The Evolving Role of Humans in Weather Prediction and Communication

Abstract

A series of webinars and panel discussions were conducted on the topic of the evolving role of humans in weather prediction and communication, in recognition of the 100th anniversary of the founding of the AMS. One main theme that arose was the inevitability that new tools using artificial intelligence will improve data analysis, forecasting, and communication. We discussed what tools are being created, how they are being created, and how the tools will potentially affect various duties for operational meteorologists in multiple sectors of the profession. Even as artificial intelligence increases automation, humans will remain a vital part of the forecast process as that process changes over time. Additionally, both university training and professional development must be revised to accommodate the evolving forecasting process, including addressing the need for computing and data skills (including artificial intelligence and visualization), probabilistic and ensemble forecasting, decision support, and communication skills. These changing skill sets necessitate that both the U.S. government’s Meteorologist General Schedule-1340 requirements and the AMS standards for a bachelor’s degree need to be revised. Seven recommendations are presented for student and forecaster preparation and career planning, highlighting the need for students and operational meteorologists to be flexible life-long learners, acquire new skills, and be engaged in the changes to forecast technology in order to best serve the user community throughout their careers. The article closes with our vision for the ways that humans can maintain an essential role in weather prediction and communication, highlighting the interdependent relationship between computers and humans.

Challenges of Operational Weather Forecast Verification and Evaluation

“…As forecast automation increases, the nature of operations-to-research feedback is evolving. Meteorologists are transitioning from making products to engaging customers in decision support (Stuart et al 2022). However, customer-facing personnel can be distant from model developers (who may not even be in the same agency).…”

Innovations in Winter Storm Forecasting and Decision Support Services

“…For example, a warning may be appropriate for a high probability of a minor snowfall event near rush hour, even if probabilities of warning criteria do not meet an established threshold (Demuth et al 2020). Being able to skillfully derive and provide information to meet this array of needs and decision contexts is an important part of the subjective aspect of IDSS, and is a uniquely human role (Stuart et al 2022). Nevertheless, a probabilistic framework can be used to root decisions in skillful, objective information.…”

A Review of Machine Learning for Convective Weather

“…McCloskey et al (2022) takes the first step with this, but we need more studies that can tackle this question to obtain the most useful, trustworthy AI systems. Human-AI teams are being studied across a wide range of applications and have immense import in the weather world (Stuart et al 2022).…”