Precipitation: Advances in Measurement, Estimation and Prediction
Precipitation: Advances in Measurement, Estimation and Prediction
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DOI：
10.1007/978-3-540-77655-0
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
S. Michaelides
中科院分区：
文献类型：
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作者：
S. Michaelides
必须评估天气预报系统，并且必须量化评估误差。如今，有限区域数值天气预报系统提供公里级水平网格间距的气象预报。高分辨率降水预报是人们最感兴趣的。例如，在洪水预报系统中，降水细节是一个关键的输入参数。此处，作为说明性的总面积为 41,300 平方公里，瑞士山区流域的典型面积小至约 1,500 平方公里（参见图 1）。最近，集合预测系统（EPS）开始投入使用，它通过整合初始状态略有不同的数值天气预报模型集合来预测预报概率
Weather forecast systems have to be evaluated and evaluation errors have to be quantified. Nowadays, limited-area numerical weather prediction systems provide meteorological forecasts with kilometerscale horizontal grid spacing. High resolution precipitation forecasts are of primary interest. For example, in flood forecasting systems the precipitation details are a crucial input parameter. Here, as an illustrative total area of 41,300 km2 and in Swiss mountainous catchments with a typical area as small as about 1,500 km2 shall be evaluated (cf. Fig. 1). Recently, ensemble prediction systems (EPS) became operational which predict forecast probabilities by integration of an ensemble of numerical weather prediction models from slightly different initial states