Validation and calibration of daily precipitation forecast considering the influence of typhoon events
[Objective]The heavy precipitation caused by typhoons often leads to floods and other disasters in local areas.[Methods]Typhoon events were screened through the typhoon path buffer zone to check the distribution of typhoon and non-typhoon events.The accuracy of raw daily precipitation forecast data from the GEFSv12,provided by the National Environment Forecasting Center,was evaluated.By designing various calibration schemes,the Bernoulli-Gamma-Gaussian model was employed to calibrate the GEFSv12 precipitation forecast in the Guangdong-Hong Kong-Macao Greater Bay Area.This calibration was performed under different scenarios to assess forecast skill improvement before and after calibration under varying precipitati-on conditions.[Results]The landfall time of typhoons affecting the southeast coast of China is mainly concentrated from July to September,with typhoon intensities predominantly below grade 14.In the case of typhoon events,the forecast BIAS approached 0 after using typhoon events samples to train the model,resulting in an average increase of nearly 15％in the continuous ranked probability skill score and the alpha-index increased of nearly 0.16.[Conclusion]The Bernoulli-Gamma-Gaussian model can ef-fectively calibrate the systematic deviation of the raw forecast and improve predictive performance.Calibration effects vary across different scenarios.For non-typhoon events with less extreme precipitation,the calibration effect is more pronounced.In the case of typhoon events,training the model with typhoon samples consistently outperforms the other two models,enhancing reliability and forecast skill.The calibration's impact correlates with the value of the correlation coefficient;areas with higher correlation coefficient exhibit superior prediction skill scores.This attribute bodes for subsequent application in hydrological ensemble pre-diction and post-calibration model enhancements.
万方数据
维普
