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The salinity signature of the cross-shelf exchanges in the Southwestern Atlantic Ocean: Satellite observations.

Guerrero RA, Piola AR, Fenco H, Matano RP, Combes V, Chao Y, James C, Palma ED, Saraceno M, Strub PT - J Geophys Res Oceans (2014)

Bottom Line: However, the combined analysis of SSS, satellite-derived sea surface elevation and surface velocity data suggest that the precise location of the export of shelf waters depends on offshore circulation patterns, such as the location of the Brazil Malvinas Confluence and mesoscale eddies and meanders of the Brazil Current.The satellite data indicate that in summer, mixtures of low-salinity shelf waters are swiftly driven toward the ocean interior along the axis of the Brazil/Malvinas Confluence.Satellite salinity sensors capture low-salinity detrainment events from shelves SW Atlantic low-salinity detrainments cause highest basin-scale variability In summer low-salinity detrainments cause extended low-salinity anomalies.

View Article: PubMed Central - PubMed

Affiliation: Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP) Mar del Plata, Argentina.

ABSTRACT

: Satellite-derived sea surface salinity (SSS) data from Aquarius and SMOS are used to study the shelf-open ocean exchanges in the western South Atlantic near 35°S. Away from the tropics, these exchanges cause the largest SSS variability throughout the South Atlantic. The data reveal a well-defined seasonal pattern of SSS during the analyzed period and of the location of the export of low-salinity shelf waters. In spring and summer, low-salinity waters over the shelf expand offshore and are transferred to the open ocean primarily southeast of the river mouth (from 36°S to 37°30'S). In contrast, in fall and winter, low-salinity waters extend along a coastal plume and the export path to the open ocean distributes along the offshore edge of the plume. The strong seasonal SSS pattern is modulated by the seasonality of the along-shelf component of the wind stress over the shelf. However, the combined analysis of SSS, satellite-derived sea surface elevation and surface velocity data suggest that the precise location of the export of shelf waters depends on offshore circulation patterns, such as the location of the Brazil Malvinas Confluence and mesoscale eddies and meanders of the Brazil Current. The satellite data indicate that in summer, mixtures of low-salinity shelf waters are swiftly driven toward the ocean interior along the axis of the Brazil/Malvinas Confluence. In winter, episodic wind reversals force the low-salinity coastal plume offshore where they mix with tropical waters within the Brazil Current and create a warmer variety of low-salinity waters in the open ocean.

Key points: Satellite salinity sensors capture low-salinity detrainment events from shelves SW Atlantic low-salinity detrainments cause highest basin-scale variability In summer low-salinity detrainments cause extended low-salinity anomalies.

No MeSH data available.


Related in: MedlinePlus

(a) Summer (DJF) and (b) winter (JJA) distribution of SSS from Aquarius reprocessed from along-track L2 data. The gray thick line indicates the 200 m isobath.
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fig03: (a) Summer (DJF) and (b) winter (JJA) distribution of SSS from Aquarius reprocessed from along-track L2 data. The gray thick line indicates the 200 m isobath.

Mentions: This study employs Aquarius and SMOS sea surface salinity data (hereafter referred to as SSS-Aq and SSS-SMOS, respectively). SMOS data encompasses the period from January 2010 to December 2013 and Aquarius data from September 2011 to December 2013. The Aquarius L3 data are limited to SSS > 30 and have a resolution of 1 month and 1° × 1°. Land contamination limits the radiometer data retrieval nearshore [Meissner, 2014], because the target salinity precision of 0.2 requires the integration from the three radiometer beams and poses a serious limitation on the analysis of the effect of continental discharges. To overcome these limitations in the L3 data we have generated a new L3 data product with finer spatial resolution, shorter temporal averaging and a careful selection of data quality flags. This procedure allows us to better resolve the mesoscale variability and to capture low-salinity detrainments from the shelf region. We use Aquarius Level 2 version 2.0 (L2 v2.0) data to construct weekly SSS fields with salinities >20 with a 0.5° × 0.5° resolution. These data were obtained from NASA Jet Propulsion Laboratory (ftp://podaac.jpl.nasa.gov/). Figure 3 presents the austral summer (DJF) and winter (JJA) averaged for 2011–2013. Following Lilly and Lagerloef [2008] we applied a Local Polynomial gridding technique with an order 1 polynomial, a Gaussian kernel with a smoothing factor of 0.01, and a variable bandwidth. The bandwidth is determined by the number of observations, ∼70 km for 1 week of L2 data. The gridded data are on a 1° × 1° longitude/latitude grid over a weekly time window. Centered on each week a 3 week weighted moving average was applied with a weight of 0.25 for the side weeks and 0.5 for the center week. Thus, the weekly product is the results of a 3 week average that uses a number of observations similar to the standard Aquarius monthly L3 product in order to maintain an equivalent accuracy, but with a weighting distribution that better represents the SSS patterns observed in the center week. The choice to use Aquarius v2.0, instead of the more recent v2.5.1, is based on the fact that the former better represents the observed salinity over the relatively homogenous Patagonia continental shelf (SSS ∼ 33.6–33.8). In addition, version 2.5.1 adjustment of ascending-descending SSS data at track crossovers applied by the Aquarius Validation Data System (AVDS) led to a bias at low salinities (T. Liu, personal communication, 2014). This is in agreement with our own results based on the comparison of 1241 salinity observations from Argo floats available in the South Atlantic with concomitant SSS-Aq at 0.5° × 0.5° resolution, which for v2.5.1 presents a positive salinity bias of ∼0.5 at SSS < 35 (see supporting information Figure S1). While this article was under revision NASA released the Aquarius L3 data version 3.0. We compared the SSS distribution derived from L3 v3.0 data with the v2.0 distribution for the 11 December 2011 (Figure S1). We note that at salinities lower than 35.5 SSS-Aq v2.0 is fresher than v3.0. Moreover, SSS-Aq v2.0 data also compare better with observations over the continental shelf than v3.0, while both data versions are in good agreement at salinities higher than 35 (Figure S1). Despite of these differences, the SSS patterns that emerge from the most recent data set are in good qualitative agreement with the ones derived from v2.0 used in our analysis. Further details on the Aquarius data processing are presented as supporting information.


The salinity signature of the cross-shelf exchanges in the Southwestern Atlantic Ocean: Satellite observations.

Guerrero RA, Piola AR, Fenco H, Matano RP, Combes V, Chao Y, James C, Palma ED, Saraceno M, Strub PT - J Geophys Res Oceans (2014)

(a) Summer (DJF) and (b) winter (JJA) distribution of SSS from Aquarius reprocessed from along-track L2 data. The gray thick line indicates the 200 m isobath.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4508963&req=5

fig03: (a) Summer (DJF) and (b) winter (JJA) distribution of SSS from Aquarius reprocessed from along-track L2 data. The gray thick line indicates the 200 m isobath.
Mentions: This study employs Aquarius and SMOS sea surface salinity data (hereafter referred to as SSS-Aq and SSS-SMOS, respectively). SMOS data encompasses the period from January 2010 to December 2013 and Aquarius data from September 2011 to December 2013. The Aquarius L3 data are limited to SSS > 30 and have a resolution of 1 month and 1° × 1°. Land contamination limits the radiometer data retrieval nearshore [Meissner, 2014], because the target salinity precision of 0.2 requires the integration from the three radiometer beams and poses a serious limitation on the analysis of the effect of continental discharges. To overcome these limitations in the L3 data we have generated a new L3 data product with finer spatial resolution, shorter temporal averaging and a careful selection of data quality flags. This procedure allows us to better resolve the mesoscale variability and to capture low-salinity detrainments from the shelf region. We use Aquarius Level 2 version 2.0 (L2 v2.0) data to construct weekly SSS fields with salinities >20 with a 0.5° × 0.5° resolution. These data were obtained from NASA Jet Propulsion Laboratory (ftp://podaac.jpl.nasa.gov/). Figure 3 presents the austral summer (DJF) and winter (JJA) averaged for 2011–2013. Following Lilly and Lagerloef [2008] we applied a Local Polynomial gridding technique with an order 1 polynomial, a Gaussian kernel with a smoothing factor of 0.01, and a variable bandwidth. The bandwidth is determined by the number of observations, ∼70 km for 1 week of L2 data. The gridded data are on a 1° × 1° longitude/latitude grid over a weekly time window. Centered on each week a 3 week weighted moving average was applied with a weight of 0.25 for the side weeks and 0.5 for the center week. Thus, the weekly product is the results of a 3 week average that uses a number of observations similar to the standard Aquarius monthly L3 product in order to maintain an equivalent accuracy, but with a weighting distribution that better represents the SSS patterns observed in the center week. The choice to use Aquarius v2.0, instead of the more recent v2.5.1, is based on the fact that the former better represents the observed salinity over the relatively homogenous Patagonia continental shelf (SSS ∼ 33.6–33.8). In addition, version 2.5.1 adjustment of ascending-descending SSS data at track crossovers applied by the Aquarius Validation Data System (AVDS) led to a bias at low salinities (T. Liu, personal communication, 2014). This is in agreement with our own results based on the comparison of 1241 salinity observations from Argo floats available in the South Atlantic with concomitant SSS-Aq at 0.5° × 0.5° resolution, which for v2.5.1 presents a positive salinity bias of ∼0.5 at SSS < 35 (see supporting information Figure S1). While this article was under revision NASA released the Aquarius L3 data version 3.0. We compared the SSS distribution derived from L3 v3.0 data with the v2.0 distribution for the 11 December 2011 (Figure S1). We note that at salinities lower than 35.5 SSS-Aq v2.0 is fresher than v3.0. Moreover, SSS-Aq v2.0 data also compare better with observations over the continental shelf than v3.0, while both data versions are in good agreement at salinities higher than 35 (Figure S1). Despite of these differences, the SSS patterns that emerge from the most recent data set are in good qualitative agreement with the ones derived from v2.0 used in our analysis. Further details on the Aquarius data processing are presented as supporting information.

Bottom Line: However, the combined analysis of SSS, satellite-derived sea surface elevation and surface velocity data suggest that the precise location of the export of shelf waters depends on offshore circulation patterns, such as the location of the Brazil Malvinas Confluence and mesoscale eddies and meanders of the Brazil Current.The satellite data indicate that in summer, mixtures of low-salinity shelf waters are swiftly driven toward the ocean interior along the axis of the Brazil/Malvinas Confluence.Satellite salinity sensors capture low-salinity detrainment events from shelves SW Atlantic low-salinity detrainments cause highest basin-scale variability In summer low-salinity detrainments cause extended low-salinity anomalies.

View Article: PubMed Central - PubMed

Affiliation: Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP) Mar del Plata, Argentina.

ABSTRACT

: Satellite-derived sea surface salinity (SSS) data from Aquarius and SMOS are used to study the shelf-open ocean exchanges in the western South Atlantic near 35°S. Away from the tropics, these exchanges cause the largest SSS variability throughout the South Atlantic. The data reveal a well-defined seasonal pattern of SSS during the analyzed period and of the location of the export of low-salinity shelf waters. In spring and summer, low-salinity waters over the shelf expand offshore and are transferred to the open ocean primarily southeast of the river mouth (from 36°S to 37°30'S). In contrast, in fall and winter, low-salinity waters extend along a coastal plume and the export path to the open ocean distributes along the offshore edge of the plume. The strong seasonal SSS pattern is modulated by the seasonality of the along-shelf component of the wind stress over the shelf. However, the combined analysis of SSS, satellite-derived sea surface elevation and surface velocity data suggest that the precise location of the export of shelf waters depends on offshore circulation patterns, such as the location of the Brazil Malvinas Confluence and mesoscale eddies and meanders of the Brazil Current. The satellite data indicate that in summer, mixtures of low-salinity shelf waters are swiftly driven toward the ocean interior along the axis of the Brazil/Malvinas Confluence. In winter, episodic wind reversals force the low-salinity coastal plume offshore where they mix with tropical waters within the Brazil Current and create a warmer variety of low-salinity waters in the open ocean.

Key points: Satellite salinity sensors capture low-salinity detrainment events from shelves SW Atlantic low-salinity detrainments cause highest basin-scale variability In summer low-salinity detrainments cause extended low-salinity anomalies.

No MeSH data available.


Related in: MedlinePlus