Social Science Considerations in Twitter Weather Discussion: A March 2019 Case Study

Today’s scientific community relies not merely on one expertise, but rather collaborative understanding spanning diverse skill sets. Social science encourages collaboration, and can strengthen weather communication. This presentation explores social considerations in developing the Winter Storm Severity Index (WSSI). The WSSI, housed within the National Centers for Environmental Prediction (NCEP) Weather Prediction Center (WPC), is an experimental product that will be evaluated throughout the 2019/2020 cold season. The WSSI monitors six different components crucial to assessing winter weather impact: Snow amount, snow load, blowing snow, ground blizzard, flash freeze, and ice accumulation. Geographic Information Systems (GIS) based visualizations provide flexibility in displaying and communicating information. In order to strengthen these efforts, we examined product usability from a social science perspective. A particular case study from March 2019 is presented here. Nearly 565 tweets were collected via the keywords ‘freezing rain,’ ‘snow,’ ‘ice,’ and ‘blizzard.’ A sample size of 437 tweets remained upon filtering data for relevance. Event narratives from National Centers for Environmental Information (NCEI)’s Storm Events Database were also obtained. Generated word clouds assess weather discussion among the public (Twitter users) and National Weather Service (NWS) forecasters (obtained through event narratives). Social science findings from this case study may contribute to WSSI enhancements to effective weather communication.