Ocean bottom pressure signals around Southern Africa from in situ measurements, satellite data, and modeling

Kuhlmann, Julian; Dobslaw, Henryk; Petrick, Christof; Thomas, Maik

doi:10.1002/jgrc.20372

Cited by 6 publications

(6 citation statements)

References 44 publications

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“…This area includes the Agulhas Current and the Antarctic Circumpolar Current characterized by high eddy activity; therefore, the effects of eddies on the OBP variability, if essential, should be visible in these regions. As noted by Kuhlmann et al (2013), the OBP variability in this region, in addition to the eddy activity pattern, is also related to coastal and topographic features leading to characteristic resonances that can be excited by local wind fields, affecting the turbulence-induced variability of OBP. We begin with the brief description of OBP data set used here (section 2).…”

Section: Introductionmentioning

confidence: 80%

Ocean Bottom Pressure Variability: Can It Be Reliably Modeled?

et al. 2020

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Ocean bottom pressure (OBP) variability serves as a proxy of ocean mass variability, the knowledge of which is needed in geophysical applications. The question of how well it can be modeled by the present general ocean circulation models on time scales in excess of 1 day is addressed here by comparing the simulated OBP variability with the observed one. To this end, a new multiyear data set is used, obtained with an array of bottom pressure gauges deployed deeply along a transect across the Southern Ocean. We present a brief description of OBP data and show large‐scale correlations over several thousand kilometers at all time scales using daily and monthly averaged data. Annual and semiannual cycles are weak. Close to the Agulhas Retroflection, signals of up to 30 cm equivalent water height are detected. Further south, signals are mostly intermittent and noisy. It is shown that the models simulate consistent patterns of bottom pressure variability on monthly and longer scales except for areas with high mesoscale eddy activity, where high resolution is needed to capture the variability due to eddies. Furthermore, despite good agreement in the amplitude of variability, the in situ and simulated OBP show only modest correlation.

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Section: Introductionmentioning

confidence: 80%

Ocean Bottom Pressure Variability: Can It Be Reliably Modeled?

et al. 2020

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“…In the tropical western Pacific (Region A) and southeastern South Indian Ocean (Region B), the annual cycle of OBP, sea level and steric anomalies simulated by the model are quite similar to the observations (Figs. 2 and 5) and results based on volume-conserving models 1a) (e.g., Ponte 1999;Ponte et al 2007;Bingham and Hughes 2008;Köhl et al 2012;Kuhlmann et al 2013;Poropat et al 2018;Androsov et al 2020). Figures 4 and 5 indicate that the PCOM can simulate the seasonal cycle of regional OBP quite well; thus, this model can be used to study the dynamics of OBP variability.…”

Section: Simulated Obp From Pcom Modelmentioning

confidence: 86%

“…Besides satellite and hydrographic observations, numerical models can also serve as good tools for the study of sea level variations and correlative physical processes. However, most currently used models are based on the Boussinesq approximations (e.g., Ponte 1999;Ponte et al 2007;Bingham and Hughes 2008;Köhl et al 2012;Kuhlmann et al 2013;Poropat et al 2018;Androsov et al 2020); such models cannot properly represent the OBP changes associated with thermal expansion or contraction. Surface heating gives rise to decline of bottom pressure in the Boussinesq models; while in a mass-conserving model surface heating/cooling does not directly change bottom pressure.…”

Section: Introductionmentioning

confidence: 99%

On the seasonal variations of ocean bottom pressure in the world oceans

Cheng

Chen

et al. 2021

Geosci. Lett.

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Seasonal variability of the ocean bottom pressure (OBP) in the world oceans is investigated using 15 years of GRACE observations and a Pressure Coordinate Ocean Model (PCOM). In boreal winter, negative OBP anomalies appear in the northern North Pacific, subtropical South Pacific and north of 40 °S in the Indian Ocean, while OBP anomaly in the Southern Ocean is positive. The summer pattern is opposite to that in winter. The centers of positive (negative) OBP signals have a good coherence with the mass convergence/divergence due to Ekman transport, indicating the importance of wind forcing. The PCOM model reproduces the observed OBP quite well. Sensitivity experiments indicate that wind forcing dominates the regional OBP seasonal variations, while the contributions due to heat flux and freshwater flux are unimportant. Experiments with daily sea level pressure (SLP) forcing suggest that at high frequencies the non-static effect of SLP is not negligible.

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“…The oceanic components of all currently available AOD models rely on either barotropic (Carrère and Lyard , 2003) or baroclinic (Thomas et al, 2001) global ocean circulation models forced with atmospheric data from numerical weather models that do not assimilate any type of high-frequency observational data. Such simulations typically exclude meso-scale variability and small-scale eddies, which are primarily near-surface features but partially have also bottom pressure signatures in particularly energy-rich areas of the world's ocean (Kuhlmann et al, 2013).…”

Section: Oceanic Signals Omitted In Aod Modelsmentioning

confidence: 99%