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How sensitive are probabilistic precipitation forecasts to the choice of ensemble generation method?

机译:概率降水预报对集合生成方法的选择有多敏感?

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@@ 1. Intruduction As described by Wilks and Hamill 2007, errors in PQPF forecast have several sources, including initial conditions and model errors. These two particular error sources motivate two different approaches for ensemble generation: the initial and boundary condition perturbation ensemble (Toth and Kalnay 1997, Molteni et al 1996 among many others) and ensembles with different formulation of model physics or multimodel ensembles (Ebert et al. 2001, Krishnamurti et al. 1999, Park et al. 2008). The main objective of this paper is to evaluate which approach leads to a better PQPF skill over our region of interest and also to perform a comparison between perturbed initial conditions and/or perturbed physics generated ensembles with simpler and computationally cheap ensembles like the one proposed by Theis et al. 2005, which only takes into account displacement errors in the forecasted field.
机译:@@ 1.引言如Wilks和Hamill 2007所述,PQPF预测中的误差有多种来源,包括初始条件和模型误差。这两个特殊的误差源激发了两种不同的合奏方法:初始条件和边界条件摄动合奏(Toth和Kalnay 1997,Molteni等1996)以及采用不同形式的模型物理或多模型合奏的合奏(Ebert等人。 (2001年,克里希那穆提(Krishnamurti)等人,1999年,公园(Park)等人,2008年)。本文的主要目的是评估哪种方法可以在我们感兴趣的区域内提高PQPF技能,还可以比较扰动的初始条件和/或扰动的物理生成的乐团,并采用更简单且计算便宜的乐团进行比较,例如: Theis等。 2005年,仅考虑了预测领域中的位移误差。

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