TY - JOUR
T1 - TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015
AU - Abatzoglou, John T.
AU - Dobrowski, Solomon Z.
AU - Parks, Sean A.
AU - Hegewisch, Katherine C.
N1 - Publisher Copyright:
©The Author(s) 2018.
PY - 2018/1/9
Y1 - 2018/1/9
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85040374705&partnerID=8YFLogxK
U2 - 10.1038/sdata.2017.191
DO - 10.1038/sdata.2017.191
M3 - Article
C2 - 29313841
AN - SCOPUS:85040374705
SN - 2052-4463
VL - 5
JO - Scientific data
JF - Scientific data
M1 - 170191
ER -