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Federal
Projected Future LOCA Statistical Downscaling (Localized Constructed Analogs) Statistically downscaled CMIP5 climate projections for North America 16 recent views
Department of the Interior —
LOCA is a statistical downscaling technique that uses past history to add improved fine-scale detail to global climate models. We have used LOCA to downscale 32... -
Federal
North Pacific Nearshore Sea Surface Temperature (SST) shapefile format (1981-2009)
Department of the Interior —
The Sea Surface Temperature (SST) data of the nearshore region of the North Pacific show temperature ranges in degrees C using points whose locations correspond to... -
Federal
Hydrology and climate elements on the Rio Grande/Bravo basin
Department of the Interior —
This is one of five general categories that contain the water related elements of the Rio Grande/Bravo basin. This category includes some of hydrologic and climatic... -
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: 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
Water balance across regional climate gradients: A comparison of two potential evapotranspiration metrics (1980-2099).
Department of the Interior —
Historical and projected climate data and water balance data under three GCMs (CNRM-CM5, CCSM4, and IPSL-CM5A-MR) from 1980 to 2099 was used to assess projected... -
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
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: 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)... -
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: 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: 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)... -
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
4-km North Pacific Nearshore Sea Surface Temperature (SST) ESRI GRID format (1981-2009)
Department of the Interior —
The Sea Surface Temperature (SST) data of the nearshore region of the North Pacific show temperature ranges in degrees C using points whose locations correspond to... -
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
Data release: Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes
Department of the Interior —
Climate change and land use change have been shown to influence lake temperatures and water clarity in different ways. To better understand the diversity of lake... -
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: 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: 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...