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Richard E. Thomson and Isaac V. Fine

Abstract

This paper presents a simple diagnostic model for estimating mixed layer depth based solely on the one-dimensional heat balance equation, the surface heat flux, and the sea surface temperature. The surface fluxes drive heating or cooling of the upper layer whereas the surface temperature acts as a “thermostat” that regulates the vertical extent of the layer. Daily mixed layer depth estimates from the diagnostic model (and two standard bulk mixed layer models) are compared with depths obtained from oceanic profiles collected during the 1956–80 Canadian Weathership program at Station P and more recent (2001–07) profiles from the vicinity of this station from Argo drifters. Summer mixed layer depths from the diagnostic model agree more closely with observed depths and are less sensitive to heat flux errors than those from bulk models. For the Weathership monitoring period, the root-mean-square difference between modeled and observed monthly mean mixed layer depths is ∼6 m for the diagnostic model and ∼10 m for the bulk models. The diagnostic model is simpler to apply than bulk models and sidesteps the need for wind data and turbulence parameterization required by these models. Mixed layer depths obtained from the diagnostic model using NCEP–NCAR reanalysis data reveal that—contrary to reports for late winter—there has been no significant trend in the summer mixed layer depth in the central northeast Pacific over the past 52 yr.

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Richard E. Thomson and Isaac V. Fine

Abstract

Estimates of mixed layer depth are important to a wide variety of oceanic investigations including upper-ocean productivity, air–sea exchange processes, and long-term climate change. In the absence of direct turbulent dissipation measurements, mixed layer depth is commonly derived from oceanic profile data using threshold, integral, least squares regression, or other proxy variables. The different methodologies often yield different values for mixed layer depth. In this paper, a new method—the split-and-merge (SM) method—is introduced for determining the depth of the surface mixed layer and associated upper-ocean structure from digital conductivity–temperature–depth (CTD) profiles. Two decades of CTD observations for the continental margin of British Columbia are used to validate the SM method and to examine differences in mixed layer depth estimates for the various computational techniques. On a profile-by-profile basis, close agreement is found between the SM and de facto standard threshold methods. However, depth estimates from these two methods can differ significantly from those obtained using the integral and least squares regression methods. The SM and threshold methods are found to approximate the “true” mixed layer depth whereas the integral and regression methods typically compute the depth of the underlying pycnocline. On a statistical basis, the marginally smaller standard errors for spatially averaged mixed layer depths for the SM method suggest a slight improvement in depth determination over threshold methods. This improvement, combined with the added ability of the SM method to delineate simultaneously ancillary features of the upper ocean (such as the depth and gradient of the permanent pycnocline), make it a valuable computational tool for characterizing the structure of the upper ocean.

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Richard E. Thomson and Isaac V. Fine

Abstract

We use bottom pressure records from 59 sites of the global tsunami warning system to examine the nonisostatic response of the World Ocean to surface air pressure forcing within the 4–6-day band. It is within this narrow “5-day” band that sea level fluctuations strongly depart from the isostatic inverted barometer response. Numerical simulations of the observed bottom pressures were conducted using a two-dimensional Princeton Ocean Model forced at the upper boundary by two versions of the air pressure loading: (i) an analytical version having the form of the westward propagating, 5-day Rossby–Haurwitz air pressure mode; and (ii) an observational version based on a 16-yr record of global-scale atmospheric reanalysis data with a spatial resolution of 2.5°. Simulations from the two models—consisting of barotropic standing waves of millibar amplitudes and near uniform phases in the Pacific, Atlantic, and Indian Oceans—are in close agreement and closely reproduce the observed bottom pressures. The marked similarity of the outputs from the two models and the ability of both models to accurately reproduce the seafloor pressure records indicate a pronounced dynamic response of the World Ocean to nonstationary air pressure fields resembling the theoretical Rossby–Haurwitz air pressure mode.

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