Intercomparison of statistical and dynamical downscaling models under the EURO- and MED-CORDEX initiative framework: present climate evaluations
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- 作者：Pradeebane Vaittinada Ayar ; Mathieu Vrac ; Sophie Bastin ; Julie Carreau…
- 关键词：Statistical downscaling ; Dynamical downscaling ; CORDEX ; Precipitation ; Intercomparison
- 刊名：Climate Dynamics
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：46
- 期：3-4
- 页码：1301-1329
- 全文大小：9,018 KB
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Mathieu Vrac (1)
Sophie Bastin (2) (3) (4)
Julie Carreau (5)
Michel Déqué (6)
Clemente Gallardo (7)
1. Laboratoire des Sciences du Climat et de l’Environnement (LSCE-IPSL), CNRS/CEA/UVSQ, Centre d’Etudes de Saclay, Orme des Merisiers, 91191, Gif-sur-Yvette, France
2. Université Versailles St-Quentin, Versailles, France
3. Sorbonne Universités, UPMC Univ. Paris 06, Paris, France
4. CNRS/INSU, LATMOS-IPSL, 11 bd d’Alembert, 78280, Guyancourt, France
5. HydroSciences Montpellier (HSM), CNRS/IRD/UM1/UM2, Place Eugène Bataillon, 34095, Montpellier, France
6. Météo-France, Centre National de Recherches Météorologiques, 42 Av. Coriolis, 31057, Toulouse, France
7. Instituto de Ciencias Ambientales, Universidad de Castilla-La Mancha, Toledo, Spain - 刊物类别：Earth and Environmental Science
- 刊物主题：Earth sciences
Geophysics and Geodesy
Meteorology and Climatology
Oceanography - 出版者：Springer Berlin / Heidelberg
- ISSN：1432-0894
文摘
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 0.44° 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. Keywords Statistical downscaling Dynamical downscaling CORDEX Precipitation Intercomparison