IMPROVER: The New Probabilistic Postprocessing System at the Met Office

Author:

Roberts Nigel1,Ayliffe Benjamin1,Evans Gavin1,Moseley Stephen1,Rust Fiona1,Sandford Caroline1,Trzeciak Tomasz1,Abernethy Paul1,Beard Laurence1,Crosswaite Neil1,Fitzpatrick Ben1,Flowerdew Jonathan1,Gale Tom2,Holly Leigh1,Hopkinson Aaron1,Hurst Katharine1,Jackson Simon1,Jones Caroline1,Mylne Ken1,Sampson Christopher1,Sharpe Michael1,Wright Bruce1,Backhouse Simon1,Baker Mark1,Brierley Daniel1,Booton Anna1,Bysouth Clare1,Coulson Robert1,Coultas Sean1,Crocker Ric1,Harbord Roger1,Howard Kathryn1,Hughes Teresa1,Mittermaier Marion1,Petch Jon1,Pillinger Tim1,Smart Victoria1,Smith Eleanor1,Worsfold Mark1

Affiliation:

1. Met Office, Exeter, United Kingdom;

2. Bureau of Meteorology, Melbourne, Victoria, Australia

Abstract

Abstract 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.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference58 articles.

1. Accounting for skew when postprocessing MOGREPS-UK temperature forecast fields;Allen, S.,2021a

2. Incorporating the North Atlantic Oscillation into the post-processing of MOGREPS-G wind speed forecasts;Allen, S.,2021b

3. Development and verification of two convection-allowing multi-model ensembles over western Europe;Beck, J.,2016

4. Spatial techniques applied to precipitation ensemble forecasts: From verification results to probabilistic products;Ben Bouallègue, Z.,2014

5. Accounting for representativeness in the verification of ensemble precipitation forecasts;Ben Bouallègue, Z.,2020

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