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processes can explain modifications to the water masses of the Solomon Sea. The strong and vertically sheared WBC ( AM10 ) may lead to instabilities. Interactions of external tides with the topography give rise to strong internal tide generation and tidal energy dissipation in the Solomon Sea, as shown by different observational ( Egbert and Ray 2000 ) and numerical studies ( Jayne and St. Laurent 2001 ; Niwa and Hibiya 2001 ; Simmons et al. 2004 ; Arbic et al. 2004 ). These processes, as well as
processes can explain modifications to the water masses of the Solomon Sea. The strong and vertically sheared WBC ( AM10 ) may lead to instabilities. Interactions of external tides with the topography give rise to strong internal tide generation and tidal energy dissipation in the Solomon Sea, as shown by different observational ( Egbert and Ray 2000 ) and numerical studies ( Jayne and St. Laurent 2001 ; Niwa and Hibiya 2001 ; Simmons et al. 2004 ; Arbic et al. 2004 ). These processes, as well as
, such as tidal mixing or interaction of dense water plumes with topography, which is known to be important in the formation of certain water masses in the world’s ocean. Initial condition and boundary condition (including surface forcing) errors can also result in errors in ocean model simulations. Because the surface ocean directly interacts with the atmosphere, previous studies have focused on identifying biases in surface properties. For example, Large and Danabasoglu (2006) found that the
, such as tidal mixing or interaction of dense water plumes with topography, which is known to be important in the formation of certain water masses in the world’s ocean. Initial condition and boundary condition (including surface forcing) errors can also result in errors in ocean model simulations. Because the surface ocean directly interacts with the atmosphere, previous studies have focused on identifying biases in surface properties. For example, Large and Danabasoglu (2006) found that the
, 2015 ; Durazo 2015 ) or are not focused on water masses ( Cepeda-Morales et al. 2013 ). The scarcity of data in the TPCM, in comparison with the available amount of historical data in surrounding areas like the California Current System or the Gulf of California, has hindered the characterization of the circulation and the water masses in this region. The TPCM is a region with complex dynamics ( Kessler 2006 ). At seasonal scale, the circulation in this area is dominated by the confluence of the
, 2015 ; Durazo 2015 ) or are not focused on water masses ( Cepeda-Morales et al. 2013 ). The scarcity of data in the TPCM, in comparison with the available amount of historical data in surrounding areas like the California Current System or the Gulf of California, has hindered the characterization of the circulation and the water masses in this region. The TPCM is a region with complex dynamics ( Kessler 2006 ). At seasonal scale, the circulation in this area is dominated by the confluence of the
1. Introduction The Southern Ocean water masses play an important role in the global climate system by storing heat, freshwater, and dissolved gases and absorbing a large portion of the global anthropogenic CO 2 ( Sarmiento et al. 1998 ; Sabine et al. 1999 ). Subantarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW) make up the upper limb of the Southern Ocean’s thermohaline circulation and can extend as far as 30°N ( Drijfhout et al. 2005 ), ventilating the subtropical gyres and
1. Introduction The Southern Ocean water masses play an important role in the global climate system by storing heat, freshwater, and dissolved gases and absorbing a large portion of the global anthropogenic CO 2 ( Sarmiento et al. 1998 ; Sabine et al. 1999 ). Subantarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW) make up the upper limb of the Southern Ocean’s thermohaline circulation and can extend as far as 30°N ( Drijfhout et al. 2005 ), ventilating the subtropical gyres and
), the construction of climatological datasets for temperature and salinity devoid of spurious water masses ( Lozier et al. 1994 ), the construction of inverse models of the ocean circulation ( Wunsch 1996 ), the tracking and analysis of water masses ( Montgomery 1938 ; Walin 1982 ), the construction of isopycnal models of the ocean based on generalized coordinate systems ( Griffies et al. 2000 ; de Szoeke 2000 ), the study of the residual circulation ( Wolfe 2014 ), and the parameterization of
), the construction of climatological datasets for temperature and salinity devoid of spurious water masses ( Lozier et al. 1994 ), the construction of inverse models of the ocean circulation ( Wunsch 1996 ), the tracking and analysis of water masses ( Montgomery 1938 ; Walin 1982 ), the construction of isopycnal models of the ocean based on generalized coordinate systems ( Griffies et al. 2000 ; de Szoeke 2000 ), the study of the residual circulation ( Wolfe 2014 ), and the parameterization of
1. Introduction The ocean takes up atmospheric CO 2 in the ventilation zones at mid and high latitudes, where the water masses are formed, and releases it in the equatorial upwelling regions ( Takahashi et al. 2002 ). Observations and models estimate that about 40% of the global anthropogenic CO 2 uptake by the global ocean occurs south of 30°S (e.g., Orr et al. 2001 ; Sabine et al. 2004 ). However, less than 18% of the anthropogenic Southern Ocean CO 2 uptake is via high-latitude water
1. Introduction The ocean takes up atmospheric CO 2 in the ventilation zones at mid and high latitudes, where the water masses are formed, and releases it in the equatorial upwelling regions ( Takahashi et al. 2002 ). Observations and models estimate that about 40% of the global anthropogenic CO 2 uptake by the global ocean occurs south of 30°S (e.g., Orr et al. 2001 ; Sabine et al. 2004 ). However, less than 18% of the anthropogenic Southern Ocean CO 2 uptake is via high-latitude water
circumpolar ocean–sea ice–ice shelf model driven by atmospheric surface forcing derived from a century-scale atmospheric reanalysis data to examine the long-term linear trend and interannual-to-decadal variability in basal melting of the Antarctic ice shelves and to coastal water masses ( section 4a ). In this study, we show sea ice and ocean model results mainly for validation purposes ( appendix ). Furthermore, from a series of numerical experiments, we examine the factors responsible for these ocean
circumpolar ocean–sea ice–ice shelf model driven by atmospheric surface forcing derived from a century-scale atmospheric reanalysis data to examine the long-term linear trend and interannual-to-decadal variability in basal melting of the Antarctic ice shelves and to coastal water masses ( section 4a ). In this study, we show sea ice and ocean model results mainly for validation purposes ( appendix ). Furthermore, from a series of numerical experiments, we examine the factors responsible for these ocean
1. Introduction The overturning circulation in the Southern Ocean is primarily controlled by a combination of surface buoyancy forcing and diapycnal mixing, but the relative importance of each process for different water masses is unclear. The meridional transfer across the Antarctic Circumpolar Current (ACC) is achieved via an upper overturning cell involves a formation and subduction of Subantarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW) and a deep cell involving the
1. Introduction The overturning circulation in the Southern Ocean is primarily controlled by a combination of surface buoyancy forcing and diapycnal mixing, but the relative importance of each process for different water masses is unclear. The meridional transfer across the Antarctic Circumpolar Current (ACC) is achieved via an upper overturning cell involves a formation and subduction of Subantarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW) and a deep cell involving the
A Simple Nonlinear and End-Member-Free Approach for Obtaining Ocean Remineralization Patterns-nutrients generation. The most usual is through simple regression models between the biogeochemical variables ( Chen and Bada 1992 ; Hayase and Shinozuka 1995 ; Hayase et al. 1989 ; Jørgensen et al. 2011 ; Yamashita and Tanoue 2008 ; Yamashita et al. 2007 ). However, an important bias in the calculation of the biogeochemical ratios is introduced in those water masses with a high initial content of FDOM, acquired through river input of terrestrial humic compounds in the area of source water formation. For
-nutrients generation. The most usual is through simple regression models between the biogeochemical variables ( Chen and Bada 1992 ; Hayase and Shinozuka 1995 ; Hayase et al. 1989 ; Jørgensen et al. 2011 ; Yamashita and Tanoue 2008 ; Yamashita et al. 2007 ). However, an important bias in the calculation of the biogeochemical ratios is introduced in those water masses with a high initial content of FDOM, acquired through river input of terrestrial humic compounds in the area of source water formation. For
). Thomas and Shakespeare (2015) described a mode water formation mechanism involving the mixing of cross-front temperature–salinity contrasts, cabbeling, and frontogenesis that has the potential to select the density, temperature, and salinity of a particular mode water. The fronts that border mode waters are characterized by density-compensated temperature and salinity contrasts that decrease in magnitude with depth. Along-isopycnal mixing of the disparate water masses across the fronts leads to an
). Thomas and Shakespeare (2015) described a mode water formation mechanism involving the mixing of cross-front temperature–salinity contrasts, cabbeling, and frontogenesis that has the potential to select the density, temperature, and salinity of a particular mode water. The fronts that border mode waters are characterized by density-compensated temperature and salinity contrasts that decrease in magnitude with depth. Along-isopycnal mixing of the disparate water masses across the fronts leads to an
