article · Hydrological Sciences Journal
This research evaluates how nine high-resolution global precipitation products perform in areas marked by complex topography and extreme rainfall, focusing on Debundscha alongside Idenau and Limbe. Using both qualitative and quantitative error metrics, the assessment found that while most datasets successfully tracked the annual rainfall cycle and demonstrated acceptable Pearson correlation scores, their overall performance was poor according to metrics such as Kling-Gupta efficiency, root mean squared error, and percent bias. The datasets also showed a limited capacity to identify drought events in these very wet environments. Among all evaluated options, CHIRPS and MSWEPv2 proved to be the most reliable products. These outcomes provide clear guidance on which global precipitation datasets are best suited for hydroclimatic analyses in locations with challenging terrain and exceptionally high rainfall.
Reliable rainfall data is essential for managing water resources and preparing for extreme weather. In regions with very high precipitation and complex terrain, satellite and global datasets often struggle. Identifying which tools actually work helps hydrologists and environmental planners select the best data for water monitoring and climate resilience.
This work represents early-stage comparative research that identifies CHIRPS and MSWEPv2 as preferred datasets. While the abstract does not describe a direct commercial product, these insights can be utilised by environmental consultancies, water resource managers, and meteorological service providers who require validated inputs for hydroclimatic modelling and risk planning in high-rainfall terrains.
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The aim of this study was to assess the performance of nine high-resolution globalprecipitationproducts (GPPs) and their ability to capture droughts in Debundscha, one of the rainiest places on Earth. The performance of the GPPs was assessed using both quantitative and qualitative error metrics. The analysis revealed that most GPPs successfully captured the annual rainfall cycle in the region. The non-parametric Kling-Gupta efficiency, root mean squared error and percent bias scores indicated that the GPPs performed poorly in Debundscha, Idenau, and Limbe where annual rainfall is extremely high. In contrast, Pearson correlation scores were generally acceptable across most stations. Furthermore, the study found that the GPPs had limited ability to capture droughts. Overall, CHIRPS and MSWEPv2 emerged as the most suitable products for hydroclimatic analysis in the study area. These findings offer valuable insights into the performance and potential use of GPPs for hydroclimatic applications in complex topographies and high precipitation regions.
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DOI: 10.1080/02626667.2025.2579875
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