IMPROVER overview and updates Article Swipe
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5194/ems2022-254
<p>IMPROVER (Integrated Model Post-Processing and Verification) has been developed by the Met Office as an open-source probability-based post-processing system to fully exploit our convection permitting, hourly cycling ensemble forecasts. Post-processed MOGREPS-UK model forecasts are blended with deterministic UKV model forecasts and data from the coarser resolution global ensemble, MOGREPS-G, to produce seamless probabilistic forecasts from now out to 7 days ahead. For precipitation, an extrapolation nowcast is also blended in at the start. Forecasts are converted to probabilities at the start, and all initial stages of post-processing are performed on gridded data, with site-specific forecasts extracted as a final step, helping to ensure consistency. Data are processed on a 10km global grid and on a 2km UK-centred grid.</p><p>This talk will briefly describe the post-processing sequence from raw NWP model data to fully-blended, gridded and spot forecasts as probabilities and percentiles of a broad range of meteorological diagnostics, with the application of physical and statistical post-processing techniques. The system became operational in early May 2022, and the this talk will focus on some of the work that has been undertaken in the last year to achieve this, including ensemble calibration of temperature and wind speed data at observed and non-observed sites. There will be discussion of some of the verification used to prove this system, as well as a brief look at the technical aspects of this complex system, the initial customers and collaborators and the planned future work, including the use of ECMWF forecast data to extend the range of IMPROVER out to 14 days.</p>
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.5194/ems2022-254
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4283656249Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5194/ems2022-254Digital Object Identifier
- Title
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IMPROVER overview and updatesWork title
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preprintOpenAlex work type
- Language
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enPrimary language
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2022Year of publication
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2022-06-28Full publication date if available
- Authors
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Stephen Moseley, Ken Mylne, Bruce Wright, Simon Jackson, Fiona Rust, G. R. Evans, Ben Ayliffe, Kat Hurst, Marcus Spelman, Ben Fitzpatrick, Christopher SampsonList of authors in order
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https://doi.org/10.5194/ems2022-254Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.5194/ems2022-254Direct OA link when available
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Probabilistic logic, Computer science, Consistency (knowledge bases), Grid, Meteorology, Extrapolation, Calibration, Database, Environmental science, Artificial intelligence, Geography, Mathematics, Statistics, GeodesyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| publication_date | 2022-06-28 |
| publication_year | 2022 |
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