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The THORPEX Interactive Grand Global Ensemble
Open accessAbstract
Ensemble forecasting is increasingly accepted as a powerful tool to improve early warnings for high-impact weather. Recently, ensembles combining forecasts from different systems have attracted a considerable level of interest. The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Globa l Ensemble (TIGGE) project, a prominent contribution to THORPEX, has been initiated to enable advanced research and demonstration of the multimodel ensemble concept and to pave the way toward operational implementation of such a system at the international level. The objectives of TIGGE are 1) to facilitate closer cooperation between the academic and operational meteorological communities by expanding the availability of operational products for research, and 2) to facilitate exploring the concept and benefits of multimodel probabilistic weather forecasts, with a particular focus on high-impact weather prediction. Ten operational weather forecasting centers producing daily global ensemble forecasts to 1–2 weeks ahead have agreed to deliver in near–real time a selection of forecast data to the TIGGE data archives at the China Meteorological Agency, the European Centre for Medium-Range Weather Forecasts, and the National Center for Atmospheric Research. The volume of data accumulated daily is 245 GB (1.6 million global fields). This is offered to the scientific community as a new resource for research and education. The TIGGE data policy is to make each forecast accessible via the Internet 48 h after it was initially issued by each originating center. Quicker access can also be granted for field experiments or projects of particular interest to the World Weather Research Programme and THORPEX. A few examples of initial results based on TIGGE data are discussed in this paper, and the case is made for additional research in several directions.
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“Recently MLWP has helped improve on NWP-based forecasting in regimes where traditional NWP is relatively weak, for example sub-seasonal heat wave prediction [16] and precipitation nowcasting from radar images [32, 33, 29, 8]”
From Learning skillful medium-range global weather forecasting (2023) · cites this paper as [8]
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“For the HRES baseline, we used the TIGGE archive, which provides cyclone tracks estimated with the operational tracker, from HRES's forecasts at 0.1° resolution [8, 46].”
From Learning skillful medium-range global weather forecasting (2023) · cites this paper as [8]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“However, the HRES cyclone tracks in the TIGGE archive [8] are only initialized at 00z and 12z.”
From Learning skillful medium-range global weather forecasting (2023) · cites this paper as [8]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“We note that we do not use our tracker for the HRES baseline, as its tracks are directly recovered from the TIGGE archives [8].”
From Learning skillful medium-range global weather forecasting (2023) · cites this paper as [8]
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Research works printed but not linked: 5
- Champion, A., 2008: Properties of ensemble forecasts from different weather centres. M.S. thesis, Univer- sity of Reading.
- Matsueda, M., and H. L. Tanaka, 2008: Can MCGE outperform the ECMWF ensemble? Sci. Online Lett. Atmos., 4, 77-80, doi:10.2151/sola.2008-020. · DOI
- Pappenberger, F., J. Bartholmes, J. Thielen, H. L. Cloke, R. Buizza, and A. de Roo, 2008: New dimensions in early flood warning across the globe using grand- ensemble weather predictions. Geophys. Res. Lett., 35, L10404, doi:10.1029/2008GL033837. · DOI
- Richardson, D., R. Buizza, and R. Hagedorn, 2005: First Workshop on the THORPEX Interactive Grand Global Ensemble (TIGGE): Final report. World Meteorological Organization WMO/TD-No. 1273, WWRP/THORPEX No. 5, 39 pp. [Available online at http://tigge.ecmwf.int/references_pdf_files/ TIGGE_report_WS1_WMO_TD1273_2005.pdf.]
- Toth, Z., and Coauthors, 2005: The North American Ensemble Forecast System (NAEFS). Proc. First THORPEX Int. Science Symp., Montreal, QC, Canada, WMO.
Cited by
Sorted by citations
Accurate medium-range global weather forecasting with 3D neural networks
Bi, K., Xie, L., Zhang, H., Chen, X., Gu, X., & Tian, Q. (2023) · Nature · doi:10.1038/s41586-023-06185-3 · Cited by 1,670
Learning skillful medium-range global weather forecasting
Lam, R., Sanchez-Gonzalez, A., Willson, M., Wirnsberger, P., Fortunato, M., Alet, F., Ravuri, S., Ewalds, T., Eaton-Rosen, Z., Hu, W., et al. (2023) · Science · doi:10.1126/science.adi2336 · Cited by 1,466
Why Should Ensemble Spread Match the RMSE of the Ensemble Mean?
Fortin, V., Abaza, M., Anctil, F., & Turcotte, R. (2014) · Journal of Hydrometeorology · doi:10.1175/jhm-d-14-0008.1 · Cited by 263
FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model
Zhong, X., Chen, L., Liu, J., Lin, C., Qi, Y., & Li, H. (2024) · Science China Earth Sciences · doi:10.1007/s11430-023-1427-x · Cited by 37
Metadata
- Authors
- Bougeault, P., Toth, Z., Bishop, C., Brown, B., Burridge, D., Chen, D. H., Ebert, B., Fuentes, M., Hamill, T. M., Mylne, K., Nicolau, J., Paccagnella, T., Park, Y.-Y., Parsons, D., Raoult, B., Schuster, D., Dias, P. S., Swinbank, R., Takeuchi, Y., Tennant, W., Wilson, L., & Worley, S.
- Affiliations
- European Centre for Medium-Range Weather Forecasts (GB)
- United States Naval Research Laboratory (US)
- NSF National Center for Atmospheric Research (US)
- United Nations (US)
- China Meteorological Administration (CN)
- National Oceanic and Atmospheric Administration (US)
- Met Office (GB)
- Universidade de São Paulo (BR)
- Korea Meteorological Administration (KR)
- Japan Meteorological Agency (JP)
- Corresponding author
- Bougeault, Philippe
- ORCID
- Venue
- Bulletin of the American Meteorological Society
- Publisher
- American Meteorological Society
- Published
- 2010-08
- Volume
- 91
- Issue
- 8
- Pages
- 1059-1072
- ISSN
- 0003-0007 (ISSN-L)
- 1520-0477
- OpenAlex
- W2091361900
- Cited by
- 499
- References
- 0
- Citations by year
- 2026: 35 · 2025: 34 · 2024: 43 · 2023: 33 · 2022: 29 · 2021: 42 · 2020: 36 · 2019: 30 · 2018: 33 · 2017: 26 · 2016: 32 · 2015: 26 · 2014: 27 · 2013: 26 · 2012: 16
- FWCI
- 13.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- Locations
- Bulletin of the American Meteorological Society (publishedVersion, other-oa)
- Scientific Electronic Library Online (São Paulo Research Foundation, Latin American and Caribbean Center on Health Sciences Information, Conselho Nacional de Desenvolvimento Científico e Tecnológico) (publishedVersion)
- Funders
- National Center for Atmospheric Research
- China Meteorological Administration
- 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
- TIGGE, THORPEX, probabilistic weather forecasting, early warning
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- CoChat. (2026). Citation check: The THORPEX Interactive Grand Global Ensemble. https://app.cochat.ai/papers/10.1175/2010bams2853.1
- The paper
- Bougeault, P., Toth, Z., Bishop, C., Brown, B., Burridge, D., Chen, D. H., Ebert, B., Fuentes, M., Hamill, T. M., Mylne, K., Nicolau, J., Paccagnella, T., Park, Y.-Y., Parsons, D., Raoult, B., Schuster, D., Dias, P. S., Swinbank, R., Takeuchi, Y., . . . Worley, S. (2010). The THORPEX Interactive Grand Global Ensemble. Bulletin of the American Meteorological Society. https://doi.org/10.1175/2010bams2853.1
