Articles | Volume 12, issue 3
https://doi.org/10.5194/gmd-12-1087-2019
https://doi.org/10.5194/gmd-12-1087-2019
Model description paper
 | 
22 Mar 2019
Model description paper |  | 22 Mar 2019

SEAS5: the new ECMWF seasonal forecast system

Stephanie J. Johnson, Timothy N. Stockdale, Laura Ferranti, Magdalena A. Balmaseda, Franco Molteni, Linus Magnusson, Steffen Tietsche, Damien Decremer, Antje Weisheimer, Gianpaolo Balsamo, Sarah P. E. Keeley, Kristian Mogensen, Hao Zuo, and Beatriz M. Monge-Sanz

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Cited articles

Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), J. Hydrometeorol., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003. a
Ahlgrimm, M. and Forbes, R.: Improving the representation of low clouds and drizzle in the ECMWF model based on ARM observations from the Azores, Mon. Weather Rev., 142, 668–685, 2014. a
Balmaseda, M. A., Mogensen, K., and Weaver, A. T.: Evaluation of the ECMWF ocean reanalysis system ORAS4, Q. J. Roy. Meteor. Soc., 139, 1132–1161, https://doi.org/10.1002/qj.2063, 2013. a, b
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A revised hydrology for the ECMWF model: Verification from field site to terrestrial water storage and impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, 2009. a, b
Balsamo, G., Salgado, R., Dutra, E., Boussetta, S., Stockdale, T., and Potes, M.: On the contribution of lakes in predicting near-surface temperature in a global weather forecasting model, Tellus A, 64, 15829, https://doi.org/10.3402/tellusa.v64i0.15829, 2012. a
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In this article, we describe the new ECMWF seasonal forecast system, SEAS5, which replaced its predecessor in November 2017. We describe the forecast methodology used in SEAS5 and compare results from SEAS5 to results from the previous seasonal forecast system, highlighting the strengths and weaknesses of SEAS5. SEAS5 data are publicly available through the Copernicus Climate Change Service's multi-system seasonal forecast.