The Chinese Air-Sea heat Flux (CASFlux) gridded dataset: description and validation

As a new member of the global family of air-sea heat flux gridded datasets, this paper introduces the main production processes and evaluates the performance of the first version of Chinese Air-Sea heat Flux gridded dataset (CASFlux). The CASFlux dataset absorbed multi-source satellite remote sensing and reanalysis data and was trained by in situ observations from moored buoys, offshore platforms, flux towers, and so on. Machine learning approaches and improved parameterization algorithms were employed in the production of CASFlux. The output CASFlux dataset is provided at a daily interval and has a spatial resolution of 0.25°, spanning from January 1988 to the present. Compared to other widely used flux products, CASFlux exhibits a higher level of agreement with independent in situ observations from seas around China. Furthermore, CASFlux demonstrates significantly enhanced capability in accurately representing the intricate structure of tropical cyclones. Regarding the seasonal and long-term variations in air-sea heat flux, CASFlux shows similarities to the existing flux products and also possesses its own distinct features. It is anticipated that CASFlux will play a positive role in enhancing understandings of the changes in air-sea heat flux in the seas around China.