Implications of Cognitive Processing in Visually Complex Emerging AI-Generated TV Weathercast Graphics

Datos Bibliográficos

ID21578747
AutoresRobert C Gauthreaux (0009-0006-9493-4024, Sam Houston State University, autor de correspondencia)
Año2026
Páginas1-16
Fecha de publicación2026-07-02
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaJournal of Broadcasting & Electronic Media (JOURNAL)
Identificadores de la revistaISSN: 0883-8151 • E-ISSN: 1550-6878
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/08838151.2026.2694049
OpenAlexW7167037249
IdiomaEN
Referencias citadas26

Despite demonstrably increasing accuracy in weather forecasts, rapid technological innovation, widespread access to weather information, and meteorological expertise particularly sought for modern TV weathercaster positions, public distrust and misinterpretation persist, resulting in avoidable casualties and significant financial losses from property damage. Visually busy TV weather graphics are suggested to cognitively weigh on the viewer’s ability to properly interpret and recall the forecast, especially through the limited medium of a television newscast, where the traditional weather segment is relatively brief. This essay explores the application of modern AI and AR strategies in the design and construction of contemporary TV weather graphics, as well as innovations to communicate risk during TV weathercasts. Theoretically-grounded recommendations are made for this transitional period from manual to AI-generated graphics. It is suggested that future studies should supplement the growing body of weather social science literature by drawing on research in traditional media and communication and by examining individual differences rather than relying on behaviorist approaches and self-report alone

Cognition · Distrust · Graphics · Recall · Climate Change Communication and Perception · Data Visualization and Analytics · Meteorological Phenomena and Simulations