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首页> 外文期刊>Quarterly Journal of the Royal Meteorological Society >STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP
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STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP

机译:步骤:一种概率降水预报方案,该方案将临近预报与缩小的NWP合并

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摘要

An ensemble-based probabilistic precipitation forecasting scheme has been developed that blends an extrapolation nowcast with a downscaled NWP forecast, known as STEPS: Short-Term Ensemble Prediction System. The uncertainties in the motion and evolution of radar-inferred precipitation fields are quantified, and the uncertainty in the evolution of the precipitation pattern is shown to be the more important. The use of ensembles allows the scheme to be used for applications that require forecasts of the probability density function of areal and temporal averages of precipitation, such as fluvial flood forecasting—a capability that has not been provided by previous probabilistic precipitation nowcast schemes. The output from a NWP forecast model is downscaled so that the small scales not represented accurately by the model are injected into the forecast using stochastic noise. This allows the scheme to better represent the distribution of precipitation rate at spatial scales finer than those adequately resolved by operational NWP. The performance of the scheme has been assessed over the month of March 2003. Performance evaluation statistics show that the scheme possesses predictive skill at lead times in excess of six hours.
机译:已经开发了一种基于集合的概率降水预报方案,该方案将临近预报和缩小的NWP预报相结合,称为STEPS:短期集合预报系统。量化了由雷达推断的降水场的运动和演化中的不确定性,并且表明降水模式的演化中的不确定性更为重要。集成的使用使该方案可用于需要预测降水的面积和时间平均值的概率密度函数的应用(例如河流洪水预报),而以前的概率降水临近预报方案未提供此功能。 NWP预测模型的输出将按比例缩小,以便使用随机噪声将模型无法准确表示的小比例注入到预测中。这使该方案能够更好地表示比实际NWP能够充分解决的降水量分布更精细的空间尺度上的降水量分布。该计划的性能已于2003年3月进行了评估。性能评估统计数据表明,该方案在提前六个小时以上的时间内具有预测能力。

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