Improved Retrieval of Cloud Liquid Water from CloudSat and MODIS

AbstractA revised version of the CloudSat–MODIS cloud liquid water retrieval algorithm is presented. The new algorithm, which combines measurements of radar reflectivity and cloud optical depth, addresses issues discovered in the current CloudSat–MODIS cloud water content (CWC) product. This current product is shown to be underconstrained by observations and to be too dependent on prior information incorporated into the Bayesian optimal-estimation algorithm. The most significant change made to the algorithm in this study was decreasing the number of independent variables to allow the observations to constrain the retrieved values better. The retrieval was also reformulated for improved compliance with the mathematical assumptions of the optimal-estimation algorithm. To validate the accuracy of the revised algorithm, the path-integrated attenuation (PIA) of the CloudSat radar signal was computed from the algorithm results. These modeled values were compared with independent measurements of the PIA that were obtained using a surface reference technique. This comparison shows that the cloud liquid water retrieved by the algorithm is close to being unbiased. The revised algorithm was also found to be an improvement over the current CloudSat CWC product and, to a lesser degree, the MODIS-derived cloud liquid water path.

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Joint Cloud Water Path and Rain Water Path Retrievals from ORACLES Observations

10.5194/acp-2020-849 ◽

2020 ◽

Author(s):

Andrew M. Dzambo ◽

Tristan L'Ecuyer ◽

Kenneth Sinclair ◽

Bastiaan van Diedenhoven ◽

Siddhant Gupta ◽

...

Keyword(s):

Optical Depth ◽

Liquid Water ◽

Cloud Water ◽

Retrieval Algorithm ◽

Liquid Water Path ◽

Cloud Optical Depth ◽

Water Path ◽

Surface Precipitation ◽

Uncertainty Estimates ◽

Cloud Water Path

Abstract. This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar-3rd generation (APR-3), passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ~ 10–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g m−2 and almost all CWPs (99 %) between 6 to 445 g m−2. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP) with more than 70 % of raining clouds having less than 10 g m−2 of rainwater. In heavier warm rain (i.e. rain rate exceeding 40 mm h−1 or 1000 mm d−1), however, RWP is observed to exceed 2500 g m−2. CWP (RWP) is found to be approximately 30 g m−2 (7 g m−2) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in-situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud-precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

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Cross-comparison of cloud liquid water path derived from observations by two space-borne and one ground-based instrument in northern Europe

Atmospheric Measurement Techniques ◽

10.5194/amt-12-5927-2019 ◽

2019 ◽

Vol 12 (11) ◽

pp. 5927-5946 ◽

Cited By ~ 2

Author(s):

Vladimir S. Kostsov ◽

Anke Kniffka ◽

Martin Stengel ◽

Dmitry V. Ionov

Keyword(s):

Liquid Water ◽

Spatial Inhomogeneity ◽

Retrieval Algorithm ◽

Liquid Water Path ◽

Simple Estimate ◽

Cloud Liquid Water ◽

Water Path ◽

Geographical Regions ◽

Temporal And Spatial ◽

Cloud Liquid Water Path

Abstract. Cloud liquid water path (LWP) is one of the target atmospheric parameters retrieved remotely from ground-based and space-borne platforms using different observation methods and processing algorithms. Validation of LWP retrievals is a complicated task since a cloud cover is characterised by strong temporal and spatial variability while remote sensing methods have different temporal and spatial resolutions. An attempt has been made to compare and analyse the collocated LWP data delivered by two satellite instruments SEVIRI and AVHRR together with the data derived from microwave observations by the ground-based radiometer RPG-HATPRO. The geographical region of interest is the vicinity of St. Petersburg, Russia, where the RPG-HATPRO radiometer is operating. The study is focused on two problems. The first one is the so-called scale difference problem, which originates from dissimilar spatial resolutions of measurements. The second problem refers to the land–sea LWP gradient. The radiometric site is located 2.5 km from the coastline where the effects of the LWP gradient are pronounced. A good agreement of data obtained at the microwave radiometer location by all three instruments (HATPRO, SEVIRI, and AVHRR) during warm and cold seasons is demonstrated (the largest correlation coefficient 0.93 was detected for HATPRO and AVHRR datasets). The analysis showed no bias of the SEVIRI results with respect to HATPRO data and a large positive bias (0.013–0.017 kg m−2) of the AVHRR results for both warm and cold seasons. The analysis of LWP maps plotted on the basis of the SEVIRI and AVHRR measurements over land and water surfaces in the vicinity of St. Petersburg revealed the unexpectedly high LWP values delivered by AVHRR during the cold season over the Neva River bay and over the Saimaa Lake and the abnormal land–sea LWP gradient in these areas. For the detailed evaluation of atmospheric state and ice cover in the considered geographical regions during the periods of ground-based and satellite measurements, reanalysis data were used. It is shown that the most probable reason for the observed artefacts in the AVHRR measurements over water and ice surfaces is the coarse resolution of the land–sea and snow–ice masks used by the AVHRR retrieval algorithm. The influence of a cloud field inhomogeneity on the agreement between the satellite and the ground-based data is studied. For this purpose, the simple estimate of the LWP temporal variability is used as a measure of the spatial inhomogeneity. It has been demonstrated that both instruments are equally sensitive to the inhomogeneity of a cloud field despite the fact that they have different spatial resolutions.

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On the Consequences of Resampling Microwave Radiometer Observations for Use in Retrieval Algorithms

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2155.1 ◽

2009 ◽

Vol 48 (9) ◽

pp. 1981-1993 ◽

Cited By ~ 18

Author(s):

Anita D. Rapp ◽

M. Lebsock ◽

C. Kummerow

Keyword(s):

Wind Speed ◽

Liquid Water ◽

Microwave Radiometer ◽

Retrieval Algorithm ◽

Time Averaging ◽

Liquid Water Path ◽

Cloud Liquid Water ◽

Water Path ◽

Brightness Temperatures ◽

Cloud Liquid Water Path

Abstract How to deal with the different spatial resolutions of multifrequency satellite microwave radiometer measurements is a common problem in retrievals of cloud properties and rainfall. Data convolution and deconvolution is a common approach to resampling the measurements to a single resolution. Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) measurements are resampled to the resolution of the 19-GHz field of view for use in a multifrequency optimal estimation retrieval algorithm of cloud liquid water path, total precipitable water, and wind speed. Resampling the TMI measurements is found to have a strong influence on retrievals of cloud liquid water path and a slight influence on wind speed. Beam-filling effects in the resampled brightness temperatures are shown to be responsible for the large differences between the retrievals using the TMI native resolution and resampled brightness temperatures. Synthetic retrievals are performed to test the sensitivity of the retrieved parameters to beam-filling effects in the resampling of each of the different channels. Beam-filling effects due to the convolution of the 85-GHz channels are shown to be the largest contributor to differences in retrieved cloud liquid water path. Differences in retrieved wind speeds are found to be a combination of effects from deconvolving the 10-GHz brightness temperatures and compensation effects due to the lower liquid water path being retrieved by the high-frequency channels. The influence of beam-filling effects on daily and monthly averages of cloud liquid water path is also explored. Results show that space–time averaging of cloud liquid water path cannot fully compensate for the beam-filling effects and should be considered when using cloud liquid water path data for validation or in climate studies.

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Cross-comparison of cloud liquid water path derived from observations by two space-borne and one ground-based instrument in Northern Europe

10.5194/amt-2019-225 ◽

2019 ◽

Author(s):

Vladimir S. Kostsov ◽

Anke Kniffka ◽

Martin Stengel ◽

Dmitry V. Ionov

Keyword(s):

Spatial Resolution ◽

Liquid Water ◽

Retrieval Algorithm ◽

Liquid Water Path ◽

Simple Estimate ◽

Cloud Liquid Water ◽

Water Path ◽

Geographical Regions ◽

Temporal And Spatial ◽

Cloud Liquid Water Path

Abstract. Cloud liquid water path (LWP) is one of the target atmospheric parameters retrieved remotely from ground-based and space-borne platforms using different observation methods and processing algorithms. Validation of LWP retrievals is a complicated task since a cloud cover is characterised by strong temporal and spatial variability while remote sensing methods have different temporal and spatial resolution. An attempt has been made to compare and analyse the collocated LWP data delivered by two satellite instruments SEVIRI and AVHRR together with the data derived from microwave observations by the ground-based radiometer RPG‑HATPRO. The geographical region of interest is the vicinity of St.Petersburg, Russia, where the RPG‑HATPRO radiometer is operating. The study is focused on two problems. The first one is the so-called scale difference problem which originates from dissimilar spatial resolutions of measurements. The second problem refers to the land-sea LWP gradient. The radiometric site is located 2.5 km from the coastline where the effects of the LWP gradient are pronounced. A good agreement of data obtained at the microwave radiometer location by all three instruments (HATPRO, SEVIRI and AVHRR) during warm and cold seasons is demonstrated (the largest correlation coefficient 0.93 was detected for HATPRO and AVHRR data sets). The analysis showed no bias of the SEVIRI results with respect to HATPRO data and a high bias (0.013–0.017 kg m−2) of the AVHRR results for both warm and cold seasons. The analysis of LWP maps plotted on the basis of the SEVIRI and AVHRR measurements over land and water surfaces in the vicinity of St.Petersburg revealed the unexpectedly high LWP values delivered by AVHRR during cold season over the Neva river bay and over the Saimaa Lake and the abnormal land-sea LWP gradient in these areas. For the detailed evaluation of atmospheric state and ice cover in the considered geographical regions during the periods of ground-based and satellite measurements, reanalysis data were used. It is shown that the most probable reason for the observed artifacts in the AVHRR measurements over water/ice surfaces is the coarse resolution of the land-sea and snow/ice masks used by the AVHRR retrieval algorithm. The influence of a cloud field inhomogeneity on the agreement between the satellite and the ground-based data was studied. For this purpose, the simple estimate of the LWP temporal variability was used as a measure of the spatial inhomogeneity. It has been demonstrated that both instruments are equally sensitive to the inhomogeneity of a cloud field despite the fact that they have different spatial resolution.

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Cloud-type dependencies of MODIS and AMSR-E liquid water path differences

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-3367-2009 ◽

2009 ◽

Vol 9 (1) ◽

pp. 3367-3399 ◽

Cited By ~ 6

Author(s):

M. de la Torre Juárez ◽

B. H. Kahn ◽

E. J. Fetzer

Keyword(s):

Optical Thickness ◽

Liquid Water ◽

Near Infrared ◽

Cloud Type ◽

Liquid Water Path ◽

Cloud Liquid Water ◽

Water Path ◽

Cloud Water Content ◽

Cloud Optical Thickness ◽

Cloud Top Temperature

Abstract. Comparisons of cloud liquid water path (LWP) retrievals are presented from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer (AMSR-E) located aboard the Aqua spacecraft. LWP differences as a function of cloud top height, cloud fraction, cloud top temperature, LWP, cloud effective radius and cloud optical thickness are quantified in most geophysical conditions. The assumption of vertically homogeneous distributions of cloud water content in the MODIS LWP retrieval yields a slightly poorer agreement than the assumption of stratified cloud liquid water. Furthermore, for a fixed cloud top pressure, the cloud top temperature can lead to sign changes in the LWP difference. In general, AMSR-E LWP is larger than MODIS for small cloud fractions, low values of LWP, and warmer cloud top temperatures. On the other hand, clouds with optical thicknesses above 20 lead to larger MODIS LWP. Using cloud optical thickness as a proxy for cloud type, deep convective clouds and stratus are shown to have the poorest agreement between AMSR-E and MODIS LWP. Particularly large differences are also found at latitudes poleward of 50°. The results of this work help characterize the scene- and cloud-dependent performance of microwave and visible/near infrared retrievals of LWP.

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Joint cloud water path and rainwater path retrievals from airborne ORACLES observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-5513-2021 ◽

2021 ◽

Vol 21 (7) ◽

pp. 5513-5532

Author(s):

Andrew M. Dzambo ◽

Tristan L'Ecuyer ◽

Kenneth Sinclair ◽

Bastiaan van Diedenhoven ◽

Siddhant Gupta ◽

...

Keyword(s):

Optical Depth ◽

Liquid Water ◽

Cloud Water ◽

Retrieval Algorithm ◽

Liquid Water Path ◽

Cloud Optical Depth ◽

Water Path ◽

Surface Precipitation ◽

Uncertainty Estimates ◽

Cloud Water Path

Abstract. This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar – third generation (APR-3) passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ∼10 %–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two-thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g m−2 and almost all CWPs (99 %) between 6 to 445 g m−2. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP), with more than 70 % of raining clouds having less than 10 g m−2 of rainwater. In heavier warm rain (i.e., rain rate exceeding 40 mm h−1 or 1000 mm d−1), however, RWP is observed to exceed 2500 g m−2. CWP (RWP) is found to be approximately 30 g m−2 (7 g m−2) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud–precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

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Variational Assimilation of Cloud Liquid/Ice Water Path and Its Impact on NWP

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-14-0243.1 ◽

2015 ◽

Vol 54 (8) ◽

pp. 1809-1825 ◽

Cited By ~ 18

Author(s):

Yaodeng Chen ◽

Hongli Wang ◽

Jinzhong Min ◽

Xiang-Yu Huang ◽

Patrick Minnis ◽

...

Keyword(s):

Data Assimilation ◽

Liquid Water ◽

Weather Prediction ◽

Wrf Model ◽

Liquid Water Path ◽

Cloud Liquid Water ◽

Water Path ◽

Ice Water Path ◽

Ice Water ◽

The Impact

AbstractAnalysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data assimilation (DA) system for the Weather Research and Forecasting (WRF) Model (WRFDA) is further developed to assimilate satellite cloud products that will produce the cloud liquid water and ice water analysis. Observation operators for the cloud liquid water path and cloud ice water path are developed and incorporated into the WRFDA system. The updated system is tested by assimilating cloud liquid water path and cloud ice water path observations from Global Geostationary Gridded Cloud Products at NASA. To assess the impact of cloud liquid/ice water path data assimilation on short-term regional numerical weather prediction (NWP), 3-hourly cycling data assimilation and forecast experiments with and without the use of the cloud liquid/ice water paths are conducted. It is shown that assimilating cloud liquid/ice water paths increases the accuracy of temperature, humidity, and wind analyses at model levels between 300 and 150 hPa after 5 cycles (15 h). It is also shown that assimilating cloud liquid/ice water paths significantly reduces forecast errors in temperature and wind at model levels between 300 and 150 hPa. The precipitation forecast skills are improved as well. One reason that leads to the improved analysis and forecast is that the 3-hourly rapid update cycle carries over the impact of cloud information from the previous cycles spun up by the WRF Model.

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Cloud albedo changes in response to anthropogenic sulfate and non-sulfate aerosol forcings in CMIP5 models

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-9145-2017 ◽

2017 ◽

Vol 17 (14) ◽

pp. 9145-9162 ◽

Cited By ~ 5

Author(s):

Lena Frey ◽

Frida A.-M. Bender ◽

Gunilla Svensson

Keyword(s):

Water Content ◽

Liquid Water ◽

Coupled Model ◽

Cmip5 Models ◽

Liquid Water Path ◽

Anthropogenic Aerosols ◽

Aerosol Composition ◽

Cloud Albedo ◽

Cloud Water Content ◽

Absorbing Aerosols

Abstract. The effects of different aerosol types on cloud albedo are analysed using the linear relation between total albedo and cloud fraction found on a monthly mean scale in regions of subtropical marine stratocumulus clouds and the influence of simulated aerosol variations on this relation. Model experiments from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to separately study the responses to increases in sulfate, non-sulfate and all anthropogenic aerosols. A cloud brightening on the month-to-month scale due to variability in the background aerosol is found to dominate even in the cases where anthropogenic aerosols are added. The aerosol composition is of importance for this cloud brightening, that is thereby region dependent. There is indication that absorbing aerosols to some extent counteract the cloud brightening but scene darkening with increasing aerosol burden is generally not supported, even in regions where absorbing aerosols dominate. Month-to-month cloud albedo variability also confirms the importance of liquid water content for cloud albedo. Regional, monthly mean cloud albedo is found to increase with the addition of anthropogenic aerosols and more so with sulfate than non-sulfate. Changes in cloud albedo between experiments are related to changes in cloud water content as well as droplet size distribution changes, so that models with large increases in liquid water path and/or cloud droplet number show large cloud albedo increases with increasing aerosol. However, no clear relation between model sensitivities to aerosol variations on the month-to-month scale and changes in cloud albedo due to changed aerosol burden is found.

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

Atmospheric Chemistry and Physics ◽

10.5194/acp-10-9851-2010 ◽

2010 ◽

Vol 10 (20) ◽

pp. 9851-9861 ◽

Cited By ~ 12

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.

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Understanding the Extratropical Liquid Water Path Feedback in Mixed-Phase Clouds with an Idealized Global Climate Model

Journal of Climate ◽

10.1175/jcli-d-21-0334.1 ◽

2022 ◽

pp. 1-48

Author(s):

Yi Ming

Keyword(s):

Water Content ◽

Liquid Water ◽

Climate Model ◽

Global Climate Model ◽

Cloud Water ◽

Mixed Phase ◽

Liquid Water Path ◽

Water Path ◽

Cloud Water Content ◽

Mixed Phase Clouds

Abstract A negative shortwave cloud feedback associated with higher extratropical liquid water content in mixed-phase clouds is a common feature of global warming simulations, and multiple mechanisms have been hypothesized. A set of process-level experiments performed with an idealized global climate model (a dynamical core with passive water and cloud tracers and full Rotstayn-Klein single-moment microphysics) show that the common picture of the liquid water path (LWP) feedback in mixed-phase clouds being controlled by the amount of ice susceptible to phase change is not robust. Dynamic condensate processes—rather than static phase partitioning—directly change with warming, with varied impacts on liquid and ice amounts. Here, three principal mechanisms are responsible for the LWP response, namely higher adiabatic cloud water content, weaker liquid-to-ice conversion through the Bergeron-Findeisen process, and faster melting of ice and snow to rain. Only melting is accompanied by a substantial loss of ice, while the adiabatic cloud water content increase gives rise to a net increase in ice water path (IWP) such that total cloud water also increases without an accompanying decrease in precipitation efficiency. Perturbed parameter experiments with a wide range of climatological LWP and IWP demonstrate a strong dependence of the LWP feedback on the climatological LWP and independence from the climatological IWP and supercooled liquid fraction. This idealized setup allows for a clean isolation of mechanisms and paints a more nuanced picture of the extratropical mixed-phase cloud water feedback than simple phase change.

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