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Process-guided deep learning water temperature predictions: 4a Lake Mendota...
This dataset includes compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature records from North... -
Process-guided deep learning water temperature predictions: 4b Sparkling...
This dataset includes compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature records from North... -
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 2...
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 temperature... -
Process-based water temperature predictions in the Midwest US: 1 Spatial...
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 (.shp, .shx,... -
Process-based water temperature predictions in the Midwest US: 1 Spatial...
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 (.shp, .shx,... -
Process-guided deep learning water temperature predictions: 2 Model...
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 indexed for each... -
Process-guided deep learning water temperature predictions: 6c All lakes...
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB) models were... -
Process-guided deep learning water temperature predictions: 3 Model inputs...
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 outputs... -
Process-guided deep learning water temperature predictions: 4c All lakes...
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 learning... -
Process-guided deep learning water temperature predictions: 6a Lake Mendota...
This dataset includes "test data" compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature records from... -
Model configuration: A large-scale database of modeled contemporary and...
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 to manage... -
Data release: Process-based predictions of lake water temperature in the Midwest US
<p>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 managers... -
Process-guided deep learning water temperature predictions: 1 Spatial data...
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 (.shp, .shx,... -
Temperature data: A large-scale database of modeled contemporary and future...
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 to manage... -
Process-guided deep learning water temperature predictions: 6 Model...
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB) models were... -
Process-guided deep learning water temperature predictions: 5c All lakes...
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. Process-... -
Process-guided deep learning water temperature predictions: 4b Sparkling...
This dataset includes compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature records from North... -
Process-based water temperature predictions in the Midwest US: 6 Habitat metrics
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) and 449... -
Process-based water temperature predictions in the Midwest US: 3 Temperature...
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 process-based... -
Process-guided deep learning water temperature predictions: 6c All lakes...
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB) models were...