Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing ‐ comparisons with observations

Carrère, Loren; Lyard, Florent

doi:10.1029/2002gl016473

Cited by 591 publications

(463 citation statements)

References 15 publications

Supporting

Mentioning

457

Contrasting

Order By: Relevance

“…Bindoff et al, 2007). This was evidenced by the comparison between altimetrybased and steric trend patterns deduced from in-situ hydrographic measurements (Ishii and Kimoto, 2009;Levitus, 2005;Levitus et al, 2009;Lombard et al, 2005a, b) and ocean general circulation models (OGCMs) outputs (Wunsch et al, 2007;Kohl and Stammer, 2008;Carton and Giese, 2008;Lombard et al, 2009). Analyses of in situ ocean temperature measurements showed that the thermosteric component is the most important contribution to the observed sea level regional variability.…”

Section: Introductionmentioning

confidence: 99%

“…It is corrected for the long wavelength orbit errors , ocean tides, and wet/dry troposphere and ionosphere (see Ablain et al, 2009 for more details). The inverted barometer (IB) correction has also been applied in order to minimize aliasing effects (Volkov et al, 2007) through the MOG2D barotropic model correction that includes the dynamic ocean response to short period (<20 day) atmospheric wind and pressure forcing and the static IB correction at periods above 20 day (see Carrere and Lyard, 2003 for details).…”

Section: Satellite Altimetry Sea Level Data (1993-2009)mentioning

confidence: 99%

See 1 more Smart Citation

Tropical Pacific spatial trend patterns in observed sea level: internal variability and/or anthropogenic signature?

et al. 2012

View full text Add to dashboard Cite

Abstract. In this study we focus on the sea level trend pattern observed by satellite altimetry in the tropical Pacific over the 1993-2009 time span (i.e. 17 yr). Our objective is to investigate whether this 17-yr-long trend pattern was different before the altimetry era, what was its spatio-temporal variability and what have been its main drivers. We try to discriminate the respective roles of the internal variability of the climate system and of external forcing factors, in particular anthropogenic emissions (greenhouse gases and aerosols). On the basis of a 2-D past sea level reconstruction over 1950-2009 (based on a combination of observations and ocean modelling) and multi-century control runs (i.e. with constant, preindustrial external forcing) from eight coupled climate models, we have investigated how the observed 17-yr sea level trend pattern evolved during the last decades and centuries, and try to estimate the characteristic time scales of its variability. For that purpose, we have computed sea level trend patterns over successive 17-yr windows (i.e. the length of the altimetry record), both for the 60-yr long reconstructed sea level and the model runs. We find that the 2-D sea level reconstruction shows spatial trend patterns similar to the one observed during the altimetry era. The pattern appears to have fluctuated with time with a characteristic time scale of the order of 25-30 yr. The same behaviour is found in multicentennial control runs of the coupled climate models. A similar analysis is performed with 20th century coupled climate model runs with complete external forcing (i.e. solar plus volcanic variability and changes in anthropogenic forcing). Results suggest that in the tropical Pacific, sea level trend fluctuations are dominated by the internal variability of the ocean-atmosphere coupled system. While our analysis cannot rule out any influence of anthropogenic forcing, it concludes that the latter effect in that particular region is still hardly detectable.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Satellite Altimetry Sea Level Data (1993-2009)mentioning

confidence: 99%

Tropical Pacific spatial trend patterns in observed sea level: internal variability and/or anthropogenic signature?

et al. 2012

View full text Add to dashboard Cite

show abstract

“…A numerical model that accurately represents high-frequency sea level variability, such as the model of Carrère and Lyard (2003), would be very useful for removing high-frequency signals and thus leaving behind the lower-frequency sea level variability.…”

Section: November 2014 K U S a H A R A A N D O H S H I M Amentioning

confidence: 99%

Kelvin Waves around Antarctica

Kusahara

Ohshima

2014

Journal of Physical Oceanography

View full text Add to dashboard Cite

The Southern Ocean allows circumpolar structure and the Antarctic coastline plays a role as a waveguide for oceanic Kelvin waves. Under the cyclic conditions, the horizontal wavenumbers and frequencies for circumpolarly propagating waves are quantized, with horizontal wavenumbers 1, 2, and 3, corresponding to periods of about 32, 16, and 11 h, respectively. At these frequencies, westward-propagating signals are detected in sea level variation observed at Antarctic coastal stations. The occurrence frequency of westward-propagating signals far exceeds the statistical significance, and the phase speed of the observed signal agrees well with the theoretical phase speed of external Kelvin waves. Therefore, this study concludes that the observed, westward-propagating sea level variability is a signal of the external Kelvin waves of wavenumbers 1, 2, and 3 around Antarctica. A series of numerical model experiments confirms that Kelvin waves around Antarctica are driven by surface air pressure and that these waves are excited not only by local forcing over the Southern Ocean, but also by remote forcing over the Pacific Ocean. Sea level variations generated over the Pacific Ocean can travel to the western side of the South American coast and cross over Drake Passage to the Antarctic continent, constituting a part of the Kelvin waves around Antarctica.

show abstract

“…Along track sea-level data are corrected for long wavelength errors (Traon et al 1998;Le Traon et al 2003) and an estimate of the inverse barometer (IB) effect is subtracted as well as wind and tidal effects in addition to other atmospheric corrections (taken together these are called dynamic atmospheric corrections; Carrère and Lyard 2003). The dynamic atmospheric Starting with different satellite along-track data, the different SLA signals are interpolated with objective analyses (Ducet et al 2000), thereby producing a field on a regular grid with a horizontal resolution of 1/8 • (∼ 13 km), every seven days.…”

Section: Satellite Datamentioning

confidence: 99%

Sea-level variability in the Mediterranean Sea from altimetry and tide gauges

et al. 2016

View full text Add to dashboard Cite

mean sea-level and the coastal stations. From 1993 to 2012, the mean sea-level trend (2.44 ± 0.5 mm year −1 ) was found to be affected by the positive anomalies of 2010 and 2011, which were observed in all the cases analysed and were mainly distributed in the eastern part of the basin. Ensemble empirical mode decomposition showed that these events were related to the processes that have dominant periodicities of ∼10 years, and positive residual sea-level trend were generally observed in both data-sets. In terms of mean sea-level trends, a significant positive sea-level trend (>95 %) in the Mediterranean Sea was found on the basis of at least 15 years of data.

show abstract

Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing ‐ comparisons with observations

Cited by 591 publications

References 15 publications

Tropical Pacific spatial trend patterns in observed sea level: internal variability and/or anthropogenic signature?

Tropical Pacific spatial trend patterns in observed sea level: internal variability and/or anthropogenic signature?

Kelvin Waves around Antarctica

Sea-level variability in the Mediterranean Sea from altimetry and tide gauges

Contact Info

Product

Resources

About