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Max Yaremchuk
,
Dmitri Nechaev
, and
Chudong Pan

Abstract

A hybrid background error covariance (BEC) model for three-dimensional variational data assimilation of glider data into the Navy Coastal Ocean Model (NCOM) is introduced. Similar to existing atmospheric hybrid BEC models, the proposed model combines low-rank ensemble covariances with the heuristic Gaussian-shaped covariances to estimate forecast error statistics. The distinctive features of the proposed BEC model are the following: (i) formulation in terms of inverse error covariances, (ii) adaptive determination of the rank m of with information criterion based on the innovation error statistics, (iii) restriction of the heuristic covariance operator to the null space of , and (iv) definition of the BEC magnitudes through separate analyses of the innovation error statistics in the state space and the null space of .

The BEC model is validated by assimilation experiments with simulated and real data obtained during a glider survey of the Monterey Bay in August 2003. It is shown that the proposed hybrid scheme substantially improves the forecast skill of the heuristic covariance model.

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Gleb Panteleev
,
Max Yaremchuk
, and
W. Erick Rogers

Abstract

A variational data assimilation algorithm is developed for the ocean wave prediction model [Wave Model (WAM)]. The algorithm employs the adjoint-free technique and was tested in a series of data assimilation experiments with synthetic observations in the Chukchi Sea region from various platforms. The types of considered observations are directional spectra estimated from point measurements by stationary buoys, significant wave height (SWH) observations by coastal high-frequency radars (HFRs) within a geographic sector, and SWH from satellite altimeter along a geographic track. Numerical experiments demonstrate computational feasibility and robustness of the adjoint-free variational algorithm with the regional configuration of WAM. The largest improvement of the model forecast skill is provided by assimilating HFR data (the most numerous among the considered types). Assimilating observations of the wave spectrum from a moored platform provides only moderate improvement of the skill, which disappears after 3 h of running WAM in the forecast mode, whereas skill improvement provided by HFRs is shown to persist up to 9 h. Space-borne observations, being the least numerous, do not have a significant impact on the forecast skill but appear to have a noticeable effect when assimilated in combination with other types of data. In particular, when spectral data from a single mooring are used, the satellite data are found to be the most beneficial as a supplemental data type, suggesting the importance of spatial coverage of the domain by observations.

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Alexei Sentchev
,
Max Yaremchuk
,
Denis Bourras
,
Ivane Pairaud
, and
Philippe Fraunié

Abstract

A method of assessing the mean eddy viscosity profile (EVP) in the sea surface boundary layer (SBL) under variable wind conditions is proposed. Performance of the method is tested using observations by an ADCP-equipped platform in the coastal environment of the northwestern Mediterranean Sea under variable (3–12 m s−1) wind conditions. EVP retrievals are made by a variational method strongly constrained by the Ekman dynamics, with the wind and velocity observations assumed to be uncertain within the prescribed error bars. Results demonstrate a reasonable agreement of the EVPs with KPP shape functions for stronger (8–12 m s−1) wind conditions and appear to be consistent with the classical Pacanowski–Philander parameterization of the viscosity profile based on the Richardson number. For weaker (3–5 m s−1) winds, the EVP retrievals turn out to be less accurate, which is primarily attributed to the decay of the wind-driven turbulence energy in the SBL. Feasibility and prospects of the retrieval technique are discussed in the context of uncertainties in the structure of the background flow and limitations of the microstructure and ADCP profiling.

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Joseph M. D’Addezio
,
Gregg A. Jacobs
,
Max Yaremchuk
, and
Innocent Souopgui

Abstract

We analyze high-resolution (1 km) simulations of the western Pacific, Gulf of Mexico, and Arabian Sea to understand submesoscale eddy dynamics. A mask based on the Okubo–Weiss parameter isolates small-scale eddies, and we further classify those with |ζ/f| ≥ 1 as being submesoscale eddies. Cyclonic submesoscale eddies exhibit a vertical depth structure in which temperature anomalies from the large-scale background are negative. Peak density anomalies associated with cyclonic submesoscale eddies are found at a depth approximately twice the mixed layer depth (MLD). Within anticyclonic submesoscale eddies, temperature anomalies are positive and have peak density anomalies at the MLD. The depth–depth covariance structure for the cyclonic and anticyclonic submesoscale eddies have maxima over a shallow region near the surface and weak off diagonal elements. The observed vertical structure suggests that submesoscale eddies have a shallower depth profile and smaller vertical correlation scales when compared to the mesoscale phenomenon. We test a two-dimensional submesoscale eddy dynamical balance. Compared to a geostrophic dynamical balance using only pressure gradient and Coriolis force, including velocity tendency and advection produces lower errors by about 20%. In regions with strong tides and associated internal waves (western Pacific and Arabian Sea), using the mixed layer integrated small-scale steric height within the dynamical equations produces the lowest magnitude errors. In areas with weak tides (Gulf of Mexico), using small-scale sea surface height (SSH) produces the lowest magnitude errors. Recovering a submesoscale eddy with the correct magnitude and rotation requires integration of small-scale specific volume anomalies well below the mixed layer.

Free access
Zuojun Yu
,
Julian P. McCreary Jr.
,
Max Yaremchuk
, and
Ryo Furue

Abstract

The South China Sea (SCS) is often treated as a semienclosed water body, with the Luzon Strait as its only connection to the Pacific Ocean. A branch of the Kuroshio flows northwestward across the Luzon Strait to enter the SCS, carrying North Pacific Tropical Water (NPTW) into the basin. Using the subsurface salinity maximum as a tracer for NPTW, the authors show how important three secondary straits—the Taiwan Strait to the north and the Karimata and Mindoro Straits to the south—are to the NPTW intrusion at the Luzon Strait. The authors demonstrate that the SCS cannot reach an equilibrium state that is consistent with the observed subsurface salinity distribution unless all of the following components are in place: the Kuroshio, transports through the three secondary straits, downward mixing of freshwater, horizontal mixing induced by mesoscale eddies, and forcing by the local monsoonal winds.

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Max Yaremchuk
,
Julian McCreary Jr.
,
Zuojun Yu
, and
Ryo Furue

Abstract

The salinity distribution in the South China Sea (SCS) has a pronounced subsurface maximum from 150–220 m throughout the year. This feature can only be maintained by the existence of a mean flow through the SCS, consisting of a net inflow of salty North Pacific tropical water through the Luzon Strait and outflow through the Mindoro, Karimata, and Taiwan Straits. Using an inverse modeling approach, the authors show that the magnitude and space–time variations of the SCS thermohaline structure, particularly for the salinity maximum, allow a quantitative estimate of the SCS throughflow and its distribution among the three outflow straits. Results from the inversion are compared with available observations and output from a 50-yr simulation of a highly resolved ocean general circulation model.

The annual-mean Luzon Strait transport is found to be 2.4 ± 0.6 Sv (Sv ≡ 106 m3 s−1). This inflow is balanced by the outflows from the Karimata (0.3 ± 0.5 Sv), Mindoro (1.5 ± 0.4), and Taiwan (0.6 ± 0.5 Sv) Straits. Results of the inversion suggest that the Karimata transport tends to be overestimated in numerical models. The Mindoro Strait provides the only passage from the SCS deeper than 100 m, and half of the SCS throughflow (1.2 ± 0.3 Sv) exits the basin below 100 m in the Mindoro Strait, a result that is consistent with a climatological run of a 0.1° global ocean general circulation model.

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J. N. Stroh
,
Gleb Panteleev
,
Max Yaremchuk
,
Oceana Francis
, and
Richard Allard

Abstract

Sea ice models that allow for deformation are primarily based on rheological formulations originally developed in the 1970s. In both the original viscoplastic (VP) and elastic-VP schemes, the internal pressure term is modeled as a function of variable sea ice thickness and concentration with spatially and temporally constant empirical parameters for ice strength. This work considers a spatially variable extension of the rheology parameters as well as wind stress in a one-dimensional VP sea ice data assimilation system. In regions of total ice cover, experiments that assimilate synthetic ice-state observations using variable rheological parameters show larger improvements than equivalent experiments using homogeneous parameters. For partially ice-covered regions where internal ice stresses are relatively unimportant, experiments assimilating synthetic sea ice velocity observations demonstrate reasonable reconstruction of spatially variable wind stresses. These results suggest practical benefits for sea ice–state reconstruction and forecasts by using sea ice velocity, thickness, and concentration observations to optimize spatially varying rheological parameters and to improve wind stress forcing.

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Gleb Panteleev
,
Max Yaremchuk
,
Jacob Stroh
,
Pamela Posey
,
David Hebert
, and
Dmitri A. Nechaev

Abstract

Monitoring surface currents by coastal high-frequency radars (HFRs) is a cost-effective observational technique with good prospects for further development. An important issue in improving the efficiency of HFR systems is the optimization of radar positions on the coastline. Besides being constrained by environmental and logistic factors, such optimization has to account for prior knowledge of local circulation and the target quantities (such as transports through certain key sections) with respect to which the radar positions are to be optimized.

In the proposed methodology, prior information of the regional circulation is specified by the solution of the 4D variational assimilation problem, where the available climatological data in the Bering Strait (BS) region are synthesized with dynamical constraints of a numerical model. The optimal HFR placement problem is solved by maximizing the reduction of a posteriori error in the mass, heat, and salt (MHS) transports through the target sections in the region. It is shown that the MHS transports into the Arctic and their redistribution within the Chukchi Sea are best monitored by placing HFRs at Cape Prince of Wales and on Little Diomede Island. Another equally efficient configuration involves placement of the second radar at Sinuk (western Alaska) in place of Diomede. Computations show that 1) optimization of the HFR deployment yields a significant (1.3–3 times) reduction of the transport errors compared to nonoptimal positioning of the radars and 2) error reduction provided by two HFRs is an order of magnitude better than the one obtained from three moorings permanently maintained in the region for the last 5 yr. This result shows a significant advantage of BS monitoring by HFRs compared to the more traditional technique of in situ moored observations. The obtained results are validated by an extensive set of observing system simulation experiments.

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Tangdong Qu
,
Yoo Yin Kim
,
Max Yaremchuk
,
Tomoki Tozuka
,
Akio Ishida
, and
Toshio Yamagata

Abstract

The Luzon Strait transport (LST) from the Pacific into the South China Sea (SCS) is examined using results from a high-resolution ocean general circulation model. The LST from the model has a mean value of 2.4 Sv (Sv ≡ 106 m3 s−1) and reaches its seasonal maximum (6.1 Sv westward) in winter and seasonal minimum (0.9 Sv eastward) in summer. Both the annual mean and seasonal variation of LST compare favorably with earlier observations. On an interannual time scale, LST tends to be higher during El Niño years and lower during La Niña years, with its maximum (minimum) leading the mature phase of El Niño (La Niña) by 1 month. The interannual variation of LST appears to be oppositely phased with the Kuroshio transport east of Luzon, indicating a possible nonlinear hysteresis of the Kuroshio as a driving mechanism of LST. For the annual average, water leaving the SCS in the south is of higher temperature than that with LST, thus producing a cooling advection in the upper 405 m equivalent to a surface heat flux of −19 W m−2. Most of this cooling advection is balanced by the atmospheric heating (17 W m−2). From late spring to early fall, surface heat flux is the primary heating process; only a small part of the heat content change can be explained by heat advection. But, in winter, heat advection seems to be the only important process responsible for the cooling in the upper layer of the SCS. The interannual variation of the upper-layer heat content has a strong signature of ENSO, cooling in the development of El Niño and warming in the development of La Niña. An oceanic connection is revealed, in which LST seems to be a key process conveying the impact of the Pacific ENSO into the SCS.

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Douglas R. Allen
,
Sergey Frolov
,
Rolf Langland
,
Craig H. Bishop
,
Karl W. Hoppel
,
David D. Kuhl
, and
Max Yaremchuk

Abstract

An ensemble-based linearized forecast model has been developed for data assimilation applications for numerical weather prediction. Previous studies applied this local ensemble tangent linear model (LETLM) to various models, from simple one-dimensional models to a low-resolution (~2.5°) version of the Navy Global Environmental Model (NAVGEM) atmospheric forecast model. This paper applies the LETLM to NAVGEM at higher resolution (~1°), which required overcoming challenges including 1) balancing the computational stencil size with the ensemble size, and 2) propagating fast-moving gravity modes in the upper atmosphere. The first challenge is addressed by introducing a modified local influence volume, introducing computations on a thin grid, and using smaller time steps. The second challenge is addressed by applying nonlinear normal mode initialization, which damps spurious fast-moving modes and improves the LETLM errors above ~100 hPa. Compared to a semi-Lagrangian tangent linear model (TLM), the LETLM has superior skill in the lower troposphere (below 700 hPa), which is attributed to better representation of moist physics in the LETLM. The LETLM skill slightly lags in the upper troposphere and stratosphere (700–2 hPa), which is attributed to nonlocal aspects of the TLM including spectral operators converting from winds to vorticity and divergence. Several ways forward are suggested, including integrating the LETLM in a hybrid 4D variational solver for a realistic atmosphere, combining a physics LETLM with a conventional TLM for the dynamics, and separating the LETLM into a sequence of local and nonlocal operators.

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