The Subseasonal to Seasonal (S2S) Prediction Project Database

Vitart, F.; Ardilouze, C.; Bonet, A.; Brookshaw, A.; Chen, M.; Codorean, C.; Déqué, M.; Ferranti, L.; Fucile, E.; Fuentes, M.; Hendon, H.; Hodgson, J.; Kang, H.-S.; Kumar, A.; Lin, H.; Liu, G.; Liu, X.; Malguzzi, P.; Mallas, I.; Manoussakis, M.; Mastrangelo, D.; MacLachlan, C.; McLean, P.; Minami, A.; Mladek, R.; Nakazawa, T.; Najm, S.; Nie, Y.; Rixen, M.; Robertson, A. W.; Ruti, P.; Sun, C.; Takaya, Y.; Tolstykh, M.; Venuti, F.; Waliser, D.; Woolnough, S.; Wu, T.; Won, D.-J.; Xiao, H.; Zaripov, R.; Zhang, L.

doi:10.1175/bams-d-16-0017.1

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The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

i

The Subseasonal to Seasonal (S2S) Prediction Project Database

2017
By Vitart, F. ; Ardilouze, C. ; Bonet, A. ; ...
Source: Bulletin of the American Meteorological Society, 98(1), 163-173

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Journal Title:

Bulletin of the American Meteorological Society
Personal Author:

Vitart, F. ; Ardilouze, C. ; Bonet, A. ; Brookshaw, A. ; Chen, M. ; ... More +

Vitart, F. ; Ardilouze, C. ; Bonet, A. ; Brookshaw, A. ; Chen, M. ; Codorean, C. ; Déqué, M. ; Ferranti, L. ; Fucile, E. ; Fuentes, M. ; Hendon, H. ; Hodgson, J. ; Kang, H.-S. ; Kumar, A. ; Lin, H. ; Liu, G. ; Liu, X. ; Malguzzi, P. ; Mallas, I. ; Manoussakis, M. ; Mastrangelo, D. ; MacLachlan, C. ; McLean, P. ; Minami, A. ; Mladek, R. ; Nakazawa, T. ; Najm, S. ; Nie, Y. ; Rixen, M. ; Robertson, A. W. ; Ruti, P. ; Sun, C. ; Takaya, Y. ; Tolstykh, M. ; Venuti, F. ; Waliser, D. ; Woolnough, S. ; Wu, T. ; Won, D.-J. ; Xiao, H. ; Zaripov, R. ; Zhang, L. Less -
NOAA Program & Office:

NCEP (National Centers for Environmental Prediction) ; NWS (National Weather Service)

NCEP (National Centers for Environmental Prediction) ; NWS (National Weather Service) Less -
Description:

Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days).
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Atmospheric Science
Source:

Bulletin of the American Meteorological Society, 98(1), 163-173
DOI:

https://doi.org/10.1175/bams-d-16-0017.1
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0003-0007;1520-0477;
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PDF
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American Meteorological Society
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Journal Article
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urn:sha-512:b66d5a43e650027e4c36fa0bfdffba8f878f6455bf17cc065253dd7d7fce1b9f8c1b773d51347a3caa5583b0dbbcc233cf053109ad030ddad7399548cbd750ba
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The Subseasonal to Seasonal (S2S) Prediction Project Database

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