Incorporating the North Atlantic Oscillation into the post‐processing of MOGREPS‐G wind speed forecasts. (11th February 2021)

• Record Type: Journal Article
• Authors: Allen, Sam; Evans, Gavin R.; Buchanan, Piers; Kwasniok, Frank
• Is Part Of: Quarterly journal of the Royal Meteorological Society. Volume 147:Number 735(2021)
• Page Start: 1403
• Page End: 1418
• Publication Date: 2021-02-11
• Subjects: North Atlantic Oscillation -- statistical post‐processing -- weather forecasting -- weather regimes -- wind speed; Meteorology -- Periodicals; 551.5
• DOI: 10.1002/qj.3983
• Languages: English
• ISSNs: 0035-9009

Abstract

Abstract: 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. Abstract : A framework is developed that can identify situations in which MOGREPS‐G wind speed forecasts depend strongly on the prevailing phase of the North Atlantic Oscillation (NAO). In such situations, a separate post‐processing method is applied to forecasts depending on whether a positive or negative NAO event is expected to occur. Since the resulting forecasts can account for regime‐dependent forecast errors, they perform significantly better than those generated using standard post‐processing methods, and are particularly adept at forecasting more extreme wind speeds.