Bias adjustment and ensemble recalibration methods for seasonal forecasting: a comprehensive intercomparison using the C3S dataset

Author:

Manzanas R.,Gutiérrez J. M.,Bhend J.,Hemri S.,Doblas-Reyes F. J.,Torralba V.,Penabad E.,Brookshaw A.

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Reference43 articles.

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2. Bedia J, Golding N, Casanueva A, Iturbide M, Buontempo C, Gutiérrez JM (2018) Seasonal predictions of Fire Weather Index: paving the way for their operational applicability in Mediterranean Europe. Clim Serv 9:101–110. https://doi.org/10.1016/j.cliser.2017.04.001

3. Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Holm EV, Isaksen L, Kallberg P, Koehler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thepaut JN, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597. https://doi.org/10.1002/qj.828

4. Déqué M (2007) Frequency of precipitation and temperature extremes over France in an anthropogenic scenario: Model results and statistical correction according to observed values. Glob Planet Change 57(1–2):16–26. https://doi.org/10.1016/j.gloplacha.2006.11.030

5. Doblas-Reyes FJ, Hagedorn R, Palmer TN (2005) The rationale behind the success of multi-model ensembles in seasonal forecasting II. Calibration and combination. Tellus A 57(3):234–252. https://doi.org/10.1111/j.1600-0870.2005.00104.x

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