Publications des scientifiques de l'IRD

Ayar P. V., Vrac M., Bastin S., Carreau Julie, Deque M., Gallardo C. (2016). Intercomparison of statistical and dynamical downscaling models under the EURO- and MED-CORDEX initiative framework : present climate evaluations. Climate Dynamics, 46 (3-4), 1301-1329. ISSN 0930-7575.

Titre du document
Intercomparison of statistical and dynamical downscaling models under the EURO- and MED-CORDEX initiative framework : present climate evaluations
Année de publication
2016
Type de document
Article référencé dans le Web of Science WOS:000370030900037
Auteurs
Ayar P. V., Vrac M., Bastin S., Carreau Julie, Deque M., Gallardo C.
Source
Climate Dynamics, 2016, 46 (3-4), 1301-1329 ISSN 0930-7575
Given the coarse spatial resolution of General Circulation Models, finer scale projections of variables affected by local-scale processes such as precipitation are often needed to drive impacts models, for example in hydrology or ecology among other fields. This need for high-resolution data leads to apply projection techniques called downscaling. Downscaling can be performed according to two approaches: dynamical and statistical models. The latter approach is constituted by various statistical families conceptually different. If several studies have made some intercomparisons of existing downscaling models, none of them included all those families and approaches in a manner that all the models are equally considered. To this end, the present study conducts an intercomparison exercise under the EURO- and MED-CORDEX initiative hindcast framework. Six Statistical Downscaling Models (SDMs) and five Regional Climate Models (RCMs) are compared in terms of precipitation outputs. The downscaled simulations are driven by the ERAinterim reanalyses over the 1989-2008 period over a common area at 0.44A degrees of resolution. The 11 models are evaluated according to four aspects of the precipitation: occurrence, intensity, as well as spatial and temporal properties. For each aspect, one or several indicators are computed to discriminate the models. The results indicate that marginal properties of rain occurrence and intensity are better modelled by stochastic and resampling-based SDMs, while spatial and temporal variability are better modelled by RCMs and resampling-based SDM. These general conclusions have to be considered with caution because they rely on the chosen indicators and could change when considering other specific criteria. The indicators suit specific purpose and therefore the model evaluation results depend on the end-users point of view and how they intend to use with model outputs. Nevertheless, building on previous intercomparison exercises, this study provides a consistent intercomparison framework, including both SDMs and RCMs, which is designed to be flexible, i.e., other models and indicators can easily be added. More generally, this framework provides a tool to select the downscaling model to be used according to the statistical properties of the local-scale climate data to drive properly specific impact models.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Sciences du milieu [021] ; Hydrologie [062]
Descripteurs
ZONE MEDITERRANEENNE
Description Géographique
EUROPE ; MEDITERRANEE
Localisation
Fonds IRD [F B010066201]
Identifiant IRD
fdi:010066201
Contact