Sunday, 7 January 2018
Exhibit Hall 5 (ACC) (Austin, Texas)
To help Emergency Departments properly prepare for patients with symptoms of heat exhaustion, cramps, or stroke during potential heat waves, it is important that forecasts from the National Digital Forecast Database (NDFD) are accurate as far in advance as possible. Mid-Atlantic NDFD forecasts of apparent temperature are pulled for North Carolina, South Carolina, Georgia, and Virginia using the State Climate Office of North Carolina’s THREDDS (Thematic Real-time Environmental Distribution Data Services) data server. Observed data from three Automated Surface Observing System (ASOS) stations in each state are analyzed for six different heat wave events between the months of May and September from 2013 through 2016. Heat waves affecting all four states are classified as three consecutive days with heat indices greater than 95 degrees Fahrenheit. Using 1800 UTC (14:00 EST) apparent temperature forecasts from the NDFD, lead times from 0, 6, 12, 24, and 48 hours are compared to the observed heat index values for each day of the heat event. Statistics - bias, correlation, and root mean square error – are used to determine which state, lead time, and heat wave are forecasted more accurately for apparent temperature. By determining which lead times are more accurate in forecasting heat index, public health officials can communicate the dangers of heat exposure in a timelier manner, and Emergency Departments can prepare for increasing visits during and after heat events. In the future, this research will be expanded to more stations across North Carolina, South Carolina, Georgia, and Virginia.
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