Ocean Bottom Pressure Variability: Can It Be Reliably Modeled?.

Androsov, Alexey, Boebel, Olaf, Schröter, Jens, Danilov, Sergey, Macrander, Andreas and Ivanciu, Ioana (2020) Ocean Bottom Pressure Variability: Can It Be Reliably Modeled?. Journal of Geophysical Research: Oceans, 125 (3). DOI 10.1029/2019JC015469.

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Abstract

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.

Document Type: Article
Keywords: atmospheric loading; daily and monthly scales; in situ ocean bottom pressure; modeling OBP variability; pressure inverted echo sounder PIES
Research affiliation: OceanRep > GEOMAR > FB1 Ocean Circulation and Climate Dynamics > FB1-ME Maritime Meteorology
AWI
Refereed: Yes
Open Access Journal?: No
DOI etc.: 10.1029/2019JC015469
ISSN: 2169-9275
Related URLs:
Date Deposited: 06 Apr 2020 12:49
Last Modified: 28 Apr 2020 14:04
URI: http://oceanrep.geomar.de/id/eprint/49369

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