Preliminary Evaluation of Cloud Fraction Simulations by GAMIL2 Using COSP

Abstract The Cloud Feedback Model Intercomparisons Project (CFMIP) Observation Simulator Package (COSP) is adopted in the Grid-point Atmospheric Model of IAP LASG (GAMIL2) during CFMIP at Phase II to evaluate the model cloud fractions in a consistent way with satellite observations. The cloud simulation results embedded in the Atmospheric Model Intercomparison Project (AMIP) control experiment are presented using three satellite simulators: International Satellite Cloud Climatology Project (ISCCP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Overall, GAMIL2 can produce horizontal distributions of the low cloud fraction that are similar to the satellite observations, and its similarities to the observations on different levels are shown in Taylor diagrams. The discrepancies among satellite observations are also shown, which should be considered during evaluation.

[1]  Elizabeth C. Kent,et al.  Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century , 2003 .

[2]  R. Marchand,et al.  An analysis of cloud cover in multiscale modeling framework global climate model simulations using 4 and 1 km horizontal grids , 2010 .

[3]  Dong Li,et al.  Evaluating the Performances of GAMIL1.0 and GAMIL2.0 during TWPICE with CAPT , 2012 .

[4]  Andrew Gettelman,et al.  A new two-moment bulk stratiform cloud microphysics scheme in the Community Atmosphere Model, version 3 (CAM3). Part I: Description and numerical tests , 2008 .

[5]  S. Bony,et al.  Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models , 2001 .

[6]  宇如聪.  A Two-Step Shape-Preserving Advection Scheme , 1994 .

[7]  G. Zhang,et al.  Effects of modifications to the Zhang-McFarlane convection parameterization on the simulation of the tropical precipitation in the National Center for Atmospheric Research Community Climate Model, version 3 , 2005 .

[8]  Kuan-Man Xu,et al.  Evaluation of cloudiness parameterizations using a cumulus ensemble model , 1991 .

[9]  John M. Haynes,et al.  A Multipurpose Radar Simulation Package: QuickBeam , 2007 .

[10]  S. Bony,et al.  The GCM‐Oriented CALIPSO Cloud Product (CALIPSO‐GOCCP) , 2010 .

[11]  Yun Qian,et al.  Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model , 2011 .

[12]  Minghua Zhang,et al.  Evaluation of Clouds and Their Radiative Effects Simulated by the NCAR Community Atmospheric Model Against Satellite Observations , 2004 .

[13]  Philip J. Rasch,et al.  A Comparison of the CCM3 Model Climate Using Diagnosed and Predicted Condensate Parameterizations , 1998 .

[14]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[15]  N. McFarlane,et al.  Sensitivity of Climate Simulations to the Parameterization of Cumulus Convection in the Canadian Climate Centre General Circulation Model , 1995, Data, Models and Analysis.

[16]  John M. Haynes,et al.  COSP: Satellite simulation software for model assessment , 2011 .

[17]  Influences of Two Convective Schemes on the Radiative Energy Budget in GAMIL1.0 , 2010 .

[18]  Wang Bin,et al.  Influences of Two Convective Schemes on the Radiative Energy Budget in GAMIL1.0 , 2010 .

[19]  J. Slingo.  The Development and Verification of A Cloud Prediction Scheme For the Ecmwf Model , 2007 .

[20]  Hui Wan,et al.  Design of a new dynamical core for global atmospheric models based on some efficient numerical methods , 2004 .

[21]  S. Klein,et al.  Validation and Sensitivities of Frontal Clouds Simulated by the ECMWF Model , 1999 .

[22]  S. Bony,et al.  Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements , 2005 .

[23]  Robert Pincus,et al.  Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators in Climate Models , 2011 .

[24]  Charles Doutriaux,et al.  Performance metrics for climate models , 2008 .

[25]  W. Rossow,et al.  Advances in understanding clouds from ISCCP , 1999 .

[26]  H. Treut,et al.  THE CALIPSO MISSION: A Global 3D View of Aerosols and Clouds , 2010 .

[27]  W. Paul Menzel,et al.  Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS , 2003, IEEE Trans. Geosci. Remote. Sens..

[28]  H. Treut,et al.  A methodology study of the validation of clouds in GCMs using ISCCP satellite observations , 1996 .

[29]  Robert Pincus,et al.  Exposing Global Cloud Biases in the Community Atmosphere Model (CAM) Using Satellite Observations and Their Corresponding Instrument Simulators , 2012 .

[30]  K. Taylor.  Summarizing multiple aspects of model performance in a single diagram , 2001 .