Understanding precipitation patterns is critical to managing water resources and forecasting extreme events such as floods and droughts. In the Peruvian Andes, however, the region’s complex topography and lack of reliable data from ground-based weather stations make it difficult to track these patterns and how they are changing.
A new study by researchers from the University of Oklahoma (OU) and the Universidad Nacional de San Agustín de Arequipa (UNSA) shows that careful selection of a gridded precipitation data product allows for improved precipitation estimates in the Andean region. The research team analyzed four different precipitation data products. They found that accuracy is dependent on the regional climate— with some performing well in the higher precipitation and humid conditions of the tropical regions of Peru, and others more suitable for use in the low precipitation and hyper arid regions such as the Atacama Desert.
This is the first publication from a collaborative research project led by OU Professor Ming Xue and UNSA Professor Hector Novoa that seeks to produce high resolution regional climate projections and hydrological simulations for the Arequipa region of Peru. The project is supported by the OU-UNSA Global Change and Human Health Institute and administered through OU’s Latin America Sustainability Initiative, an initiative of the OU Institute for Resilient Environmental and Energy Systems.
The paper, “Cross-Examining Precipitation Products by Rain Gauge, Remote Sensing, and WRF Simulations over a South American Region Across the Pacific Coast and Andes," was published in the open-access journal, Atmosphere.
