Predictability of Impacts Associated with the February 2011 'Groundhog's Day' Storm

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Sunday, 2 February 2014
Hall C3 (The Georgia World Congress Center )
Stephanie A. Bonney, Central Michigan University, Rockford, MI; and M. A. Baxter

Heavy snow and freezing rain affected 100 million people and caused billions of dollars in damages during the ‘Groundhog's Day' storm of February 2011. Some of the financial and societal impacts could have been mitigated had the influence of the storm been anticipated further in advance. The use of ensemble forecasting enables better predictions of weather events by analyzing an array of potential results. The Grand Global Ensemble is a collection of ensembles from 10 forecasting centers around the world. It has been created to allow research studies that will help increase the accuracy of 1-14 day forecasts for high-impact weather events. Data was downloaded between 12Z January 18th and 12Z February 2nd from the TIGGE archive from seven of the 10 forecast centers, comprised of 198 ensemble members. Research was conducted through qualitatively analyzing plots via The Grid Analysis and Display System (GrADS) scripting. Quantitative analysis was completed by computing the 500 mb Mean Absolute Error and Anomaly Correlation for these centers, which revealed that the ensemble members were able to begin picking up on the storm up to 9 days in advance. By thoroughly investigating the predictability of the ‘Groundhog's Day' storm in particular, results can be applied to other large-scale Midwest winter events in general if improved results are achieved with an increase in ensemble members, thereby showing an advantage of multiple center ensembles over single center ensembles.