A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables
<p>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 the Köppen climates have been observed and projected in the last 2 centuries. Curre...
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/18572d8ed30e4d1cbb444968c37c6bd2 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:18572d8ed30e4d1cbb444968c37c6bd2 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:18572d8ed30e4d1cbb444968c37c6bd22021-11-04T08:53:11ZA 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables10.5194/essd-13-5087-20211866-35081866-3516https://doaj.org/article/18572d8ed30e4d1cbb444968c37c6bd22021-11-01T00:00:00Zhttps://essd.copernicus.org/articles/13/5087/2021/essd-13-5087-2021.pdfhttps://doaj.org/toc/1866-3508https://doaj.org/toc/1866-3516<p>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 the Köppen climates have been observed and projected in the last 2 centuries. Current accuracy, temporal coverage and spatial and temporal resolution of historical and future climate classification maps cannot sufficiently fulfill 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 six historical periods in 1979–2013 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 than existing climate map products 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 the 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 via <span class="uri">http://glass.umd.edu/KGClim</span> (Cui et al., 2021d) and can also be downloaded at <a href="https://doi.org/10.5281/zenodo.5347837">https://doi.org/10.5281/zenodo.5347837</a> (Cui et al., 2021c) for historical climate and <a href="https://doi.org/10.5281/zenodo.4542076">https://doi.org/10.5281/zenodo.4542076</a> (Cui et al., 2021b) for future climate.</p>D. CuiS. LiangD. WangZ. LiuCopernicus PublicationsarticleEnvironmental sciencesGE1-350GeologyQE1-996.5ENEarth System Science Data, Vol 13, Pp 5087-5114 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
| spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 D. Cui S. Liang D. Wang Z. Liu A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables |
| description |
<p>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 the
Köppen climates have been observed and projected in the last 2
centuries. Current accuracy, temporal coverage and spatial and temporal
resolution of historical and future climate classification maps cannot
sufficiently fulfill 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 six historical periods in 1979–2013 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 than existing climate map products
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 the 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 via <span class="uri">http://glass.umd.edu/KGClim</span> (Cui et al., 2021d) and can also be downloaded at <a href="https://doi.org/10.5281/zenodo.5347837">https://doi.org/10.5281/zenodo.5347837</a> (Cui et al., 2021c) for historical climate and <a href="https://doi.org/10.5281/zenodo.4542076">https://doi.org/10.5281/zenodo.4542076</a> (Cui et al., 2021b) for future climate.</p> |
| format |
article |
| author |
D. Cui S. Liang D. Wang Z. Liu |
| author_facet |
D. Cui S. Liang D. Wang Z. Liu |
| author_sort |
D. Cui |
| title |
A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables |
| title_short |
A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables |
| title_full |
A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables |
| title_fullStr |
A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables |
| title_full_unstemmed |
A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables |
| title_sort |
1 km global dataset of historical (1979–2013) and future (2020–2100) köppen–geiger climate classification and bioclimatic variables |
| publisher |
Copernicus Publications |
| publishDate |
2021 |
| url |
https://doaj.org/article/18572d8ed30e4d1cbb444968c37c6bd2 |
| work_keys_str_mv |
AT dcui a1thinspkmglobaldatasetofhistorical19792013andfuture20202100koppengeigerclimateclassificationandbioclimaticvariables AT sliang a1thinspkmglobaldatasetofhistorical19792013andfuture20202100koppengeigerclimateclassificationandbioclimaticvariables AT dwang a1thinspkmglobaldatasetofhistorical19792013andfuture20202100koppengeigerclimateclassificationandbioclimaticvariables AT zliu a1thinspkmglobaldatasetofhistorical19792013andfuture20202100koppengeigerclimateclassificationandbioclimaticvariables AT dcui 1thinspkmglobaldatasetofhistorical19792013andfuture20202100koppengeigerclimateclassificationandbioclimaticvariables AT sliang 1thinspkmglobaldatasetofhistorical19792013andfuture20202100koppengeigerclimateclassificationandbioclimaticvariables AT dwang 1thinspkmglobaldatasetofhistorical19792013andfuture20202100koppengeigerclimateclassificationandbioclimaticvariables AT zliu 1thinspkmglobaldatasetofhistorical19792013andfuture20202100koppengeigerclimateclassificationandbioclimaticvariables |
| _version_ |
1718444945360027648 |