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A Spatiotemporal Interactive Processing Bias Correction Method for Operational Ocean Wave Forecasts
Authors:AI Bo  YU Mengchao  GUO Jingtian  ZHANG Wei  JIANG Tao  LIU Aichao  WEN Lianjie  LI Wenbo
Abstract:Numerical models and correct predictions are important for marine forecasting, but the forecasting results are often unable to satisfy the requirements of operational wave forecasting. Because bias between the predictions of numerical models and the actual sea state has been observed, predictions can only be released after correction by forecasters. This paper proposes a spati-otemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and re-lease of operational ocean wave forecasting products. The proposed method combines the advantages of numerical models and Forecast Discussion; specifically, it integrates subjective and objective information to achieve interactive spatiotemporal correc-tions for numerical prediction. The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judg-ment of forecasters to achieve numerical prediction accuracy. The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis, thereby achieving highly efficient correction for multi-time forecasting fields. In this paper, the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis. Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states. The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.
Keywords:numerical models  ocean wave forecasts  spatial interpolation  time series interpolation  successive correction
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