Global and Planetary Change ( IF 3.9 ) Pub Date : 2022-06-26 , DOI: 10.1016/j.gloplacha.2022.103873 Ushnanshu Dutta , Anupam Hazra , Hemantkumar S. Chaudhari , Subodh Kumar Saha , Samir Pokhrel , Utkarsh Verma
We have analyzed the teleconnection of total cloud fraction (TCF) with global sea surface temperature (SST) in multi-model ensembles (MME) of the fifth and sixth Coupled Model Intercomparison Projects (CMIP5 and CMIP6). CMIP6-MME has a more robust and realistic teleconnection (TCF and global SST) pattern over the extra-tropics (R ~ 0.43) and North Atlantic (R ~ 0.39) region, which in turn resulted in an improvement of rainfall bias over the Asian summer monsoon (ASM) region. CMIP6-MME can better reproduce mean TCF and have reduced dry (wet) rainfall bias on land (ocean) over the ASM region. Model bias with respect to seasonal mean rainfall, TCF, and outgoing longwave radiation (OLR) in CMIP6-MME are improved over the Indian Summer Monsoon (ISM) region by ~40%, ~45%, and ~ 31%, respectively, as compared to CMIP5-MME. Further, CMIP6-MME demonstrates a better spatial correlation with observation/reanalysis. The present study has also shown the lag correlations in the teleconnection analysis, i.e., the correlation of June–September (JJAS) mean of rainfall/TCF with October–December (OND) SST from observation/reanalysis, CMIP5-MME, and CMIP6-MME. The CMIP6-MME performs better than CMIP5-MME as compared to observation/reanalysis. The results establish the credibility of the CMIP6 models and provide a scientific basis for improving the seasonal prediction of ISM.
中文翻译:
揭开印度夏季风云的全球遥相关:从 CMIP5 到 CMIP6 的考察
我们分析了第五和第六耦合模式比对项目(CMIP5 和 CMIP6)的多模式集合(MME)中总云分数(TCF)与全球海面温度(SST)的遥相关。CMIP6-MME 在热带外 (R ~ 0.43) 和北大西洋 (R ~ 0.39) 地区具有更稳健和现实的遥相关(TCF 和全球 SST)模式,这反过来又导致亚洲降雨偏差的改善夏季风 (ASM) 地区。CMIP6-MME 可以更好地再现平均 TCF,并减少 ASM 地区陆地(海洋)的干(湿)降雨偏差。CMIP6-MME 中关于季节性平均降雨量、TCF 和输出长波辐射 (OLR) 的模型偏差在印度夏季风 (ISM) 区域分别提高了约 40%、约 45% 和约 31%,因为与 CMIP5-MME 相比。更远,CMIP6-MME 与观察/再分析表现出更好的空间相关性。本研究还显示了遥相关分析中的滞后相关性,即来自观测/再分析、CMIP5-MME 和 CMIP6- 的 6-9 月(JJAS)降雨/TCF 平均值与 10-12 月(OND)SST 的相关MME。与观察/再分析相比,CMIP6-MME 的性能优于 CMIP5-MME。研究结果确立了CMIP6模型的可信度,为改进ISM的季节预测提供了科学依据。与观察/再分析相比,CMIP6-MME 的性能优于 CMIP5-MME。研究结果确立了CMIP6模型的可信度,为改进ISM的季节预测提供了科学依据。与观察/再分析相比,CMIP6-MME 的性能优于 CMIP5-MME。研究结果确立了CMIP6模型的可信度,为改进ISM的季节预测提供了科学依据。