Understanding Errors in Cloud Liquid Water Path Retrievals Derived from CloudSat Path-Integrated Attenuation

Matthew Lebsock aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California

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Hanii Takahashi aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California
bJoint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, Los Angeles, California

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Richard Roy aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California

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Marcin J. Kurowski aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California

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Lazaros Oreopoulos cEarth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Abstract

An algorithm that derives the nonprecipitating cloud liquid water path Wcld from CloudSat using a surface reference technique (SRT) is presented. The uncertainty characteristics of the SRT are evaluated. It is demonstrated that an accurate analytical formulation for the pixel-scale precision can be derived. The average precision of the SRT is estimated to be 34 g m−2 at the individual pixel scale; however, precision systematically decreases from around 30 to 40 g m−2 as cloud fraction varies from 0% to 100%. The retrievals of clear-sky Wcld have a mean bias of 0.9 g m−2. Output from a large-eddy simulation coupled to a radar simulator shows that an additional bias of −8% may result from nonuniformity within the footprint of cloudy pixels. The retrieval yield for the SRT, measured relative to all warm clouds over ocean between 60°N and 60°S latitude is 43%. The SRT Wcld is compared with one estimate of Wcld from the Moderate Resolution Imaging Spectroradiometer (MODIS) using an adiabatic cloud profile and an effective radius derived from 3.7-μm reflectance. A strong correlation between the mean MODIS Wcld and SRT Wcld is found across diverse cloud regimes, but with biases in the mean Wcld that are cloud-regime dependent. Overall, the mean bias of the SRT relative to MODIS is −13.1 g m−2. Systematic underestimates of Wcld by the SRT resulting from nonuniform beamfilling cannot be ruled out as an explanation for the retrieval bias.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Matthew Lebsock, matthew.d.lebsock@jpl.nasa.gov

Abstract

An algorithm that derives the nonprecipitating cloud liquid water path Wcld from CloudSat using a surface reference technique (SRT) is presented. The uncertainty characteristics of the SRT are evaluated. It is demonstrated that an accurate analytical formulation for the pixel-scale precision can be derived. The average precision of the SRT is estimated to be 34 g m−2 at the individual pixel scale; however, precision systematically decreases from around 30 to 40 g m−2 as cloud fraction varies from 0% to 100%. The retrievals of clear-sky Wcld have a mean bias of 0.9 g m−2. Output from a large-eddy simulation coupled to a radar simulator shows that an additional bias of −8% may result from nonuniformity within the footprint of cloudy pixels. The retrieval yield for the SRT, measured relative to all warm clouds over ocean between 60°N and 60°S latitude is 43%. The SRT Wcld is compared with one estimate of Wcld from the Moderate Resolution Imaging Spectroradiometer (MODIS) using an adiabatic cloud profile and an effective radius derived from 3.7-μm reflectance. A strong correlation between the mean MODIS Wcld and SRT Wcld is found across diverse cloud regimes, but with biases in the mean Wcld that are cloud-regime dependent. Overall, the mean bias of the SRT relative to MODIS is −13.1 g m−2. Systematic underestimates of Wcld by the SRT resulting from nonuniform beamfilling cannot be ruled out as an explanation for the retrieval bias.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Matthew Lebsock, matthew.d.lebsock@jpl.nasa.gov
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