IMPROVER: The New Probabilistic Postprocessing System at the Met Office

Autor: Nigel Roberts, Benjamin Ayliffe, Gavin Evans, Stephen Moseley, Fiona Rust, Caroline Sandford, Tomasz Trzeciak, Paul Abernethy, Laurence Beard, Neil Crosswaite, Ben Fitzpatrick, Jonathan Flowerdew, Tom Gale, Leigh Holly, Aaron Hopkinson, Katharine Hurst, Simon Jackson, Caroline Jones, Ken Mylne, Christopher Sampson, Michael Sharpe, Bruce Wright, Simon Backhouse, Mark Baker, Daniel Brierley, Anna Booton, Clare Bysouth, Robert Coulson, Sean Coultas, Ric Crocker, Roger Harbord, Kathryn Howard, Teresa Hughes, Marion Mittermaier, Jon Petch, Tim Pillinger, Victoria Smart, Eleanor Smith, Mark Worsfold
Rok vydání: 2023
Předmět:
Zdroj: Bulletin of the American Meteorological Society. 104:E680-E697
ISSN: 1520-0477
0003-0007
DOI: 10.1175/bams-d-21-0273.1
Popis: The Met Office in the United Kingdom has developed a completely new probabilistic postprocessing system called IMPROVER to operate on outputs from its operational numerical weather prediction (NWP) forecasts and precipitation nowcasts. The aim is to improve weather forecast information to the public and other stakeholders while better exploiting the current and future generations of underpinning kilometer-scale NWP ensembles. We wish to provide seamless forecasts from nowcasting to medium range, provide consistency between gridded and site-specific forecasts, and be able to verify every stage of the processing. The software is written in a modern modular framework that is easy to maintain, develop, and share. IMPROVER allows forecast information to be provided with greater spatial and temporal detail and a faster update frequency than previous postprocessing. Independent probabilistic processing chains are constructed for each meteorological variable consisting of a series of processing stages that operate on predefined grids and blend outputs from several NWP inputs to give a frequently updated, probabilistic forecast solution. Probabilistic information is produced as standard, with the option of extracting a most likely or yes–no outcome if required. Verification can be performed at all stages, although it is only currently switched on for the most significant stages when run in real time. IMPROVER has been producing real-time output since March 2021 and became operational in spring 2022.
Databáze: OpenAIRE
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