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signals with phase speeds of O(10) and O(100 to 300) km day −1 and time scales of 2 to 3 weeks. The signals with slow phase speed are only observed in southern California. It is hypothesized that they are scattered and reflected by shoreline curvature and bathymetry change and do not penetrate north of Point Conception. The seasonal transition of alongshore surfacecirculationforcedbyupwelling‐favorablewindsandtheirrelaxationiscapturedinfine detail.Submesoscaleeddies,identifiedusingflowgeometry,haveRossbynumbersof0.1to3, diameters in the range of 10 to 60 km, and persistence for 2 to 12 days. The HFR surface currents resolve coastal surface ocean variability continuously across scales from

[1] Three years of continuous Spray glider observations in the southern California Current System (CCS) are combined with a numerical simulation to describe the mean and variability of poleward flows in the southern CCS. Gliders provide upper ocean observations with good across-shore and temporal resolution along two across-shore survey lines while the numerical simulation provides a dynamically consistent estimate of the ocean state. Persistent poleward flows are observed in three areas: within 100 km of the coast at Point Conception, within the Southern California Bight (SCB), and offshore of the SCB and the Santa Rosa Ridge (SRR). Poleward transport by the flows within the SCB and offshore of the SRR exceeds the poleward transport off Point Conception, suggesting that the poleward flows are not continuous over the 225 km between observation lines. The numerical simulation shows offshore transport between the survey lines that is consistent with some of the poleward flow turning offshore before reaching Point Conception. The poleward current offshore of the SRR is unique in that it is strongest at depths greater than 350 m and it is observed to migrate westward away from the coast. This westward propagation is tied to westward propagating density anomalies originating in the SCB during the spring-summer upwelling season when wind stress curl is most strongly positive. The across-shore wave number, frequency, and phase speed of the westward propagation and the lack of across-shore transport of salinity along isopycnals are consistent with first-mode baroclinic Rossby dynamics.

[1] An eddy-permitting adjoint-based assimilation system has been implemented to estimate the state of the tropical Pacific Ocean. The system uses the Massachusetts Institute of Technology's general circulation model and its adjoint. The adjoint method is used to adjust the model to observations by controlling the initial temperature and salinity; temperature, salinity, and horizontal velocities at the open boundaries; and surface fluxes of momentum, heat, and freshwater. The model is constrained with most of the available data sets in the tropical Pacific, including Tropical Atmosphere and Ocean, ARGO, expendable bathythermograph, and satellite SST and sea surface height data, and climatologies. Results of hindcast experiments in 2000 suggest that the iterated adjoint-based descent is able to significantly improve the model consistency with the multivariate data sets, providing a dynamically consistent realization of the tropical Pacific circulation that generally matches the observations to within specified errors. The estimated model state is evaluated both by comparisons with observations and by checking the controls, the momentum balances, and the representation of small-scale features that were not well sampled by the observations used in the assimilation. As part of these checks, the estimated controls are smoothed and applied in independent model runs to check that small changes in the controls do not greatly change the model hindcast. This is a simple ensemble-based uncertainty analysis. In addition, the original and smoothed controls are applied to a version of the model with doubled horizontal resolution resulting in a broadly similar “downscaled” hindcast, showing that the adjustments are not tuned to a single configuration (meaning resolution, topography, and parameter settings). The time-evolving model state and the adjusted controls should be useful for analysis or to supply the forcing, initial, and boundary conditions for runs of other models.

[1] Over the decade 1996–2006, acoustic sources located off central California (1996–1999) and north of Kauai (1997–1999, 2002–2006) transmitted to receivers distributed throughout the northeast and north central Pacific. The acoustic travel times are inherently spatially integrating, which suppresses mesoscale variability and provides a precise measure of ray-averaged temperature. Daily average travel times at 4-day intervals provide excellent temporal resolution of the large-scale thermal field. The interannual, seasonal, and shorter-period variability is large, with substantial changes sometimes occurring in only a few weeks. Linear trends estimated over the decade are small compared to the interannual variability and inconsistent from path to path, with some acoustic paths warming slightly and others cooling slightly. The measured travel times are compared with travel times derived from four independent estimates of the North Pacific: (1) climatology, as represented by the World Ocean Atlas 2005 (WOA05); (2) objective analysis of the upper-ocean temperature field derived from satellite altimetry and in situ profiles; (3) an analysis provided by the Estimating the Circulation and Climate of the Ocean project, as implemented at the Jet Propulsion Laboratory (JPL-ECCO); and (4) simulation results from a high-resolution configuration of the Parallel Ocean Program (POP) model. The acoustic data show that WOA05 is a better estimate of the time mean hydrography than either the JPL-ECCO or the POP estimates, both of which proved incapable of reproducing the observed acoustic arrival patterns. The comparisons of time series provide a stringent test of the large-scale temperature variability in the models. The differences are sometimes substantial, indicating that acoustic thermometry data can provide significant additional constraints for numerical ocean models.

[1] A small-scale model of the Southern California–Northern Baja California coastline has been developed to explore dispersion over the continental shelf, with specific attention to physical parameters pertinent to simulations of larval dispersal and population connectivity. The ROMS simulation employs a nested grid system, with an inner domain resolution of 600 m and an outer domain resolution of 1.5 km. Realistic bathymetry and forcing were employed to investigate the effects of passive transport of tracers introduced at locations with known communities of mytilid mussels along the coastline. The effects of topographic resolution, boundary conditions, and choice of meteorological forcing products on dispersion rates, tracer trajectories, and the subsequent measures of population connectivity were examined. In particular, the choice of wind forcing product resulted in different circulation patterns and tracer trajectories and had especially important consequences on measures of larval connectivity such as self-seeding, potential for larval settlement (import), and contribution to the pool of available larvae (export). While some forcing products performed better when model data were compared to field measurements, no product was clearly superior. The uncertainty in results, which may appear minor in larger-scale temperature or surface velocity fields, is significant when examining a sensitive passive tracer. This modeling uncertainty needs to be addressed when interpreting connectivity results.

[1] An optimal interpolation (OI) method to compute surface vector current fields from radial velocity measurements derived from high-frequency (HF) radars is presented. The method assumes a smooth spatial covariance relationship between neighboring vector currents, in contrast to the more commonly used un-weighted least-squares fitting (UWLS) method, which assumes a constant vector velocity within a defined search radius. This OI method can directly compute any quantities linearly related to the radial velocities, such as vector currents and dynamic quantities (divergence and vorticity) as well as the uncertainties of those respective fields. The OI method is found to be more stable than the UWLS method and reduces spurious vector solutions near the baselines between HF radar installations. The OI method produces a covariance of the uncertainty of the estimated vector current fields. Three nondimensional uncertainty indices are introduced to characterize the uncertainty of the vector current at a point, representing an ellipse with directional characteristics. The vector current estimation using the OI method eliminates the need for multiple mapping steps and optimally fills intermittent coverage gaps. The effects of angular interpolation of radial velocities, a commonly used step in the preprocessing of radial velocity data prior to vector current computation in the UWLS method, are presented.

[1] Surface currents measured by high-frequency radars are objectively mapped using covariance matrices computed from hourly surface current vectors spanning two years. Since retrievals of surface radial velocities are inherently gappy in space and time, the irregular density of surface current data leads to negative eigenvalues in the sample covariance matrix. The number and the magnitude of the negative eigenvalues depend on the degree of data continuity used in the matrix computation. In a region of 90% data coverage, the negative eigenvalues of the sample covariance matrix are small enough to be removed by adding a noise term to the diagonal of the matrix. The mapping is extended to regions of poorer data coverage by applying a smoothed covariance matrix obtained by spatially averaging the sample covariance matrix. This approach estimates a stable covariance matrix of surface currents for regions with the intermittent radar coverage. An additional benefit is the removal of baseline errors that often exist between two radar sites. The covariance matrices and the correlation functions of the surface currents are exponential in space rather than Gaussian, as is often assumed in the objective mapping of oceanographic data sets. Patterns in the decorrelation length scale provide the variabilities of surface currents and the insights on the influence of topographic features (bathymetry and headlands). The objective mapping approach presented herein lends itself to various applications, including the Lagrangian transport estimates, dynamic analysis through divergence and vorticity of current vectors, and statistical models of surface currents.

[1] Satellite altimetric height was combined with approximately 1,000,000 in situ temperature profiles to produce global estimates of upper ocean heat content, temperature, and thermosteric sea level variability on interannual timescales. Maps of these quantities from mid-1993 through mid-2003 were calculated using the technique developed by Willis et al. [2003]. The time series of globally averaged heat content contains a small amount of interannual variability and implies an oceanic warming rate of 0.86 ± 0.12 watts per square meter of ocean (0.29 ± 0.04 pW) from 1993 to 2003 for the upper 750 m of the water column. As a result of the warming, thermosteric sea level rose at a rate of 1.6 ± 0.3 mm/yr over the same time period. Maps of yearly heat content anomaly show patterns of warming commensurate with ENSO variability in the tropics, but also show that a large part of the trend in global, oceanic heat content is caused by regional warming at midlatitudes in the Southern Hemisphere. In addition to quantifying interannual variability on a global scale, this work illustrates the importance of maintaining continuously updated monitoring systems that provide global coverage of the world's oceans. Ongoing projects, such as the Jason/TOPEX series of satellite altimeters and the Argo float program, provide a critical foundation for characterizing variability on regional, basin, and global scales and quantifying the oceans' role as part of the climate system.

[1] A new technique is demonstrated for combining altimetric height (AH) and sea-surface temperature (SST) with in situ data to produce improved estimates of 0/800 m steric height (SH), heat content, and temperature variability. The technique uses a linear regression onto AH to construct an initial guess for the subsurface quantity. This guess is then corrected toward the in situ data creating an estimate with substantially less error than could be achieved using either data set alone. Inclusion of the SST data further improves the estimates and illustrates how the procedure can be generalized to allow inclusion of additional data sets. The technique is demonstrated over a region in the southwestern Pacific enclosing the Tasman Sea. Nine-year time series of heat storage and temperature variability, averaged over 4° latitude and longitude and 1 year in time, are calculated. The estimates have RMS errors of approximately 4.6 W/m2 in heat storage, 0.10°C in subsurface temperature and 0.11°C in surface temperature, and fractional errors of 20, 28, and 18%, respectively, relative to the total variance overall spatial and temporal scales considered. These represent significant improvements over previous estimates of these quantities. All the time series show strong interannual variability including the El Nino event of 1997. Application of these techniques on a global scale could provide new insight into the variability of the general circulation and heat budget of the upper ocean.

Large-scale depth-integrated currents and relative vorticity were measured in the central North Pacific Ocean during summer 1987 using long-range reciprocal acoustic transmissions between transceivers in a triangle approximately 1000 km on a side. Inverse techniques were used to estimate the depth-averaged (barotropic) current bihourly at 4-day intervals from differential travel times. Tidal constituent amplitudes and phases found from the acoustically determined currents agree with those found from current meters and with the tidal models of Schwiderski (1980) and Cartwright et al. (1992), providing confirmation that the tomographically derived barotropic currents are correct within the expected uncertainties. The estimated low-frequency, large-scale currents are compared with depth-averaged currents determined by point measurements using current meters and bottom-mounted electrometers. Meridional and zonal currents are calculated using the topographic Sverdrup balance with the Fleet Numerical Oceanography Center wind field. The measured time derivative of the areally averaged relative vorticity is shown to be insignificant to the Sverdrup balance. Currents and vorticity calculated using the Sverdrup balance are an order of magnitude smaller than the observations. The magnitude and variability of the large-scale currents and vorticity determined from the Semtner and Chervin (1988) eddy-resolving model of ocean circulation are similar to the direct measurements.

The velocity structure of Jasper Seamount was modeled using one- and three-dimensional inversions of P wave travel times. The results represent the first detailed seismic images of a submerged, intraplate volcano. Two seismic refraction experiments were completed on Jasper Seamount, incorporating ocean bottom seismometers and navigated seafloor shots. The P wave travel times were first used to compute a one-dimensional velocity profile which served as a starting model for a three-dimensional tomographic inversion. The seamount P velocities are significantly slower than those observed in typical oceanic crust at equivalent subbasement depths. This suggests that Jasper Seamount is constructed predominantly of extrusive lavas with high average porosity. The velocity models confirm morphological predictions: Jasper Seamount is a shield volcano with rift zone development. High seismic velocities were detected beneath the large radial ridges while low velocities characterize the shallow summit and flanks. Comparisons between P velocity models of Jasper Seamount and the island of Hawaii reveal that these two shield volcanoes are not structurally proportional. Jasper Seamount is far smaller than Hawaii, yet both volcanoes exhibit an outer extrusive layer of similar thickness. This suggests that seamount size influences the intrusive/extrusive proportions; density equilibrium between melt and country rock may explain this behavior.

Broadband acoustic signals transmitted from a moored 250-Hz source to a 3-km-long vertical line array of hydrophones 1000 km distant in the north central Pacific Ocean were used to determine the amount of information available from tomographic techniques used in the vertical plane connecting a source-receiver pair. A range-independent, pure acoustic inverse to obtain the sound speed field using travel time data from the array is shown to be possible by iterating from climatological data without using any information from concurrent environmental measurements. Range-dependent inversions indicate resolution of components of oceanic variability with horizontal wavelengths shorter than 50 km, although the limited spatial resolution of concurrent direct measurements does not provide a strong cross-validation, since the typical cast spacing of 20–25 km gives a Nyquist wavelength of 40–50 km. The small travel time signals associated with high-wavenumber ocean variability place stringent but achievable requirements on travel time measurement precision. The forward problem for the high-wavenumber components of the model is found to be subject to relatively large linearization errors, however, unless the sound speed field at wavelengths greater than about 50 km is known from other measurements or from a two-dimensional tomographic array. The high-ocean-wavenumber resolution that is in principle available from tomographic measurements is therefore achievable only under restricted conditions.

Objective mapping can remove the equatorial singularity from the problem of estimating geostrophic shear from noisy density measurements. The method uses the complete thermal wind relation, so it is valid uniformly on and off the equator. Errors in the thermal wind balance are due to neglected terms in the momentum balance, which are treated as noise in the inverse problem. The question of whether the geostrophic balance holds near the equator is restated as a need to estimate the size of the ageostrophic noise in the thermal wind equation. Objective mapping formalizes the assumptions about the magnitudes and scales of the geostrophic currents and about the magnitudes and scales of the ageostrophic terms and measurement errors. The uncertainty of the velocity estimates is calculated as part of the mapping and depends on the signal to noise ratio (geostrophic density signal to ageostrophic “noise”) in the data, as well as the station spacing and the scales assumed for the geostrophic velocities. The method is used to map zonal velocity from a mean Hawaii-Tahiti Shuttle density section. These are compared with previous velocity estimates for the same dataset calculated using other techniques. By choosing appropriate scales, the objective map can duplicate previous results. New temperature data are presented from a repeating, high-resolution expendable bathythermograph section crossing the equator at about 170° W with four cruises a year between 1987–1991. There appear to be significant differences between this mean temperature and the shuttle mean temperature. Temperature is converted to density with the aid of a mean T-S relation and geostrophic velocity maps are calculated for the 4-year mean. The mean geostrophic undercurrent obtained from our sections is weaker than in the shuttle estimate and is centered slightly north of the equator. Enforcing symmetry about the equator removes the offset of the current, giving a stronger, but narrow undercurrent. The density field apparently includes significant (O (0.5 kg m−3)) large-scale ageostrophic variability which makes velocity estimates from single cruises poorly determined near the equator.

Ocean tomography as originally proposed required all sources and recievers to be tautly moored and acoustically tracked to separate travel time perturbations due to mooring motion from those due to ocean features. It is possible to process the tomographic travel times to estimate both ocean sound speed perturbations and mooring offsets, effecting a separation without external tracking. A side effect of this processing is a check on the ray identification, since the varying instrument positions can be used as a synthetic array for estimating ray angle. Simulations and examples with actual data were used to contrast mapping performance with and without mooring tracking for a variety of ray data sets. In general, the ocean maps degrade when the tracking data are withheld. However, when many high-precision ray travel time measurements are available, the degradation is small; in these cases it would be possible to deploy free-drifting instruments as part of a monitoring experiment.

Mesoscale mapping of the ocean sound speed field in a 1000×1000 km area by means of ocean acoustic tomography is greatly enhanced by augmenting a few acoustic moorings with a movable ship-based receiver. Computer simulations based on realistic noise levels in the measured acoustic travel times give 5% (1%) residual variance in ΔC(x;y,z) for four (six) acoustic source moorings in an ocean perturbed in the gravest baroclinic mode. For comparison, objective mapping based on traditional vertical profiles requires 3 times the steaming distance to yield equivalent residual error. Detailed results depend on many parameters: the assumed mesoscale spectrum and vertical mode structure, the number of observed multipaths, the mooring configuration, the number of ship stations and the travel time signal level (due to mesoscale eddies) and noise level (due to internal waves and position-keeping errors). These parameters have critical values, below which there is distinct deterioration and beyond which there is little gain. We believe that the critical values can be attained in practice so the ultimate limit on mesoscale mapping is imposed by the internal wave-induced travel time error. This assumes that position keeping of the submerged acoustic sources and receiver by a combination of satellite navigation and high-frequency acoustics can be achieved with ±10-m accuracy. The present study assumes a stationary ocean; a second paper will deal with reciprocal transmissions yielding currents and hence the barotropic mode. This is required in a dynamic ocean model for estimating ΔC(x,y,z;t). All this is preparatory to a tomography experiment in the Greenland Sea in 1988–1989.

Acoustic tomography uses integrating measurements which require inverse methods to resolve the averages into estimates of spatial structure. Statistical inverse methods have been extensively used to solve the reconstruction problem over different tomographic ranges and configurations. These inverses become very difficult to apply in frontal regions like the Gulf Stream (GS) system, where the statistics are acutely inhomogeneous and anisotropic and the mean is not a likely representation of the GS front at any time. In this paper we propose an alternative inverse which asks for the solution which gives a front instead of asking for the smoothest solution. The inverse solution minimizes the errors in the fit to the data while simultaneously maximizing the sum of the squares of the gradients observed in the reconstructed section and minimizing the absolute value norm for stability. The inverse is aimed at detecting changes in the GS front, thus the data are used to estimate the perturbations to a previous estimate of the frontal structure, instead of reconstructing the entire front as a perturbation from some average state. This approach is intended to merge well with eventual dynamic updating schemes and can be used with various types of data, given a proper model. Several examples have been run intercomparing the traditional linear least squares (LLSI) with the maximum gradient inverse (MGI), from very idealized cases to a real Gulf Stream section reconstructed from hydrographic data. Different transceiver configurations were also compared and mid-depth instruments were found to be superior to bottom mounted instruments. The simplest cases show a significant improvement in the estimate of the Gulf Stream front by the MGI compared to the weighted least squares inverse (LLSI). As the cases became more complicated (and more realistic), the differences between inverse methods become less pronounced, although the strength and location of the perturbation maxima were always determined more accurately by the MGI. The decline is at least partially due to the numerical algorithm which lumps data misfits and external constraints (the maximum gradient) into a single penalty criterion which is minimized. The most immediate way to overcome this limitation is to break up the problem into a two-step procedure, first a least squares inverse to fit the data and second an iterative, nonlinear optimization maximizing the gradient and minimizing the absolute value norm.