Performance of Met Office hourly cycling NWP‐based nowcasting for precipitation forecasts

The Met Office developed a prototype high‐resolution, hourly‐cycling NWP forecasting system using four‐dimensional variational data assimilation, covering the southern half of England. This system was known as the Met Office Nowcasting Demonstration Project (NDP), and ran in real time from June 2012...

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Veröffentlicht in:Quarterly journal of the Royal Meteorological Society 2017-10, Vol.143 (708), p.2862-2873
Hauptverfasser: Simonin, David, Pierce, Clive, Roberts, Nigel, Ballard, Susan P., Li, Zhihong
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Sprache:eng
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Zusammenfassung:The Met Office developed a prototype high‐resolution, hourly‐cycling NWP forecasting system using four‐dimensional variational data assimilation, covering the southern half of England. This system was known as the Met Office Nowcasting Demonstration Project (NDP), and ran in real time from June 2012 to March 2013 (covering the period of the London 2012 Olympics and Paralympic Games). It was principally developed to assess the abilities of a frequently updated NWP‐based nowcasting system to forecast precipitation at short range such as convective storms for flood forecasting. This article provides a comprehensive assessment of the precipitation forecast skill of the NDP and its comparison against the Met Office operational nowcasting system. It was found that the NWP‐based nowcasting system becomes more skilful than an advanced extrapolation‐based nowcasting system from T + 1.5 to T + 2 h depending on weather type. Over recent years, there has been a need to improved short‐range precipitation forecasts to support operations such as aviation weather, flooding or sporting events. In response to this challenge, the Met Office developed a prototype high‐resolution, hourly‐cycling NWP forecasting system using 4D‐Var data assimilation. This system was known as the Met Office Nowcasting Demonstration Project (NDP) and ran operationally during the London 2012 Olympic Games. Results suggest that NWP will certainly play an increasing role in future nowcasting systems and short‐range forecasts.
ISSN:0035-9009
1477-870X
DOI:10.1002/qj.3136