Affiliation:
1. Minnesota State University, Mankato, Minnesota
Abstract
Abstract
Heavy rainfall over mountainous terrain often results in catastrophic flooding and presents a great challenge for forecasters. Statistical downscaling methods provide a way to bridge across the scale gap between rainfall forecasts from numerical weather prediction models and the high-resolution needs of hydrologic models for flash flood prediction. In this study, multiscale statistical analysis was used to analyze several heavy convective rainfall events that produced catastrophic flooding in the Appalachian Mountains and Front Range of the Rocky Mountains with the motivation of developing predictive relationships for a priori parameter estimation needed in downscaling applications. The multiscale behavior of the rainfall was analyzed over time and linked to underlying topographic elevation and predominate orographic forcing. It was found that in storms located on the leeward side (i.e., the side of the mountain facing away from the upper-level winds), one of the parameters increased with increasing topographic elevation. An opposite trend was found for this parameter in storms located on the windward side (i.e., the side of the mountain facing toward the direction of the upper-level winds). These trends held across different geographical regions and both upslope and downslope directions of storm motion. The interaction between orographic and meteorological forcings was found to be important in developing predictive relationships for the multiscale statistical parameters.
Publisher
American Meteorological Society
Cited by
26 articles.
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