资源环境科技发展态势分析平台

In the Bay of Bengal (BoB), surface heat fluxes play a key role in monsoon dynamics and prediction. The accurate representation of large-scale surface fluxes is dependent on the quality of gridded reanalysis products. Meteorological and surface flux variables from five reanalysis products are compared and evaluated against in situ data from the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) in the BoB. The reanalysis products: ERA-Interim (ERA-I), TropFlux, MERRA-2, JRA-55, and CFSR are assessed for their characterization of air-sea fluxes during the southwest monsoon season [June-September (JJAS)]. ERA-I captured radiative fluxes best while TropFlux captured turbulent and net heat fluxes Q(net) best, and both products outperformed JRA-55, MERRA-2, and CFSR, showing highest correlations and smallest biases when compared to the in situ data. In all five products, the largest errors were in shortwave radiation Q(SW) and latent heat flux Q(LH), with nonnegligible biases up to approximately 75 W m(-2). The Q(SW) and Q(LH) are the largest drivers of the observed Q(net) variability, thus highlighting the importance of the results from the buoy comparison. There are also spatially coherent differences in the mean basinwide fields of surface flux variables from the reanalysis products, indicating that the biases at the buoy position are not localized. Biases of this magnitude have severe implications on reanalysis products' ability to capture the variability of monsoon processes. Hence, the representation of intraseasonal variability was investigated through the boreal summer intraseasonal oscillation, and we found that TropFlux and ERA-I perform best at capturing intraseasonal climate variability during the southwest monsoon season.