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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... -
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: 5 Model prediction data
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-... -
Data release: Process-based predictions of lake water temperature in the Midwest US
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 tools to... -
Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs
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 gridded... -
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 4...
This dataset includes model inputs (specifically, weather, water clarity, and flags for predicted ice-cover) and is part of a larger data release of lake temperature model... -
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 5...
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 models used... -
Daily surface temperature predictions for 185,549 U.S. lakes with associated...
Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep... -
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 3...
This dataset provides model parameters used to estimate water temperature from a process-based model (Hipsey et al. 2019) using uncalibrated model configurations (PB0) and the... -
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,... -
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: 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... -
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... -
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 4...
This dataset includes model inputs (specifically, weather, water clarity, and flags for predicted ice-cover) and is part of a larger data release of lake temperature model... -
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 7...
Using predicted lake temperatures from uncalibrated, process-based models (PB0) and process-guided deep learning models (PGDL), this dataset summarized a collection of thermal... -
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,... -
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: 5 Model...
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. General... -
Thermal metrics: 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...