Incorporating the North Atlantic Oscillation into the post-processing of MOGREPS-G wind speed forecasts

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.

Automated summary

The study found that a regime-dependent mixture model based on the North Atlantic Oscillation can substantially improve wind speed forecasts compared to traditional post-processing methods, but the model's complexity may impact forecast performance. A measure of regime dependency was defined to differentiate situations when numerical model output benefits from regime-dependent post-processing, leading to further improvements in predictive performance and more accurate forecasts of extreme wind speeds when implemented based on a certain threshold value.