Storto, Andrea; Masina, Simona (2016): The CMCC Eddy-permitting Global Ocean Physical Reanalysis (C-GLORS v5, 1980-2014), links to NetCDF files [dataset]. Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy, PANGAEA, https://doi.org/10.1594/PANGAEA.857995
Always quote citation above when using data! You can download the citation in several formats below.
Abstract:
The CMCC Global Ocean Physical Reanalysis System (C-GLORS) is used to simulate the state of the ocean in the last decades. It consists of a variational data assimilation system (OceanVar), capable of assimilating all in-situ observations along with altimetry data, and a forecast step performed by the ocean model NEMO coupled with the LIM2 sea-ice model.
KEY STRENGTHS:
- Data are available for a large number of ocean parameters
- An extensive validation has been conducted and is freely available
- The reanalysis is performed at high resolution (1/4 degree) and spans the last 30 years
KEY LIMITATIONS:
- Quality may be discontinuos and depend on observation coverage
- Uncertainty estimates are simply derived through verification skill scores
Note (2017-02-09): C-GLORSv5 is dissemniated on PANGAEA at reduced resolution, i.e. a regular 0.5x0.5 degree grid. For full resolution data sets see "CMCC Global Ocean Reanalysis System (C-GLORS), external website" (Related to:)
Related to:
CMCC Global Ocean Reanalysis System (C-GLORS), external website [webpage]. http://c-glors.cmcc.it/index/index.html
Good, Simon A; Martin, Matthew J; Rayner, Nick A (2013): EN4: Quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates. Journal of Geophysical Research: Oceans, 118(12), 6704-6716, https://doi.org/10.1002/2013JC009067
Madec, Gurvan (2015): NEMO ocean engine. Note du Pole de modélisation de l' Institut Pierre-Simon Laplace, Paris, France, 27, 401 pp, hdl:10013/epic.46840.d001
Markus, Thorsten; Cavalieri, Donald J (2000): An enhancement of the NASA Team sea ice algorithm. IEEE Transactions on Geoscience and Remote Sensing, 38(3), 1387-1398, https://doi.org/10.1109/36.843033
Reynolds, Richard W; Smith, Thomas M; Liu, Chunying; Chelton, Dudley B; Casey, Kenneth S; Schlax, Michael G (2007): Daily High-Resolution-Blended analyses for sea surface temperature. Journal of Climate, 20(22), 5473-5496, https://doi.org/10.1175/2007JCLI1824.1
Storto, Andrea; Masina, Simona; Navarra, Antonio (2015): Evaluation of the CMCC eddy-permitting global ocean physical reanalysis system (C-GLORS, 1982-2012) and its assimilation components. Quarterly Journal of the Royal Meteorological Society, 21 pp, https://doi.org/10.1002/qj.2673
Zhang, Jinlun; Rothrock, Drew A (2003): Modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates. Monthly Weather Review, 131(5), 845-861, https://doi.org/10.1175/1520-0493(2003)131%3C0845:MGSIWA%3E2.0.CO;2
Coverage:
Date/Time Start: 1980-01-01T00:00:00 * Date/Time End: 2014-12-31T23:59:59
Parameter(s):
# | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
---|---|---|---|---|---|---|
1 | DATE/TIME | Date/Time | Storto, Andrea | Geocode | ||
2 | File name | File name | Storto, Andrea | |||
3 | File size | File size | kByte | Storto, Andrea | ||
4 | Uniform resource locator/link to file | URL file | Storto, Andrea | NetCDF in gzip archives |
License:
Creative Commons Attribution 3.0 Unported (CC-BY-3.0)
Size:
2841 data points
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