Panelists Take on Bridging Gap from Data to Climate Actions

Elizabeth Mannshardt and Yawen Guan

Throughout the last decade, extreme weather events, long-term hydroclimatic change, and fire weather and management have created public concern. For scientists, the challenge resides in assessing, predicting, and documenting climate change on such events to help develop solutions that mitigate their impact on the environment, economy, and society.

The ASA’s Advisory Committee on Climate Change Policy sponsored the invited panel titled “From Data to Climate Actions” at the 2024 Joint Statistical Meetings. The panel, moderated by Elizabeth Mannshardt, was cosponsored by the ASA’s Physical and Engineering Sciences and Statistics and the Environment sections. The panelists, who are climate data experts, explored considerations and innovations, taking the audience from data to information, to scientific and policy communications, to climate actions.

Panel members stressed the importance of now as the age for information about extreme events and the possible role of anthropogenic change, as well as the critical need to understand and quantify uncertainties in data, climate models, and projections in an ever-evolving data landscape. They indicated that just as trusted data and sound methods are vital to inform data-driven decisions to guide policy, scientific communication for data-driven decisions is crucial for current impact and future development.

Panelists agreed there is a need to focus on decisions and adaptation and that there is high potential for impact at the local level. They also placed a high priority on education and public awareness—and pointed to the need to democratize access to data and data science platforms.

Panelist Amy Braverman, a senior scientist and statistician at NASA’s Jet Propulsion Laboratory with expertise in remote sensing data and climate models, opened by discussing the opportunities available with the wide array of existing and emerging data sources:

Michael Stein, distinguished professor of statistics at Rutgers University and renowned for his contributions to spatial statistics and its applications to environmental and climate science, spoke to framing the science:

In Braverman’s overview of her work exploring the satellite data record, she noted the enormous amount of data spanning decades and said we need innovative methods and platforms to enable use of this data—and the data coming.

NASA’s new Earth-focused missions provide data and key information to addressing and mitigating climate change. The Earth System Observatory will provide profoundly more data, with 1.5 million data collected per second. This drives the need for new approaches to model, test, and quantify uncertainties. NASA’s Earth Science to Action program is working to bridge the gap between the data available and what people can do with it.

Stein’s remarks also highlighted statistical challenges in modeling the extreme events over larger space and longer time scales and estimating and quantifying uncertainties for spatial and temporal data. Such statistical challenges are relevant in agriculture, electrical grid, and flood monitoring. He noted data scientists can contribute to understanding local climate impacts and adaptations.

Josh Hacker, cofounder and chief science officer at Jupiter Intelligence and renowned for climate risk analytics, spoke to business considerations and risks:

Hacker also noted that if we make climate change about money, something will happen in the business and technology space. He noted many economic models are also flawed, as models can’t possibly cover all scenarios, and that tipping points can be hard to estimate and interact with each other.

Wen-wen Tung, a data scientist and atmospheric scientist at Purdue University with a commitment to education for sustainable development, cited UNESCO’s 2024 global education monitoring report and noted the following:

She spoke about the importance of empowering youth in climate action and stressed the importance of education, touching on the social and emotional aspects of addressing climate change in one’s own community and the importance of considering human relation factors.

Discussion with the panelists included reflections on the participants’ conversations with policymakers on Capitol Hill, as well as educational resources for preparing students, highlighting the need for data science ambassadors for communication to discuss climate change with policy advisers, decision-makers, the media, and the public.

Tung pointed to tools and data sets for students—such as the NOAA Atlantic hurricane database best track data (Python script and video)—and national initiatives for increasing access to data science and AI resources for research and education, including the National Science Foundation’s National Discovery Cloud for Climate and National Artificial Intelligence Research Resource Pilot.

Each panelist offered closing thoughts. Hacker stated, “A key to making climate data actionable is separating what is useful in assessment and decision contexts when we know perfection isn’t possible.”
Tung stressed the importance of education efforts: “The impact of data science education can be amplified if higher education deeply integrates climate across various disciplines, enabling statistics students to build efficacy in climate science through exploratory data analysis and cross-disciplinary collaboration.”
“Climate change is happening,” said Braverman. “Attention has shifted to mitigation and adaptation, which creates new possibilities for statisticians and data scientists to step out [of] the shadow of climate scientists and work directly with decision-makers to help them respond.”

Stein said, “If your goal is to have an impact on policy, build relationships with policymakers, especially at the state and local levels.”

Editor’s Note: The views expressed by the authors and panelists are their own and do not necessarily represent those of their employers.