DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D3, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp370 - The Metropolitan City of Turin (CMTo, Italy)
View DatasetDISTENDER;Foundation for Climate Researh
Description
Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).More details about the domains, the provided variable, levels and periods are provided in the README file.
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Metrics Over Time
Publication Details
Subfield
Management Science and Operations Research
Field
Decision Sciences
Domain
Social Sciences
Confidence Score
43%
Source
Scholar Data Model
Keywords
DISTENDERClimateDownscalingStatisticalScenarios