European Center for Medium-Range Weather Forecasts

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ECMWF building in Reading
  • Members
  • Cooperation (as of 2016)
  • The European Center for Medium-Range Weather Forecast ( ECMWF , English European Center for Medium-Range Weather Forecasts , ECMWF ) is an independent international organization based in Reading ( UK ), which was established in 1975.

    The center is supported by 22 member states: Belgium , Denmark , Germany , Finland , France , Greece , Ireland , Iceland , Italy , Croatia , Luxembourg , Norway , the Netherlands , Austria , Portugal , Sweden , Switzerland , Serbia , Slovenia , Spain , Turkey and United Kingdom .

    The cooperating countries are Bulgaria , the Czech Republic , Estonia , Macedonia , Hungary , Israel , Latvia , Lithuania , Montenegro , Morocco , Romania and Slovakia .


    The main objectives of the center are (Art. 2 of the Convention):

    • the development of dynamic models of the atmosphere for the development of medium-term weather forecasts with the help of numerical methods
    • the regular creation of the data necessary for the preparation of medium-term weather forecasts
    • scientific and technical research to improve the quality of these predictions
    • the collection and archiving of useful meteorological data

    The most important task is the calculation of medium-term global weather forecasts twice a day based on physical models. The deterministic forecasts of the IFS model (Integrated Forcasting System, math. Model and software of the ECMWF) are calculated for 10 days in advance. The model resolution is currently around 9 km. In addition, the center was one of the first organizations to introduce ensemble calculations in 1992 . By calculating the forecast model several times with slightly changed initial conditions, statements can be made about the probability of occurrence. The atmospheric ensemble model of the ECMWF currently calculates up to 15 days in advance.

    Other important computational models of the center are the ECMWF Monthly Forecasting system , the EUROSIP multi-model seasonal forecasting system and the global atmospheric reanalyses (e.g. ERA-Interim global atmospheric reanalysis or ERA5), as well as the two oceanographic products System 3 Ocean Analysis , which is also used for seasonal forecast, and WAM (Wave Model) for swell simulation.


    Advances in numerical weather forecasting are closely related to advances in supercomputers . Over the years, the greater computing power has enabled better weather forecasts to be made.

    A Cray XC30 , which has a computing power of 3,593 TeraFLOPS, has been running in phase 1 since mid-2016 . It consists of 7,010 Intel processors of the type E5-2697v2 “ Ivy Bridge ” (12 cores, 2.7 GHz) and is retrofitted with 3610 Intel Xeon EP E5-2695 V4 “Broadwell” (18 cores, 2.1 GHz) and then reaches 8,499 TeraFLOPS. The ECMWF models had previously been running since 2006 on a dual IBM cluster (155 p5-575 +) with around 5,000 scalar CPUs at 38 T FLOPS , which runs in the Shinfield Park data center in Reading. Before that there was a Cray 1 A, then a Fujitsu VPP 700, a VPP 5000 and, since 2002, two IBM Cluster 1600s in operation.

    For the next generation of computers based on an Atos Sequana with AMD processors, a separate location outside Reading in Bologna, Italy, is planned from 2020/21.

    Known research results

    By evaluating data from the center, Yong Zhu and Reginald E. Newell of the Massachusetts Institute of Technology discovered in 1998 the atmospheric rivers that are responsible for transporting around 90 percent of the moisture from the equatorrial regions to the mid-latitudes. This discovery is also the basis for the United States Geological Survey's Arkstorm scenario .


    • Austin Woods: Medium-Range Weather Prediction: The European Approach. The Story of the European Center for Medium-Range Weather Forecasts. Springer, New York 2006, ISBN 0-387-26928-2 .

    Web links

    Individual evidence

    1. IFS Documentation ( Memento from May 31, 2012 in the Internet Archive )
    2. New forecast model cycle brings highest-ever resolution. ECMWF, March 10, 2016, accessed May 6, 2018 .
    3. ^ Ensemble Prediction System ( Memento from October 21, 2011 in the Internet Archive )
    4. ^ The ECMWF Monthly Forecasting System: Documentation ( Memento of October 24, 2008 in the Internet Archive )
    5. The EUROSIP multi-model seasonal forecasting system ( Memento from August 1, 2012 in the web archive ).
    6. ERA interim project
    7. Dee et al .: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. In: Quarterly Journal of the Royal Meteorological Society Part A. Volume 137, No. 656, pp. 553-597, April 2011, doi : 10.1002 / qj.828 .
    8. Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara , G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy , S., Hogan, RJ, Hólm, EA, Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Radnoti, G., Rosnay, PD, Rozum, I., Vamborg, F. , Villaume, S., Thépaut, J.-N .: The ERA5 global reanalysis. QJR Meteorol Soc, , 2020.
    9. ^ Ocean Analysis Documentation ( Memento of January 7, 2013 in the Internet Archive )
    10. Seasonal Forecast User Guide (System 3) ( Memento from July 29, 2012 in the web archive )
    11. Ocean waves at ECMWF. (PDF; 1 MB) ECMWF, accessed on June 14, 2018 (English).
    12. supercomputers. ECMWF, 2013, accessed June 14, 2018 .
    13. ECMWF Supercomputer History ( Memento from April 16, 2009 in the Internet Archive )
    14. ECMWF's new data center to be located in Bologna, Italy, by 2019. Retrieved October 6, 2017 (English).
    15. José Andrés Pérez León: HPC2020 - ECMWF's new High-Performance Computing Facility. April 22, 2020, accessed April 26, 2020 (English).
    16. ^ Yong Zhu, Reginald E. Newell: A Proposed Algorithm for Moisture Fluxes from Atmospheric Rivers . In: Monthly Weather Review . tape 126 , March 1998, p. 725-735 , doi : 10.1175 / 1520-0493 (1998) 126 <0725: APAFMF> 2.0.CO; 2 (free full text).
    17. Summary of the ArkStorm scenario of the US Geological Survey from: Keith Porter, Anne Wein, Charles Alpers, Allan Baez, Patrick Barnard, James Carter, Alessandra Corsi, James Costner, Dale Cox, Tapash Das, Michael Dettinger, James Done, Charles Eadie , Marcia Eymann, Justin Ferris, Prasad Gunturi, Mimi Hughes, Robert Jarrett, Laurie Johnson, Hanh Dam Le-Griffin, David Mitchell, Suzette Morman, Paul Neiman, Anna Olsen, Suzanne Perry, Geoffrey Plumlee, Martin Ralph, David Reynolds, Adam Rose, Kathleen Schaefer, Julie Serakos, William Siembieda, Jonathan Stock, David Strong, Ian Sue Wing, Alex Tang, Pete Thomas, Ken Topping, directed by Chris Wills and Lucile Jones; Project manager Dale Cox (201) Overview of the ARkStorm scenario: US Geological Survey Open-File Report 2010-1312 , 183 pages plus attachments

    Coordinates: 51 ° 25 '10.4 "  N , 0 ° 57' 2.8"  W.