日极端气温的主客观预报能力评估及多模式集成网格释用

Evaluation on Subjective and Objective Diurnal Extreme Temperature Forecasts and Multi-Model Consensus Gridded Forecast Application

精细格点天气预报是我国未来几年天气预报业务发展重点。利用ECMWF、GRAPES等业务数值模式和广东站点观测资料,对日极端气温的主客观预报能力进行了多角度综合评估。统计结果表明,T_(max)、T_(min)的主客观预报误差均存在明显季节差异,在系统误差相对平稳的夏半年主观预报具有较明显订正能力,模式预报呈现一定流依赖特征,温度越高(低),负(正)偏差越明显;主客观预报误差空间分布均受地形影响,随着时效延长误差总体增幅不大,主观订正能力也较稳定。根据以上评估特征和网格预报特点,研究开发了一套多模式动态集成网格释用技术方案(McGF)。结果表明,相比单个模式的预报和主观预报,McGF较明显提升了T_(max)的预报技巧;T_(min)的模式预报偏差总体较T_(max)偏小,McGF提升幅度相对较小;网格释用后的广东区域预报能较合理反映气温空间和强度特征,较周边未经释用区域明显更优。

Digital gridded weather forecast is the developing trend of weather forecasting operation in China. Based on NWP model products, meteorological observation data and an evaluation on subjective and objective forecast, a diurnal extreme temperature Multi-model Consensus Gridded Forecast （McGF） sys- tem was developed. Statistical results show that there are significant seasonal forecast error differences in both subjective and objective forecasts, and forecasters have more forecasting skills in summer, when the NWP systemaitc errors are more stable. NWP model shows a flow dependent （conditional bias） character- istic. When the temperature is higher （lower）, the nagative （positive） forecast error is bigger. Both sub- jective and objective forecasts are affected by topography and there are relatively significant forecast errors in the northern mountainous areas2 As the lead time of forecast extends, the growth of forecast errors is, not big and the subjective forecasting skills are stable relatively. Based on these results, McGF interpreta- tion application system was devloped with four modules, including real-time verification, station-based in- terpretation, gridded application and performance-weighted averages. The results showed that Tmax fore- casts of McGF are better than subjective and objective forecasts, with its mean absolute errors less than 2℃ within 72 h. Relatively speaking, Tmin forecast errors are much lower and the enhancements of McGF are relatively small. The cases of extreme high/low temperature showed that McGF gridded forecasts in Guangdong Province can more reasonably reflect the spatial distribution and intensity feature.