Abstract
Abstract This paper estimates return levels of extreme snow water equivalents (SWE) in the northern Great Plains region, containing North and South Dakota, Iowa, Minnesota, and Nebraska. The return levels are estimated from extreme-value methods using a new hybrid SWE dataset that improves the spatial resolution of existing data in the area. A novel aspect of the methods is the use of standard error margins to spatially smooth the estimated SWE return levels computed on individual grid cells. The end product is a reliable return-level estimate that controls for uncertainties in the raw observations. The methods should prove useful in analyses of other geographical regions.
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