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An underwater navigation algorithm that provides a “cold start” (CSA) geographic position, geo-position, underwater while submerged using travel times measured from a constellation of acoustic sources is described in Mikhalevsky, Sperry, Woolfe, Dzieciuch, and Worcester [J. Acoust. Soc. Am. 147(4), 2365 – 2382 (2020)]. The CSA geo-position is used as the receive position in the ocean for acoustic modeling runs using an ocean general circulation model (GCM). A different geo-position is calculated using adjusted ranges from the travel time offsets between the data and modeled arrival times for each source. Because the CSA geo-position is close to the true position, the source to CSA position propagation model path and the source to true vehicle position data path of the acoustic arrivals are nearly coincident, enabling accurate measurement of travel time offsets. The cold start with model (CSAM) processing reduced the CSA geo-position errors from a mean of 58 to 25 m. A simulation is developed to estimate CSA and CSAM performances as a function of group speed variability between the source paths. The CSAM geolocation accuracy can be calculated from and is controlled by the accuracy of the GCM.

A novel tidal analysis package (red_tide) has been developed to characterize low-amplitude non-phase-locked tidal energy and dominant tidal peaks in noisy, irregularly sampled, or gap-prone time series. We recover tidal information by expanding conventional harmonic analysis to include prior information and assumptions about the statistics of a process, such as the assumption of a spectrally colored background, treated as nontidal noise. This is implemented using Bayesian maximum posterior estimation and assuming Gaussian prior distributions. We utilize a hierarchy of test cases, including synthetic data and observations, to evaluate this method and its relevance to analysis of data with a tidal component and an energetic nontidal background. Analysis of synthetic test cases shows that the methodology provides robust tidal estimates. When the background energy spectrum is nearly spectrally white, red_tide results replicate results from ordinary least squares (OLS) commonly used in other tidal packages. When background spectra are red (a spectral slope of −2 or steeper), red_tide’s estimates represent a measurable improvement over OLS. The approach highlights the presence of tidal variability and low-amplitude constituents in observations by allowing arbitrarily configurable fitted frequencies and prior statistics that constrain solutions. These techniques have been implemented in MATLAB in order to analyze tidal data with non-phase-locked components and an energetic background that pose challenges to the commonly used OLS approach.

In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS (Scripps–KAUST Regional Integrated Prediction System). The WAVEWATCH III model is implemented with flexibility, meaning the coupled system can run with or without the wave component. In our implementations, we considered the effect of Stokes drift, Langmuir turbulence, sea surface roughness, and wave-induced momentum fluxes. To demonstrate the impact of coupling we performed a case study using a series of coupled and uncoupled simulations of Tropical Cyclone Mekunu, which occurred in the Arabian Sea in May 2018. We examined the model skill in these simulations and further investigated the impact of Langmuir turbulence in the coupled system. Because of the chaotic nature of the atmosphere, we ran an ensemble of 20 members for each coupled and uncoupled experiment. We found that the characteristics of the tropical cyclone are not significantly different due to the effect of surface waves when using different parameterizations, but the coupled models better capture the minimum pressure and maximum wind speed compared with the benchmark stand-alone Weather Research and Forecasting (WRF) model. Moreover, in the region of the cold wake, when Langmuir turbulence is considered in the coupled system, the sea surface temperature is about 0.5 ∘C colder, and the mixed layer is about 20 m deeper. This indicates the ocean model is sensitive to the parameterization of Langmuir turbulence in the coupled simulations.

A strongly nonlinear eddy field is present in and around the subtropical countercurrent in the northern Philippine Sea (NPS). A regional implementation of the Massachusetts Institute of Technology General Circulation Model–Estimating the Circulation and Climate of the Ocean four-dimensional variational assimilation (MITgcm-ECCO 4DVAR) system is found to be able to produce a series of 2-month-long dynamically consistent optimized state estimates between April 2010 and April 2011 for the eddy-rich NPS region. The assimilation provides a stringent dynamical test of the model, showing that a free run of the model forced using adjusted controls remains consistent with the observations for 2 months. The 4DVAR iterative optimization reduced the total cost function for the observations and controls by 40%–50% from the reference solution, initialized using the Hybrid Coordinate Ocean Model 1/12° global daily analysis, achieving residuals approximately equal to the assumed uncertainties for the assimilated observations. The state estimates are assessed by comparing with assimilated and withheld observations and also by comparing 1-month model forecasts with future data. The state estimates and forecasts were more skillful than model persistence and the reference solutions. Finally, the continuous state estimates were used to detect and track the eddies, analyze their structure, and quantify their vertically integrated meridional heat and salt transports.

The 2010–11 North Pacific Acoustic Laboratory (NPAL) Philippine Sea experiment measured travel times between six acoustic transceiver moorings in a 660-km diameter ocean acoustic tomography array in the northern Philippine Sea (NPS). The travel-time series compare favorably with travel times computed for a yearlong series of state estimates produced for this region using the Massachusetts Institute of Technology General Circulation Model–Estimating the Circulation and Climate of the Ocean four-dimensional variational (MITgcm-ECCO 4DVAR) assimilation system constrained by satellite sea surface height and sea surface temperature observations and by Argo temperature and salinity profiles. Fluctuations in the computed travel times largely match the fluctuations in the measurements caused by the intense mesoscale eddy field in the NPS, providing a powerful test of the observations and state estimates. The computed travel times tend to be shorter than the measured travel times, however, reflecting a warm bias in the state estimates. After processing the travel times to remove tidal signals and extract the low-frequency variability, the differences between the measured and computed travel times were used in addition to SSH, SST, and Argo temperature and salinity observations to further constrain the model and generate improved state estimates. The assimilation of the travel times reduced the misfit between the measured and computed travel times, while not increasing the misfits with the other assimilated observations. The state estimates that used the travel times are more consistent with temperature measurements from an independent oceanographic mooring than the state estimates that did not incorporate the travel times.

Southern Ocean (SO) surface winds are essential for ventilating the upper ocean by bringing heat and CO2 to the ocean interior. The relationships between mixed-layer ventilation, the Southern Annular Mode (SAM), and the storm tracks remain unclear because processes can be governed by short-term wind events as well as long-term means.In this study, observed time-varying 5-day probability density functions (PDFs) of ERA5 surface winds and stresses over the SO are used in a singular value decomposition to derive a linearly independent set of empirical basis functions. The first modes of wind (72% of the total wind variance) and stress (74% of the total stress variance) are highly correlated with a standard SAM index (r = 0.82) and reflect SAM’s role in driving cyclone intensity and, in turn, extreme westerly winds. This Joint PDFs of zonal and meridional wind show that southerly and less westerly winds associated with strong mixed-layer ventilation are more frequent during short and distinct negative SAM phases. The probability of these short-term events might be related to mid-latitude atmospheric circulation. The second mode describes seasonal changes in the wind variance (16% of the total variance) that are uncorrelated with the first mode.The analysis produces similar results when repeated using 5-day PDFs from a suite of scatterometer products. Differences between wind product PDFs resemble the first mode of the PDFs. Together, these results show a strong correlation between surface stress PDFs and the leading modes of atmospheric variability, suggesting that empirical modes can serve as a novel pathway for understanding differences and variability of surface stress PDFs.

The Arctic Ocean is undergoing dramatic changes in response to increasing atmospheric concentrations of greenhouse gases. The 2016–2017 Canada Basin Acoustic Propagation Experiment was conducted to assess the effects of the changes in the sea ice and ocean structure in the Beaufort Gyre on low-frequency underwater acoustic propagation and ambient sound. An ocean acoustic tomography array with a radius of 150 km that consisted of six acoustic transceivers and a long vertical receiving array measured the impulse responses of the ocean at a variety of ranges every four hours using broadband signals centered at about 250 Hz. The peak-to-peak low-frequency travel-time variability of the early, resolved ray arrivals that turn deep in the ocean was only a few tens of milliseconds, roughly an order of magnitude smaller than observed in previous tomographic experiments at similar ranges, reflecting the small spatial scale and relative sparseness of mesoscale eddies in the Canada Basin. The high-frequency travel-time fluctuations were approximately 2 ms root-mean-square, roughly comparable to the expected measurement uncertainty, reflecting the low internal-wave energy level. The travel-time spectra show increasing energy at lower frequencies and enhanced semidiurnal variability, presumably due to some combination of the semidiurnal tides and inertial variability.

Conventional observations of atmospheric rivers (ARs) over the northeastern Pacific Ocean are sparse. Satellite radiances are affected by the presence of clouds and heavy precipitation, which impact their distribution in the lower atmosphere and in precipitating areas. The goal of this study is to document a data gap in existing observations of ARs in the northeastern Pacific, and to investigate how a targeted field campaign called AR Reconnaissance (AR Recon) can effectively fill this gap. When reconnaissance data are excluded, there is a gap in AR regions from near the surface to the middle troposphere (below 450 hPa), where most water vapor and its transport are concentrated. All-sky microwave radiances provide data within the AR object, but their quality is degraded near the AR core and its leading edge, due to the existence of thick clouds and precipitation. AR Recon samples ARs and surrounding areas to improve downstream precipitation forecasts over the western United States. This study demonstrates that despite the apparently extensive swaths of modern satellite radiances, which are critical to estimate large-scale flow, the data collected during 15 AR Recon cases in 2016, 2018, and 2019 supply about 99% of humidity, 78% of temperature, and 45% of wind observations in the critical maximum water vapor transport layer from the ocean surface to 700 hPa in ARs. The high-vertical-resolution dropsonde observations in the lower atmosphere over the northeastern Pacific Ocean can significantly improve the sampling of low-level jets transporting water vapor to high-impact precipitation events in the western United States.

Surface gravity waves play a major role in the exchange of momentum, heat, energy, and gases between the ocean and the atmosphere. The interaction between currents and waves can lead to variations in the wave direction, frequency, and amplitude. In the present work, we use an ensemble of synthetic currents to force the wave model WAVEWATCH III and assess the relative impact of current divergence and vorticity in modifying several properties of the waves, including direction, period, directional spreading, and significant wave height Hs. We find that the spatial variability of Hs is highly sensitive to the nature of the underlying current and that refraction is the main mechanism leading to gradients of Hs. The results obtained using synthetic currents were used to interpret the response of surface waves to realistic currents by running an additional set of simulations using the llc4320 MITgcm output in the California Current region. Our findings suggest that wave parameters could be used to detect and characterize strong gradients in the velocity field, which is particularly relevant for the Surface Water and Ocean Topography (SWOT) satellite as well as several proposed satellite missions.

Three simulations of the circulation in the Gulf of Mexico (the “Gulf”) using different numerical general circulation models are compared with results of recent large-scale observational campaigns conducted throughout the deep (>1500 m) Gulf. Analyses of these observations have provided new understanding of large-scale mean circulation features and variability throughout the deep Gulf. Important features include cyclonic flow along the continental slope, deep cyclonic circulation in the western Gulf, a counterrotating pair of cells under the Loop Current region, and a cyclonic cell to the south of this pair. These dominant circulation features are represented in each of the ocean model simulations, although with some obvious differences. A striking difference between all the models and the observations is that the simulated deep eddy kinetic energy under the Loop Current region is generally less than one-half of that computed from observations. A multidecadal integration of one of these numerical simulations is used to evaluate the uncertainty of estimates of velocity statistics in the deep Gulf computed from limited-length (4 years) observational or model records. This analysis shows that the main deep circulation features identified from the observational studies appear to be robust and are not substantially impacted by variability on time scales longer than the observational records. Differences in strengths and structures of the circulation features are identified, however, and quantified through standard error analysis of the statistical estimates using the model solutions.

A regional ocean model for Fram Strait provides a framework for interpretation of the variability and structure of acoustic tomography arrivals. The eddy-permitting model (52 vertical levels and 4.5 km horizontal resolution) was evaluated using long-term moored hydrography data and time series of depth-range averaged temperature obtained from the inversion of acoustic tomography measurements. Geometric ray modeling using the ocean model fields reproduces the measured arrival structure of the acoustic tomography experiment. The combination of ocean and acoustic models gives insights into acoustic propagation during winter and spring. Moreover, overlapping arrivals coming from different vertical angles can be resolved and explained. The overlapping arrival of purely refracted rays and surface-reflected/bottom-reflected (SRBR) rays has implications for the inversion of tomography data in Fram Strait. The increased knowledge about the ray-length variations of SRBR rays is valuable for choosing appropriate observation kernels for the data assimilation of acoustic tomography data in Fram Strait.

The cross correlation of the underwater noise field recorded at two receivers conveys information about the time-domain Green's function between the two locations, provided that sufficient energy is channeled into the acoustic paths connecting these. The efficiency of this procedure depends on the locations and characteristics of the receivers and noise sources, as well as on the refraction properties of the ocean sound channel. The sensitivity of the finite-frequency noise cross-correlation function with respect to the location and amplitude of the noise sources is studied here, taking into account the refractive features of the ocean environment. The sensitivity kernel describing changes in the cross-correlation envelope due to changes in the noise source distribution is used to highlight noise-source locations with maximum potential impact on the cross-correlation output.

Airborne lidar altimetry can measure the sea surface height (SSH) over scales ranging from hundreds of kilometers to a few meters. Here, we analyze the spectrum of SSH observations collected during an airborne lidar campaign conducted off the California coast. We show that the variance in the surface wave band can be over 20 times larger than the variance at submesoscales and that the observed SSH variability is sensitive to the directionality of surface waves. Our results support the hypothesis that there is a spectral gap between meso-to-submesoscale motions and small-scale surface waves and also indicate that aliasing of surface waves into lower wavenumbers may complicate the interpretation of SSH spectra. These results highlight the importance of better understanding the contributions of different physics to the SSH variability and considering the SSH spectrum as a continuum in the context of future satellite altimetry missions.

Tides and Earth-Moon system evolution are coupled over geological time. Tidal energy dissipation on Earth slows Earth's rotation rate, increases obliquity, lunar orbit semi-major axis and eccentricity, and decreases lunar inclination. Tidal and core-mantle boundary dissipation within the Moon decrease inclination, eccentricity and semi-major axis. Here we integrate the Earth-Moon system backwards for 4.5Ga with orbital dynamics and explicit ocean tide models that are "high-level" (i.e., not idealized). To account for uncertain plate tectonic histories, we employ Monte Carlo simulations, with tidal energy dissipation rates (normalized relative to astronomical forcing parameters) randomly selected from ocean tide simulations with modern ocean basin geometry and with 55, 116, and 252Ma reconstructed basin paleogeometries. The normalized dissipation rates depend upon basin geometry and Earth's rotation rate. Faster Earth rotation generally yields lower normalized dissipation rates. The Monte Carlo results provide a spread of possible early values for the Earth-Moon system parameters. Of consequence for ocean circulation and climate, absolute (un-normalized) ocean tidal energy dissipation rates on the early Earth may have exceeded today's rate due to a closer Moon. Prior to ∼3Ga , evolution of inclination and eccentricity is dominated by tidal and core-mantle boundary dissipation within the Moon, which yield high lunar orbit inclinations in the early Earth-Moon system. A drawback for our results is that the semi-major axis does not collapse to near-zero values at 4.5Ga, as indicated by most lunar formation models. Additional processes, missing from our current efforts, are discussed as topics for future investigation.

An ocean acoustic tomography array with a radius of 150 km was installed in the central Beaufort Gyre during 2016–2017 for the Canada Basin Acoustic Propagation Experiment (CANAPE). Five transceivers were deployed in a pentagon shape with a sixth transceiver at the center and a long vertical receiving array northwest of the central mooring. At least 12 refracted-surface-reflected (RSR) ray arrivals with lower turning points at depths between 500 and 3500 m were resolved in the acoustic receptions at all receivers. Travel-time anomalies were computed relative to a range-dependent sound-speed reference made by objectively interpolating annual-average sound-speed profiles constructed from the temperature data at each mooring. The travel time anomalies were inverted to estimate the 3-D sound-speed anomaly, including corrections to the positions of sources and receivers consistent with the uncertainty from long-baseline acoustic navigation systems at each mooring. Although the deep water in the Canada Basin is nearly homogeneous in temperature and salinity and highly stable (slowly warming in response to geothermal heating), it proved necessary to allow for a sound-speed change in the deep ocean to obtain consistent inversions, suggesting that the sound-speed equation at high pressure and low temperature is in error by about 0.1–0.2 ms−1.

A new regional coupled ocean–atmosphere model is developed and its implementation is presented in this paper. The coupled model is based on two open-source community model components: the MITgcm ocean model and the Weather Research and Forecasting (WRF) atmosphere model. The coupling between these components is performed using ESMF (Earth System Modeling Framework) and implemented according to National United Operational Prediction Capability (NUOPC) protocols. The coupled model is named the Scripps–KAUST Regional Integrated Prediction System (SKRIPS). SKRIPS is demonstrated with a real-world example by simulating a 30 d period including a series of extreme heat events occurring on the eastern shore of the Red Sea region in June 2012. The results obtained by using the coupled model, along with those in forced stand-alone oceanic or atmospheric simulations, are compared with observational data and reanalysis products. We show that the coupled model is capable of performing coupled ocean–atmosphere simulations, although all configurations of coupled and uncoupled models have good skill in modeling the heat events. In addition, a scalability test is performed to investigate the parallelization of the coupled model. The results indicate that the coupled model code scales well and the ESMF/NUOPC coupler accounts for less than 5 % of the total computational resources in the Red Sea test case. The coupled model and documentation are available at https://library.ucsd.edu/dc/collection/bb1847661c (last access: 26 September 2019), and the source code is maintained at https://github.com/iurnus/scripps_kaust_model (last access: 26 September 2019).

The spatial correlation of a diffuse isotropic noise field generated from a uniform distribution of uncorrelated noise sources contains information about the time-domain Green's function (TDGF) corresponding to propagation between the correlated locations. The distribution of noise in the ocean due to shipping—the prevailing origin of continuous low-frequency noise—is far from uniform. Besides the location of noise sources, the propagation conditions and the hydrophone locations have a significant influence on whether the TDGF can be reliably reconstructed through the cross-correlation procedure. A wave-theoretic scheme is implemented to simulate the cross-correlation function of a noise field in the time domain for arbitrary distributions of deterministic or random noise sources in refractive environments, and it is used to study the influence of propagation conditions and receiver motion on the efficiency of the cross-correlation procedure to obtain the TDGF from shipping noise.The spatial correlation of a diffuse isotropic noise field generated from a uniform distribution of uncorrelated noise sources contains information about the time-domain Green's function (TDGF) corresponding to propagation between the correlated locations. The distribution of noise in the ocean due to shipping—the prevailing origin of continuous low-frequency noise—is far from uniform. Besides the location of noise sources, the propagation conditions and the hydrophone locations have a significant influence on whether the TDGF can be reliably reconstructed through the cross-correlation procedure. A wave-theoretic scheme is implemented to simulate the cross-correlation function of a noise field in the time domain for arbitrary distributions of deterministic or random noise sources in refractive environments, and it is used to study the influence of propagation conditions and receiver motion on the efficiency of the cross-correlation procedure to obtain the TDGF from shipping noise.

We gratefully acknowledge the ECCO consortium, including MIT, JPL, and the University of Hamburg, and the NCAR Data Assimilation Research Section (DAReS). The MITgcm code used in this study is checkpoint 64Y, and was obtained from http://mitgcm.org/. The Ssalto/Duacs altimeter product AVISO is produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS: http://marine.copernicus.eu/). The HYCOM/NCODA 1/12° global analysis data were obtained from the HYCOM consortium (http://hycom.org/dataserver/). The along-track altimetry data were obtained from the Radar Altimeter Database System (RADS: http://rads.tudelft.nl/rads/index.shtml). The SST data were obtained from Remote Sensing Systems Inc. (http://www.remss.com/). The NCEP/NCAR-Reanalysis-1 atmospheric forcings were obtained from http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html. The MITgcm–DART EnKF and MITgcm–ECCO 4DVAR state estimates, input files including observations and error fields, are available from the authors upon request (email:ggopalakrishnan@ucsd.edu). BDC gratefully acknowledges support from the Office of Naval Research grants N000141512285 and N000141512598. Research reported in this publication was supported by the Gulf Research Program of the National Academy of Sciences under award number 2000006422. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Gulf Research Program or the National Academy of Sciences.

We gratefully acknowledge the research funding (grant number: OSR-2-16-RPP-3268.02 from KAUST (King Abdullah University of Science and Technology). We also appreciate the computational resources related to the supercomputer Shaheen II and the assistance provided by KAUST Supercomputer Laboratory. A.B.V.B. was funded by the SWOT program with NASA grants NNX16AH67G and 80NSSC20K1136. We wish to thank Fabrice Ardhuin for discussing the simulation results and the setup of the numerical simulations

This paper summarizes the online panel discussion special session “ Underwater Sound Modeling: Comprehensive Environmental Descriptions ” that took place during the first Acoustics-in-Focus virtual meeting, the 180th Meeting of the Acoustical Society of America, on June 8, 2021. The session was sponsored by the Underwater Acoustics Technical Committee and consisted of seven panelists, verbal participation by about a dozen other attendees, and attendance by more than 50 additional people. The background slides that were presented, and the discussion, began things by considering the methods used to insert environmental information into acoustical models, mainly computational propagation simulations, but then moved into a broader discussion that included statistical models and inverse methodology.

The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.

Author(s): Hell, Momme C; Gille, Sarah T; Cornuelle, Bruce D; Miller, Arthur J; Bromirski, Peter D; Crawford, Alex D

A data-constrained state estimate of the southern California Current System (CCS) is presented and compared with withheld California Cooperative Oceanic Fisheries Investigations (CalCOFI) data and assimilated glider data over 2007–17. The objective of this comparison is to assess the ability of the California State Estimate (CASE) to reproduce the key physical features of the CCS mean state, annual cycles, and interannual variability along the three sections of the California Underwater Glider Network (CUGN). The assessment focuses on several oceanic metrics deemed most important for characterizing physical variability in the CCS: 50-m potential temperature, 80-m salinity, and 26 kg m−3 isopycnal depth and salinity. In the time mean, the CASE reproduces large-scale thermohaline and circulation structures, including observed temperature gradients, shoaling isopycnals, and the locations and magnitudes of the equatorward California Current and poleward California Undercurrent. With respect to the annual cycle, the CASE captures the phase and, to a lesser extent, the magnitude of upper-ocean warming and stratification from late summer to early fall and of isopycnal heave during springtime upwelling. The CASE also realistically captures near-surface diapycnal mixing during upwelling season and the semiannual cycle of the California Undercurrent. In terms of interannual variability, the most pronounced signals are the persistent warming and downwelling anomalies of 2014–16 and a positive isopycnal salinity anomaly that peaked with the 2015–16 El Niño.

The 2010i–2012 ACOBAR acoustic thermometry experiment in Fram Strait resulted in 2-year-long timeseries of sound speed and temperature. These timeseries are section- and depth-average along 4 sections covering the deep part of Fram Strait (77.9°–78.9°N, 4.2°W–8.7°E). They were obtained by inversion from the acoustic travel times measured in the thermometry experiment. Such large-scale average measurements in a highly turbulent environment at one of the important sites for ocean circulation in the Arctic are unique and will hopefully increase our understanding of volume and heat exchanges between the Arctic and Atlantic. A regional ocean model of Fram Strait was set up for the assimilation of the ACOBAR measurements using the 4-DVAR data assimilation technique. The forward model part was evaluated using both oceanographic and acoustic measurements (Geyer et al., 2019). First assimilation results show a cost reduction of 85% after 10 iterations. The resulting ocean state estimate will be evaluated using the long-term oceanographic mooring section in Fram Strait at 78°50’N. The aim of this study is to use the ocean state estimate to facilitate the interpretation of the acoustic thermometry results and to investigate how the circulation dynamics in Fram Strait are influencing the volume and heat exchanges through the strait.

A moving source tomography experiment was conducted in 2016 off the coast of Southern California. From the travel time data extracted from the experiment, ocean sound speed and its uncertainty were estimated. The moving source poses extra complexity and adds components that need to be accounted for in a successful inversion. The sound speed estimation with uncertainties was validated against in situ observations to quantify the efficacy and accuracy of the method. Experimental results and additional simulations suggest that the ray diversity available in the moving source case reduces the posterior sound speed uncertainty compared to the fixed source case. [Work sponsored by the Office of Naval Research.]

Sensitivity kernels for travel-time observables defined on the noise cross-correlation pattern – the envelope of the cross-correlation function of the underwater noise field between two locations – with respect to changes in the sound-speed field in refractive underwater environments will be addressed. A wave-theoretic scheme allowing for finite-frequency calculations in 2 and 3 dimensions combined with the Born approximation for perturbations of the Green’s function and the peak-arrival approach is used to obtain peak-time sensitivity kernels (PTSKs) with respect to environmental (sound-speed) changes. PTSK results for different propagation conditions and noise-source distributions, ranging from spatial distributions of uncorrelated noise sources to point sources such as individual ships, will be presented. The PTSKs can be a useful tool for obtaining environmental information from noise measurements. [Work supported by the Office of Naval Research.]

Surface waves are crucial for the dynamics of the upper ocean not only because they mediate exchanges of momentum, heat, energy, and gases between the ocean and the atmosphere, but also because they determine the sea state. The surface wave field in a given region is set by the combination of local and remote forcing. The present work characterizes the seasonal variability of the deep water surface wave field in the California Current region, as retrieved from over two decades of satellite altimetry data combined with wave buoys and wave model hindcast (WaveWatch III). In particular, the extent to which the local wind modulates the variability of the significant wave height, peak period, and peak direction is assessed. During spring/summer, regional-scale wind events of up to 10 m/s are the dominant forcing for waves off the California coast, leading to relatively short-period waves (8–10 s) that come predominantly from the north-northwest. The wave climatology throughout the California Current region shows average significant wave heights exceeding 2 m during most of the year, which may have implications for the planning and retrieval methods of the Surface Water and Ocean Topography (SWOT) satellite mission.

This paper presents a least squares method to estimate the horizontal (isotropic or anisotropic) spatial covariance of two-dimensional orthogonal vector components, without introducing an intervening mapping step and biases, from the spatial covariance of the nonorthogonally and irregularly sampled raw scalar velocities. The field is assumed to be locally homogeneous in space and sampled in an ensemble so the unknown spatial covariance is a function of spatial lag only. The transformation between the irregular grid on which nonorthogonal scalar projections of the vector are sampled and the regular orthogonal grid on which they will be mapped is created using the geometry of the problem. The spatial covariance of the orthogonal velocity components of the field is parameterized by either the energy (power) spectrum in the wavenumber domain or the lagged covariance in the spatial domain. The energy spectrum is constrained to be nonnegative definite as part of the solution of the inverse problem. This approach is applied to three example sets of data, using nonorthogonally and irregularly sampled radial velocity data obtained from 1) a simple spectral model, 2) a regional numerical model, and 3) an array of high-frequency radars. In tests where the true covariance is known, the proposed direct approaches fitting to parameterizations of the nonorthogonally and irregularly sampled raw data in the wavenumber domain and spatial domain outperform methods that map the data to a regular grid before estimating the covariance.