scholarly journals Quality assessment of spaceborne sea surface salinity observations over the northern North Atlantic

2015 ◽  
Vol 120 (1) ◽  
pp. 94-112 ◽  
Author(s):  
Julia Köhler ◽  
Meike Sena Martins ◽  
Nuno Serra ◽  
Detlef Stammer
Keyword(s):  
Quality Assessment ◽  
North Atlantic ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity

scholarly journals Response of Freshwater Flux and Sea Surface Salinity to Variability of the Atlantic Warm Pool

2013 ◽  
Vol 26 (4) ◽  
pp. 1249-1267 ◽  
Author(s):  
Chunzai Wang ◽  
Liping Zhang ◽  
Sang-Ki Lee
Keyword(s):  
Central America ◽  
North Atlantic ◽  
Warm Pool ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Freshwater Flux ◽  
Surface Salinity ◽  
Atlantic Warm Pool ◽  
Mean Circulation ◽  
Circulation Dynamics

Abstract The response of freshwater flux and sea surface salinity (SSS) to the Atlantic warm pool (AWP) variations from seasonal to multidecadal time scales is investigated by using various reanalysis products and observations. All of the datasets show a consistent response for all time scales: A large (small) AWP is associated with a local freshwater gain (loss) to the ocean, less (more) moisture transport across Central America, and a local low (high) SSS. The moisture budget analysis demonstrates that the freshwater change is dominated by the atmospheric mean circulation dynamics, while the effect of thermodynamics is of secondary importance. Further decomposition points out that the contribution of the mean circulation dynamics primarily arises from its divergent part, which mainly reflects the wind divergent change in the low level as a result of SST change. In association with a large (small) AWP, warmer (colder) than normal SST over the tropical North Atlantic can induce anomalous low-level convergence (divergence), which favors anomalous ascent (decent) and thus generates more (less) precipitation. On the other hand, a large (small) AWP weakens (strengthens) the trade wind and its associated westward moisture transport to the eastern North Pacific across Central America, which also favors more (less) moisture residing in the Atlantic and hence more (less) precipitation. The results imply that variability of freshwater flux and ocean salinity in the North Atlantic associated with the AWP may have the potential to affect the Atlantic meridional overturning circulation.

scholarly journals Comparison of Satellite-Derived Sea Surface Temperature and Sea Surface Salinity Gradients Using the Saildrone California/Baja and North Atlantic Gulf Stream Deployments

2020 ◽  
Vol 12 (11) ◽  
pp. 1839 ◽  
Author(s):  
Jorge Vazquez-Cuervo ◽  
Jose Gomez-Valdes ◽  
Marouan Bouali
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Gulf Stream ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Temporal Sampling ◽  
The North

Validation of satellite-based retrieval of ocean parameters like Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) is commonly done via statistical comparison with in situ measurements. Because in situ observations derived from coastal/tropical moored buoys and Argo floats are only representatives of one specific geographical point, they cannot be used to measure spatial gradients of ocean parameters (i.e., two-dimensional vectors). In this study, we exploit the high temporal sampling of the unmanned surface vehicle (USV) Saildrone (i.e., one measurement per minute) and describe a methodology to compare the magnitude of SST and SSS gradients derived from satellite-based products with those captured by Saildrone. Using two Saildrone campaigns conducted in the California/Baja region in 2018 and in the North Atlantic Gulf Stream in 2019, we compare the magnitude of gradients derived from six different GHRSST Level 4 SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and two SSS (JPLSMAP, RSS40km) datasets. While results indicate strong consistency between Saildrone- and satellite-based observations of SST and SSS, this is not the case for derived gradients with correlations lower than 0.4 for SST and 0.1 for SSS products.

scholarly journals Nine years of SMOS Sea Surface Salinity global maps at the Barcelona Expert Center

2020 ◽  
Author(s):  
Estrella Olmedo ◽  
Cristina González-Haro ◽  
Nina Hoareau ◽  
Marta Umbert ◽  
Verónica González-Gambau ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Quality Assessment ◽  
Global Scale ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Low Resolution ◽  
Surface Salinity ◽  
Resolution Level ◽  
Level 3 ◽  
Expert Center

Abstract. After more than 10 years in orbit, the Soil Moisture and Ocean Salinity (SMOS) European mission is still a unique, highquality instrument for providing Soil Moisture over land and Sea Surface Salinity (SSS) over the oceans. At the Barcelona Expert Center (BEC), a new reprocessing of 9 years (2011–2019) of global SMOS SSS maps has been generated. This work presents the algorithms used in the generation of BEC global SMOS SSS product v2.0, as well as an extensive quality assessment. Three SMOS SSS fields are distributed: a high-resolution level 3 product (with https://doi.org/10.20350/digitalCSIC/12601 (Olmedo et al., 2020a)) consisting of a binned SSS in 9-day maps at 0.25 × 0.25°; a low-resolution level 3 SSS computed from the binned salinity by applying a smoothening spatial window of 50-km radius; and a level 4 SSS (with https://doi.org/10.20350/digitalCSIC/12600 (Olmedo et al., 2020b)) consisting of daily, 0.05 × 0.05° maps that are computed by multifractal fusion with Sea Surface Temperature maps. For the validation of BEC SSS products, we have applied a battery of tests aiming at the assessment of quality of the products both in value and in structure. First, we have compared BEC SSS products with near-to-surface salinity measurements provided by Argo floats. Secondly, we have assessed the geophysical consistency of the products characterized by singularity analysis, and also the effective spatial resolutions are estimated by means of Power Density Spectra and Singularity Density Spectra. Finally, we have calculated full maps of SSS errors by using Correlated Triple Collocation. We have compared the performance of BEC SMOS product with other satellite SSS and reanalysis products. The main outcomes of this quality assessment are: i) the bias between BEC SMOS and Argo salinity is lower than 0.02 psu at global scale, while the standard deviation of their difference is lower than 0.34 and 0.27 psu for the high and low resolution level 3 fields (respectively) and 0.24 psu for the level 4 salinity; ii) the effective spatial resolution is around 40 km for all SSS products and regions; and iii) BEC SMOS level 4 product is globally the one with the lowest salinity error, while BEC SMOS low-resolution level 3 more accurate in regions strongly affected by rainfall and continental freshwater discharges.

North Atlantic Sea Surface Salinity, Ice Melting and Abrupt Climatic Changes

1993 ◽  
pp. 623-631 ◽  
Author(s):  
Martine Paterne ◽  
Jean-Claude Duplessy ◽  
Laurent Labeyrie ◽  
Maurice Arnold
Keyword(s):  
North Atlantic ◽  
Climatic Changes ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Ice Melting ◽  
Surface Salinity

scholarly journals Spatial Scales of Sea Surface Salinity Subfootprint Variability in the SPURS Regions

2020 ◽  
Vol 12 (23) ◽  
pp. 3996
Author(s):  
Frederick M. Bingham ◽  
Zhijin Li
Keyword(s):  
North Atlantic ◽  
Spatial Scales ◽  
Remote Sensing Data ◽  
Ocean Modeling ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Regional Ocean Modeling System ◽  
Surface Salinity ◽  
In Situ Data

Subfootprint variability (SFV), or representativeness error, is variability within the footprint of a satellite that can impact validation by comparison of in situ and remote sensing data. This study seeks to determine the size of the sea surface salinity (SSS) SFV as a function of footprint size in two regions that were heavily sampled with in situ data. The Salinity Processes in the Upper-ocean Regional Studies-1 (SPURS-1) experiment was conducted in the subtropical North Atlantic in the period 2012–2013, whereas the SPURS-2 study was conducted in the tropical eastern North Pacific in the period 2016–2017. SSS SFV was also computed using a high-resolution regional model based on the Regional Ocean Modeling System (ROMS). We computed SFV at footprint sizes ranging from 20 to 100 km for both regions. SFV is strongly seasonal, but for different reasons in the two regions. In the SPURS-1 region, the meso- and submesoscale variability seemed to control the size of the SFV. In the SPURS-2 region, the SFV is much larger than SPURS-1 and controlled by patchy rainfall.

scholarly journals Implications of North Atlantic Sea Surface Salinity for Summer Precipitation over the U.S. Midwest: Mechanisms and Predictive Value

2016 ◽  
Vol 29 (9) ◽  
pp. 3143-3159 ◽  
Author(s):  
Laifang Li ◽  
Raymond W. Schmitt ◽  
Caroline C. Ummenhofer ◽  
Kristopher B. Karnauskas
Keyword(s):  
United States ◽  
Soil Moisture ◽  
North Atlantic ◽  
Summer Precipitation ◽  
Moisture Flux ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Southern United States ◽  
Surface Salinity ◽  
The U.S

Abstract Moisture originating from the subtropical North Atlantic feeds precipitation throughout the Western Hemisphere. This ocean-to-land moisture transport leaves its imprint on sea surface salinity (SSS), enabling SSS over the subtropical oceans to be used as an indicator of terrestrial precipitation. This study demonstrates that springtime SSS over the northwestern portion of the subtropical North Atlantic significantly correlates with summertime precipitation over the U.S. Midwest. The linkage between springtime SSS and the Midwest summer precipitation is established through ocean-to-land moisture transport followed by a soil moisture feedback over the southern United States. In the spring, high SSS over the northwestern subtropical Atlantic coincides with a local increase in moisture flux divergence. The moisture flux is then directed toward and converges over the southern United States, which experiences increased precipitation and soil moisture. The increased soil moisture influences the regional water cycle both thermodynamically and dynamically, leading to excessive summer precipitation in the Midwest. Thermodynamically, the increased soil moisture tends to moisten the lower troposphere and enhances the meridional humidity gradient north of 36°N. Thus, more moisture will be transported and converged into the Midwest by the climatological low-level wind. Dynamically, the increases in soil moisture over the southern United States enhance the west–east soil moisture gradient eastward of the Rocky Mountains, which can help to intensify the Great Plains low-level jet in the summer, converging more moisture into the Midwest. Owing to these robust physical linkages, the springtime SSS outweighs the leading SST modes in predicting the Midwest summer precipitation and significantly improves rainfall prediction in this region.

scholarly journals Impact of Initialization Methods on the Predictive skill in NorCPM - An Arctic-Atlantic Case Study

2021 ◽  
Author(s):  
Leilane Passos ◽  
Helene Langehaug ◽  
Marius Årthun ◽  
Tor Eldevik ◽  
Ingo Bethke ◽  
...  
Keyword(s):  
Data Assimilation ◽  
North Atlantic ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Complex Data ◽  
Surface Salinity ◽  
Norwegian Sea ◽  
Predictive Skill ◽  
The Impact

Abstract The skilful prediction of climatic conditions on a forecast horizon of months to decades into the future remains a main scientific challenge of large societal benefit. Here we assess the hindcast skill of the Norwegian Climate Prediction Model (NorCPM) – for sea surface temperature (SST) and sea surface salinity (SSS) in the Arctic-Atlantic region – focusing on the impact of different initialization methods. We find the skill to be distinctly larger for the Subpolar North Atlantic than for the Norwegian Sea, and generally for all lead years analyzed. For the Subpolar North Atlantic, there is furthermore consistent benefit in increasing the amount of data assimilated, and also in updating the sea ice based on SST with strongly coupled data assimilation. The predictive skill is furthermore significant for at least two model versions up to 8-10 lead years with the exception for SSS at the longer lead years. For the Norwegian Sea, significant predictive skill is more rare; there is relatively higher skill with respect to SSS than for SST. A systematic benefit from more complex data assimilation approach can not be identified for this region. Somewhat surprisingly, skill deteriorates quite consistently for both the Subpolar North Atlantic and the Norwegian Sea when going from CMIP5 to corresponding CMIP6 versions. We find this to relate to change in the regional performance of the underlying physical model that dominates the benefit from initialization.

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