A41E-0101
Evaluation of Aerosol Properties in GCMs using Satellite Measurements

Thursday, 17 December 2015
Poster Hall (Moscone South)
Yuan Wang1, Jonathan H. Jiang1, Hui Su1 and Hongliang Zhang2, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Louisiana State University, Civil and Environmental Engineering, BATON ROUGE, LA, United States
Abstract:
Atmospheric aerosols from natural or anthropogenic sources have profound impacts on the regional and global climate. Currently the radiative forcing of aerosols predicted by global climate models remains highly uncertain, representing the largest uncertainty in climate predictions. The uncertainty mainly arises from the complicated aerosol chemical and physical properties, coarse emission inventories for pre-cursor gases as well as unrealistic representations of aerosol activation and cloud processing in global climate models. In this study, we will utilize multiple satellite measurements including MODIS, MISR and CALIPSO to quantitatively evaluate aerosol simulations from climate models. Our analyses show that the global means in AOD climatology from NCAR CAM5 and GFDL AM3 simulations are comparable with satellite measurements. However, the overall correlation coefficient between the AOD spatial patterns from CAM5 and satellite is only 0.4. Moreover, at finer scales, the magnitude of AOD in CAM5 is much lower than satellite measurements for most of the non-dust regions, especially over East Asia. GFDL AM3 shows better AOD simulations over East Asia. The underestimated AOD over remote maritime areas in CAM5 was attributed to the unrealistic wet removal processes in convective clouds of CAM5. Over continents, biases on AOD could stem from underestimations in the emissions inventory and unresolved sub-grid variations of relative humidity due to the model’s coarse resolution. Uncertainty from emission inventory over developing countries in East Asia will be assessed using the newly updated Regional Emission inventory in Asia (REAS) and Multi-resolution Emission Inventory in China (MEIC) in the model simulations.