Forecast assimilation: a unified framework for the combination of multi-model weather and climate predictions
Open accessAbstract
In this paper we present a unified conceptual framework for the creation of calibrated probability forecasts of observable variables based on information from ensembles of weather/climate model predictions. For the same reasons that data assimilation is required to feed observed information into numerical prediction models, an analogous process of forecast assimilation is required to convert model predictions into well-calibrated forecasts of observable variables. Forecast assimilation includes and generalizes previous calibration methods such as model output statistics and statistical downscaling. To illustrate the approach, we present a flexible variational form of forecast assimilation based on a Bayesian multivariate normal model capable of assimilating multi-model predictions of gridded fields. This method is then successfully applied to equatorial Pacific sea surface temperature grid point predictions produced by seven coupled models in the DEMETER project. The results show improved forecast skill compared to individual model forecasts and multi-model mean forecasts.
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In seasonal forecasting, performance-based weighting schemes have been successfully implemented and improve average prediction skill.
“Given that, in seasonal forecasting, performance-based weighting schemes have been successfully implemented and have been demonstrated to improve the average prediction skill (e.g., Rajagopalan et al. 2002;Robertson et al. 2004;Stephenson et al. 2005;Weigel et al. 2008b)”
From Risks of Model Weighting in Multimodel Climate Projections (2010) · cites this paper as Stephenson et al. 2005
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Flagged first, then by citations
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Cited by
Sorted by citations
Risks of Model Weighting in Multimodel Climate Projections
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- Authors
- Stephenson, D. B., Coelho, C. A. S., Doblas-Reyes, F. J., & Balmaseda, M.
- Affiliations
- University of Reading (GB)
- European Centre for Medium-Range Weather Forecasts (GB)
- Corresponding author
- Stephenson, D. B.
- Venue
- Tellus A: Dynamic Meteorology and Oceanography
- Publisher
- Stockholm University Press
- Published
- 2005-01-01
- Volume
- 57
- Issue
- 3
- Pages
- 253
- ISSN
- 0280-6495 (ISSN-L)
- 1600-0870
- OpenAlex
- W2156850505
- Cited by
- 111
- References
- 31
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 5 · 2022: 2 · 2021: 3 · 2020: 1 · 2019: 6 · 2018: 8 · 2017: 3 · 2016: 3 · 2015: 3 · 2014: 5 · 2013: 10 · 2012: 7
- FWCI
- 6.39
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Tellus A Dynamic Meteorology and Oceanography (publishedVersion, cc-by)
- Tellus A Dynamic Meteorology and Oceanography (publishedVersion)
- CentAUR (University of Reading) (submittedVersion)
- Biblioteca Digital da Memória Científica do INPE (National Institute for Space Research) (submittedVersion)
- Funders
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- China Aerospace Science and Technology Corporation
- Topics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
- Keywords
- multi-model prediction, forecast calibration, model output statistics, statistical downscaling, variational data assimilation, ensemble weather prediction, coupled climate model, sea surface temperature prediction, equatorial Pacific, DEMETER project
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