T. Barnett and R. Preisendorfer, Multifield Analog Prediction of Short-Term Climate Fluctuations Using a Climate State vector, Journal of the Atmospheric Sciences, vol.35, issue.10, pp.1771-1787, 1978.
DOI : 10.1175/1520-0469(1978)035<1771:MAPOST>2.0.CO;2

A. Beaulant, B. Joly, O. Nuissier, S. Somot, V. Ducrocq et al., Statistico-dynamical downscaling for Mediterranean heavy precipitation, Quarterly Journal of the Royal Meteorological Society, vol.34, issue.656, pp.736-748, 2011.
DOI : 10.1002/qj.796

J. Beirlant, Y. Goegebeur, J. Teugels, J. Segers, D. D. Waal et al., Statistics of extremes. Theory and applications, 2004.

J. Blanchet and A. C. Davison, Spatial modeling of extreme snow depth, The Annals of Applied Statistics, vol.5, issue.3, pp.1699-1725, 2011.
DOI : 10.1214/11-AOAS464SUPP

B. M. Brown and S. I. Resnick, Extreme values of independent stochastic processes, Journal of Applied Probability, vol.14, issue.04, pp.732-739, 1977.
DOI : 10.1214/aop/1176996221

T. Buishand, L. De-haan, and C. Zhou, On spatial extremes: With application to a rainfall problem, The Annals of Applied Statistics, vol.2, issue.2, pp.624-642, 2008.
DOI : 10.1214/08-AOAS159

R. E. Caflisch, Monte Carlo and quasi-Monte Carlo methods, Acta Numerica, vol.73, issue.7, pp.1-49, 1998.
DOI : 10.1137/S0036142994277468

G. Casella and E. I. George, Explaining the gibbs sampler, The American Statistician, vol.46, issue.3, pp.167-174, 1992.

S. Coles and J. Tawn, Statistical Methods for Multivariate Extremes: An Application to Structural Design, Applied Statistics, vol.43, issue.1, pp.1-48, 1994.
DOI : 10.2307/2986112

D. Cooley, P. Naveau, and P. Poncet, Variograms for spatial max-stable random fields, Dependence in probability and statistics, pp.373-390, 2006.
DOI : 10.1007/0-387-36062-X_17

A. C. Davison and M. M. Gholamrezaee, Geostatistics of extremes, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.21, issue.3, pp.581-608, 2012.
DOI : 10.1093/biomet/92.3.519

A. C. Davison, S. A. Padoan, and M. Ribatet, Statistical Modeling of Spatial Extremes, Statistical Science, vol.27, issue.2, pp.161-186, 2012.
DOI : 10.1214/12-STS376REJ

L. De-haan, A Spectral Representation for Max-stable Processes, The Annals of Probability, vol.12, issue.4, pp.1194-1204, 1984.
DOI : 10.1214/aop/1176993148

L. De-haan and J. De-ronde, Sea and wind: multivariate extremes at work, pp.7-45, 1998.

C. Dombry and F. Eyi-minko, Regular conditional distributions of continuous maxinfinitely divisible random fields, Electron. J. Probab, vol.18, issue.7, pp.1-21, 2013.

C. Dombry, F. Eyi-minko, and M. Ribatet, Conditional simulation of max-stable processes, Biometrika, vol.100, issue.1, pp.111-124, 2013.
DOI : 10.1093/biomet/ass067

V. Ducrocq, O. Nuissier, D. Ricard, C. Lebeaupin, and T. Thouvenin, A numerical study of three catastrophic precipitating events over southern France. II: Mesoscale triggering and stationarity factors, Quarterly Journal of the Royal Meteorological Society, vol.21, issue.630, pp.131-145, 2008.
DOI : 10.1002/qj.199

URL : https://hal.archives-ouvertes.fr/meteo-00260840

L. Fawcett and D. Walshaw, Estimating return levels from serially dependent extremes, Environmetrics, vol.99, issue.Book 2, pp.272-283, 2012.
DOI : 10.1002/env.2133

P. Friederichs and T. L. Thorarinsdottir, Forecast verification for extreme value distributions with an application to probabilistic peak wind prediction, Environmetrics, vol.100, issue.4, pp.579-594, 2012.
DOI : 10.1002/env.2176

M. Fuentes, J. Henry, and B. Reich, Nonparametric spatial models for extremes: application to extreme temperature data, Extremes, vol.50, issue.2, pp.75-101, 2013.
DOI : 10.1007/s10687-012-0154-1

J. Gaume, N. Eckert, G. Chambon, M. Naaim, and L. Bel, Mapping extreme snowfalls in the French Alps using max-stable processes, Water Resources Research, vol.141, issue.9, pp.1079-1098, 2013.
DOI : 10.1002/wrcr.20083

URL : https://hal.archives-ouvertes.fr/hal-01001316

J. Geweke, Efficient simulation from the multivariate normal and student-t distributions subject to linear constraints and the evaluation of constraint probabilities, Computing science and statistics: Proceedings of the 23rd symposium on the interface. Citeseer, pp.571-578, 1991.

T. Gneiting and A. E. Raftery, Strictly proper scoring rules, prediction, and esti- mation, 2007.
DOI : 10.1198/016214506000001437

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

Z. Kabluchko, M. Schlather, and L. De-haan, Stationary max-stable fields associated to negative definite functions, The Annals of Probability, vol.37, issue.5, pp.2042-2065, 2009.
DOI : 10.1214/09-AOP455

URL : http://arxiv.org/abs/0806.2780

C. Lantuéjoul, Geostatistical simulation: models and algorithms, 2002.
DOI : 10.1007/978-3-662-04808-5

C. Lebeaupin, V. Ducrocq, and H. Giordani, Sensitivity of torrential rain events to the sea surface temperature based on high-resolution numerical forecasts, Journal of Geophysical Research, vol.16, issue.5, 2006.
DOI : 10.1029/2005JD006541

URL : https://hal.archives-ouvertes.fr/meteo-00248768

B. G. Lindsay, Composite likelihood methods, Contemporary Mathematics, vol.80, issue.1, pp.221-260, 1988.
DOI : 10.1090/conm/080/999014

G. Mariethoz, P. Renard, F. Cornaton, and O. Jaquet, Truncated Plurigaussian Simulations to Characterize Aquifer Heterogeneity, Ground Water, vol.39, issue.no. 3, pp.13-24, 2009.
DOI : 10.1111/j.1745-6584.2008.00489.x

M. Oesting and M. Schlather, Conditional sampling for max-stable processes with a mixed moving maxima representation, Extremes, vol.19, issue.2, pp.157-192, 2014.
DOI : 10.1007/s10687-013-0178-1

T. Opitz, Extremal processes: Elliptical domain of attraction and a spectral representation, Journal of Multivariate Analysis, vol.122, pp.409-413, 2013.
DOI : 10.1016/j.jmva.2013.08.008

URL : https://hal.archives-ouvertes.fr/hal-00818117

S. A. Padoan, Multivariate extreme models based on underlying skew-<mml:math altimg="si47.gif" display="inline" overflow="scroll" xmlns:xocs="http://www.elsevier.com/xml/xocs/dtd" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.elsevier.com/xml/ja/dtd" xmlns:ja="http://www.elsevier.com/xml/ja/dtd" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:tb="http://www.elsevier.com/xml/common/table/dtd" xmlns:sb="http://www.elsevier.com/xml/common/struct-bib/dtd" xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:cals="http://www.elsevier.com/xml/common/cals/dtd"><mml:mi>t</mml:mi></mml:math> and skew-normal distributions, Journal of Multivariate Analysis, vol.102, issue.5, pp.977-991, 2011.
DOI : 10.1016/j.jmva.2011.01.014

S. A. Padoan, M. Ribatet, and S. A. Sisson, Likelihood-Based Inference for Max-Stable Processes, Journal of the American Statistical Association, vol.105, issue.489, pp.263-277, 2010.
DOI : 10.1198/jasa.2009.tm08577

URL : https://hal.archives-ouvertes.fr/hal-00361245

Y. Pascal, S. Tamara, D. Philippe, M. Laurent, V. Robert et al., Ensemble reconstruction of the atmospheric column from surface pressure using analogues, Climate dynamics, vol.41, pp.5-6, 2013.

P. Quintana-seguí, P. Le-moigne, Y. Durand, E. Martin, F. Habets et al., Analysis of Near-Surface Atmospheric Variables: Validation of the SAFRAN Analysis over France, Journal of Applied Meteorology and Climatology, vol.47, issue.1, pp.92-107, 2008.
DOI : 10.1175/2007JAMC1636.1

M. Ribatet, Spatial Extremes and Max-Stable Processes, Journal de la Societe Francaise de Statistique, vol.154, issue.2, pp.156-177, 2013.
DOI : 10.1201/b19721-10

M. Ribatet, Spatialextremes : Modelling spatial extremes, 2013.

M. Schlather, Models for stationary max-stable random fields, pp.33-44, 2002.

M. Schlather and J. A. Tawn, A dependence measure for multivariate and spatial extreme values: Properties and inference, Biometrika, vol.90, issue.1, pp.139-156, 2003.
DOI : 10.1093/biomet/90.1.139

R. L. Smith, Max-stable processes and spatial extreme, 1990.

M. Z. Spivey, A generalized recurrence for bell numbers, Journal of Integer Sequences, vol.11, issue.2, 2008.

C. Varin, N. M. Reid, and D. D. Firth, An overview of composite likelihood methods, Statistica Sinica, vol.21, issue.1, pp.5-42, 2011.

M. Vrac, P. Drobinski, A. Merlo, M. Herrmann, C. Lavaysse et al., Dynamical and statistical downscaling of the French Mediterranean climate: uncertainty assessment, Natural Hazards and Earth System Science, vol.12, issue.9, pp.2769-2784, 2012.
DOI : 10.5194/nhess-12-2769-2012

URL : https://hal.archives-ouvertes.fr/hal-01111697

M. Vrac and P. Yiou, Weather regimes designed for local precipitation modeling: Application to the Mediterranean basin, D12), pp.2156-2202, 2010.
DOI : 10.1029/2009JD012871

Y. Wang and S. A. Stoev, Conditional sampling for spectrally discrete max-stable random fields, Advances in Applied Probability, vol.43, issue.2, pp.461-483, 2011.
DOI : 10.1239/aap/1308662488

X. Xu and N. Reid, On the robustness of maximum composite likelihood estimate, Journal of Statistical Planning and Inference, vol.141, issue.9, pp.3047-3054, 2011.
DOI : 10.1016/j.jspi.2011.03.026

E. Zorita, V. Storch, and H. , The Analog Method as a Simple Statistical Downscaling Technique: Comparison with More Complicated Methods, Journal of Climate, vol.12, issue.8, pp.2474-2489, 1999.
DOI : 10.1175/1520-0442(1999)012<2474:TAMAAS>2.0.CO;2