Impact of revised cloud microphysical scheme in CFSv2 on the simulation of the Indian summer monsoon

摘要

Role of the cloud parameterization scheme and critical relative humidity (RHcrit) for large-scale precipitation is examined for simulating Indian summer monsoon (ISM) by the National Centers for Environmental Prediction (NCEP) climate forecast system version 2 (CFSv2). The major biases of the model simulations namely dry bias over the major continents, cold tropospheric temperature (TT) bias and cold sea surface temperature (SST) bias are related to biases in distribution of clouds. This study evaluates the role of variable RHcrit to get better simulation of high level clouds and reduce TT bias and cloud microphysical parameterization to improve the meridional gradient of TT towards achieving better simulation of south Asian monsoon precipitation. Sensitivity experiments of CFSv2 with the modified RHcrit and cloud microphysical scheme compared to the control simulation show that while the RHcrit leads to some development of the cloud distribution and contributes to some progress of the dry bias over India, the cloud microphysics changes lead to a significant improvement of the cloud simulations. Particularly, revised cloud microphysics scheme coupled with modified RHcrit results in a much improved global distribution of cloud fraction with zonal mean cloud fraction being close to observation. This leads to significant improvement in the meridional gradient of TT leading to rainfall over south Asian monsoon region. The dry bias is not only reduced over the Indian subcontinent but also over other regions of global tropics such as the central Africa and the northern South America. The annual cycle of all India rainfall is in good agreement with observation not only in amount but also in the onset and withdrawal phases. Thus, modifications in the cloud microphysical parameterization scheme in CFSv2 have played a vital role in simulation of the ISM in particular. The sensitivity experiments demonstrate the betterment of the mean monsoon and may lead to help improve monsoon forecasts.