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Statistically Extrapolated Nowcasting of Summertime Precipitation over the Eastern Alps

查看全文 作  者:Min [1]CHEN;Benedikt [2]BICA;Lukas T[2]CHLER;Alexander [2]KANN;Yong [2]WANG 高影响力作者 机构地区:[1]Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China;[2]Central Institute for Meteorology and Geodynamics, Vienna 1190, Austria高影响力机构 出  处:《Advances in Atmospheric Sciences》索引2017年第34卷第7期,共14页高影响力期刊 基  金:supported by Beijing Science & Technology Commission (Grant No. Z151100002115012) 摘  要:This paper presents a new multiple linear regression(MLR) approach to updating the hourly, extrapolated precipitation forecasts generated by the INCA(Integrated Nowcasting through Comprehensive Analysis) system for the Eastern Alps.The generalized form of the model approximates the updated precipitation forecast as a linear response to combinations of predictors selected through a backward elimination algorithm from a pool of predictors. The predictors comprise the raw output of the extrapolated precipitation forecast, the latest radar observations, the convective analysis, and the precipitation analysis. For every MLR model, bias and distribution correction procedures are designed to further correct the systematic regression errors. Applications of the MLR models to a verification dataset containing two months of qualified samples,and to one-month gridded data, are performed and evaluated. Generally, MLR yields slight, but definite, improvements in the intensity accuracy of forecasts during the late evening to morning period, and significantly improves the forecasts for large thresholds. The structure–amplitude–location scores, used to evaluate the performance of the MLR approach,based on its simulation of morphological features, indicate that MLR typically reduces the overestimation of amplitudes and generates similar horizontal structures in precipitation patterns and slightly degraded location forecasts, when compared with the extrapolated nowcasting. 关 键 词:阿尔卑斯 夏季降水 统计推断 预测算法 临近 多元线性回归 降水预报 应用程序
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