Process-guided deep learning water temperature predictions: 3c All lakes historical inputs

Description

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 al. 2004). There are two comma-separated 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).

Resources

Name Format Description Link
55 The metadata original source https://data.doi.gov/harvest/object/47f24243-050c-4893-9571-c7c0dd824b6c
0 https://doi.org/10.5194/gmd-12-473-2019
0 http://dx.doi.org/10.1029/2019WR024922
0 http://dx.doi.org/10.1029/2003JD003823
0 http://dx.doi.org/10.5066/P9AQPIVD

Tags

  • reservoirs
  • hybrid-modeling
  • usgs-5d98e0a3e4b0c4f70d1186ee
  • modeling
  • temperate-lakes
  • deep-learning
  • united-states
  • thermal-profiles
  • us
  • climate-change
  • water
  • temperature
  • machine-learning

Topics

Categories