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Hemp, Andreas ; Hemp, Judith:
Weather or not - Global climate databases: Reliable on tropical mountains?
In: PLoS One.
Bd. 19
(2024)
Heft 3
.
- e0299363.
ISSN 1932-6203
DOI: https://doi.org/10.1371/journal.pone.0299363
Abstract
Global, spatially interpolated climate datasets such as WorldClim and CHELSA, widely used in research, are based on station data, which are rare in tropical mountains. However, such biodiversity hotspots are of high ecological interest and require accurate data. Therefore, the quality of such gridded datasets needs to be assessed. This poses a kind of dilemma, as proving the reliability of these potentially weakly modelled data is usually not possible due to the lack of stations. Using a unique climate dataset with 170 stations, mainly from the montane and alpine zones of sixteen mountains in Tanzania including Kilimanjaro, we show that the accuracy of such datasets is very poor. Not only is the maximum amount of mean annual precipitation drastically underestimated (partly more than 50%), but also the elevation of the precipitation maximum deviates up to 850m. Our results show that, at least in tropical regions, they should be used with greater caution than before.
Weitere Angaben
| Publikationsform: | Artikel in einer Zeitschrift |
|---|---|
| Begutachteter Beitrag: | Ja |
| Institutionen der Universität: | Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Biologie > Lehrstuhl Pflanzensystematik Forschungseinrichtungen > Zentrale wissenschaftliche Einrichtungen > Bayreuther Zentrum für Ökologie und Umweltforschung - BayCEER |
| Titel an der UBT entstanden: | Ja |
| Themengebiete aus DDC: | 500 Naturwissenschaften und Mathematik > 550 Geowissenschaften, Geologie 500 Naturwissenschaften und Mathematik > 580 Pflanzen (Botanik) |
| Eingestellt am: | 27 Mai 2026 06:19 |
| Letzte Änderung: | 27 Mai 2026 06:19 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/97722 |