Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs
Description
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 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).
Resources
| Name |
Format |
Description |
Link |
|
55 |
Landing page for access to the data |
http://dx.doi.org/10.5066/P9AQPIVD |
|
55 |
The metadata original format |
https://data.usgs.gov/datacatalog/metadata/USGS.5d98e0c4e4b0c4f70d1186f1.xml |
Tags
- environment
- reservoirs
- hybrid-modeling
- modeling
- biota
- temperate-lakes
- deep-learning
- wi
- united-states
- thermal-profiles
- us
- inlandwaters
- climate-change
- usgs-5d98e0c4e4b0c4f70d1186f1
- water
- temperature
- wisconsin
- machine-learning