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Federal
Predictions of lake water temperatures for eight reservoirs in Missouri US, 1980-2021
Department of the Interior —
Lake temperature is an important environmental metric for understanding habitat suitability for many freshwater species and is especially useful when temperatures are... -
Federal
Data release: Process-based predictions of lake water temperature in the Midwest US
Department of the Interior —
Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give... -
Federal
Process-based water temperature predictions in the Midwest US: 5 Model prediction data
Department of the Interior —
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin.... -
Federal
Process-based water temperature predictions in the Midwest US: 4 Model inputs (meteorological inputs and ice flags)
Department of the Interior —
This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and is part of a larger data release of lake temperature model inputs and... -
Federal
Data release: Process-guided deep learning predictions of lake water temperature
Department of the Interior —
Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give... -
Federal
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 2 Water temperature observations
Department of the Interior —
Observed water temperatures from 1980-2018 were compiled for 877 lakes in Minnesota (USA). There were four lakes included in this data release that did not have... -
Federal
Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags)
Department of the Interior —
This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and is part of a larger data release of lake temperature model inputs and... -
Federal
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 5 Model prediction data
Department of the Interior —
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. state of Minnesota. Uncalibrated... -
Federal
Process-guided deep learning water temperature predictions: 4b Sparkling Lake detailed training data
Department of the Interior —
This dataset includes compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature records from... -
Federal
Process-guided deep learning water temperature predictions: 5c All lakes historical prediction data
Department of the Interior —
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin.... -
Federal
Thermal metrics: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes
Department of the Interior —
Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools... -
Federal
Process-guided deep learning water temperature predictions: 5a Lake Mendota detailed prediction data
Department of the Interior —
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin.... -
Federal
Process-guided deep learning water temperature predictions: 4c All lakes historical training data
Department of the Interior —
Observed water temperatures from 1980-2018 were compiled for 68 lakes in Minnesota and Wisconsin (USA). These data were used as training data for process-guided deep... -
Federal
Process-based water temperature predictions in the Midwest US: 6 Habitat metrics
Department of the Interior —
This dataset summarized a collection of annual thermal metrics to characterize lake temperature impacts on fish habitat for 7,150 lakes from uncalibrated models (PB0)... -
Federal
Process-guided deep learning water temperature predictions: 2 Model configurations (lake metadata and parameter values)
Department of the Interior —
This dataset provides model specifications used to estimate water temperature from a process-based model (Hipsey et al. 2019). The format is a single JSON file... -
Federal
GENMOM model: Projected shifts in fish species dominance in Wisconsin lakes under climate change
Department of the Interior —
Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater species such as largemouth bass (Micropterus salmoides). Recent... -
Federal
Process-guided deep learning water temperature predictions: 6c All lakes historical evaluation data
Department of the Interior —
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB)... -
Federal
Process-guided deep learning water temperature predictions: 6b Sparkling Lake detailed evaluation data
Department of the Interior —
This dataset includes "test data" compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature... -
Federal
Process-based water temperature predictions in the Midwest US: 3 Temperature observations
Department of the Interior —
Observed water temperatures from 1980-2019 were compiled for 5,584 lakes in Minnesota and Wisconsin (USA). A subset of these data were used as calibration for... -
Federal
Spatial data: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes
Department of the Interior —
Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools...