Precipitation Data Representativeness Worldwide

Código

I-EBHE0114

Autores

Mijael Rodrigo Vargas Godoy, Yannis Markonis, Johanna Ruth Thomson, André S. Ballarin, Saverio Perri, Annalisa Molini, Chiyuan Miao, Qiaohong Sun, Martin Hanel, Simon Michael Papalexiou

Tema

WG 1.02: Decomposing Complexity

Resumo

Precipitation is a critical component of the Earth's hydrological cycle and plays a crucial role in shaping climate patterns and ecosystem dynamics. However, in the face of the seemingly evergrowing number of available datasets, which one should we rely upon? This question has driven numerous dataset evaluation and intercomparison studies worldwide, recently exploring multi-source approaches to enhance the estimates. Here, we show how to assess multiple datasets and define an evaluation reference benchmark in order to identify the dataset that best represents the ensemble over different spatial domains, including countries, IPCC assessment report reference regions, major world river basins, land cover types, elevation zones, biome categories, and Köppen-Geiger climate classes. We repeatedly found GPM IMERG v07 to emerge as the dataset representative over multiple domains. Furthermore, the representativeness of a dataset appears to be predominantly determined by the characteristics of the spatial domain rather than its scale. We discuss the implications of our findings and provide recommendations for dataset selection tailored to specific needs. This work underscores the importance of dataset selection in ensuring accurate analysis and offers a framework for selecting the appropriate precipitation dataset for global research endeavors.