Improving skill precipitation forecast of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) model by using the quantile mapping method for Central Vietnam

Tóm tắt

The research employs the Quantile Mapping (QM) post-processing method to improve the skill forecasts of the deterministic forecast of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). The selected research areais Central Vietnam, and the analysis utilizes observation data from 41 stations and 10-year ECMWF-IFS data from 2013 to 2022, with a lead time of up to 10 days for the QM applications. The findings indicate that the QM facilitates enhanced forecasting skills in the IFS model for all lead times up to 10 days, exhibiting varying magnitudes based on the specific lead time and rainfall thresholds. Notably, the impact of QM is found to be negligible for heavy rainfall events, with the skill limit being determined