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Formulation and evaluation of a scale decomposition-based stochastic precipitation nowcast scheme

机译:基于尺度分解的随机降水临近预报方案的制定与评估

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摘要

[1] There are significant uncertainties inherent in precipitation forecasts and these uncertainties can be communicated to users via large ensembles that are generated using stochastic models of forecast error. The Met Office and the Australian Bureau of Meteorology developed the Short Term Ensemble Prediction System (STEPS) was developed to address these user requirements and has been operational for a number of years. The initial formulation of Bowler et al. (2006) has been revised and extended to improve the performance over large domains, to include radar observation errors, and to facilitate the combination of forecasts from a number of sources. This paper reviews the formulation of STEPS, discusses those aspects of the formulation that have proved most problematic and presents some solutions. The performance of STEPS nowcasts is evaluated using a combination of case study examples and statistical verification from the UK. Routine forecast verification demonstrates that STEPS is capable of producing near optimal blends of a rainfall nowcast and high resolution NWP forecast. It also shows that the spread of STEPS nowcast ensembles are a good predictor of the error in the control member (unperturbed) nowcast.
机译:[1]降水预报存在固有的重大不确定性,这些不确定性可以通过使用预报误差随机模型生成的大型集合传达给用户。大都会办公室和澳大利亚气象局开发了短期集合预报系统(STEPS),旨在满足这些用户需求,并且已经运行了很多年。 Bowler等人的初始公式。 (2006)已进行了修订和扩展,以提高大范围内的性能,包括雷达观测误差,并有利于组合来自多个来源的预测。本文回顾了STEPS的公式,讨论了公式中最有问题的方面,并提出了一些解决方案。结合案例研究示例和英国的统计验证,对STEPS快播节目的性能进行了评估。例行预报验证表明,STEPS能够产生降雨临近预报和高分辨率NWP预报的最佳混合。它还表明,STEPS临近预报合奏的传播很好地预测了控件成员(不受干扰)临近预报中的错误。

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  • 来源
    《Water resources research》 |2013年第10期|6624-6641|共18页
  • 作者单位

    Centre for Australian Weather and Climate Research, Bureau of Meteorology, Melbourne, 700 Collins St., Melbourne, Vic 3000, Australia;

    Met Office, Exeter, UK;

    Met Office, Exeter, UK;

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