Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs

This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).

Data and Resources

Field Value
accessLevel public
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identifier eda1bee5-e03d-4658-9b01-e9e2e0b3e0cd
metadata_type geospatial
modified 2020-08-20
old-spatial {"type": "Polygon", "coordinates": [[[-89.7037723045, 46.0022721953], [-89.6957319045, 46.0022721953], [-89.6957319045, 46.0152963952], [-89.7037723045, 46.0152963952], [-89.7037723045, 46.0022721953]]]}
publisher Climate Adaptation Science Centers
resource-type Dataset
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theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • ckan
  • climate-change
  • deep-learning
  • geo
  • geoss
  • hybrid-modeling
  • machine-learning
  • modeling
  • national
  • north-america
  • reservoirs
  • temperate-lakes
  • temperature
  • thermal-profiles
  • united-states
  • us
  • usgs-5d98e0dbe4b0c4f70d1186f3
  • water
isopen False
license_id notspecified
license_title License not specified
maintainer U.S. Geological Survey (Point of Contact)
maintainer_email jread@usgs.gov
metadata_created 2025-11-21T09:54:51.991089
metadata_modified 2025-11-21T09:54:51.991093
notes This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).
num_resources 4
num_tags 20
title Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs