Preprints
https://doi.org/10.5194/essd-2021-186
https://doi.org/10.5194/essd-2021-186

  03 Jun 2021

03 Jun 2021

Review status: this preprint is currently under review for the journal ESSD.

A 1-km global dataset of historical (1979–2017) and future (2020–2100) Köppen-Geiger climate classification and bioclimatic variables

Diyang Cui, Shunlin Liang, Dongdong Wang, and Zheng Liu Diyang Cui et al.
  • Department of Geographical Sciences, University of Maryland, College Park, 20740, USA

Abstract. The Köppen-Geiger classification scheme provides an effective and ecologically meaningful way to characterize climatic conditions and has been widely applied in climate change studies. Significant changes in Köppen climates have been observed and projected in the recent two centuries. Current accuracy, temporal coverage, spatial and temporal resolution of historical and future climate classification maps cannot sufficiently fulfil the current needs of climate change research. Comprehensive assessment of climate change impacts requires a more accurate depiction of fine-grained climatic conditions and continuous long-term time coverage. Here, we present a series of improved 1-km Köppen-Geiger climate classification maps for ten historical periods in 1979–2017 and four future periods in 2020–2099 under RCP2.6, 4.5, 6.0, and 8.5. The historical maps are derived from multiple downscaled observational datasets and the future maps are derived from an ensemble of bias-corrected downscaled CMIP5 projections. In addition to climate classification maps, we calculate 12 bioclimatic variables at 1-km resolution, providing detailed descriptions of annual averages, seasonality, and stressful conditions of climates. The new maps offer higher classification accuracy and demonstrate the ability to capture recent and future projected changes in spatial distributions of climate zones. On regional and continental scales, the new maps show accurate depictions of topographic features and correspond closely with vegetation distributions. We also provide a heuristic application example to detect long-term global-scale area changes of climate zones. This high-resolution dataset of Köppen-Geiger climate classification and bioclimatic variables can be used in conjunction with species distribution models to promote biodiversity conservation and to analyze and identify recent and future interannual or interdecadal changes in climate zones on a global or regional scale. The dataset referred to as KGClim, is publicly available at http://doi.org/10.5281/zenodo.4546140 for historical climate and http://doi.org/10.5281/zenodo.4542076 for future climate.

Diyang Cui et al.

Status: open (until 29 Jul 2021)

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Diyang Cui et al.

Data sets

KGClim historical: A 1-km global dataset of historical (1979-2017) Köppen-Geiger climate classification and bioclimatic variables Cui, Diyang; Liang, Shunlin; Wang, Dongdong; Liu, Zheng http://doi.org/10.5281/zenodo.4546140

KGClim future: A 1-km global dataset of future (2020-2100) Köppen-Geiger climate classification and bioclimatic variables Cui, Diyang; Liang, Shunlin; Wang, Dongdong; Liu, Zheng http://doi.org/10.5281/zenodo.4542076

Diyang Cui et al.

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Short summary
Large portions of the Earth's surface are expected to experience changes in climatic conditions. The rearrangement of climate distributions can lead to serious impacts on ecological and social systems. Major climate zones are distributed in a predictable pattern and are largely defined following the Köppen climate classification. This creates an urgent need to compile a series of Köppen climate classification maps with finer spatial and temporal resolutions and improved accuracy.