Stochastic weather generators: an overview of weather type models

A recurrent issue encountered in environmental, ecological or agricultural impact studies in which climate is an important driving force is to provide fast and realistic simulations of atmospheric variables such as temperature, precipitation and wind at a few specific locations, at daily or hourly temporal scales. Spatio-temporal dynamics and correlation structures among the variables of interest, as well as weather persistence and natural variability have to be reproduced accurately in a distributional sense. This quest leads to a large variety of so-called stochastic weather generators (WGs) in the literature. Here, we provide an up-to-date overview of weather type WG models.Weather types classically represent daily characteristics of the relevant atmospheric information at hand. There are many ways to build such weather states, either hidden or observed, and to infer their properties. This overview should help statisticians as well as meteorologists and climate product users to understand the probabilistic concepts and models behind weather type WGs, and to identify their advantages and limits. Resume : Pour realiser des etudes d’impact dans lesquelles le climat est un parametre d’entree important, un probleme frequemment rencontre consiste a produire des series temporelles de variables climatiques telles que temperatures, precipitation, vent ou humidite relative, en plusieurs sites simultanement, au pas de temps journalier et parfois horaire. Ces series doivent etre faciles a generer. Elles doivent aussi etre realistes en ce sens que les distributions des statistiques liees a la dynamique spatio-temporelle, telles que les correlation entre variables, la persistence temporelle et les differentes sources de variabilite doivent etre correctement reproduites. De nombreux generateurs stochastiques de conditions meteorologiques ont ete proposes dans ce but. Dans cet article, nous proposons de passer en revue la classe particuliere des generateurs stochastiques a base de types de temps. En regle generale, un type de temps est une caracterisation grossiere des conditions atmospheriques journalieres. Il existe de nombreuses facons de definir les types de temps, qu’ils soient observes ou caches dans une structure latente, et d’en inferer leur proprietes. Cette revue a pour objet d’aider les statisticiens, les scientifiques du climat et les utilisateurs de produits climatiques a apprehender les concepts et modeles probabilistes utilises dans les generateurs stochastiques de conditions meteorologiques et d’en cerner les avantages et leurs limites.

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