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Dataset for "Forecasting Coastal Hypoxia Using a Blend of Numeric and Artificial Intelligence Models"

Authors:
Owners:		This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource.
Type:	Resource
Storage:	The size of this resource is 1.4 GB
Created:	Nov 01, 2023 at 9:04 p.m. (UTC)
Last updated:	Jul 09, 2024 at 10:30 p.m. (UTC)
Citation:	See how to cite this resource
Content types:	Multidimensional Content

Sharing Status:	Public
Views:	2014
Downloads:	24
+1 Votes:	1 other +1 this
Comments:	No comments (yet)

Abstract

Dataset (splitted into 14 files due to file size limitation) for training, validating, and evaluating AI model which was developed for daily hypoxia prediction in the Louisiana-Texas shelf. The dateset is derived from a coupled hydrodynamic-biogeochemical model embedded in the Regional Ocean Modeling System. External dataset from three independent hydrodynamic forecast products: HYCOM, NEMO, and FVCOM.

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Coverage

Spatial

Coordinate System/Geographic Projection:

WGS 84 EPSG:4326

Coordinate Units:

Decimal degrees

North Latitude

30.8105°

East Longitude

-87.7307°

South Latitude

27.1777°

West Longitude

-98.0649°

Temporal

Start Date:
End Date:

Content

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Data Services

The following web services are available for data contained in this resource. Geospatial Feature and Raster data are made available via Open Geospatial Consortium Web Services. The provided links can be copied and pasted into GIS software to access these data. Multidimensional NetCDF data are made available via a THREDDS Data Server using remote data access protocols such as OPeNDAP. Other data services may be made available in the future to support additional data types.

THREDDS Data Service

https://thredds.hydroshare.org/thredds/catalog/hydroshare/resources/0cc2093cc67543fd82b06d6b5b9c79e4/data/contents/catalog.html

THREDDS Documentation OPeNDAP Documentation

How to Cite

Ou, Y. (2024). Dataset for "Forecasting Coastal Hypoxia Using a Blend of Numeric and Artificial Intelligence Models", HydroShare, http://www.hydroshare.org/resource/0cc2093cc67543fd82b06d6b5b9c79e4

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/

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