What CloudSat cannot see: liquid water content profiles inferred from MODIS and CALIOP observations

Abstract. Single-layer nonprecipitating warm clouds are integral to Earth's climate, and accurate estimates of cloud liquid water content for these critical constraining models understanding climate feedbacks. As the only cloud-sensitive radar currently in space, CloudSat provides very important cloud-profiling capabilities. However, a significant fraction is missed by because they either too thin or close surface. We find that Radar-Visible Optical Depth Cloud Water Content Product, 2B-CWC-RVOD, misses about 73 % cloudy pixels 63 total compared coincident Moderate Resolution Imaging Spectroradiometer (MODIS) observations. Those percentages increase 84 69 %, respectively, if MODIS “partly cloudy” included. develop method, based on adiabatic parcel theory but modified account fact observed often subadiabatic, estimate profiles observations cloud-top effective radius optical depth combined with lidar height. that, detected CloudSat, resulting subadiabatic similar what retrieved from CloudSat. For not can be used supplement profiles, recovering much missing generating realistic-looking merged water. Adding this CWC-RVOD product increases mean path 228 single-layer clouds. This method will included subsequent reprocessing 2B-CWC-RVOD algorithm.