Changes in the North Atlantic Oscillation (NAO) heavily influence the weather across the UK and the rest of Europe. Due to an incorrect representation of the polar jet stream and its associated physical processes, it is reasonable to believe that errors in numerical weather prediction models may also depend on the prevailing behaviour of the NAO. To address this, information regarding the NAO is incorporated into statistical post‐processing methods through a regime‐dependent mixture model, which is then applied to wind speed forecasts from the Met Office's global ensemble prediction system, MOGREPS‐G. The mixture model offers substantial improvements upon conventional post‐processing methods when the local wind speed depends strongly on the NAO, but the additional complexity of the model can hinder forecast performance otherwise. A measure of regime dependency is thus defined that can be used to differentiate between situations when the numerical model output is, and is not, expected to benefit from regime‐dependent post‐processing. Implementing the regime‐dependent mixture model only when this measure exceeds a certain threshold is found to further improve predictive performance, while also producing more accurate forecasts of extreme wind speeds.

中文翻译：

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将北大西洋涛动纳入MOGREPS-G风速预报的后处理

北大西洋涛动（NAO）的变化严重影响了英国和欧洲其他地区的天气。由于极性射流及其相关物理过程的表示不正确，因此有理由相信，数值天气预报模型中的错误也可能取决于NAO的普遍行为。为了解决这个问题，有关NAO的信息通过依赖于制度的混合模型纳入统计后处理方法，然后将其应用于大都会办公室全球整体预报系统MOGREPS-G的风速预报。当本地风速强烈依赖于NAO时，混合模型对传统的后处理方法进行了实质性的改进，但是该模型的额外复杂性可能会阻碍预测性能。因此，定义了一种制度依赖的度量，该度量可用于区分数值模型输出是否预期会受益于依赖制度的后处理的情况。仅当发现该措施超过一定阈值时，才实施依赖于制度的混合模型，以进一步改善预测性能，同时还可以更精确地预测极端风速。