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Federal
Temperature 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... -
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
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 3 Model configurations (lake model parameter values)
Department of the Interior —
This dataset provides model parameters used to estimate water temperature from a process-based model (Hipsey et al. 2019) using uncalibrated model configurations... -
Federal
Process-guided deep learning water temperature predictions: 4a Lake Mendota detailed training data
Department of the Interior —
This dataset includes compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature records from... -
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: 4 Training data
Department of the Interior —
This dataset includes compiled water temperature data from a variety of sources, including the Water Quality Portal (Read et al. 2017), the North Temperate Lakes... -
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
Process-guided deep learning water temperature predictions: 6a Lake Mendota detailed evaluation data
Department of the Interior —
This dataset includes "test data" compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature... -
Federal
Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs
Department of the Interior —
This dataset includes model inputs that describe local weather conditions for Lake Mendota, WI. Weather data comes from two sources: locally measured (2009-2017) and... -
Federal
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 6 model evaluation
Department of the Interior —
Water temperature estimates from multiple models were evaluated by comparing predictions to observed water temperatures. The performance metric of root-mean square... -
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
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 1 Lake information for 881 lakes
Department of the Interior —
This dataset provides shapefile outlines of the 881 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined (.shp,... -
Federal
Process-based water temperature predictions in the Midwest US: 1 Spatial data (GIS polygons for 7,150 lakes)
Department of the Interior —
This dataset provides shapefile outlines of the 7,150 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined... -
Federal
Data release: 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: 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
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-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes)
Department of the Interior —
This dataset provides shapefile of outlines of the 68 lakes where temperature was modeled as part of this study. The format is a shapefile for all lakes combined... -
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-guided deep learning water temperature predictions: 3c All lakes historical inputs
Department of the Interior —
This dataset includes model inputs that describe weather conditions for the 68 lakes included in this study. Weather data comes from gridded estimates (Mitchell et... -
Federal
Process-guided deep learning water temperature predictions: 6 Model evaluation (test data and RMSE)
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)...