Journal Article
Geoscientific Model Development, vol. 11, iss. 8, pp. 3147-3158, 2018
Authors
Hua Song, Zhibo Zhang, Po-Lun Ma, Steven Ghan, Minghuai Wang
Abstract
Abstract. Satellite cloud observations have become an indispensable tool for evaluating
general circulation models (GCMs). To facilitate the satellite and GCM
comparisons, the CFMIP (Cloud Feedback Model Inter-comparison Project)
Observation Simulator Package (COSP) has been developed and is now
increasingly used in GCM evaluations. Real-world clouds and precipitation can
have significant sub-grid variations, which, however, are often ignored or
oversimplified in the COSP simulation. In this study, we use COSP cloud
simulations from the Super-Parameterized Community Atmosphere Model (SPCAM5)
and satellite observations from the Moderate Resolution Imaging
Spectroradiometer (MODIS) and CloudSat to demonstrate the importance of
considering the sub-grid variability of cloud and precipitation when using
the COSP to evaluate GCM simulations. We carry out two sensitivity tests:
SPCAM5 COSP and SPCAM5-Homogeneous COSP. In the SPCAM5 COSP run, the sub-grid
cloud and precipitation properties from the embedded
cloud-resolving model (CRM) of SPCAM5 are used to drive the COSP simulation, while in
the SPCAM5-Homogeneous COSP run only grid-mean cloud and precipitation
properties (i.e., no sub-grid variations) are given to the COSP. We find that
the warm rain signatures in the SPCAM5 COSP run agree with the MODIS and
CloudSat observations quite well. In contrast, the SPCAM5-Homogeneous COSP
run which ignores the sub-grid cloud variations substantially overestimates
the radar reflectivity and probability of precipitation compared to the
satellite observations, as well as the results from the SPCAM5 COSP run. The
significant differences between the two COSP runs demonstrate that it is
important to take into account the sub-grid variations of cloud and
precipitation when using COSP to evaluate the GCM to avoid confusing and
misleading results.
