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High-resolution monthly precipitation and temperature time series from 2006 to 2100.

ABSTRACT: Predicting future climatic conditions at high spatial resolution is essential for many applications and impact studies in science. Here, we present monthly time series data on precipitation, minimum- and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation at ~5?km spatial resolution globally for the years 2006-2100. We validated the performance of the downscaling algorithm by comparing model output with the observed climate of the historical period 1950-1969.

SUBMITTER: Karger DN

PROVIDER: S-EPMC7378208 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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High-resolution monthly precipitation and temperature time series from 2006 to 2100.

Karger Dirk Nikolaus DN Schmatz Dirk R DR Dettling Gabriel G Zimmermann Niklaus E NE

Scientific data 20200723 1

Predicting future climatic conditions at high spatial resolution is essential for many applications and impact studies in science. Here, we present monthly time series data on precipitation, minimum- and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation at ~5 km spatial resolution globally ...[more]

PMID: 32703947

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