4.2A Developing a Localized Climate Extremes Index for Individual State (Formerly Poster 609)

Tuesday, 8 January 2013: 3:45 PM
Room 15 (Austin Convention Center)
Adrienne M. Wootten, North Carolina State University, Raleigh, NC; and M. Griffin, R. Boyles, and D. F. Zierden

In 2011, North Carolina experienced extremes associated with temperature, precipitation, severe weather, tropical cyclones and winter weather. However, the National Climatic Data Center (NCDC) Climate Extremes Index (NCDC CEI) reflects the impact of extremes in temperature and precipitation on the country each year. However, this index does not include representation of the effects of extremes in severe weather, tropical cyclone activity or winter weather in a given region. In addition, the NCDC CEI considers only regions of the country at its finest resolution. This project discusses the development of a climate extremes index which is localized to impacts in any given state and includes information on historical extremes in severe weather, tropical activity and winter weather. This Localized Climate Extremes Index (LCEI) uses a combination of station and climate division data, Storm Prediction Center Storm Reports, National Hurricane Center Storm Track information, and winter weather data from the State Climate Office of North Carolina Winter Storms database. This combination of datasets allows the LCEI to capture historical trends in extremes associated with each aspect, though there are challenges associated with the period of record of each dataset and the measurement practices of each. In addition, the LCEI methodology has flexibility to adapt to other states. Three different versions of the LCEI for Florida are also discussed and demonstrate the ability of the methodology to function without specific components and with different datasets for winter weather events. The initial tests of the LCEI methodology in Florida and North Carolina show the value of each component and the overall index. However, there are challenges associated with appropriate datasets for winter weather events in multiple states and station data quality.
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