KEYWORDS: Satellites, Data fusion, Data modeling, Spatial resolution, Statistical modeling, Data acquisition, Machine learning, Error analysis, Data corrections, Water
China's coastal waters have significant alternating winter and summer monsoons, various meteorological activities are frequent, and marine resources are rich, and the development prospects are broad. Energy such as heat, function, and potential energy has a huge impact on human production and life. Therefore, accurate wind field data is useful for studying the coastal waters of China. This article uses multi-source satellite data, combined with the ERA-5 data provided by the European Weather Forecast Center (ECMWF), and uses classic machine learning methods and traditional interpolation methods to propose a feasible wind field interpolation method. The experiment generated seamless fined wind field data, and the wind field data has good accuracy, which can provide good data support for the construction of offshore areas in China.
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