S32
The Great Colorado Flood of September 2013 Forecast Model Analysis

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Sunday, 2 February 2014
Hall C3 (The Georgia World Congress Center )
Casey D. McClure, Metropolitan State University, Denver, CO

A week prior to the Flood Disaster of 2013; the city of Boulder, Colorado experienced temperatures in the upper 90s, along with warm, downsloping winds, and clear skies. According to the model data given for that upcoming week, it was apparent that relief from the heat was on its way. Colorado, in general, can be one of the most challenging forecast areas in the U.S. when the unique topography interacts with the speed and strength of weather systems as upslope events feed on moisture sources from the Gulf of Mexico and the Tropical Pacific. The 12Z GFS, NAM, and RAP model runs on 11 September 2013 all predicted high Precipitable Water values (PW) and cooler temperatures for the Front Range of Colorado. Some of the highest precipitation amounts were indicated along the foothills, ranging from Golden to Fort Collins. Depending on the model, PW values ranged from 1-3 inches over the entire event. Some of the actual rainfall amounts observed along the Front Range over the entire flooding event include: Aurora 17.17 inches, Golden 11.05 inches, Boulder 18.34 inches, Lyons 12.95 inches, Fort Collins 11.81 inches; some local amounts in Boulder exceeded 20 inches as well as other areas along the Front Range. This rare event can serve as a dataset for exploring the capacity of our current weather models to forecast extremely unusual events. Here, data is analyzed to understand the discrepancies in forecast and actual rainfall, possibly due to challenges with the models failing to predict a stalled front, and therefore, the length of the intense event. The precipitable water in the models will be analyzed and compared to actual precipitation amounts. The nature of the precipitation event will also be analyzed for forcing mechanisms. This event clearly demonstrates the need for enhanced research in numerical modeling; with this said, it will give meteorologists a better handle on weather forecasting.