Very high resolution interpolated climate surfaces for global land areas ...
(Uploaded by Plazi for the Bat Literature Project) We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum,...
| Main Authors: | , , , , |
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| Format: | Article in Journal/Newspaper |
| Language: | unknown |
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Zenodo
2005
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5281/zenodo.13451146 https://zenodo.org/doi/10.5281/zenodo.13451146 |
| Summary: | (Uploaded by Plazi for the Bat Literature Project) We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous ... |
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