High-resolution downscaled CMIP5 projections dataset of essential surface climate variables over  Europe coherent with ERA5-Land reanalyses for climate change impact assessments

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Authors

Thomas Noël , Harilaos Loukos , Dimitri Defrance , Mathieu Vrac , Guillaume Levavasseur

Abstract

A high-resolution climate projections dataset is obtained by statistically downscaling climate projections from the CMIP5 experiment using the ERA5-Land reanalyses from the Copernicus Climate Change service. The dataset is over Europe, has a spatial resolution of 0.10° x 0.10°, comprises 21 climate models and includes 5 surface daily variables: air temperature (mean, minimum, and maximum), precipitation, and mean near-surface wind speed. Two greenhouse gas emissions scenarios are available: one with mitigation policy (RCP4.5) and one without mitigation (RCP8.5). The downscaling method is a Quantile mapping method (QM) called the Cumulative Distribution Function transform (CDF-t) method that was first used for wind values and is now referenced in dozens of peer-reviewed publications. The data processing includes quality control of meta data according to the climate modeling community standards and value checking for outlier detection.

DOI

https://doi.org/10.31223/X5030F

Subjects

Engineering, Life Sciences, Physical Sciences and Mathematics

Keywords

climate change, CMIP5, downscaling, projections, High-resolution, adaptation, ERA5-Land, impact modelling

Dates

Published: 2020-11-27 07:26

Last Updated: 2020-11-27 15:26

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
Data available on demand under commercial licence

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