Status of NCEP CFS vis-a-vis IPCC AR4 models for the simulation of Indian summer monsoon
Status of NCEP CFS vis-a-vis IPCC AR4 models for the simulation of Indian summer monsoon
复制标题
NCEP CFS 相对于 IPCC AR4 模型模拟印度夏季风的现状
DOI：
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发表时间：
2012
影响因子：
3.4
通讯作者：
S. Saha
中科院分区：
文献类型：
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作者：
S. Pokhrel;A. Dhakate;H. Chaudhari;S. Saha
美国国家环境预报中心耦合预报系统（CFS）被选为季风研究（季节预报、扩展范围预报、气候预报等）的主导系统。印度政府雄心勃勃的季风使命项目。因此，作为一个先决条件，详细分析的性能NCEP CFS与IPCC AR 4模式模拟印度夏季风（ISM）的尝试。结果表明，CFS模拟的长期季风平均值与IPCC模式相当。与IPCC模式相比，CFS模式在印度次大陆范围内的降雨空间分布预示着更好的结果。CFS的主要缺点是降雨类型的分叉;它显示几乎80- 90%的降雨是对流性的，与观测结果相反，只有50- 65%;然而，同样的缺陷也在IPCC的其他模式中蔓延。唯一的喘息是，它真实地模拟了印度中部和南部对流和层状降雨的适当比例。在局部海气相互作用的情况下，它优于其他模型。然而，对于季风遥相关，它与IPCC的更好的模型竞争。这一研究结果使我们相信CFS可以很好地用于季风研究，并可以安全地用于ISM可靠预报系统的未来发展。
National Centers for Environmental Prediction (NCEP) Coupled Forecast System (CFS) is selected to play a lead role for monsoon research (seasonal prediction, extended range prediction, climate prediction, etc.) in the ambitious Monsoon Mission project of Government of India. Thus, as a prerequisite, a detail analysis for the performance of NCEP CFS vis-a-vis IPCC AR4 models for the simulation of Indian summer monsoon (ISM) is attempted. It is found that the mean monsoon simulations by CFS in its long run are at par with the IPCC models. The spatial distribution of rainfall in the realm of Indian subcontinent augurs the better results for CFS as compared with the IPCC models. The major drawback of CFS is the bifurcation of rain types; it shows almost 80–90 % rain as convective, contrary to the observation where it is only 50–65 %; however, the same lacuna creeps in other models of IPCC as well. The only respite is that it realistically simulates the proper ratio of convective and stratiform rain over central and southern part of India. In case of local air–sea interaction, it outperforms other models. However, for monsoon teleconnections, it competes with the better models of the IPCC. This study gives us the confidence that CFS can be very well utilized for monsoon studies and can be safely used for the future development for reliable prediction system of ISM.