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

Journal Article · · Journal of Geophysical Research: Atmospheres
DOI:https://doi.org/10.1029/2017JD027680· OSTI ID:1478332
 [1];  [2];  [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)
+ Show Author Affiliations
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.
Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
National Aeronautic and Space Administration (NASA)
Grant/Contract Number:
AC04-94AL85000
OSTI ID:
1478332
Report Number(s):
SAND--2017-9318J; 656637
Journal Information:
Journal of Geophysical Research: Atmospheres, Journal Name: Journal of Geophysical Research: Atmospheres Journal Issue: 14 Vol. 123; ISSN 2169-897X
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (4)

Dependence of Vertical Alignment of Cloud and Precipitation Properties on Their Effective Fall Speeds journal February 2019
Cloud Heterogeneity in the Marine Midlatitudes: Dependence on Large‐Scale Meteorology and Implications for General Circulation Models journal March 2019
The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models collection January 2018
The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models journal January 2018

Figures / Tables (10)

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Related Subjects

54 ENVIRONMENTAL SCIENCES
COSP
cloud condensate heterogeneity
cloud overlap
global climate model
multiscale modeling framework
satellite simulator