Rescaling Transposed Extreme Rainfall within a Heterogeneous Region

Abstract

Geospatial transposition of observed storms can be useful for examining potential rainfall and flood hazards, and several recent software packages help facilitate transposition of remote sensing–based rainfall observations from radar or satellites. Two unanswered questions persist, however, in regions that exhibit heterogeneity in extreme rainfall properties: is transposition reasonable, and, if so, how should it be performed? This note posits that the answer to the first question depends on the degree of heterogeneity, and it attempts to answer the second question via “rescaling” transposed rainfall according to the degree of heterogeneity between two locations. General considerations for this rescaling are discussed, and two rescaling methods are introduced. Both methods are illustrated using gauge-corrected radar rainfall data from three locations in the Front Range of the Rocky Mountains in Colorado that exhibit moderate heterogeneity in an extreme rainfall hydroclimate. The second of these methods, termed stochastic distribution ratio rescaling, is presented here for the first time and has the advantage of straightforward uncertainty estimation.