Understanding and Communicating Local Climate Change

A number of “feels like” indices exist that relate current weather conditions to what a person might feel, such as heat index and wind chill index. This two-fold project sought to create a climate version of such an index to relate the temperature on a given day to the historical average temperature of another day, known as a “seems like” index. This type of index is useful in communicating local climate change to a public audience, as people naturally relate higher temperatures to summer months and lower temperatures to winter months (e.g. a hot day in April feeling more like July). Human experience is defined by what is personally seen or felt, as opposed to seemingly abstract measures like temperature anomaly, so such an index allows the public to relate climate change to their everyday lives more effectively. Using this index, an informative and easily digestible graphic regarding the departure from normal temperatures can be created for use in media. The second purpose of this index was to create scientifically relevant statistics that can be analyzed by climatologists to examine seasonal shifts. Four locations were chosen for this study: State College, PA, Orlando, FL, Oklahoma City, OK, and Portland, OR. Maximum and minimum temperature data from spring (March, April, May) and fall (September, October, November) seasons for all four cities were compared to climate normals downloaded from the National Centers for Environmental Information (NCEI) and plotted as time series. Data from all four cities showed recent divergence between fall and spring values, indicating an earlier onset of spring and summer and later onset of fall and winter. Some cities showed this divergence more prominently in the maximum temperatures, while others showed this tendency more in their minimum temperatures.