TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015
We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim data...
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| Vydané v: | Scientific data Ročník 5; číslo 1; s. 170191 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
London
Nature Publishing Group UK
09.01.2018
Nature Publishing Group |
| Predmet: | |
| ISSN: | 2052-4463, 2052-4463 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.
Design Type(s)
data integration objective • observation design • source-based data analysis objective
Measurement Type(s)
climate
Technology Type(s)
digital curation
Factor Type(s)
temporal_interval
Sample Characteristic(s)
Earth • temperature of air • pressure of air • hydrological precipitation process • atmospheric wind • porosity of soil
Machine-accessible metadata file describing the reported data
(ISA-Tab format) |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 J.T.A. conceived of the development of the dataset and the development of the code, validation efforts, and manuscript writing. S.Z.D. helped conceive the development of the dataset and writing of the manuscript. S.A.P. helped conceive the development of the dataset and writing of the manuscript. K.C.H. aided in the coding and data processing issues. |
| ISSN: | 2052-4463 2052-4463 |
| DOI: | 10.1038/sdata.2017.191 |