研究目的
To improve the accuracy of predicted wind fields for operational storm surge forecasting applications in the Gulf of Venice by reducing the bias between scatterometer wind observations and atmospheric model winds.
研究成果
The wind bias mitigation procedure improves model forecast wind speed using scatterometer observations, with the linear least squares regression approach (LLSRE) performing best. The method is advantageous for both storm surge and random meteorological conditions, though slightly less efficient in the latter. It is suitable for operational use but requires further investigation into wind direction bias and regional performance.
研究不足
The study does not investigate wind direction bias, performance in other spatial regions, or causes of method failure in approximately 25% of cases.
1:Experimental Design and Method Selection:
The study compares four mathematical approaches to the wind bias mitigation (WBM) method, totaling eight different formulations of the multiplicative factor ?ws.
2:Sample Selection and Data Sources:
Four datasets are used, including storm surge events and random sea level conditions from 2004 to
3:List of Experimental Equipment and Materials:
20 ECMWF model wind analysis and forecast data, scatterometer wind data from various satellites.
4:Experimental Procedures and Operational Workflow:
The WBM procedure uses scatterometer observations to adjust model wind fields, with statistical analysis to assess performance.
5:Data Analysis Methods:
Statistical estimators like RMS differences, Pearson’s correlation coefficients, and standard deviations are used to compare standard and mitigated forecasts against scatterometer observations.
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