Our Weather, Water, and Climate Enterprise is undergoing rapid transformation — in the AI technologies reshaping how we conduct our science and how the public receives it, and in the funding systems that support both. Navigating this transformation requires cross-sector collaboration, and the AMS has long been the common ground where practitioners from across the enterprise forge exactly those connections. Cultivating this diverse, interdisciplinary community isn't just the AMS' greatest asset; it's our most urgent imperative.

AI is reshaping how we predict weather and climate and how we inform the public. Many of these advances arise from machine learning communities outside the traditional enterprise, such as technology companies and startups. Pairing these advances with domain expertise is critical to maximizing their real-world impact. Collaborations like Google DeepMind's work with the National Hurricane Center highlight what's possible when these communities meet; the AMS can be the forum where such partnerships form at scale.

Shifting federal funding priorities and private sector expansion into areas including modeling and observation create new challenges with data sovereignty and open access. These changes also generate deep uncertainty across the research establishment, especially for the early-career scientists who will become our next generation of leaders. The AMS can play an invaluable role in fostering the dialogue that will galvanize our community to action on these challenges.If elected to the AMS Council, I'll draw both from my career spanning academic research, industry, and the AI-weather frontier and from leadership in the AMS fostering dialogue on AI, data sovereignty and cross-sector collaboration at AMS Meetings to strengthen the Society’s role as the forum where our community confronts these transformations. My goal is to help the AMS fulfill its highest purpose: serving as the common ground where practitioners foster the interdisciplinary connections that translate our science into lasting impact on society.

If elected to the AMS Council, I'll draw both from my career spanning academic research, industry, and the AI-weather frontier and from leadership in the AMS fostering dialogue on AI, data sovereignty and cross-sector collaboration at AMS Meetings to strengthen the Society’s role as the forum where our community confronts these transformations. My goal is to help the AMS fulfill its highest purpose: serving as the common ground where practitioners foster the interdisciplinary connections that translate our science into lasting impact on society.

Daniel A. Rothenberg has spent 15 years working at the intersection of weather, climate, and technology. In 2024 he co-founded Brightband, a Public Benefit Corporation making AI weather forecasting tools broadly accessible — helping communities adapt to increasingly extreme weather. As Head of Data and Weather, he leads Brightband's data engineering functions and key scientific collaborations, including a CRADA with NOAA to develop AI-ready observational datasets for next-generation machine learning applications.

Daniel has led teams at the forefront of applying new technologies to weather observation and prediction. As Chief Scientist at Tomorrow.io, he built hydrometeorological sensing networks leveraging commercial microwave communications. As Technical Lead for Waymo's weather program, he used networks of autonomous vehicles for real-time sensing of urban weather hazards. He also worked to bridge atmospheric science and leading-edge AI/ML research through collaborations with Google DeepMind and invited engagements at the National Academies and White House OSTP.

A founding member of the Pangeo community, Daniel develops open-source tools that unlock petascale weather and climate applications and actively trains researchers to use them — including through the Python Symposium at the AMS Annual Meeting.

Daniel holds a B.S. in Atmospheric Science from Cornell University and a Ph.D. in Atmospheric Science from MIT, and is an AMS Macelwane Award recipient (2011). He has served the AMS in numerous capacities: co-chairing the Student Conference Planning Committee (2015–2016); serving on the Annual Meeting Oversight Committee (2017–2020) and the Committee on Open Environmental Information Services (2023–2026); and currently contributing to the AI Ethics and Policy Committee and serving as an Associate Editor for Artificial Intelligence for the Earth Systems. A former participant in the Summer Policy Colloquium and Early Career Leadership Academy, he has regularly convened sessions on machine learning, AI, and research-to-operations at the Annual Meeting and Washington Forum since 2019.