Variability of the frontal and eddies dynamics of the Kara Sea in the summer period

2021 ◽  
Author(s):  
Aleksandr Konik ◽  
Alexey Zimin
Keyword(s):  
Warm Season ◽  
Arctic Region ◽  
Kara Sea ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Surface Salinity ◽  
Radar Images ◽  
Percentage Difference ◽  
Frontal Zones

<p>The dynamics of fronts in the Arctic region is crucial in the formation and further variability of processes in the atmosphere and hydrosphere as a whole. However, the significant synoptic variability of the boundaries of the frontal zones and their characteristics determines the relevance of their study in a changing climate.</p><p>The article considers the relationship between the position of frontal zones and eddies structures in the Kara Sea in August and September 2019. To identify frontal zones, a single database is used, formed based on data on sea surface temperature from the Suomi NPP Viirs satellite, sea surface salinity from the NASA SMAP satellite and sea level from the international AVISO base. The cluster analysis method is used to detect frontal zones in the Kara Sea. To register the manifestations of eddies structures 358 Sentinel-1A and-1B satellite radar images obtained in the C-band at BB polarization and EW and IW shooting modes are analyzed.</p><p>It was possible to identify four classes of water in the sea area, one of which was identified as the River Plums frontal zone (RPFZ) the Ob and Yenisei. The maximum synoptic temperature gradient in the RPFZ region is 0.14°C/km, salinity is 0.12‰/km, and the level is 2 cm/km. It was found that the area of the RPFZ varies from 190K km<sup>2</sup> in August to 221K km<sup>2</sup> in September. During the research period, 1272 eddies structures were identified. It is shown that in August the number of eddies observed inside and within the boundaries of the frontal zones was twice as high as in September. In general, in the warm season of 2019 in the Kara Sea, most eddies occur in the RPFZ region. Thus, the number of eddies on the borders and inside the RPFZ in August is 30% more, and in September it is 20% more. The percentage difference is related to the wind impact over the Kara Sea, which is observed in September.</p><p>The analysis of the frontal zones and eddies in this work was supported by RFBR grant 20-35-90053.</p>

scholarly journals Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models

2021 ◽  
Vol 13 (5) ◽  
pp. 831
Author(s):  
Jorge Vazquez-Cuervo ◽  
Chelle Gentemann ◽  
Wenqing Tang ◽  
Dustin Carroll ◽  
Hong Zhang ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Future Research ◽  
Surface Salinity ◽  
Cold Temperatures ◽  
Yukon River ◽  
Arctic Sea ◽  
The Arctic Ocean

The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the −2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations.

scholarly journals Intercomparison of Salinity Products in the Beaufort Gyre and Arctic Ocean

2021 ◽  
Vol 14 (1) ◽  
pp. 71
Author(s):  
Sarah B. Hall ◽  
Bulusu Subrahmanyam ◽  
James H. Morison
Keyword(s):  
Soil Moisture ◽  
Arctic Ocean ◽  
Satellite Observations ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Surface Salinity ◽  
Beaufort Gyre ◽  
The Arctic Ocean

Salinity is the primary determinant of the Arctic Ocean’s density structure. Freshwater accumulation and distribution in the Arctic Ocean have varied significantly in recent decades and certainly in the Beaufort Gyre (BG). In this study, we analyze salinity variations in the BG region between 2012 and 2017. We use in situ salinity observations from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), CTD casts from the Beaufort Gyre Exploration Project (BGP), and the EN4 data to validate and compare with satellite observations from Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Aquarius Optimally Interpolated Sea Surface Salinity (OISSS), and Arctic Ocean models: ECCO, MIZMAS, HYCOM, ORAS5, and GLORYS12. Overall, satellite observations are restricted to ice-free regions in the BG area, and models tend to overestimate sea surface salinity (SSS). Freshwater Content (FWC), an important component of the BG, is computed for EN4 and most models. ORAS5 provides the strongest positive SSS correlation coefficient (0.612) and lowest bias to in situ observations compared to the other products. ORAS5 subsurface salinity and FWC compare well with the EN4 data. Discrepancies between models and SIZRS data are highest in GLORYS12 and ECCO. These comparisons identify dissimilarities between salinity products and extend challenges to observations applicable to other areas of the Arctic Ocean.

scholarly journals Using Remotely Sensed Sea Surface Salinity and Colored Detrital Matter to Characterize Freshened Surface Layers in the Kara and Laptev Seas during the Ice-Free Season

2021 ◽  
Vol 13 (19) ◽  
pp. 3828
Author(s):  
Marta Umbert ◽  
Carolina Gabarro ◽  
Estrella Olmedo ◽  
Rafael Gonçalves-Araujo ◽  
Sebastien Guimbard ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
River Runoff ◽  
River Discharge ◽  
Active Material ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Optical Data ◽  
Surface Salinity ◽  
The Arctic Ocean

The overall volume of freshwater entering the Arctic Ocean has been growing as glaciers melt and river runoff increases. Since 1980, a 20% increase in river runoff has been observed in the Arctic system. As the discharges of the Ob, Yenisei, and Lena rivers are an important source of freshwater in the Kara and Laptev Seas, an increase in river discharge might have a significant impact on the upper ocean circulation. The fresh river water mixes with ocean water and forms a large freshened surface layer (FSL), which carries high loads of dissolved organic matter and suspended matter into the Arctic Ocean. Optically active material (e.g., phytoplankton and detrital matter) are spread out into plumes, which are evident in satellite data. Russian river signatures in the Kara and Laptev Seas are also evident in recent SMOS Sea Surface Salinity (SSS) Arctic products. In this study, we compare the new Arctic+ SSS products, produced at the Barcelona Expert Center, with the Ocean Color absorption coefficient of colored detrital matter (CDM) in the Kara and Laptev Seas for the period 2011–2019. The SSS and CDM are found to be strongly negatively correlated in the regions of freshwater influence, with regression coefficients between −0.72 and −0.91 in the studied period. Exploiting this linear correlation, we estimate the SSS back to 1998 using two techniques: one assuming that the relationship between the CDM and SSS varies regionally in the river-influenced areas, and another assuming that it does not. We use the 22-year time-series of reconstructed SSS to estimate the interannual variability of the extension of the FSL in the Kara and Laptev Seas as well as their freshwater content. For the Kara and Laptev Seas, we use 32 and 28 psu as reference salinities, and 26 and 24 psu isohalines as FSL boundaries, respectively. The average FSL extension in the Kara Sea is 2089–2611 km2, with a typical freshwater content of 11.84–14.02 km3. The Laptev Sea has a slightly higher mean FSL extension of 2320–2686 km2 and a freshwater content of 10.15–12.44 km3. The yearly mean freshwater content and extension of the FSL, computed from SMOS SSS and Optical data, is (as expected) found to co-vary with in situ measurements of river discharge from the Arctic Great Rivers Observatory database, demonstrating the potential of SMOS SSS to better monitor the river discharge changes in Eurasia and to understand the Arctic freshwater system during the ice-free season.

scholarly journals Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions

2018 ◽  
Vol 10 (11) ◽  
pp. 1772 ◽  
Author(s):  
Estrella Olmedo ◽  
Carolina Gabarró ◽  
Verónica González-Gambau ◽  
Justino Martínez ◽  
Joaquim Ballabrera-Poy ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Remotely Sensed ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Surface Salinity ◽  
In Situ Data ◽  
Arctic Regions ◽  
The Difference

This paper aims to present and assess the quality of seven years (2011–2017) of 25 km nine-day Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) objectively analyzed maps in the Arctic and sub-Arctic oceans ( 50 ∘ N– 90 ∘ N). The SMOS SSS maps presented in this work are an improved version of the preliminary three-year dataset generated and freely distributed by the Barcelona Expert Center. In this new version, a time-dependent bias correction has been applied to mitigate the seasonal bias that affected the previous SSS maps. An extensive database of in situ data (Argo floats and thermosalinograph measurements) has been used for assessing the accuracy of this product. The standard deviation of the difference between the new SMOS SSS maps and Argo SSS ranges from 0.25 and 0.35. The major features of the inter-annual SSS variations observed by the thermosalinographs are also captured by the SMOS SSS maps. However, the validation in some regions of the Arctic Ocean has not been feasible because of the lack of in situ data. In those regions, qualitative comparisons with SSS provided by models and the remotely sensed SSS provided by Aquarius and SMAP have been performed. Despite the differences between SMOS and SMAP, both datasets show consistent SSS variations with respect to the model and the river discharge in situ data, but present a larger dynamic range than that of the model. This result suggests that, in those regions, the use of the remotely sensed SSS may help to improve the models.

scholarly journals New insights into SMOS sea surface salinity retrievals in the Arctic Ocean

2020 ◽  
Vol 249 ◽  
pp. 112027
Author(s):  
Alexandre Supply ◽  
Jacqueline Boutin ◽  
Jean-Luc Vergely ◽  
Nicolas Kolodziejczyk ◽  
Gilles Reverdin ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Surface Salinity ◽  
The Arctic Ocean

scholarly journals Sea Surface Salinity and Wind Speed Retrievals Using GNSS-R and L-Band Microwave Radiometry Data from FMPL-2 Onboard the FSSCat Mission

2021 ◽  
Vol 13 (16) ◽  
pp. 3224
Author(s):  
Joan Francesc Munoz-Martin ◽  
Adriano Camps
Keyword(s):  
Wind Speed ◽  
Microwave Radiometer ◽  
Sea Surface ◽  
Third Party ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Weekly Schedule ◽  
Surface Salinity ◽  
Sea Ice Concentration ◽  
L Band

The Federated Satellite System mission (FSSCat), winner of the 2017 Copernicus Masters Competition and the first ESA third-party mission based on CubeSats, aimed to provide coarse-resolution soil moisture estimations and sea ice concentration maps by means of the passive microwave measurements collected by the Flexible Microwave Payload-2 (FMPL-2). The mission was successfully launched on 3 September 2020. In addition to the primary scientific objectives, FMPL-2 data are used in this study to estimate sea surface salinity (SSS), correcting for the sea surface roughness using a wind speed estimate from the L-band microwave radiometer and GNSS-R data themselves. FMPL-2 was executed over the Arctic and Antarctic oceans on a weekly schedule. Different artificial neural network algorithms have been implemented, combining FMPL-2 data with the sea surface temperature, showing a root-mean-square error (RMSE) down to 1.68 m/s in the case of the wind speed (WS) retrieval algorithms, and RMSE down to 0.43 psu for the sea surface salinity algorithm in one single pass.

scholarly journals Improved BEC SMOS Arctic Sea Surface Salinity product v3.1

2021 ◽  
Author(s):  
Justino Martínez ◽  
Carolina Gabarró ◽  
Antonio Turiel ◽  
Verónica González-Gambau ◽  
Marta Umbert ◽  
...  
Keyword(s):  
Major Change ◽  
New Product ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Surface Salinity ◽  
Accuracy Requirement ◽  
Mesoscale Structures ◽  
Arctic Sea ◽  
Expert Center

Abstract. Measuring salinity from space is challenging since the sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) is low (about 0.5 K / psu), while the SSS range in the open ocean is narrow (about 5 psu, if river discharge areas are not considered). This translates into a high accuracy requirement of the radiometer (about 2–3 K). Moreover, the sensitivity of the TB to SSS at cold waters is even lower (0.3 K / psu), making the retrieval of the SSS in the cold waters even more challenging. Due to this limitation, ESA launched a specific initiative in 2019, the Arctic+Salinity project (AO/1-9158/18/I-BG), to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product (Martínez et al., 2020) . The product consists of 9-day averaged maps in an EASE 2.0 grid of 25 km. The product is freely distributed from the Barcelona Expert Center (BEC, http://bec.icm.csic.es/) with the DOI number: 10.20350/digitalCSIC/12620. The major change in this new product is its improvement of the effective spatial resolution that permits better monitoring of the mesoscale structures (larger than 50 Km), which benefits the river discharges monitoring.

scholarly journals The Potential of Space-Based Sea Surface Salinity on Monitoring the Hudson Bay Freshwater Cycle

2020 ◽  
Vol 12 (5) ◽  
pp. 873 ◽  
Author(s):  
Wenqing Tang ◽  
Simon H. Yueh ◽  
Daqing Yang ◽  
Ellie Mcleod ◽  
Alexander Fore ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Sea Ice ◽  
River Discharge ◽  
Open Water ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Hudson Bay ◽  
Surface Salinity ◽  
Ice Melt

Hudson Bay (HB) is the largest semi-inland sea in the Northern Hemisphere, connecting with the Arctic Ocean through the Foxe Basin and the northern Atlantic Ocean through the Hudson Strait. HB is covered by ice and snow in winter, which completely melts in summer. For about six months each year, satellite remote sensing of sea surface salinity (SSS) is possible over open water. SSS links freshwater contributions from river discharge, sea ice melt/freeze, and surface precipitation/evaporation. Given the strategic importance of HB, SSS has great potential in monitoring the HB freshwater cycle and studying its relationship with climate change. However, SSS retrieved in polar regions (poleward of 50°) from currently operational space-based L-band microwave instruments has large uncertainty (~ 1 psu) mainly due to sensitivity degradation in cold water (<5°C) and sea ice contamination. This study analyzes SSS from NASA Soil Moisture Active and Passive (SMAP) and European Space Agency (ESA) Soil Moisture and Ocean Salinity(SMOS) missions in the context of HB freshwater contents. We found that the main source of the year-to-year SSS variability is sea ice melting, in particular, the onset time and places of ice melt in the first couple of months of open water season. The freshwater contribution from surface forcing P-E is smaller in magnitude comparing with sea ice contribution but lasts on longer time scale through the whole open water season. River discharge is comparable with P-E in magnitude but peaks before ice melt. The spatial and temporal variations of freshwater contents largely exceed the remote sensed SSS uncertainty. This fact justifies the use of remote sensed SSS for monitoring the HB freshwater cycle.

scholarly journals Surface Freshwater Fluxes in the Arctic and Subarctic Seas during Contrasting Years of High and Low Summer Sea Ice Extent

2021 ◽  
Vol 13 (8) ◽  
pp. 1570
Author(s):  
Sarah B. Hall ◽  
Bulusu Subrahmanyam ◽  
Ebenezer S. Nyadjro ◽  
Annette Samuelsen
Keyword(s):  
Sea Ice ◽  
Global Climate ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Spatial And Temporal Variability ◽  
Polar Regions ◽  
Surface Salinity ◽  
Sea Ice Concentration ◽  
Sea Ice Extent

Freshwater (FW) flux between the Arctic Ocean and adjacent waterways, predominantly driven by wind and oceanic currents, influences halocline stability and annual sea ice variability which further impacts global circulation and climate. The Arctic recently experienced anomalous years of high and low sea ice extent in the summers of 2013/2014 and 2012/2016, respectively. Here we investigate the interannual variability of oceanic surface FW flux in relation to spatial and temporal variability in sea ice concentration (SIC), sea surface salinity (SSS), and sea surface temperature (SST), focusing on years with summer sea–ice extremes. Our analysis between 2010–2018 illustrate high parameter variability, especially within the Laptev, Kara, and Barents seas, as well as an overall decreasing trend of FW flux through the Fram Strait. We find that in 2012, a maximum average FW flux of 0.32 × 103 ms−1 in October passed over a large portion of the Northeast Atlantic Ocean at 53°N. This study highlights recent changes in the Arctic and Subarctic Seas and the importance of continued monitoring of key variables through remote sensing to understand the dynamics behind these ongoing changes. Observations of FW fluxes through major Arctic routes will be increasingly important as the polar regions become more susceptible to warming, with major impacts on global climate.

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