Bottom pressure measurements across the Antarctic circumpolar current and their relation to the wind

Wearn, R. B.; Baker, D. James

doi:10.1016/0198-0149(80)90001-1

Cited by 74 publications

(61 citation statements)

References 12 publications

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“…With simultaneous observations of OBP in different locations, the barotropic mass transport between the locations may be determined (Wearn and Baker 1980;Morison 1991). Ocean mass transport may be used to study overturning flow variations (Roussenov et al 2008), mass exchange between ocean basins (Hughes and Stepanov 2004;Stepanov and Hughes 2006;Chambers and Willis 2009), and freshwater changes in the ocean (Morison et al 2007(Morison et al , 2012.…”

Section: Introductionmentioning

confidence: 99%

Arctic Ocean Circulation Patterns Revealed by GRACE

et al. 2014

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Measurements of ocean bottom pressure (OBP) anomalies from the satellite mission Gravity Recovery and Climate Experiment (GRACE), complemented by information from two ocean models, are used to investigate the variations and distribution of the Arctic Ocean mass from 2002 through 2011. The forcing and dynamics associated with the observed OBP changes are explored. Major findings are the identification of three primary temporal-spatial modes of OBP variability at monthly-to-interannual time scales with the following characteristics. Mode 1 (50% of the variance) is a wintertime basin-coherent Arctic mass change forced by southerly winds through Fram Strait, and to a lesser extent through Bering Strait. These winds generate northward geostrophic current anomalies that increase the mass in the Arctic Ocean. Mode 2 (20%) reveals a mass change along the Siberian shelves, driven by surface Ekman transport and associated with the Arctic Oscillation. Mode 3 (10%) reveals a mass dipole, with mass decreasing in the Chukchi, East Siberian, and Laptev Seas, and mass increasing in the Barents and Kara Seas. During the summer, the mass decrease on the East Siberian shelves is due to the basin-scale anticyclonic atmospheric circulation that removes mass from the shelves via Ekman transport. During the winter, the forcing mechanisms include a large-scale cyclonic atmospheric circulation in the eastern-central Arctic that produces mass divergence into the Canada Basin and the Barents Sea. In addition, strengthening of the Beaufort high tends to remove mass from the East Siberian and Chukchi Seas. Supporting previous modeling results, the month-to-month variability in OBP associated with each mode is predominantly of barotropic character.

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Section: Introductionmentioning

confidence: 99%

Arctic Ocean Circulation Patterns Revealed by GRACE

et al. 2014

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“…Similar idealized solution was utilized in previous theoretical studies of barotropic ACC dynamics (Wearn and Baker 1980, Weijer and Gille 2005, Olbers and Lettmann 2007.…”

Section: Analytical Ode Modelmentioning

confidence: 99%

“…We wish to resolve the uncertainty due to the mechanisms governing this variability. It has been established (Wearn and Baker 1980, Withworth 1983, Meredith et al 2011) that the subannual variability is mainly barotropic. Accordingly, we will focus on the uncertainty of the barotropic ACC mechanisms.…”

Section: Uncertainty Of Drake Passage Transportmentioning

confidence: 99%

Uncertainty quantification in ocean state estimation

Kalmikov¹

2013

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Quantifying uncertainty and error bounds is a key outstanding challenge in ocean state estimation and climate research. It is particularly difficult due to the large dimensionality of this nonlinear estimation problem and the number of uncertain variables involved. The "Estimating the Circulation and Climate of the Oceans" (ECCO) consortium has developed a scalable system for dynamically consistent estimation of global timeevolving ocean state by optimal combination of ocean general circulation model (GCM) with diverse ocean observations. The estimation system is based on the "adjoint method" solution of an unconstrained least-squares optimization problem formulated with the method of Lagrange multipliers for fitting the dynamical ocean model to observations. The dynamical consistency requirement of ocean state estimation necessitates this approach over sequential data assimilation and reanalysis smoothing techniques. In addition, it is computationally advantageous because calculation and storage of large covariance matrices is not required. However, this is also a drawback of the adjoint method, which lacks a native formalism for error propagation and quantification of assimilated uncertainty. The objective of this dissertation is to resolve that limitation by developing a feasible computational methodology for uncertainty analysis in dynamically consistent state estimation, applicable to the large dimensionality of global ocean models.Hessian (second derivative-based) methodology is developed for Uncertainty Quantification (UQ) in large-scale ocean state estimation, extending the gradient-based adjoint method to employ the second order geometry information of the model-data misfit function in a high-dimensional control space. Large error covariance matrices are evaluated by inverting the Hessian matrix with the developed scalable matrix-free numerical linear algebra algorithms. Hessian-vector product and Jacobian derivative codes of the MIT general circulation model (MITgcm) are generated by means of algorithmic differentiation (AD). Computational complexity of the Hessian code is reduced by tangent linear differentiation of the adjoint code, which preserves the speedup of adjoint checkpointing schemes in the second derivative calculation. A Lanczos algorithm is applied for extracting the leading rank eigenvectors and eigenvalues of the Hessian matrix. The eigenvectors represent the constrained uncertainty patterns. The inverse eigenvalues are the corresponding uncertainties. The dimensionality of UQ calculations is reduced by eliminating the uncertainty null-space unconstrained by the 4 supplied observations. Inverse and forward uncertainty propagation schemes are designed for assimilating observation and control variable uncertainties, and for projecting these uncertainties onto oceanographic target quantities. Two versions of these schemes are developed: one evaluates reduction of prior uncertainties, while another does not require prior assumptions. The analysis of uncertainty propagation in the oc...

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“…Pressure records from 500m depth on both sides of Drake Passage during 1977 -1978 were obtained, which showed a strong semiannual signal (Wearn and Baker, 1980). Attempts have been made to relate the observed variability of sonal transport in Drake Passage to that of the wind stress over the Southern Ocean.…”

Section: Observational Backgroundmentioning

confidence: 99%

“…Wearn & Baker (1980) analyzed a 3-year time series of transport at Drake Passage inferred from the bottom pressure measurement on both sides of Drake Passage. They found a high correlation with the circumpolar-averaged zonal component of wind stress over the latitude band 400S -600S.…”

Section: Observational Backgroundmentioning

confidence: 99%

The dynamic role of ridges in a Beta-plane channel : towards understanding the dynamics of large scale circulation in the Southern Ocean

Wang¹

1993

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Bottom pressure measurements across the Antarctic circumpolar current and their relation to the wind

Cited by 74 publications

References 12 publications

Arctic Ocean Circulation Patterns Revealed by GRACE

Arctic Ocean Circulation Patterns Revealed by GRACE

Uncertainty quantification in ocean state estimation

The dynamic role of ridges in a Beta-plane channel : towards understanding the dynamics of large scale circulation in the Southern Ocean

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