20 Mar 2023
 | 20 Mar 2023
Status: a revised version of this preprint is currently under review for the journal AMT.

What CloudSat can't see: Liquid water content profiles inferred from MODIS and CALIOP observations

Richard M. Schulte, Matthew D. Lebsock, and John M. Haynes

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

Richard M. Schulte et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-49', Anonymous Referee #1, 18 Apr 2023
    • AC1: 'Reply on RC1', Rick Schulte, 26 May 2023
  • RC2: 'Comment on amt-2023-49', Anonymous Referee #2, 29 Apr 2023
    • AC2: 'Reply on RC2', Rick Schulte, 26 May 2023

Richard M. Schulte et al.

Richard M. Schulte et al.


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Short summary
In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.