Broadcast Meteorologist Decision Making with Probabilistic Hazard Information in the 2017 Hazardous Weather Testbed (64)

Holly Obermeier, CU CIRES/ESRL, Boulder, CO

Kodi Berry, OU CIMMS/NSSL

Kimberly Klockow-McClain, OU CIMMS/NSSL

Tiffany Meyer, OU CIMMS/NSSL

Alan Gerard, NOAA/OAR/NSSL

 

Abstract:

 

Broadcast meteorologists serve a critical and complex role in the communication of weather warnings. Surveys conducted after tornadic events indicate that approximately 85% of respondents received severe weather warnings from local broadcast meteorologists. Viewers cited trust of broadcaster advice as a main influence in deciding to seek shelter.

As intermediaries between NWS forecasters and the publics, one broadcast meteorologist was included each week in the 2016 and 2017 Hazardous Weather Testbed (HWT) Probabilistic Hazard Information (PHI) projects. A main objective of the HWT PHI projects was to learn how the continuous flow of probabilistic information may impact broadcast meteorologists and their decision making. Research protocols were developed and used to systematically study how broadcast meteorologists interpreted, used, and communicated probabilistic information. Coverage decision points of interest included when to run crawls, post to social media, interrupt commercials, and interrupt programming. Broadcast participants performed typical job functions under a simulated television studio environment as they received experimental PHI during three realtime and three displaced realtime events. Results from the 2016 experiment indicated that probability information added complexity into the participants' typical decision-making and communication routines. The participants were overwhelmed managing studio resources alone when multiple warnings were in effect and updating swiftly. Further, the hazard-following, probabilistic warnings presented unique challenges regarding the incorporation of PHI into the on-air crawl and graphics system, which are currently optimized for binary polygons. Building off these findings, in the 2017 experiment, warning update frequencies were varied daily to better understand optimal flow of information for the specific needs of broadcast meteorologists and their television stations. Preliminary results from the project will be shared, as well as plans for future experimentation.