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).
Complete Metadata
| bureauCode |
[ "010:12" ] |
|---|---|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_5d98e0dbe4b0c4f70d1186f3 |
| spatial | -89.7037723045351, 46.002272195262, -89.6957319045477, 46.0152963952417 |
| theme |
[ "Geospatial" ] |
