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Radiation budget biases in AMIP5 models over the East Asian monsoon region
Author(s) -
Wang Fang,
Yang Song,
Wu Tongwen
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2014jd022243
Subject(s) - shortwave , environmental science , atmospheric sciences , shortwave radiation , longwave , cloud cover , downwelling , atmosphere (unit) , climatology , atmospheric model , climate model , radiative transfer , sky , meteorology , radiation , upwelling , climate change , physics , geology , cloud computing , oceanography , quantum mechanics , computer science , operating system
The abilities of 27 Atmospheric Model Intercomparison Projection models to simulate the radiation budget (RB) over the East Asian monsoon region (EAMR) are analyzed based on Clouds and the Earth's Radiant Energy System Energy Balanced and Filled, hereafter CERES, products. The regional mean values of annual top of the atmosphere (TOA) net RB in the simulations are constantly larger than the CERES values in the majority of the models (24 of 27), due mainly to the overestimation of its shortwave (SW) component. The TOA SW RB overestimation in most models (25 of 27) is due mainly to the insufficient SW absorption by the atmosphere and the consequent superfluous downwelling shortwave radiation reaching and being absorbed by the surface. Both the intensity underestimation of SW cloud radiative forcing (CRF) and the inadequate clear‐sky atmospheric SW absorption contribute to the overestimation of TOA SW RB in the models. The underestimation of SW CRF intensity is mainly due to the reduced total cloud cover simulated in most of the models compared with the general circulation model‐oriented CALIPSO Cloud Product. Black carbon explains the greatest part of the clear‐sky atmospheric SW absorption biases in most of the models. The persistent underestimation of TOA SW CRF intensity over the EAMR across all seasons largely explains the seasonally constant overestimation of TOA SW RB. The seasonal variation in clear‐sky longwave (LW) RB demonstrates the remarkable seasonal variation in atmospheric and surface LW RB biases.