TY - JOUR
T1 - Incorporation of inline warm rain diagnostics into the COSP2 satellite simulator for process-oriented model evaluation
AU - Michibata, Takuro
AU - Suzuki, Kentaroh
AU - Ogura, Tomoo
AU - Jing, Xianwen
N1 - Funding Information:
Acknowledgements. We thank the developers of the COSP satellite simulator and the CFMIP community. This work has benefited from fruitful discussions with Alejandro Bodas-Salcedo, Robert Pincus, and Dustin Swales. The authors also thank Koji Ogochi for his testing and code optimization of COSP on MIROC6. Simulations by MIROC-SPRINTARS were executed on the SX-ACE supercomputer system of the National Institute for Environmental Studies, Japan. This study was supported by the following: the JSPS KAKENHI under grant numbers JP18J00301, JP19K14795, and JP19H05669; the Integrated Research Program for Advancing Climate Models (TOUGOU program) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan; and the Collaborative Research Program of the Research Institute for Applied Mechanics, Kyushu University. Kentaroh Suzuki was supported by the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections program with grant number NA15OAR4310153. The authors are grateful to Johannes Mülmen-städt (Universität Leipzig) and two anonymous reviewers for providing constructive suggestions and comments that helped to improve the paper.
Funding Information:
Financial support. This research has been supported by the Japan
Publisher Copyright:
© 2019 Geoscientific Model Development. All rights reserved.
PY - 2019/10/10
Y1 - 2019/10/10
N2 - The Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) is used to diagnose model performance and physical processes via an apple-to-apple comparison to satellite measurements. Although the COSP provides useful information about clouds and their climatic impact, outputs that have a subcolumn dimension require large amounts of data. This can cause a bottleneck when conducting sets of sensitivity experiments or multiple model intercomparisons. Here, we incorporate two diagnostics for warm rain microphysical processes into the latest version of the simulator (COSP2). The first one is the occurrence frequency of warm rain regimes (i.e., non-precipitating, drizzling, and precipitating) classified according to CloudSat radar reflectivity, putting the warm rain process diagnostics into the context of the geographical distributions of precipitation. The second diagnostic is the probability density function of radar reflectivity profiles normalized by the in-cloud optical depth, the so-called contoured frequency by optical depth diagram (CFODD), which illustrates how the warm rain processes occur in the vertical dimension using statistics constructed from CloudSat and MODIS simulators. The new diagnostics are designed to produce statistics online along with subcolumn information during the COSP execution, eliminating the need to output subcolumn variables. Users can also readily conduct regional analysis tailored to their particular research interest (e.g., land-ocean differences) using an auxiliary post-process package after the COSP calculation. The inline diagnostics are applied to the MIROC6 general circulation model (GCM) to demonstrate how known biases common among multiple GCMs relative to satellite observations are revealed. The inline multi-sensor diagnostics are intended to serve as a tool that facilitates process-oriented model evaluations in a manner that reduces the burden on modelers for their diagnostics effort.
AB - The Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) is used to diagnose model performance and physical processes via an apple-to-apple comparison to satellite measurements. Although the COSP provides useful information about clouds and their climatic impact, outputs that have a subcolumn dimension require large amounts of data. This can cause a bottleneck when conducting sets of sensitivity experiments or multiple model intercomparisons. Here, we incorporate two diagnostics for warm rain microphysical processes into the latest version of the simulator (COSP2). The first one is the occurrence frequency of warm rain regimes (i.e., non-precipitating, drizzling, and precipitating) classified according to CloudSat radar reflectivity, putting the warm rain process diagnostics into the context of the geographical distributions of precipitation. The second diagnostic is the probability density function of radar reflectivity profiles normalized by the in-cloud optical depth, the so-called contoured frequency by optical depth diagram (CFODD), which illustrates how the warm rain processes occur in the vertical dimension using statistics constructed from CloudSat and MODIS simulators. The new diagnostics are designed to produce statistics online along with subcolumn information during the COSP execution, eliminating the need to output subcolumn variables. Users can also readily conduct regional analysis tailored to their particular research interest (e.g., land-ocean differences) using an auxiliary post-process package after the COSP calculation. The inline diagnostics are applied to the MIROC6 general circulation model (GCM) to demonstrate how known biases common among multiple GCMs relative to satellite observations are revealed. The inline multi-sensor diagnostics are intended to serve as a tool that facilitates process-oriented model evaluations in a manner that reduces the burden on modelers for their diagnostics effort.
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U2 - 10.5194/gmd-12-4297-2019
DO - 10.5194/gmd-12-4297-2019
M3 - Article
AN - SCOPUS:85073230501
SN - 1991-959X
VL - 12
SP - 4297
EP - 4307
JO - Geoscientific Model Development
JF - Geoscientific Model Development
IS - 10
ER -