Abstract
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.
Highlights
Background & SummaryGlobal environmental questions that invoke climate as a driver of a specific phenomenon require spatially and temporally consistent datasets
While time varying and high spatial resolution (o 5-km) climate datasets have been developed at national and continental scales[6,7,8], and highspatial resolution climate normals have been developed for the globe[9,10,11], we are unaware of time varying, high-resolution climate data that covers all global land surfaces and encompasses many of the essential surface climate variables
While WorldClim provides a complete set of variables to assess long-term monthly normals for several climate variables, it does not lend itself to temporal analysis that may be important for linking climate variability and climate impacts in ecological, agricultural, and hydrological systems
Summary
Background & SummaryGlobal environmental questions that invoke climate as a driver of a specific phenomenon require spatially and temporally consistent datasets. This paper outlines the development of a global monthly high-resolution climate dataset from 1958–2015, referred to as TerraClimate, that includes the requisite variables for calculating energybased reference potential evapotranspiration and a water balance model.
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