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Title: Sensitivities of Simulated Satellite Views of Clouds to Subgrid-Scale Overlap and Condensate Heterogeneity

Abstract

Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of this framework is to enable more robust evaluation of model cloud properties, so that differences between models and observations can more confidently be attributed to model errors. A critical step in this process is accounting for the difference between the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4-km global model output from the multiscale modeling framework to evaluate the sensitivity of simulated satellite retrievals to common assumptions about cloud and precipitation overlap and condensate variability used in climate models whose grid spacing is many tens to hundreds of kilometers. We find the simulated retrievals are sensitive to these assumptions. Using maximum-random overlap with homogeneous cloud and precipitation condensate leads to errors in Multiangle Imaging Spectroradiometer and International Satellite Cloud Climatology Project-simulated cloud cover and in CloudSat-simulated radar reflectivity that are significant compared to typical differences between the model simulations and observations. A more realistic treatment of unresolved clouds and precipitation is shown tomore » substantially reduce these errors. The sensitivity to these assumptions underscores the need for the adoption of more realistic subcolumn treatments in models and the need for consistency among subcolumn assumptions between models and simulators to ensure that simulator-diagnosed errors are consistent with the model formulation.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Univ. of Washington, Seattle, WA (United States). Dept. of Atmospheric Sciences
  3. Univ. of Washington, Seattle, WA (United States). Dept. of Atmospheric Sciences; Joint Inst. for the Study of the Atmosphere and Ocean, Seattle WA (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
National Aeronautic and Space Administration (NASA)
OSTI Identifier:
1478332
Report Number(s):
SAND-2017-9318J
Journal ID: ISSN 2169-897X; 656637
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 123; Journal Issue: 14; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; global climate model; satellite simulator; COSP; cloud overlap; cloud condensate heterogeneity; multiscale modeling framework

Citation Formats

Hillman, Benjamin R., Marchand, R. T., and Ackerman, T. P. Sensitivities of Simulated Satellite Views of Clouds to Subgrid-Scale Overlap and Condensate Heterogeneity. United States: N. p., 2018. Web. doi:10.1029/2017JD027680.
Hillman, Benjamin R., Marchand, R. T., & Ackerman, T. P. Sensitivities of Simulated Satellite Views of Clouds to Subgrid-Scale Overlap and Condensate Heterogeneity. United States. doi:10.1029/2017JD027680.
Hillman, Benjamin R., Marchand, R. T., and Ackerman, T. P. Fri . "Sensitivities of Simulated Satellite Views of Clouds to Subgrid-Scale Overlap and Condensate Heterogeneity". United States. doi:10.1029/2017JD027680. https://www.osti.gov/servlets/purl/1478332.
@article{osti_1478332,
title = {Sensitivities of Simulated Satellite Views of Clouds to Subgrid-Scale Overlap and Condensate Heterogeneity},
author = {Hillman, Benjamin R. and Marchand, R. T. and Ackerman, T. P.},
abstractNote = {Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of this framework is to enable more robust evaluation of model cloud properties, so that differences between models and observations can more confidently be attributed to model errors. A critical step in this process is accounting for the difference between the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4-km global model output from the multiscale modeling framework to evaluate the sensitivity of simulated satellite retrievals to common assumptions about cloud and precipitation overlap and condensate variability used in climate models whose grid spacing is many tens to hundreds of kilometers. We find the simulated retrievals are sensitive to these assumptions. Using maximum-random overlap with homogeneous cloud and precipitation condensate leads to errors in Multiangle Imaging Spectroradiometer and International Satellite Cloud Climatology Project-simulated cloud cover and in CloudSat-simulated radar reflectivity that are significant compared to typical differences between the model simulations and observations. A more realistic treatment of unresolved clouds and precipitation is shown to substantially reduce these errors. The sensitivity to these assumptions underscores the need for the adoption of more realistic subcolumn treatments in models and the need for consistency among subcolumn assumptions between models and simulators to ensure that simulator-diagnosed errors are consistent with the model formulation.},
doi = {10.1029/2017JD027680},
journal = {Journal of Geophysical Research: Atmospheres},
number = 14,
volume = 123,
place = {United States},
year = {2018},
month = {6}
}

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Cited by: 4 works
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Figures / Tables:

Figure 1 Figure 1: Total cloud (left) and precipitation (right) mixing ratios for each case described in the text.

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