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Evaluation of gridded precipitation datasets over international basins and large lakes

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Full Publication Date
February 3, 2022

Reliable precipitation estimates are a crucial component for hydrologic modeling and hydro-climate applications. However, watersheds that extend across international boundaries or those that contain large bodies of water pose particular challenges to the acquisition of consistent and accurate precipitation estimates. The North American Great Lakes basin is characterized by both of these features, which has led to long-standing challenges to water budget analysis and hydrologic prediction. In order to provide optimal conditions for hydrologic model calibration, retrospective analyses, and real-time forecasting, this study comprehensively evaluates four gridded datasets over the Great Lakes basin, including the Analysis of Record for Calibration (AORC), Canadian Precipitation Analysis (CaPA), Multi-sensor Precipitation Estimate (MPE), and a merged CaPA-MPE. These products are analyzed at multiple spatial (overland, overlake, sub-basin, country) and temporal (daily, monthly, annual) scales using station observations and a statistical water balance model. In comparison with gauge observations from the Global Historical Climatology Network Daily (GHCN-D), gridded datasets generally agree with ground observations, however the international border clearly delineates a decrease in gridded precipitation accuracy over the Canadian portion of the basin. Analysis reveals that rank in gridded precipitation accuracy differs for overland and overlake regions, and between colder and warmer months. Overall, the AORC has the lowest variance compared to gauge observations and has greater performance over temporal and spatial scales. While CaPA and AORC may better capture atmospheric dynamics between land and lake regions, comparison with a statistical water balance model suggests that AORC and MPE provide the best estimates of monthly overlake precipitation.

Yi Hong
Hong Xuan Do
James Kessler
Lauren Fry
Laura Read
Arezoo Rafieei Nasab
Lacey Mason
Eric J. Anderson
Research Areas
Water Resources

Gridded precipitation datasets

International basins

Overlake precipitation

National water model


Overlake-to-overland precipitation ratio

Publication Type
Journal Article
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Full Citation

Yi Hong, Hong Xuan Do, James Kessler, Lauren Fry, Laura Read, Arezoo Rafieei Nasab, Andrew D. Gronewold, Lacey Mason, Eric J. Anderson, Evaluation of gridded precipitation datasets over international basins and large lakes, Journal of Hydrology, Volume 607, 2022, 127507. CSS22-36