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投稿时间:2020-08-13 修订日期:2021-06-07
投稿时间:2020-08-13 修订日期:2021-06-07
中文摘要: 为了研究随机物理倾向扰动(SPPT)方法在复杂地形条件下对对流尺度集合预报中的影响,针对SPPT随机扰动场的时间尺度、空间尺度和格点标准差三个参数进行敏感性试验,分析扰动变化规律,探讨其预报效果。结果表明:空间尺度90 km、时间尺度3 h和格点标准差0.525参数构造的SPPT随机扰动场结构对西部山地对流尺度集合预报整体效果较好,该试验不同层次高空要素(纬向风场、温度场和湿度场)和近地面要素(10 m风和2 m温度)的离散度增长较快,考虑预报误差的离散度/RMSE也好于其他试验。虽然最优配置试验的3 h累积降水的集合平均相对于其他参数试验没有明显在各个量级上都有提高,但在≥10 mm、≥25 mm和≥50 mm的降水等级的ETS评分接近或者高于控制试验,概率预报技巧较好。综合来看,空间尺度参数的选取比时间尺度对离散度的影响更加明显,增加扰动振幅对离散度的增加也起到积极的作用,同时可以提高不同量级降水的概率预报技巧。
Abstract:To investigate the influence of stochastically perturbed parameterization tendencies (SPPT) on convective-scale ensemble prediction under complex topography conditions, sensitivity experiments were conducted on three parameters of SPPT random perturbed field, including temporal scale, spatial scale and grid standard deviation, to explore its prediction effect. The results showed that the SPPT built with the parameters of 90 km spatial scale, 3 h time scale and 0.525 grid standard deviation performed best in this case. The spreads of upper-air physical quantities (zonal wind field, temperature field and humidity field) and near-surface physical quantities (10 m wind and 2 m temperature) increase rapidly. The spread/RMSE that considers prediction errors is also better than other experiments. Although the ensemble mean of 3 h accumulated precipitation is not significantly improved at all categories compared with other experiments, the ETS scores of precipitation grades ≥10 mm, ≥25 mm and ≥50 mm are close to or higher than those of the control experiment, and the probability prediction skills are better. On the whole, the influence of spatial scale parameter on spread is more obvious than that of time scale. The increase of perturbation amplitude plays a positive role in increasing spread, and meanwhile can improve the probability prediction skills of precipitation different magnitudes.
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基金项目:国家重点研发计划(2018YFC1507200和2016YFE0109400)共同资助
引用文本:
王明欢,李俊,熊洁,赖安伟,孙玉婷,许建玉,2021.随机物理倾向扰动方案在西部山地对流尺度集合预报中的研究[J].气象,47(8):966-981.
WANG Minghuan,LI Jun,XIONG Jie,LAI Anwei,SUN Yuting,XU Jianyu,2021.Study of Stochastically Perturbed Parameterization Tendencies in West China Mountains Convective-Scale Ensemble Forecast[J].Meteor Mon,47(8):966-981.
王明欢,李俊,熊洁,赖安伟,孙玉婷,许建玉,2021.随机物理倾向扰动方案在西部山地对流尺度集合预报中的研究[J].气象,47(8):966-981.
WANG Minghuan,LI Jun,XIONG Jie,LAI Anwei,SUN Yuting,XU Jianyu,2021.Study of Stochastically Perturbed Parameterization Tendencies in West China Mountains Convective-Scale Ensemble Forecast[J].Meteor Mon,47(8):966-981.