High-resolution monthly precipitation and temperature time series from 2006 to 2100
| Autor: | Niklaus E. Zimmermann, Dirk Nikolaus Karger, Dirk R. Schmatz, Gabriel Dettling |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Data Descriptor 010504 meteorology & atmospheric sciences Atmospheric circulation 0208 environmental biotechnology High resolution 02 engineering and technology Library and Information Sciences 01 natural sciences Education Atmospheric science Climate change Precipitation Time series lcsh:Science Image resolution 0105 earth and related environmental sciences Series (mathematics) 020801 environmental engineering Computer Science Applications Model output statistics Climatology Environmental science lcsh:Q Statistics Probability and Uncertainty Information Systems Downscaling |
| Zdroj: | Scientific Data Scientific Data, Vol 7, Iss 1, Pp 1-10 (2020) |
| ISSN: | 2052-4463 |
| DOI: | 10.1038/s41597-020-00587-y |
| Popis: | 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. Measurement(s) hydrological precipitation process • temperature Technology Type(s) computational modeling technique Factor Type(s) monthly time series data • year of data collection Sample Characteristic - Environment climate system Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12593735 |
| Databáze: | OpenAIRE |
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