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Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags)

Metadata Updated: October 28, 2023

This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and 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).

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date May 31, 2023
Metadata Updated Date October 28, 2023

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date May 31, 2023
Metadata Updated Date October 28, 2023
Publisher Climate Adaptation Science Centers
Maintainer
@Id http://datainventory.doi.gov/id/dataset/f1ec6016798aa85c9446c91c2bc9173d
Identifier e1b7de03-92ae-44fe-a737-63bf107a858f
Data Last Modified 2020-08-20
Category geospatial
Public Access Level public
Bureau Code 010:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 25a5cdd2-35d0-4468-bcfd-3a1fde9d6df8
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -94.2609062308,42.5692312673,-87.9475441739,48.6427837912
Source Datajson Identifier True
Source Hash 9c1c784ec017b3866ad188b29680344e071c81306cfdc670cd326cbeb07493c5
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -94.2609062308, 42.5692312673, -94.2609062308, 48.6427837912, -87.9475441739, 48.6427837912, -87.9475441739, 42.5692312673, -94.2609062308, 42.5692312673}

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