Skip to main content

“Hyperscale” Modeling to Understand and Predict Temperature Changes in Midwest Lakes

Hyperscale Modeling for Understanding and Predicting Climate Change Effects on Lakes
Principal Investigator
Jordan Read


Start Date
End Date
Release Date


Many inland waters across the United States are experiencing warming water temperatures. The impacts of this warming on aquatic ecosystems are significant in many areas, causing problems for fisheries management, as many economically and ecologically important fish species are experiencing range shifts and population declines. Fisheries and natural resource managers need timely and usable data and tools in order to understand and predict changes to lakes and their biota. A previous Northeast CSC-funded project modeled lake temperatures to help state agencies in the Midwest understand trends in walleye and largemouth bass populations and predict lake-specific fish populations under future climate scenarios. These results have been [...]

Child Items (3)


Principal Investigator :
Jordan Read
Co-Investigator :
Gretchen Hansen
Funding Agency :
Northeast CSC
CMS Group :
Climate Adaptation Science Centers (CASC) Program
Cooperator/Partner :
Vipin Kumar, Samantha K Oliver

Attached Files

Click on title to download individual files attached to this item.

“Day Lake, Wisconsin - Credit: USFS”
thumbnail 114.08 KB image/jpeg


Water temperatures are warming in lakes and streams, resulting in the loss of many native fish. Given clear passage, coldwater stream fishes can take refuge upstream when larger streams become too warm. Likewise, many Midwestern lakes “thermally stratify” resulting in warmer waters on top of deeper, cooler waters. Many of these lakes are connected to threatened streams. To date, assessments of the effects of climate change on fish have mostly ignored lakes, and focused instead on streams. Because surface waters represent a network of habitats, an integrated assessment of stream and lake temperatures under climate change is necessary for decision-making. This work will inform the preservation of lake/stream linkages, prioritization restoration strategies, and stocking efforts for sport fish. This project will employ state-of-the-science methods to model historical thermal habitat for nearly ten thousand lakes.The results of this project will be used by partners and stakeholders to prioritize adaptation and restoration strategies for the region’s freshwater resources. Additionally, these data products will be shared openly in machine-readable formats to spur other innovation and research.

Project Extension

typeTechnical Summary
valueIn the face of global change, access to timely, actionable data and information are critical to actively manage natural resources. Our understanding of spatial availability and connectivity of thermal habitats and their influence on species distribution are key to supporting freshwater fish populations as the landscape and climate changes. Past research has separated lake and stream linkages, and no comprehensive lake temperature data profiles exist as they do for streams. In partnership with regional experts and practitioners from Michigan, Minnesota and Wisconsin Departments of Natural Resources, University of Wisconsin Center for Limnology, and informaticists/modelers from U.S. Geological Survey’s Data Science Branch, will leverage and expand upon existing modeling frameworks to produce essential daily hindcasted lake temperature profiles lakes and post-process the results to de-bias the model outputs with machine learning techniques. Our reusable models, tools, and output data products will be widely broadcast and demonstrated via in- person and web-based training sessions to raise awareness, build support and gain feedback, and spur innovation and future research.

Budget Extension

typeAward Type
valueChange of Allocation
typeAward Number

Additional Information


Type Scheme Key
RegistrationUUID NCCWSC 982f7056-8844-4e29-8b0d-8aa43239dbba
StampID NCCWSC NE17-RJ1270

Item Actions

View Item as ...

Save Item as ...

View Item...