A high-resolution daily climate time series for Germany (1981-2100).

IF 1.9 Q3 MULTIDISCIPLINARY SCIENCES
Data in Brief Pub Date : 2026-08-30 eCollection Date: 2026-08-01 DOI:10.1016/j.dib.2026.113218
Kilian Hochholzer, Christina Dollinger, Marc Grünig, Rupert Seidl, Werner Rammer
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引用次数: 0

Abstract

The presented dataset is a high-resolution (1 × 1 km) daily climate time series for Germany covering the period 1981-2100 across a historic and nine CMIP5 climate change scenarios. The dataset is based on EURO-CORDEX projections from three Earth system models (ICHEC-EC-EARTH, MPI-M-ESM-LR, and NCC-NorESM1-M) under three representative concentration pathways (RCP 2.6, 4.5, and 8.5) and was bias-corrected against observational data from the German Weather Service (DWD). To reduce data volume in climate impact studies, the 355,944 1 × 1 km grid cells were aggregated into 10,000 spatial clusters based on multi-annual averages of five key variables for plant growth, specifically, temperature (minimum and maximum), precipitation, global radiation and vapor pressure deficit. The resulting dataset provides for each cluster nine daily climate time series of said variables until the end of the 21st century. The dataset is stored in SQLite databases and accompanied by a map relating representative climate clusters to the 1 km grid cells. To our knowledge, this is the first Germany-wide dataset that provides ready to use daily climate projections until 2100 at 1 km resolution with a climate-cluster representation that reduces computational demand, while keeping climatic variability.

德国高分辨率日气候时间序列(1981-2100)。
本文的数据集是德国的高分辨率(1 × 1 km)日气候时间序列,涵盖1981-2100年的一个历史情景和9个CMIP5气候变化情景。该数据集基于三个地球系统模式(ICHEC-EC-EARTH、MPI-M-ESM-LR和NCC-NorESM1-M)在三个代表性浓度路径(RCP 2.6、4.5和8.5)下的EURO-CORDEX预估,并根据德国气象局(DWD)的观测数据进行了偏差校正。为了减少气候影响研究的数据量,基于植物生长的五个关键变量(温度(最低和最高)、降水、全球辐射和蒸汽压亏缺)的多年平均值,将355,944个1 × 1 km网格单元聚合成10,000个空间集群。所得数据集为每一组提供了上述变量直至21世纪末的9个每日气候时间序列。该数据集存储在SQLite数据库中,并附有一张将代表性气候集群与1公里网格单元相关联的地图。据我们所知,这是第一个德国范围内的数据集,它提供了准备使用的每日气候预测,直到2100年,以1公里分辨率,气候集群表示,减少了计算需求,同时保持了气候的可变性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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