Titre de la thèse : Prévisibilité des fortes précipitations aux échéances infra-saisonnières sur le Pacifique Sud-Ouest tropical - Article de synthèse publié dans le cadre de l’obtention du Prix Gérard Beltrando 2021 attribué par l’AIC et récompensant la meilleure thèse de climatologie

Open Access

Issue		Climatologie Volume 19, 2022


Article Number		2
Number of page(s)		8
DOI		https://doi.org/10.1051/climat/202219002
Published online		31 January 2023

Batté L., 2013. Prévision d’ensemble à l’échelle saisonnière : mise en place d’une dynamique stochastique. Thèse de doctorat, Université Paris-Est. [Google Scholar]
Bjerknes J., 1969. Atmospheric teleconnections from the Equatorial Pacific. Monthly Weather Review, 97(3), 163–172, doi: 10.1175/1520-0493(1969)097<0163:atftep>2.3.co;2. [CrossRef] [Google Scholar]
Beck H. E. et al., 2017. MSWEP: 3-hourly 0.25◦ global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data. Hydrology and Earth System Sciences, 21(1), 589–615, doi: 10.5194/hess-21-589-2017. [CrossRef] [Google Scholar]
Cowan T. et al., 2019. Forecasting the extreme rainfall, low temperatures, and strong winds associated with the northern Queensland floods of February 2019. Weather and Climate Extremes, 26, 100232, doi: 10.1016/j.wace.2019.100232. [CrossRef] [Google Scholar]
de Andrade F. M. et al., 2019. Global precipitation hindcast quality assessment of the Subseasonal-to-Seasonal (S2S) prediction project models. Climate Dynamics, 52, 5451–5475. doi: 10.1007/s00382-018-4457-z. [CrossRef] [Google Scholar]
Hagedorn R. et al., 2005. The rationale behind the success of multi-model ensembles in seasonal forecasting – I. Basic concept. Tellus A: Dynamic Meteorology and Oceanography, 57(3), 219–233, doi: 10.1111/j.1600-0870.2005.00103.x. [Google Scholar]
Hogan R. J. et Mason I. B., 2012. Deterministic forecasts of binary events. In Forecast Verification, 31–59, John Wiley & Sons Ltd, doi: 10.1002/9781119960003.ch3. [Google Scholar]
Kalnay E. et Dalcher A., 1987. Forecasting forecast skill. Monthly Weather Review, 115(2), 349–356, doi: 10.1175/1520-0493(1987)115<0349:ffs>2.0.co;2. [CrossRef] [Google Scholar]
Mariotti A. et al., 2020. Windows of opportunity for skillful forecasts subseasonal to seasonal and beyond. Bulletin of the American Meteorological Society, 101(5), E608–E625, doi: 10.1175/bams-d-18-0326.1. [CrossRef] [Google Scholar]
McGree S. et al., 2014. An updated assessment of trends and variability in total and extreme rainfall in the western Pacific. International Journal of Climatology, 34(8), 2775–2791, doi: 10.1002/joc.3874. [CrossRef] [Google Scholar]
Merryfield W. J. et al., 2020. Current and emerging developments in subseasonal to decadal prediction. Bulletin of the American Meteorological Society, 101(6), E869–E896, doi: 10.1175/BAMS-D-19-0037.1. [CrossRef] [Google Scholar]
Moron V. et Robertson A. W., 2020. Tropical rainfall subseasonal-to-seasonal predictability types. npj Climate and Atmospheric. Science, 3(1), 1–8, doi: 10.1038/s41612-020-0107-3. [CrossRef] [Google Scholar]
Pariyar S. K. et al., 2020. Factors affecting extreme rainfall events in the South Pacific. Weather and Climate Extremes, 29, 100262, doi: 10.1016/j.wace.2020.100262. [CrossRef] [Google Scholar]
Specq D. et al., 2020. Multimodel forecasting of precipitation at subseasonal timescales over the southwest tropical Pacific. Earth and Space Science, 7(9), doi:10.1029/2019EA001003. [CrossRef] [Google Scholar]
Specq D. et Batté L., 2020. Improving subseasonal precipitation forecasts through a statistical-dynamical approach: application to the southwest tropical Pacific. Climate Dynamics, 55, 1913–1927, doi: 10.1007/s00382-020-05355-7. [CrossRef] [Google Scholar]
Vitart F. et al., 2017. The Subseasonal to Seasonal (S2S) prediction project database. Bulletin of the American Meteorological Society, 98(1), 163–173, doi: 10.1175/bams-d-16-0017.1. [CrossRef] [Google Scholar]
Vitart F., 2017. Madden-Julian Oscillation prediction and teleconnections in the S2S database. Quarterly Journal of the Royal Meteorological Society, 143(706), 2210–2220, doi: 10.1002/qj.3079. [CrossRef] [Google Scholar]
White C. J. et al., 2017. Potential applications of subseasonal-to-seasonal (S2S) predictions. Meteorological Applications, 24(3), 315–325, doi: 10.1002/met.1654. [CrossRef] [Google Scholar]
Zhang C., 2005. Madden-Julian Oscillation. Reviews of Geophysics, 43(2), doi: 10.1029/2004RG000158. [Google Scholar]

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