Climate-EU: Scale-free climate normals, historical time series, and future projections for Europe. – B4EST
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Climate-EU: Scale-free climate normals, historical time series, and future projections for Europe.

Marchi, Castellanos-Acuña, Hamann, Wang, Ray, Menzel

Newly published research in the journal Nature Scientific Data, describes how new climate data for Europe are downscaled to high resolution and accessed by users in a useful format for further analysis.

The data repository contains the scripts and the databases required to provide scale-free (i.e. for a specified latitude and longitude) monthly seasonal and annual user specified climate data from 1901 to 2019.

The repository additionally includes gridded climate projections (CMIP5-RCP scenarios) for 30-year climate normal periods (climate baseline [1961-1990]; 2020s [2010-2039], 2050s [2040-69] and 2080s [2070-2099]) for Europe from multiple published GCM and RCM sources.

The quality of ClimateEU estimates was evaluated against weather station data for a representative subset of climate variables. Dynamic environmental lapse rate algorithms employed by the software generate scale free climate variables for specific locations made a 10 to 50% improvement in accuracy compared to other gridded data sets.

ClimateEU was initially developed by two of the authors (Hamann and Wang). Ray and Marchi wished to use ClimateEU to access past and present climate data and future projections for their work in the B4EST project.

In B4EST ClimateEU data are used with tree trait data (e.g. relating to tree height and survival) from common garden provenance  and progeny trials. 

This enables calculation of the genetic adaptation and plasticity components of forest reproductive material under varying environmental conditions. The calculations will be used to understanding the extent to which it is possible to control the tolerance of trees to climatic and biological change through tree breeding.

The database and downscaling tool produces 48 monthly variables (monthly precipitation, minimum, maximum, and average temperature), as well as 36 derived bioclimatic variables useful in ecology forestry and agriculture.

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