽  
Author(s):  
M. Chiriaco ◽  
H. Chepfer ◽  
P. Minnis ◽  
M. Haeffelin ◽  
S. Platnick ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiant Energy ◽  
Energy System ◽  
Effective Radius ◽  
Cloud Detection ◽  
Regional Study ◽  
Crystal Face ◽  
Ice Clouds ◽  
Microphysical Properties ◽  
Cloud Properties

Abstract This study compares cirrus-cloud properties and, in particular, particle effective radius retrieved by a Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-like method with two similar methods using Moderate-Resolution Imaging Spectroradiometer (MODIS), MODIS Airborne Simulator (MAS), and Geostationary Operational Environmental Satellite imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands to infer the microphysical properties of cirrus clouds. The two other methods, using passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (using 20 spectral bands from visible to infrared, referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the Clouds and the Earth’s Radiant Energy System (CERES) team at Langley Research Center (LaRC) in support of CERES algorithms (using 0.65-, 3.75-, 10.8-, and 12.05-μm bands); the two algorithms will be referred to as the MOD06 and LaRC methods, respectively. The three techniques are compared at two different latitudes. The midlatitude ice-clouds study uses 16 days of observations at the Palaiseau ground-based site in France [Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA)], including a ground-based 532-nm lidar and the MODIS overpasses on the Terra platform. The tropical ice-clouds study uses 14 different flight legs of observations collected in Florida during the intensive field experiment known as the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE), including the airborne cloud-physics lidar and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote sensing method (CALIPSO like) for the study of subvisible ice clouds, in both the midlatitudes and Tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds, because of their particular microphysical properties.

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