Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs
Data e Risorse
-
two comma separated text files
CSDGM IMPORT ERROR: No digtinfo/formcont
-
Web Resource
-
Web Resource
-
Web Resource
-
Web Resource
-
Original MetadataXML
The metadata original source
| Campo | Valore |
|---|---|
| accessLevel | public |
| bureauCode | {010:00} |
| catalog_@context | https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld |
| catalog_conformsTo | https://project-open-data.cio.gov/v1.1/schema |
| catalog_describedBy | https://project-open-data.cio.gov/v1.1/schema/catalog.json |
| datagov_dedupe_retained | 20220721161856 |
| identifier | 6015582d-4602-4f90-aeb7-0aed108f9721 |
| metadata_type | geospatial |
| modified | 2020-08-20 |
| old-spatial | {"type": "Polygon", "coordinates": [[[-89.4836545049, 43.0771195331], [-89.3674075051, 43.0771195331], [-89.3674075051, 43.1520341997], [-89.4836545049, 43.1520341997], [-89.4836545049, 43.0771195331]]]} |
| publisher | Climate Adaptation Science Centers |
| resource-type | Dataset |
| source_datajson_identifier | true |
| source_hash | 1b08ab48cbc8b899bb999b09da7930c59fce4d24 |
| source_schema_version | 1.1 |
| spatial | {"type": "Polygon", "coordinates": [[[-89.4836545049, 43.0771195331], [-89.3674075051, 43.0771195331], [-89.3674075051, 43.1520341997], [-89.4836545049, 43.1520341997], [-89.4836545049, 43.0771195331]]]} |
| theme | {geospatial} |
| Gruppi |
|
| Tag |
|
| 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 | 2025-11-22T22:04:25.257593 |
| metadata_modified | 2025-11-22T22:04:25.257597 |
| notes | 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). |
| num_resources | 6 |
| num_tags | 20 |
| title | Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs |