Catalogue PIGMA
A Profile Classification Model from North-Atlantic Argo temperature data
A quantitative understanding of the integrated ocean heat content depends on our ability to determine how heat is distributed in the ocean and what are the associated coherent patterns. This dataset contains the results of the Maze et al., 2017 (Prog. Oce.) study demonstrating how this can be achieved using unsupervised classification of Argo temperature profiles.
The dataset contains:
- A netcdf file with classification~results (labels and probabilities) and coordinates (lat/lon/time) of 100,684 Argo temperature profiles in North Atlantic.
- A netcdf file with a Profile Classification Model (PCM) that can be used to classify new temperature profiles from observations or numerical models.
The classification method used is a Gaussian Mixture Model that decomposes the Probability Density Function of the dataset into a weighted sum of Gaussian modes. North Atlantic Argo temperature profiles between 0 and 1400m depth were interpolated onto a regular 5m grid, then compressed using Principal Component Analysis and finally classified using a Gaussian Mixture Model.
To use the netcdf PCM file to classify new data, you can checkout our PCM Matlab and Python toolbox here: https://github.com/obidam/pcm
Simple
- Date (Publication)
- 2017
- Date (Revision)
- 2021-05-12
- Other citation details
- Maze Guillaume (2017). A Profile Classification Model from North-Atlantic Argo temperature data. SEANOE. https://doi.org/10.17882/47106
- Credit
- Herlé Mercier, Ronan Fablet, Pierre Tandéo, Manuel Lopez Radcenco, Philippe Lenca, Charlène Feucher, Clément Le Goff
- Theme
-
- heat content
- classification
- North Atlantic
- stratification
- water mass
- argo
- profile
- pattern
- Physical oceanography
- Use limitation
- CC-BY (Creative Commons - Attribution)
- Use constraints
- Other restrictions
- Date (Publication)
- 2019
- Unique resource identifier
- 10.13155/61055
- Association Type
- Cross reference
- Initiative Type
- document
- Date (Publication)
- 2017
- Unique resource identifier
- 10.1016/j.pocean.2016.12.008
- Association Type
- Cross reference
- Initiative Type
- document
- Date (Publication)
- 2024
- Unique resource identifier
- 10.17882/42182
- Association Type
- Cross reference
- Initiative Type
- dataset
- Metadata language
- English
- Topic category
-
- Oceans
))
- Distribution format
-
-
NC, NETCDF
(
)
-
NC, NETCDF
(
)
- OnLine resource
-
Processed data
(
WWW:DOWNLOAD-1.0-link--download
)
Profile Classification Model - 56 KB
- OnLine resource
-
Processed data
(
WWW:DOWNLOAD-1.0-link--download
)
Classification results - 16 MB
- OnLine resource
- Get the data via ERDDAP ( WWW:LINK )
- OnLine resource
- DOI of the product ( WWW:LINK-1.0-http--metadata-URL )
- OnLine resource
- Seanoe ( rel-canonical )
- Hierarchy level
- Dataset
- File identifier
- seanoe:47106 XML
- Metadata language
- English
- Character set
- UTF8
- Hierarchy level
- Dataset
- Date stamp
- 2021-05-12
- Metadata standard name
- ISO 19115:2003/19139
- Metadata standard version
- 1.0
Overviews
Spatial extent
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