{"accessLevel": "public", "bureauCode": ["010:12"], "contactPoint": {"@type": "vcard:Contact", "fn": "Jordan S. Read", "hasEmail": "mailto:jread@usgs.gov"}, "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).", "distribution": [{"@type": "dcat:Distribution", "accessURL": "http://dx.doi.org/10.5066/P9AQPIVD", "description": "Landing page for access to the data", "format": "XML", "mediaType": "application/http", "title": "Digital Data"}, {"@type": "dcat:Distribution", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.5d98e0c4e4b0c4f70d1186f1.xml", "format": "XML", "mediaType": "text/xml", "title": "Original Metadata"}], "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5d98e0c4e4b0c4f70d1186f1", "keyword": ["biota", "inlandWaters", "United States", "environment", "US", "reservoirs", "deep learning", "machine learning", "temperature", "USGS:5d98e0c4e4b0c4f70d1186f1", "modeling", "climate change", "Wisconsin", "WI", "hybrid modeling", "thermal profiles", "water", "temperate lakes"], "modified": "2020-08-20T00:00:00Z", "publisher": {"@type": "org:Organization", "name": "U.S. Geological Survey"}, "spatial": "-89.4836545048768, 43.0771195331357, -89.3674075050573, 43.1520341996861", "theme": ["geospatial"], "title": "Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs"}