  Generative AI, such as OpenAI's GPT-4V large-language model, has rapidly
entered mainstream discourse. Novel capabilities in image processing and
natural-language communication may augment existing forecasting methods. Large
language models further display potential to better communicate weather hazards
in a style honed for diverse communities and different languages. This study
evaluates GPT-4V's ability to interpret meteorological charts and communicate
weather hazards appropriately to the user, despite challenges of
hallucinations, where generative AI delivers coherent, confident, but incorrect
responses. We assess GPT-4V's competence via its web interface ChatGPT in two
tasks: (1) generating a severe-weather outlook from weather-chart analysis and
conducting self-evaluation, revealing an outlook that corresponds well with a
Storm Prediction Center human-issued forecast; and (2) producing hazard
summaries in Spanish and English from weather charts. Responses in Spanish,
however, resemble direct (not idiomatic) translations from English to Spanish,
yielding poorly translated summaries that lose critical idiomatic precision
required for optimal communication. Our findings advocate for cautious
integration of tools like GPT-4V in meteorology, underscoring the necessity of
human oversight and development of trustworthy, explainable AI.
