Selecting and correcting RCM models ensemble: a case study for the evaluation of thermal discomfort for the city of Prato
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s11069-021-04645-5.pdf
Reference47 articles.
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2. Boeand J, Terray L, Habets F, Martin E (2007) Statistical and dynamical downscaling of the Seine basin climate for hydro-meteorological studies. Int J Climatol 27(12):16431655
3. Caldwell P, Bretherton C, Zelinka M, Klein S, Santer B, Sanderson B (2014) Statistical significance of climate sensitivity predictors obtained by data mining. Geophys Res Lett 41:18031808. https://doi.org/10.1002/2014GL059205
4. Cannon AJ (2014) Selecting GCM scenarios that span the range of changes in a multimodel ensemble: application to CMIP5 climate extremes indices. J Clim 28:12601267. https://doi.org/10.1175/JCLI-D-14-00636.1
5. Cannon AJ (2015) Selecting GCM scenarios that span the range of changes in a multimodel ensemble: application to CMIP5 climate extremes indices. J Clim 28:12601267. https://doi.org/10.1175/JCLI-D-14-00636.1
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