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Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds

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Seethala,  C.
IMPRS on Earth System Modelling, MPI for Meteorology, Max Planck Society;
Emmy Noether Junior Research Group Cloud-Climate Feedbacks, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;
Observations and Process Studies, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Horváth,  Á.
Emmy Noether Junior Research Group Cloud-Climate Feedbacks, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;
Observations and Process Studies, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Citation

Seethala, C., & Horváth, Á. (2010). Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds. Journal of Geophysical Research: Atmospheres, 115: D13202. doi:10.1029/2009JD012662.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0011-F5EE-A
Abstract
We compared 1 year of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) Wentz and Moderate Resolution Imaging Spectroradiometer (MODIS) cloud liquid water path estimates in warm marine clouds. In broken scenes AMSR-E increasingly overestimated MODIS, and retrievals became uncorrelated as cloud fraction decreased, while in overcast scenes the techniques showed generally better agreement, but with a MODIS overestimation. We found microwave and visible near-infrared retrievals being most consistent in extensive marine Sc clouds with correlations up to 0.95 and typical RMS differences of 15 g m(-2). The overall MODIS high bias in overcast domains could be removed, in a global mean sense, by adiabatic correction; however, large regional differences remained. Most notably, MODIS showed strong overestimations at high latitudes, which we traced to 3-D effects in plane-parallel visible-near-infrared retrievals over heterogeneous clouds at low Sun. In the tropics or subtropics, AMSR-E-MODIS differences also depended on cloud type, with MODIS overestimating in stratiform clouds and underestimating in cumuliform clouds, resulting in large-scale coherent bias patterns where marine Sc transitioned into trade wind Cu. We noted similar geographic variations in Wentz cloud temperature errors and MODIS 1.6-3.7 mu m droplet effective radius differences, suggesting that microwave retrieval errors due to cloud absorption uncertainties, and visible near-infrared retrieval errors due to cloud vertical stratification might have contributed to the observed liquid water path bias patterns. Finally, cloud-rain partitioning was found to introduce a systematic low bias in Wentz retrievals above 180 g m(-2) as the microwave algorithm erroneously assigned an increasing portion of the liquid water content of thicker nonprecipitating clouds to rain.