Forecast Error and Predictability for the Warm-sector and the Frontal Rainstorm in South China

In south China, warm-sector rainstorms are significantly different from the traditional frontal rainstorms due to complex mechanism, which brings great challenges to their forecast. In this study, based on ensemble forecasting, the high-resolution mesoscale numerical forecast model WRF was used to investigate the effect of initial errors on a warmsector rainstorm and a frontal rainstorm under the same circulation in south China, respectively. We analyzed the sensitivity of forecast errors to the initial errors and their evolution characteristics for the warm-sector and the frontal rainstorm. Additionally, the difference of the predictability was compared via adjusting the initial values of the GOOD member and the BAD member. Compared with the frontal rainstorm, the warm-sector rainstorm was more sensitive to initial error, which increased faster in the warm-sector. Furthermore, the magnitude of error in the warm-sector rainstorm was obviously larger than that of the frontal rainstorm, while the spatial scale of the error was smaller. Similarly, both types of the rainstorm were limited by practical predictability and inherent predictability, while the nonlinear increase characteristics occurred to be more distinct in the warm-sector rainstorm, resulting in the lower inherent predictability. The comparison between the warm-sector rainstorm and the frontal rainstorm revealed that the forecast field was closer to the real situation derived from more accurate initial errors, but only the increase rate in the frontal rainstorm was restrained evidently