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continentalshelves. A glance at a bathymetric map of GeorgesBank, for example, shows a shallow central region(<50 m) dropping away into deeper water on eachside. The flow over this bank, however, might not bereadily understood by analogy to normal shelf dynamics because of the absence of the constrainingeffect of a coastal boundary. The dynamics of GeorgesBank are further complicated by the presence ofstrong (,~ 1 m s-I) semidiurnal tidal currents whichdrive mean flows through nonlinear interactions
continentalshelves. A glance at a bathymetric map of GeorgesBank, for example, shows a shallow central region(<50 m) dropping away into deeper water on eachside. The flow over this bank, however, might not bereadily understood by analogy to normal shelf dynamics because of the absence of the constrainingeffect of a coastal boundary. The dynamics of GeorgesBank are further complicated by the presence ofstrong (,~ 1 m s-I) semidiurnal tidal currents whichdrive mean flows through nonlinear interactions
quasi-geostrophy. A comparison of model results with data is encouraging. The 26.5 sigma-theta isopyenal is argued to be adensity surface to which this theory applies. The potential vorticity structure on this surface obtains a bowl-likeshape and agrees well with the model. The subtropical mode water of the North Atlantic ( 18-C water) is centeredon this isopycnal and is identified in the model as the homogenized local potential vorticity minimum. Thestability of 18-C water characterizes
quasi-geostrophy. A comparison of model results with data is encouraging. The 26.5 sigma-theta isopyenal is argued to be adensity surface to which this theory applies. The potential vorticity structure on this surface obtains a bowl-likeshape and agrees well with the model. The subtropical mode water of the North Atlantic ( 18-C water) is centeredon this isopycnal and is identified in the model as the homogenized local potential vorticity minimum. Thestability of 18-C water characterizes
is about 1 and emphasized a temporal cascade of the spacing to large scale. Smith et al. (1987) reported that the maximum ratio is close to 3 and noted that this ratio is confined by the depth of the mixed layer. The comparison of two relatively recent studies in shallow water confirms this trend. In 15-m-deep water, the spacing is 50 m [Fig. 6 in Gargett and Wells (2007) ]. Under similar forcing conditions, but in 26-m-deep water, the spacing is 90 m ( Savidge and Gargett 2017 ). Adopting a
is about 1 and emphasized a temporal cascade of the spacing to large scale. Smith et al. (1987) reported that the maximum ratio is close to 3 and noted that this ratio is confined by the depth of the mixed layer. The comparison of two relatively recent studies in shallow water confirms this trend. In 15-m-deep water, the spacing is 50 m [Fig. 6 in Gargett and Wells (2007) ]. Under similar forcing conditions, but in 26-m-deep water, the spacing is 90 m ( Savidge and Gargett 2017 ). Adopting a
+ û z W 0 z . (15) Now (13) times W 1 minus (15) times W 0 , and integration, gives after a little algebra If W 0 is identically ĥ i (as it can be without loss of generality), then the integral on the lhs is unity, and the correction c i 1 to the phase speed is given by the difference between two integrals, which can be trivially computed. This formula is generated more generally by the truncation method to be discussed next. If W 0 is indeed mode 1 in shape, then for typical ocean
+ û z W 0 z . (15) Now (13) times W 1 minus (15) times W 0 , and integration, gives after a little algebra If W 0 is identically ĥ i (as it can be without loss of generality), then the integral on the lhs is unity, and the correction c i 1 to the phase speed is given by the difference between two integrals, which can be trivially computed. This formula is generated more generally by the truncation method to be discussed next. If W 0 is indeed mode 1 in shape, then for typical ocean
-based observations, we have used two additional ancillary datasets—the satellite-based estimates of sea surface height (SSH) and the corresponding geostrophic velocities, and the in situ CTD and ADCP observations along several sections occupied during the same cruise. The SSH maps and the associated geostrophic velocities correspond to the level-4 gridded maps product publicly available from the Copernicus website ( https
-based observations, we have used two additional ancillary datasets—the satellite-based estimates of sea surface height (SSH) and the corresponding geostrophic velocities, and the in situ CTD and ADCP observations along several sections occupied during the same cruise. The SSH maps and the associated geostrophic velocities correspond to the level-4 gridded maps product publicly available from the Copernicus website ( https
) and less deformed, with shallower ridges ( Wadhams 2012 ; Hutchings and Faber 2018 ; Kwok 2018 ). Fig. 1. Map of Canada Basin showing September sea ice concentration and location of ocean observations. (left) September 1975 mean sea ice concentration and location of measurements from AIDJEX sea ice camps (blue dots) and (right) 2006–12 September mean sea ice concentration and location of ITP observations (red dots). Region indicated by dashed lines shows the Canada Basin, which we define as
) and less deformed, with shallower ridges ( Wadhams 2012 ; Hutchings and Faber 2018 ; Kwok 2018 ). Fig. 1. Map of Canada Basin showing September sea ice concentration and location of ocean observations. (left) September 1975 mean sea ice concentration and location of measurements from AIDJEX sea ice camps (blue dots) and (right) 2006–12 September mean sea ice concentration and location of ITP observations (red dots). Region indicated by dashed lines shows the Canada Basin, which we define as
. Fig . 6. Neutrality errors on various surfaces. Maps of log 10 (| ϵ |) using (a),(b) the reference dataset and (c)–(e) ECCO2, on γ n = 27.7 kg m −3 in (a) and (c), γ SCV = 27.7 kg m −3 in (d), and ω surface initialized from the γ n = 27.7 kg m −3 isosurface in (b) and (e). (f) Histogram of log 10 (| ϵ |) of the five surfaces. For a more quantitative comparison, Fig. 6f shows a histogram of log 10 (| ϵ |) on the various surfaces. The RMS errors of the γ n and ω surfaces with the
. Fig . 6. Neutrality errors on various surfaces. Maps of log 10 (| ϵ |) using (a),(b) the reference dataset and (c)–(e) ECCO2, on γ n = 27.7 kg m −3 in (a) and (c), γ SCV = 27.7 kg m −3 in (d), and ω surface initialized from the γ n = 27.7 kg m −3 isosurface in (b) and (e). (f) Histogram of log 10 (| ϵ |) of the five surfaces. For a more quantitative comparison, Fig. 6f shows a histogram of log 10 (| ϵ |) on the various surfaces. The RMS errors of the γ n and ω surfaces with the
-geostrophic approximations are made, and 3) twoactive layers are included. The system is weakly nonconservative and the thermocline anomalies are assumed to be finite in amplitude. This paper is organized as follows. The model andthe governing equations are introduced in section 2.After some algebra, the system is reduced to one equation in one unknown, including explicit time dependence, buoyant forcing and wind forcing. This equationis further reduced to a simple wave equation by choosing special forms for the
-geostrophic approximations are made, and 3) twoactive layers are included. The system is weakly nonconservative and the thermocline anomalies are assumed to be finite in amplitude. This paper is organized as follows. The model andthe governing equations are introduced in section 2.After some algebra, the system is reduced to one equation in one unknown, including explicit time dependence, buoyant forcing and wind forcing. This equationis further reduced to a simple wave equation by choosing special forms for the
accounts for the disparity between their values and those of Manabe orCraddock (Table 1) who considered periods of severaldays or longer. In each of these studies the investigator estimatedlikely upper limits for the heat change in the atmospheric column due to radiative exchanges. The net heatexchanges across the sea-air interface, including isolation, were not calculated however. For comparison, climatic values of sea-air heat fluxesfor the month of January for each region under consideration
accounts for the disparity between their values and those of Manabe orCraddock (Table 1) who considered periods of severaldays or longer. In each of these studies the investigator estimatedlikely upper limits for the heat change in the atmospheric column due to radiative exchanges. The net heatexchanges across the sea-air interface, including isolation, were not calculated however. For comparison, climatic values of sea-air heat fluxesfor the month of January for each region under consideration
2003 , their Fig. 15). Observational evidence for the crossover is weaker, partly because it is difficult to make measurements of the time mean. There are very few time series of velocity at fixed locations, so the calculation of a mean circulation from in situ observations is out of the question. Furthermore, the relatively sparse hydrographic measurements in the Red Sea mean it is not possible to construct maps of absolute dynamic topography from altimetry, as is done in other ocean basins ( www
2003 , their Fig. 15). Observational evidence for the crossover is weaker, partly because it is difficult to make measurements of the time mean. There are very few time series of velocity at fixed locations, so the calculation of a mean circulation from in situ observations is out of the question. Furthermore, the relatively sparse hydrographic measurements in the Red Sea mean it is not possible to construct maps of absolute dynamic topography from altimetry, as is done in other ocean basins ( www
