Mesoscale characteristics

Jacobs, Gregg A.; Barron, Charlie N.; Rhodes, Robert C.

doi:10.1029/2000jc000669

Cited by 65 publications

(53 citation statements)

References 37 publications

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“…The estimated zonal and meridional correlation scales are 130 and 110 km respectively. This is consistent with results derived from altimeter data analysis in midlatitude regions (e.g., Kuragano and Kamachi, 2000;Jacobs et al, 2001;Le Traon et al, 2003). Correlation scales are significantly larger at 1000 m (Fig.…”

Section: Resultssupporting

confidence: 81%

“…Zonal and meridional scales are estimated to about 900 and 350 km. The zonal scales are smaller than those derived from TAO observations and larger than those derived from altimeter data (e.g., Kessler et al, 1996;Jacobs et al, 2001). This may be due to both the techniques used to compute scales (e.g., removing of large-scale signals before computing altimeter spatial scales) and the sparse spatial sampling of TAO observations.…”

Section: Resultsmentioning

confidence: 86%

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Spatial scales of temperature and salinity variability estimated from Argo observations

et al. 2016

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× 20 • boxes. Spatial scales are then computed over several large-scale areas. Zonal and meridional spatial scales (L x and L y which are zero crossing of covariance functions) vary as expected with latitudes. Scales are of about 100 km at high latitudes and more of 700 km in the Indian and Pacific equatorial-tropical regions. Zonal and meridional scales are similar except in tropical-equatorial regions where zonal scales are much larger (by a factor of 2 to 3) than meridional scales. Spatial scales are the largest close to the surface and have a general tendency for temperature to increase in deeper layers. There are significant differences between temperature and salinity scales, in particular, in the deep ocean. Results are consistent with previous studies based on sparse in situ observations or satellite altimetry. They provide, however, for the first time a global description of temperature and salinity scales of variability and a characterization of their variations according to depths.

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Section: Resultssupporting

confidence: 81%

Section: Resultsmentioning

confidence: 86%

Spatial scales of temperature and salinity variability estimated from Argo observations

et al. 2016

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“…It has also allowed a better characterization of space and time scales of mesoscale variability (e.g. Ducet et al, 2000;Jacobs et al, 2001), eddy propagation velocity (e.g. Brachet et al, 2004;Morrow et al, 2004;Fu, 2009;Chelton et al, 2007Chelton et al, , 2011b, anisotropy (e.g.…”

Section: P Y Le Traon: From Satellite Altimetry To Argo and Operatimentioning

confidence: 99%

From satellite altimetry to Argo and operational oceanography: three revolutions in oceanography

Traon

2013

Ocean Sci.

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Abstract. The launch of the French/US mission Topex/Poseidon (T/P) (CNES/NASA) in August 1992 was the start of a revolution in oceanography. For the first time, a very precise altimeter system optimized for largescale sea level and ocean circulation observations was flying. T/P alone could not observe the mesoscale circulation. In the 1990s, the ESA satellites ERS-1/2 were flying simultaneously with T/P. Together with my CLS colleagues, we demonstrated that we could use T/P as a reference mission for ERS-1/2 and bring the ERS-1/2 data to an accuracy level comparable to T/P. Near-real-time high-resolution global sea level anomaly maps were then derived. These maps have been operationally produced as part of the SSALTO/DUACS system for the last 15 yr. They are now widely used by the oceanographic community and have contributed to a much better understanding and recognition of the role and importance of mesoscale dynamics. Altimetry needs to be complemented with global in situ observations. At the end of the 90s, a major international initiative was launched to develop Argo, the global array of profiling floats. This has been an outstanding success. Argo floats now provide the most important in situ observations to monitor and understand the role of the ocean on the earth climate and for operational oceanography. This is a second revolution in oceanography. The unique capability of satellite altimetry to observe the global ocean in near-real-time at high resolution and the development of Argo were essential for the development of global operational oceanography, the third revolution in oceanography. The Global Ocean Data Assimilation Experiment (GODAE) was instrumental in the development of the required capabilities. This paper provides an historical perspective on the development of these three revolutions in oceanography which are very much interlinked. This is not an exhaustive review and I will mainly focus on the contributions we made together with many colleagues and friends.

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“…Real time satellite altimeter data (Geosat-Follow-On (GFO), ENVISAT, and Jason-i) are provided via the Altimeter Data Fusion Center (ADFC) at NAVOCEANO to generate the two-dimensional Modular Ocean Data Assimilation System (MODAS) SSH (1/40) analysis (Fox et al, 2002) that is assimilated daily. The MODAS analysis is an 01 technique which is using a complex covariance function that includes spatially varying length and time scales as well as propagation terms derived from many years of altimetry (Jacobs et al, 2001). The model sea surface temperature is relaxed to the daily MODAS 1/8' SST analysis which uses daily Multi-Channel Sea Surface Temperature (MCSST) data derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) -globally at 8.8 km resolution and at 2 km in selected regions.…”

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confidence: 99%

Ocean Prediction with the Hybrid Coordinate Ocean Model (HYCOM)

Chassignet

Hurlburt

Smedstad

et al.

Ocean Weather Forecasting

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Mesoscale characteristics

Cited by 65 publications

References 37 publications

Spatial scales of temperature and salinity variability estimated from Argo observations

Spatial scales of temperature and salinity variability estimated from Argo observations

From satellite altimetry to Argo and operational oceanography: three revolutions in oceanography

Ocean Prediction with the Hybrid Coordinate Ocean Model (HYCOM)

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