Affiliation:
1. Key Laboratory of Marine Hazards Forecasting, National Marine Environment Forecasting Center, Beijing 100081, China
2. National Meteorological Center, Beijing 100081, China
3. Institute of Science and Technology, China Three Gorges Corporation, Beijing 101100, China
Abstract
Utilizing observed wind speed and direction data from observation stations near the Taiwan Strait and ocean buoys, along with forecast data from the EC model, GRAPES_GFS model, and PanGu weather prediction model within the same period, RMSE, MAE, CC, and other parameters were calculated. To comparatively evaluate the forecasting performance of the PanGu weather prediction model on the sea surface wind field near the Taiwan Strait from 00:00 on 1 June 2023, to 23:00 on 31 May 2024. The PanGu weather prediction model is further divided into the ERA5 (PanGu) model driven by ERA5 initial fields and the GRAPES_GFS (PanGu) model driven by GRAPES_GFS initial fields. The main conclusions are as follows: (1) over a one-year evaluation period, for wind speed forecasts with lead times of 0 h to 120 h in the Taiwan Strait region, the overall forecasting skill of the PanGu weather prediction model is superior to that of the model forecasts; (2) different initial fields input into the PanGu weather prediction model lead to different final forecast results, with better initial field data corresponding to forecast results closer to observations, thus indicating the operational transferability of the PanGu model in smaller regions; (3) regarding forecasts of wind speed categories, the credibility of the results is high when the wind speed level is ≤7, and the PanGu weather prediction model performs better among similar forecasts; (4) although the EC model’s wind direction forecasts are closer to the observation field results, the PanGu weather forecasting model also provides relatively accurate and rapid forecasts of the main wind directions within a shorter time frame.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Research Project of China Three Gorges Corporation
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