Using a data-driven approach for climate resilience

You don’t have to look far to find examples of how climate change-driven extreme weather can damage the federal infrastructure.

Tom Temin

March 22, 2021 7:46 am

2 min read

You don’t have to look far to find examples of how climate change-driven extreme weather can damage the federal infrastructure. Case in point: When Hurricane Michael arrived as a Category 5 storm at the Florida coast in October 2018, it wrecked Tyndall Air Force Base, destroying 484 buildings. Just the immediate repairs cost nearly $700 million.

“The climate induced threats that are posed to the nation’s infrastructure are truly broad,” said Dr. Sharon Hays, the chief technology officer at government consultancy LMI. “Sea level rise caused by melting glaciers leads to inundation of buildings bases, launch pads other facilities on coastlines. We know about severe hurricanes that and the damage they caused, but climate change will also be responsible for more frequent and more freakish storms.”

Potential losses from climate-change-induced events are more than financial, added LMI’s senior consultant for sustainability, Kelli Canada. Agency leadership must also plan against the potential interruption of, or degradation in delivery, of an agency’s mission. Canada noted that some 18,000 federal buildings (with a combined value of $10 billion) are in a 100-year floodplain, meaning climate change poses a threat to continuity of operations.

Hays and Canada recommend federal agencies use a data analytics-driven approach to disaster planning to account for financial risk. Agencies such as the National Institute of Standards and Technology and those at the state and local level that set construction codes, should use the array of available climate and weather pattern data.

“Revising these types of codes and standards is really one of those greatest opportunities to help inject data analytics into improving federal preparedness,” Canada said. In particular, Hays added, it’s important to build climate models into plans and forecasts because historical weather patterns don’t necessarily help predict future ones under a shifting climate.

Hays and Canada caution that resiliency and budget planning must not remain a matter solely for the operational and data people. Rather, it starts with “the people that sit at the top of agencies; they’re formulating budgets, they’re making procurement and asset management decisions, monitoring and mitigating risk at the enterprise level,” Canada said.

They said several large private sector organizations and industries provide good guidance on how to understand, disclose and deal with climate risk. They have experience in integrating the varied data sets and analytical tools needed to operationalize the required analysis.

Canada cited LMI’s partnership with The Climate Service, whose risk analytics platform merges large climate model data sets with economic modeling.

“With an analytical tool like that, we see a tremendous amount of value to bring that kind of capability to federal agencies,” she said.

The Scope of Climate Change Threats

The people at the top of agencies [are] formulating budgets, making procurement and asset management decisions, monitoring and mitigating risk at the enterprise level. So many different functional groups at every agency need to have basic understanding of what climate change is, so that they can make better decisions to help their agency, its programs, its assets, and to protect its people.

Kelli Canada

Senior Consultant, Sustainability, LMI

Data Analytics Tools

You can't simply just look at historical weather and understand what temperature highs and lows are going to be. What we're really dependent on are climate models, which are digital twins of the Earth's environment. They're critical to understanding what to expect. That really leads to some big data related challenges.