基于雷暴演变特征的短时强降水外推订正技术OA

To address the issue that existing radar-based precipitation extrapolation techniques can not adequately characterize the evolution of thunderstorms and cause systematic biases in heavy precipitation forecasts,this paper proposes a heavy precipitation extrapolation and correction method which integrates the evolu-tion features of thunderstorms.Based on the storm cell identification and tracking(SCIT)algorithm,a thunderstorm development trend discrimination model is constructed for different thunderstorms by combi-ning key factors including strong gradient zones,newly generated cells,and echo area changes.By utili-zing radar reflectivity factor,optical flow vectors and dynamic Z-I relationship,we implement evolutionary constraints and corrections during the extrapolating process of heavy precipitation.Verification on the pre-cipitation forecasts in the main flood season of 2025 shows that in the 0-1 h forecasts,the TS scores of the corrected products at the level of ≥20 mm·h-1 and ≥50 mm·h-1 are both higher than those of the optical flow system,with the advantage increasing with precipitation intensity.In the 1-2 h forecasts,the TS scores at ≥20 mm·h-1 and ≥50 mm·h-1 are still significantly improved compared with those of the optical system,but the score at ≥50 mm·h-1 is only 0.004,indicating very limited operational guid-ance value.Further analysis of typical cases of heavy precipitation demonstrates that the correction tech-nique can capture precipitation characteristics of convective systems rapidly moving and developing to a greater extent and effectively alleviate the problems of underestimating intensity and coverage that exist in-herently in traditional extrapolation methods.