Project Spotlight: Tool Developed by the North Central CASC Helps National Parks Plan for Climate Change

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The National Park Service Climate Change Response Program helps parks plan for and adapt to climate change, but they are often slowed by challenges wrangling large climate data sets. To solve this problem, the North Central CASC partnered with the National Park Service to create the Climate Futures Toolbox, a user-friendly software program designed to help "take the pain out of climate data."

Wind Cave National Park

Like many national parks, Wind Cave National Park is incorporating climate change information into their strategic planning decisions with the help of the National Park Service Climate Change Response Program.

(Public domain.)

This spotlight was written by Jordan Bush, National CASC Science Communication Specialist.

National parks, home to some of the country’s most beautiful and unique landscapes, are particularly vulnerable to the effects of climate change. For example, wildfires destroyed millions of historic redwoods, sequoias and Joshua trees in and around California’s national parks in 2020 alone, and glaciers in Alaska’s Glacier Bay National Park and Montana’s Glacier National Park retreat further every year.

“Most parks are impacted by climate change,” says Amber Runyon, a climate change ecologist at the National Park Service (NPS) Climate Change Response Program. “And it’s not something they are looking ahead saying, ‘Oh, we might be impacted,’ no they are already being impacted and those impacts can be seen on the ground.”

Many national parks across the country are actively working to address challenges presented by climate change in the lands they manage, including through the NPS Climate Change Response Program. This office frequently collaborates with the Climate Adaptation Science Centers (CASCs) to provide parks with detailed climate information.

One of their most powerful tools for analyzing climate change effects is scenario planning. In this process, scientists use climate models to generate divergent projections for how climate change could affect a landscape over time, called climate futures. Because the future is inherently uncertain, they consider outputs from different models and carbon emissions scenarios to account for a range of possible conditions. Managers then consider how these different futures could impact valuable park resources and develop management strategies accordingly.

“[Park managers] can look at best- and worst-case situations or a broad range of scenarios,” Runyon says. “They can identify particular red-flag events that, regardless of what the climate looks like, they should plan for. Or they can look across all scenarios and say that [specific features like] droughts are going to become longer and more severe regardless.”

“You’re looking for strategies that are kind of win-win under multiple futures,” explains Aparna Bamzai-Dodson, the USGS Deputy Director for the North Central CASC. The North Central CASC has worked with the NPS on many climate futures projects, including for Devil’s Tower National Monument and Wind Cave National Park.

Yet although climate scenario planning activities are powerful, they remain difficult and time-intensive, largely because retrieving and analyzing climate data is hard. Climate data does not adhere to one set of formatting standards, meaning that users must develop a thorough understanding of the complex data structures, file types, and spatiotemporal scaling unique to each data set before they can begin any analyses.

Climate data sets are also enormous.

“For an average sized national park, we are talking about at least 50 GB of data to be able to come up with climate summaries,” says Max Joseph, an Open Science Architect in the Earth Lab program at the University of Colorado Boulder who works with the North Central CASC. “For Yellowstone or Death Valley, you are talking about over 100 GB of climate data, easily. That’s a challenge! You think about the size of the average hard drive, it doesn’t necessarily leave room for much else.”

“One of the biggest bottlenecks in our process [at the NPS Climate Change Response Program] is downloading and parsing the data,” Runyon confirms.

To combat this issue, the North Central CASC partnered with the NPS to develop the Climate Futures Toolbox, a software designed to help non-experts download and use climate data. Bamzai-Dodson, the project lead, and Joseph, one of the main developers, have worked hard to create a streamlined workflow that “takes the pain out of climate data,” Bamzai-Dodson says.

“We only expose the user to the data they care about,” says Joseph, “and we try to get the data into a familiar and simpler format.”

Developed in the statistical software R, the climate futures toolbox, or ‘cft’ package, downloads climate data for a user-defined area, such as a national park, and formats it into a data frame, a data structure similar to a spreadsheet. This data frame can then be analyzed and visualized using the R programming language, for example to create warming stripes diagrams (Figure 1). Users can specify the climate variables, time period, and climate models they wish to download, as well as the greenhouse gas emission scenarios used in model calculations. This limits the data file sizes, making the data easier to download and store.

4 diagrams each show 100 red and blue verticle color stripes representing the average max temperature in Wind Cave National Park

Figure 1. The Climate Futures Toolbox allows users to download and analyze climate data, which can be turned into visuals like warming stripes diagrams using the statistical software R. These warming stripes show the average yearly maximum temperatures from 1950-2050 predicted by four different climate models for Wind Cave National Park, South Dakota. Stripe color ranges from dark blue, representing the coldest (avgerage yearly max) temperatures (12°C or 54°F), to red, representing the warmest (average yearly max) temperatures (21°C or 70°F). They demonstrate that different climate models often forecast different possible futures, with some models predicting more relatively warm years (red stripes) and others showing more cool years (blue stripes). By comparing the outcomes of different models, resource managers can look for patterns across all possible futures, such as the warming temperatures observed across all four models in Wind Cave National Park predictions.

The figure was created by Jordan Bush.

(Public domain.)

“Our overall hopes are that we can democratize access to climate data and make it easier for non-experts to focus on answering their questions and not on wrangling their data,” Joseph says.

“Accessing and interpreting climate data is a huge barrier for a lot of our partners – DOI bureaus that we work with such as the National Park Service and U.S. Fish and Wildlife Service, state agencies and tribes,” says Bamzai-Dodson. “This [package] removes that barrier.”

The data is downloaded from the MACAv2 statistical method for downscaling Global Climate Models, although Joseph and Bamzai-Dodson are already talking about expanding the package’s functionality to include additional data sets, such as historical and hydrological data.

“The way the package code is structured, it’s designed so that you can write new modules and expand the data that you access over time,” says Bamzai-Dodson. “It’s designed to be really easily improved going forward.”

Runyon and her team at the NPS Climate Change Response Program first approached the North Central CASC several years ago about resolving their difficulties dealing with unwieldy climate data sets.

“We reached out to the North Central CASC because they have some really good climate scientists who know the data and who we regularly consult with on what climate data to use,” Runyon says. “Also, being at universities, they can tap into other resources and people who are really good at programming and managing data, better than we are.”

“We saw working with the CASC as an opportunity to do better science and to do it more efficiently and more effectively.”

The North Central CASC worked closely with the NPS to understand their workflow and to identify the program functionality that would best serve their needs. The final product is meant to fit seamlessly into the Climate Change Response Program’s broad computation processes.

“What we wanted to do was to automate [aspects of] that process for the National Park Service,” says Joseph. “So, the way that we pull down data, the way we are structuring the whole package – it's meant to emulate what the NPS Climate Change Response Program has done.”

“It’s been a pretty iterative process,” he continues. “We’ve gone through some versions and cycles of revisions from partners, including the NPS and the U.S. Forest Service and the U.S. Fish and Wildlife Service. [Our partners’] needs are very much baked-into the package.”

Runyon is thrilled about the end result. Since the software’s release this summer, her team has already begun incorporating it into upcoming NPS scenario planning workshops.

“Our workload is growing by a lot this year. Without this toolbox, we just wouldn’t be able to keep up with the demand,” she says.

The North Central CASC team hopes that other users will find the package similarly useful.

“I think the whole package is awesome,” Bamzai-Dodson says. “We developed it with a specific partner in mind, but it has such a wide applicability. As we are thinking about what features we want to start working on next, we are starting to take it out to new partners.”

Teams at both the North Central CASC and NPS Climate Change Response Program are proud of the successful partnership.

“This is just one of many successful collaborations with the CASC [network],” Runyon says. “Our collaborations with them are integral to us being successful in helping parks incorporate climate change into their park planning.”

The Climate Futures Toolkit was supported by the North Central CASC and the U.S. Geological Survey (USGS) Community for Data Integration (CDI) through the project “Open-Source and Open-Workflow Climate Futures Toolbox for Adaptation Planning.”

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