Global climate model performance in West Africa: Realizing the goals of RADAGAST

 

Authors

Mark A. Miller — Rutgers University
Virendra Prakash Ghate — Argonne National Laboratory

Category

Field Campaigns

Description

The ARM Mobile Facility (AMF) was deployed in West Africa during 2006 in support of the Radiative Atmospheric Divergence Using AMF, GERB data, and AMMA Stations (RADAGAST) campaign. The principal goal of RADAGAST was to measure the cross-atmosphere radiative flux divergence using data from the ARM Mobile Facility (AMF) and the Geostationary Earth Radiation Budget Experiment (GERB). This configuration enabled the controls of this flux divergence to be determined using measurements from the AMF (Slingo et al. 2009). The ultimate goal of the RADAGAST campaign was to determine whether the radiative flux divergence and the factors that control it are properly simulated in the current generation of GCMs. To realize this goal, we compared the RADAGAST measurements with three GCMs used in the most recent IPCC report (GISS Model-e, HADGEM1, and AM2) and the NCAR Community Climate Model Version 3 (CCM3). The surface and top-of-atmosphere radiative fluxes, cross-atmosphere radiative flux divergence, surface energy budgets, and the clouds and precipitation simulated by each model were compared with the observations from RADAGAST. A decadal window centered on the year 2006 was used to compute averages and extremes for each variable in the model. To assess the performance of the cloud parameterizations, the ability of each model to reproduce an observed relationship between the surface lifting condensation level and the structure of clouds and precipitation is examined. It is shown that models that reproduce the radiative structure tend to exhibit sub-par performance in simulating clouds and precipitation, and vice versa. Models that more faithfully represent the radiative structure are shown to possess cloud fields that are strongly modulated by tuning to satellite data from the International Satellite Cloud Climatology Project (ISCCP). These models are shown to underperform models not tuned to ISCCP when the figure of merit is the ability to faithfully represent the clouds and precipitation observed in 2006.