Satellites and Sea Ice: Using NASA Data for Ecological Forecasting in the Arctic

June 22, 2026

By Remy Licari, Canyon Crest Academy Student and SDSC Communications Intern

Deep blue stretching as far as the eye can see, silver flickers glinting in the darkness, and stark white patches rolling by: the marine Arctic is a mysterious place, becoming increasingly fragile. However, for ecological forecasters, this mystery is mitigated by the use of light transmission models, including the work of University of Maryland climate scientist Alek Petty.

In all Arctic research, ice is unavoidable. In ecology, it is the backbone of marine ecosystems. Sea ice, or free-floating ice on the ocean’s surface, functions similarly to the way clouds do on Earth, by controlling the amount of sunlight that reaches beneath the top of the water. 

“We hoped to bridge the gap between sea ice data and ecological forecasting by designing digital models, through the use of Jupyter notebooks, that illustrate changes in cloud cover, ice thickness, and, most importantly, under-ice photosynthetically active radiation (PAR),” Petty explained. “PAR determines how much phytoplankton is able to grow, which are the foundation of any marine food chain. Therefore, in tracking changes in PAR over time, more accurate predictions of changes in Arctic environments can be made.”

One of Petty’s current projects is titled “ICEY ECOSYSTEMS: Arctic Sea Ice Light Transmission For Assessing Under-Ice Ecosystem Dynamics” and leverages NASA’s ICESat-2 satellite as a source of data. This satellite, launched in 2018, measures elevations around the Earth, including sea ice thickness and concentration. 

“By combining this data along with the NASA Eulerian Snow On Sea Ice Model, for snow thickness, and ERA5 weather forecast reanalysis output hosted on the cloud by Earthmover for cloud cover, we are able to compare Arctic light transmission in specific polar regions across the years,” Petty said.

Throughout his work, it’s clear that Petty values accessibility. His choice of making the code open-source as well as his commitment to FAIR (Findability, Accessibility, Interoperability, and Reuse) reflect his true goal: widespread integration of the use of these large datasets in the sea ice and ecological forecasting community. This is perhaps best displayed in his use of DeCODER, or Democratized Cyberinfrastructure for Open Discovery to Enable Research. 

The DeCODER platform, funded by the National Science Foundation, aims to make scientific data more discoverable, and therefore usable, online. This is done by following science-on-schema conventions or guidelines that ensure the standardization of how environmental data is described so it is machine-readable), which Petty utilizes throughout his project. 

DeCODER supports an array of research by providing access to data from multiple locations at once, thus helping projects like ICEY ECOSYSTEMS increase the findability of relevant ecological datasets from across the Internet.

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