High‐resolution gridded climate data for Europe based on bias‐corrected EURO‐CORDEX: The ECLIPS dataset
Abstract Climate is an important driver of many ecological and social processes; the availability of high‐resolution climate data is thus one of the key presumptions for knowledge‐based decisions. We created a new climate dataset for Europe referred to as ECLIPS (European CLimate Index ProjectionS),...
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oai:doaj.org-article:18db8c58029647be9e9928f05894cad22021-11-23T13:44:37ZHigh‐resolution gridded climate data for Europe based on bias‐corrected EURO‐CORDEX: The ECLIPS dataset2049-606010.1002/gdj3.110https://doaj.org/article/18db8c58029647be9e9928f05894cad22021-11-01T00:00:00Zhttps://doi.org/10.1002/gdj3.110https://doaj.org/toc/2049-6060Abstract Climate is an important driver of many ecological and social processes; the availability of high‐resolution climate data is thus one of the key presumptions for knowledge‐based decisions. We created a new climate dataset for Europe referred to as ECLIPS (European CLimate Index ProjectionS), which contains gridded data for 80 annual, seasonal and monthly climate variables for two past (1961–1990 and 1991–2010) and five future (2011–2020, 2021–2140, 2041–2060, 2061–2080 and 2081–2100) periods. The future data are based on five regional climate models (RCMs) driven by two greenhouse gas concentration scenarios, RCP 4.5 and RCP 8.5. Two ECLIPS versions were developed: ECLIPS 1.1 with a spatial resolution of 0.11° × 0.11°, which is the resolution of the underlying RCMs, and ECLIPS 2.0 downscaled to the resolution of 30 arcsec employing the delta approach. Both ECLIPS versions were tested against independent station data from the European Climate Assessment (ECA) dataset. Correlations of the ECA and ECLIPS 1.1 data ranged from 0.63 to 0.78, depending on the tested variable. The correlations increased to 0.78–0.93 for ECLIPS 2.0, suggesting substantial improvement of the match with station data due to the downscaling. A large number of climate projections, periods and indices as well as the availability of these data at two different spatial resolutions can support diverse studies across a range of disciplines and thus extend our understanding of climate‐sensitive dynamics of many social and ecological systems.Debojyoti ChakrabortyLaura DoborAnita ZollesTomáš HlásnySilvio SchuelerWileyarticlebiosphereclimateweatherMeteorology. ClimatologyQC851-999GeologyQE1-996.5ENGeoscience Data Journal, Vol 8, Iss 2, Pp 121-131 (2021) |
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biosphere climate weather Meteorology. Climatology QC851-999 Geology QE1-996.5 Debojyoti Chakraborty Laura Dobor Anita Zolles Tomáš Hlásny Silvio Schueler High‐resolution gridded climate data for Europe based on bias‐corrected EURO‐CORDEX: The ECLIPS dataset |
description |
Abstract Climate is an important driver of many ecological and social processes; the availability of high‐resolution climate data is thus one of the key presumptions for knowledge‐based decisions. We created a new climate dataset for Europe referred to as ECLIPS (European CLimate Index ProjectionS), which contains gridded data for 80 annual, seasonal and monthly climate variables for two past (1961–1990 and 1991–2010) and five future (2011–2020, 2021–2140, 2041–2060, 2061–2080 and 2081–2100) periods. The future data are based on five regional climate models (RCMs) driven by two greenhouse gas concentration scenarios, RCP 4.5 and RCP 8.5. Two ECLIPS versions were developed: ECLIPS 1.1 with a spatial resolution of 0.11° × 0.11°, which is the resolution of the underlying RCMs, and ECLIPS 2.0 downscaled to the resolution of 30 arcsec employing the delta approach. Both ECLIPS versions were tested against independent station data from the European Climate Assessment (ECA) dataset. Correlations of the ECA and ECLIPS 1.1 data ranged from 0.63 to 0.78, depending on the tested variable. The correlations increased to 0.78–0.93 for ECLIPS 2.0, suggesting substantial improvement of the match with station data due to the downscaling. A large number of climate projections, periods and indices as well as the availability of these data at two different spatial resolutions can support diverse studies across a range of disciplines and thus extend our understanding of climate‐sensitive dynamics of many social and ecological systems. |
format |
article |
author |
Debojyoti Chakraborty Laura Dobor Anita Zolles Tomáš Hlásny Silvio Schueler |
author_facet |
Debojyoti Chakraborty Laura Dobor Anita Zolles Tomáš Hlásny Silvio Schueler |
author_sort |
Debojyoti Chakraborty |
title |
High‐resolution gridded climate data for Europe based on bias‐corrected EURO‐CORDEX: The ECLIPS dataset |
title_short |
High‐resolution gridded climate data for Europe based on bias‐corrected EURO‐CORDEX: The ECLIPS dataset |
title_full |
High‐resolution gridded climate data for Europe based on bias‐corrected EURO‐CORDEX: The ECLIPS dataset |
title_fullStr |
High‐resolution gridded climate data for Europe based on bias‐corrected EURO‐CORDEX: The ECLIPS dataset |
title_full_unstemmed |
High‐resolution gridded climate data for Europe based on bias‐corrected EURO‐CORDEX: The ECLIPS dataset |
title_sort |
high‐resolution gridded climate data for europe based on bias‐corrected euro‐cordex: the eclips dataset |
publisher |
Wiley |
publishDate |
2021 |
url |
https://doaj.org/article/18db8c58029647be9e9928f05894cad2 |
work_keys_str_mv |
AT debojyotichakraborty highresolutiongriddedclimatedataforeuropebasedonbiascorrectedeurocordextheeclipsdataset AT lauradobor highresolutiongriddedclimatedataforeuropebasedonbiascorrectedeurocordextheeclipsdataset AT anitazolles highresolutiongriddedclimatedataforeuropebasedonbiascorrectedeurocordextheeclipsdataset AT tomashlasny highresolutiongriddedclimatedataforeuropebasedonbiascorrectedeurocordextheeclipsdataset AT silvioschueler highresolutiongriddedclimatedataforeuropebasedonbiascorrectedeurocordextheeclipsdataset |
_version_ |
1718416689371021312 |