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Spatial partitioning of terrestrial precipitation reveals varying dataset agreement across different environments
Publikationstyp
Journal Article
Date Issued
2024-04-23
Sprache
English
Author(s)
Pradhan, Rajani Kumar
Pratap, Shailendra
Thomson, Johanna Ruth
Paschalis, Athanasios
Nikolopoulos, Efthymios
Volume
5
Issue
1
Article Number
217
Citation
Communications Earth and Environment 5 (1): 217 (2024)
Publisher DOI
Scopus ID
Publisher
Springer Nature
The study of the water cycle at planetary scale is crucial for our understanding of large-scale climatic processes. However, very little is known about how terrestrial precipitation is distributed across different environments. In this study, we address this gap by employing a 17-dataset ensemble to provide, for the first time, precipitation estimates over a suite of land cover types, biomes, elevation zones, and precipitation intensity classes. We estimate annual terrestrial precipitation at approximately 114,000 ± 9400 km<sup>3</sup>, with about 70% falling over tropical, subtropical and temperate regions. Our results highlight substantial inconsistencies, mainly, over the arid and the mountainous areas. To quantify the overall discrepancies, we utilize the concept of dataset agreement and then explore the pairwise relationships among the datasets in terms of “genealogy”, concurrency, and distance. The resulting uncertainty-based partitioning demonstrates how precipitation is distributed over a wide range of environments and improves our understanding on how their conditions influence observational fidelity.
DDC Class
600: Technology