Sharks may help improve climate forecasts, study finds
Research demonstrates how animal-borne sensors can work in tandem with traditional tools to improve ocean predictions
image:
Neil Hammerschlag, Ph.D. and Laura McDonnell, Ph.D. attach a satellite tag to a blue shark that transmitted location, temperature, and depth data.
view moreCredit: Nola Schoder, MPS
MIAMI— A new study published in the journal npj Climate and Atmospheric Science, shows that electronically tagged sharks can serve as mobile sensors, collecting ocean climate data in regions that are difficult to observe using conventional methods.
The study is led by Laura H. McDonnell, Ph.D., who conducted the research as a doctoral student at the University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science and the Abess Center for Ecosystem Science and Policy. Its findings demonstrate that temperature and depth data gathered by tagged sharks can enhance ocean forecast accuracy in dynamic regions of the Northwest Atlantic.
By incorporating shark-collected data into a seasonal climate model, McDonnell and her team found that forecast errors at the ocean surface decreased substantially in certain regions, with improvements reaching as much as 40 percent in specific cases.
This is the first study to experimentally integrate animal-borne sensor data into a seasonal climate model and quantify its impact on forecast performance, suggesting potential for future operational use.
“Sharks are already moving through parts of the ocean that are challenging for us to observe,” said McDonnell, now a postdoctoral investigator at the Woods Hole Oceanographic Institution (WHOI). “This research shows that data they collect can help fill important gaps and, when used carefully, can improve how we predict ocean conditions.”
Interdisciplinary collaboration fuels innovation
The study originated from an interdisciplinary collaboration between former Rosenstiel School shark scientist Neil Hammerschlag, Ph.D. and atmospheric scientist Ben Kirtman, Ph.D., now dean of the Rosenstiel School. In 2018, they recognized that the data from shark-tagging studies used by Hammerschlag’s lab to study shark ecology could also benefit climate modeling.
Satellite tags attached to sharks record depth and temperature as they travel through the ocean, collecting and transmitting this data in near real time. While these tags have long helped scientists track shark movements, the collaboration opened a new application and a chance to create a novel proof of concept: using the same data to improve climate forecasts.
“Marine predators like sharks naturally seek out dynamic ocean features such as fronts and eddies,” said Kirtman. “These are areas where models often lack sufficient observations.”
Supported by a grant from Cisco Systems, the team conducted fieldwork and tested the concept.
Testing sharks as ocean observers
McDonnell and Hammerschlag tagged 18 blue sharks (Prionace glauca) and one shortfin mako shark (Isurus oxyrinchus) in the Northwest Atlantic. The sharks transmitted more than 8,200 temperature-depth profiles across a wide range of locations and depths—down to nearly 2,000 meters. WHOI oceanographer and study co-author Camrin Braun, Ph.D., helped facilitate this field work off Cape Cod, MA by connecting McDonnell and Hammerschlag with a local fisherman and co-led the forecast data analysis.
“Key to this study was repurposing a more advanced tag capable of transmitting location data along with temperature and depth information,” said Hammerschlag, co-author of the study and executive director of the Shark Research Foundation. “This allowed us to link subsurface ocean conditions directly to specific locations with known accuracy.”
Kirtman integrated a subset of these data into the Community Climate System Model, a coupled ocean–atmosphere–ice–land model used in seasonal forecasting applications that forms part of the National Oceanic and Atmospheric Administration’s operational North American Multi-Model Ensemble (NMME) system, of which Kirtman is the lead scientist.
The team compared the actual resulting climate conditions with the forecasted predictions from traditional models as well as the ones that integrated the shark collected data.
The results showed measurable improvements in forecast performance, particularly in dynamic coastal and shelf regions that are important for marine ecosystems and fisheries.
The researchers emphasize that animal-borne sensors are not a replacement for traditional observing systems but a complementary tool.
“Tagged sharks won’t replace conventional observing systems,” added McDonnell. “What the preliminary results do show is that tagged marine predators can provide complementary in-situ observations at the surface and at depth.”
Why it matters
Accurate ocean forecasts are critical for fisheries management, marine operations, and understanding how climate variability affects coastal communities. However, forecasts are often least reliable in regions where conditions change rapidly and observational data are lacking.
Animal-borne sensors could enhance predictions that support decision-making across multiple sectors, ranging from seafood supply chains to climate adaptation planning.
“Marine animals are already being tracked to understand their behavior in relation to environmental conditions, but this study reveals how these data can also be leveraged for forecasting and climate applications,” said Hammerschlag.
“For fisheries and coastal communities, small improvements in ocean forecasts can make a big difference,” said Braun. “Reducing uncertainty helps people plan, whether that’s where to fish, how to manage resources, or how to respond to changing conditions.”
The study, titled “Improved seasonal climate forecasting using shark-borne sensor data in a dynamic ocean,” was published on April 28, 2026 in the journal npj Climate and Atmospheric Science.
Funding for the research was provided by Cisco Systems (AWP-014524) and the University of Miami Abess Center.
The authors and their affiliations for this study are as follows: Laura H. McDonnell & Neil Hammerschlag, Rosenstiel School of Marine, Atmospheric and Earth Science, and the Leonard and Jayne Abess Center for Ecosystem Science and Policy at the University of Miami. Ben P. Kirtman, Rosenstiel School and the Cooperative Institute for Marine and Atmospheric Studies, and the Frost Institute for Data Science and Computing, all at the University of Miami, and Camrin D. Braun, Woods Hole Oceanographic Institution.
About the University of Miami and Rosenstiel School of Marine, Atmospheric and Earth Science
The University of Miami is a private research university and academic health system with a distinct geographic capacity to connect institutions, individuals, and ideas across the hemisphere and around the world. The University’s vibrant academic community comprises 12 schools and colleges serving more than 19,000 undergraduate and graduate students in more than 180 majors and programs. Located within one of the most dynamic and multicultural cities in the world, the University is building new bridges across geographic, cultural, and intellectual borders, bringing a passion for scholarly excellence, a spirit of innovation, and a commitment to tackling the challenges facing our world. The University of Miami is a member of the prestigious Association of American Universities (AAU).
Founded in 1943, the Rosenstiel School of Marine, Atmospheric, and Earth Science is one of the world’s premier research institutions in the continental United States. The School’s basic and applied research programs seek to improve understanding and prediction of Earth’s geological, oceanic, and atmospheric systems by focusing on four key pillars:
*Saving lives through better forecasting of extreme weather and seismic events.
*Feeding the world by developing sustainable wild fisheries and aquaculture programs.
*Unlocking ocean secrets through research on climate, weather, energy and medicine.
*Preserving marine species, including endangered sharks and other fish, as well as protecting and restoring threatened coral reefs. www.earth.miami.edu
Sharks may help improve climate forecasts, study finds [VIDEO]
Example shark-derived temperature–depth profiles across four regions, with the distribution of all transmitted profile locations (October 2021–April 2022). Top panels compare tag-derived profiles within a 1° × 1° grid cell on a given day to the concurrent control (CFSR) profile (black), with shark tag data showing minimum (blue) and maximum (red) temperatures. Summary statistics for each grid cell are provided in-panel. The bottom map shows all profile locations and maximum depths (N = 8,242), with colored diamonds marking example profiles, orange lines indicating the Gulf Stream, and the black line marking 200 m depth.
Credit
Laura McDonnell, Ph.D.
Journal
npj Climate and Atmospheric Science
Method of Research
Experimental study
Subject of Research
Animals
Article Title
Improved seasonal climate forecasting using shark-borne sensor data in a dynamic ocean
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