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Dryad

Regionalized dynamic climate series for ecological climate impact research in modern controlled environment facilities

Cite this dataset

Jákli, Bálint et al. (2021). Regionalized dynamic climate series for ecological climate impact research in modern controlled environment facilities [Dataset]. Dryad. https://doi.org/10.5061/dryad.h18931zn5

Abstract

Modern controlled environment facilities (CEFs) enable the simulation of dynamic microclimates in controlled ecological experiments through their technical ability to precisely control multiple environmental parameters. However, few CEF studies exploit the technical possibilities of their facilities, as climate change treatments are frequently applied by static manipulation of an inadequate number of climate change drivers, ignoring intra-annual variability and co-variation of multiple meteorological variables. We present so called Test Reference Years (TRY) that consist of typical annual cycles of temperature, relative humidity, air pressure, global radiation, photosynthetically active photon flux density, tropospheric ozone concentration and CO2. The TRYs represent possible annual cycles of a reference period (1987-2016) and the two contrasting climate scenarios RCP2.6 and RCP8.5.

Methods

Based on the EURO-CORDEX and ReKliEs-DE model ensembles, typical annual courses of daily resolved climatologies for the reference period and the RCP scenarios were calculated from multi-model means of temperature (ta), relative humidity (rh), global radiation (Rg), air pressure (P) and ground-level ozone and complemented by CO2. To account for intra-annual variation and the co-variability of multiple climate variables, daily values were substituted by hourly resolved data resampled from the historical record of a climate station situated in a forested region of the German Spessart mountains (Jossgrund-Lettgenbrunn, Germany, 497 m asl, 50°09'52.0"N 9°23'58.0"E).

Usage notes

Files: TRY_PC.csv, TRY_RCP26.csv, TRY_RCP85.csv; TRY_README.txt

Funding

German Federal Environment Agency, Award: 3717512570