The forecast skill of Radar-basedextrapolation model MTREC (Multi-scale Tracking and Forecasting Radar Echoes) which is developed by the state key laboratory of severe weather (LaSW) of Chinese academy of meteorological science (CAMS). The forecast skill of MTREC and a meso-scale numerical weather prediction(NWP) BJ-RUC(WRF-based rapid updating cycling forecast system of Beijing meteorological bureau) were analyzed, base on thefour precipitation events observed by radar networks in Beijing in the summer of 2011. The results show that: (1) In terms of bias, both MTREC and BJ-RUC show overforecast the rain area.The bias of MTREC is stable for the considered four events, while the bias of BJ-RUC is sensitive to rainfall types. (2) In terms of the position of precipitation forecast, the forecast skill of MTREC depends on the scale of rainstorm. Larger scale rainstorm corresponds to higher forecast skill. BJ-RUC performs steadily except thelocal rainstorm event 3. (3) For 0~6 h precipitation forecast, MTREC has more skill than BJ-RUC for the first lead times. There is a cross-over point in time where BJ-RUC starts to have more skill than MTREC. The time of the cross-over point depends on the rainfall types. The larger the rainstorm scale is the later the cross-over point occurs. The results would provide some references to improve short-term quantitative precipitation based on blending MTREC and BJ-RUC.
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