The promising potential of vision language models for the generation of textual weather forecasts

Steele, Edward C. C., Mane, Dinesh, Monti, Emilio, Orus, Luis, Chantrill-Cheyette, Rebecca, Couch, Matthew, Dale, Kirstine I., Eaton, Simon, Rangarajan, Govindarajan, Majlesi, Amir, Ramsdale, Steven, Sharpe, Michael, Smith, Craig, Smith, Jonathan, Yates, Rebecca, Ellis, Holly, Ewen, Charles

arXiv.org Artificial Intelligence 

Despite the promising capability of multimodal foundation models, their application to the generation of meteorological products and services remains nascent. To accelerate aspiration and adoption, we explore the novel use of a vision language model for writing the iconic Shipping Forecast text directly from video-encoded gridded weather data. These early results demonstrate promising scalable technological opportunities for enhancing production efficiency and service innovation within the weather enterprise and beyond.