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Carol H. Pease

be little in situ freezing south of62-N farther than 100 km from land. Hydrographic data from the southern margin of the ice (seawardlimit) showed that a lens of less saline, colder water existed in the upper 20 m of the water column alongthe southern ice margin. During north-to-northeast wind events, floes were advected toward the southto southwest at rates as high as 0.5 m s-~ and rotted along the margin on the order of days. Littleridging of ice was observed over the open shelf. Rafting was

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S. Zhang, M. J. Harrison, A. Rosati, and A. Wittenberg

profiles based on irregular ship courses, and starting from the early of 1990s, satellite altimeters began to provide measurements of sea surface height. All observations have instrument measurement errors and sampling (representation) errors. Neither modeling nor observations alone provides a complete picture of climate variations (which in oceans are defined by the time series of three-dimensional temperature, salinity, and currents, etc.). Climate research requires the implementation of data

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Julie Pietrzak

regions where large gradients of temperature and salinity exist. The POM model is used in the three-dimensional primitive experiments described in this paper. While the classic one- and two-dimensional examples highlight the performance of the different limiters in simple test cases, it is unclear whether these schemes will give the same improvements in the simulation of more realistic three-dimensional flows. Very few papers in oceanography have addressed this situation. One of the notable

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Toshiaki Shinoda, Tommy G. Jensen, Maria Flatau, and Sue Chen

(light blue lines in Fig. 6 ) is defined as the depth at which density increases by Δ d above the surface value. Here, Δ d is specified to be equivalent to the density increase produced by a 0.3°C decrease in temperature from the surface value, but with the salinity held constant at the surface value. The top of the thermocline depth (black lines in Fig. 6 ) is defined as the depth at which temperature decreases by Δ T above the surface value. Δ T is specified to be 0.3°C. Although temperature

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Femke C. Vossepoel, Anthony T. Weaver, Jérôme Vialard, and Pascale Delecluse

-varying forcing from this integrated response may not be straightforward. In this study, we investigate the “invertibility” of the ocean's response to wind stress forcing. Bonekamp et al. (2001) developed a four-dimensional variational data-assimilation (4DVar) scheme that adjusts indirectly the ocean state variables (velocity, temperature, salinity and sea surface height) of an OGCM through the modification of the wind stress forcing. Stammer et al. (2002) considered a more general approach to 4DVar that

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Robert E. Hart, Ryan N. Maue, and Michael C. Watson

ocean surface and subsurface temperature and salinity structure ( Elsberry et al. 1976 ; Black 1983 ; Shay et al. 1989 ; Robertson and Ginis 2002 ). Typically, the mechanical turbulent mixing caused by TC wind stresses entrains colder and saltier water from the thermocline into the oceanic mixed layer dependent upon the temperature stratification with depth ( Dickey et al. 1998 ). As the latter layer is deepened, the SSTs cool, leaving a noticeable cold wake usually to the right of the storm

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Iam-Fei Pun, James F. Price, and Steven R. Jayne

) and expendable bathythermograph (XBT) observations ( Fig. 1 ). Of these profiles, 138 899 (88%) were used to establish (train) the regression model, while 19 076 (12%) independent profiles were withheld to assess accuracy. Table 1. Numbers and periods of in situ temperature profiles used in regression model development and validation. a. Argo profiling float data Argo floats repeatedly measure temperature, salinity, and pressure with high vertical resolution, usually 5–10 m for the upper ocean

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Andrea Alessandri, Andrea Borrelli, Simona Masina, Annalisa Cherchi, Silvio Gualdi, Antonio Navarra, Pierluigi Di Pietro, and Andrea F. Carril

initial conditions (ICs). The ocean-data assimilation system has been developed at CMCC-INGV ( Di Pietro and Masina 2009 ; Bellucci et al. 2007 ) and it has been used in order to assimilate observed profiles of temperature and salinity through the water column. The main focus of the paper is on the assessment of the impact of the assimilated initial conditions on the forecast skill. The paper is organized as follows. Section 2 describes the seasonal prediction system, the experiments performed, and

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Hal B. Gordon and Siobhan P. O’Farrell

submodels. The sea-ice model has both dynamic and thermodynamic parts, while the land surfaces have a soil–canopy model. The atmospheric model is spectral, while the ocean model is a version of the GFDL gridpoint ocean model (see below). The coupled model horizontal resolution is set at that of the spectral atmospheric model (R21), which gives a grid resolution of about 5.6° longitude by 3.2° latitude. The temperature–salinity grid points of the ocean model are coincident with the grid points (spectral

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G. R. Halliwell Jr., L. K. Shay, S. D. Jacob, O. M. Smedstad, and E. W. Uhlhorn

multivariate optimum interpolation, specifically the Navy Coupled Ocean Data Assimilation system, to assimilate all available observations. The nowcast product evaluation prior to the storms is supplemented by results from free-running simulations of the ocean response to Isidore (2002) and Ivan (2004) nested in different nowcast products to demonstrate the impact of initial temperature–salinity biases and to correct the ocean feature initialization. Collectively, these analyses demonstrate the critical

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