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 ◽  
...  

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.

2021 ◽  
Vol 13 (5) ◽  
pp. 831
Author(s):  
Jorge Vazquez-Cuervo ◽  
Chelle Gentemann ◽  
Wenqing Tang ◽  
Dustin Carroll ◽  
Hong Zhang ◽  
...  

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.


2021 ◽  
Vol 14 (1) ◽  
pp. 71
Author(s):  
Sarah B. Hall ◽  
Bulusu Subrahmanyam ◽  
James H. Morison

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.


2021 ◽  
Vol 13 (19) ◽  
pp. 3828
Author(s):  
Marta Umbert ◽  
Carolina Gabarro ◽  
Estrella Olmedo ◽  
Rafael Gonçalves-Araujo ◽  
Sebastien Guimbard ◽  
...  

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.


2018 ◽  
Vol 10 (11) ◽  
pp. 1772 ◽  
Author(s):  
Estrella Olmedo ◽  
Carolina Gabarró ◽  
Verónica González-Gambau ◽  
Justino Martínez ◽  
Joaquim Ballabrera-Poy ◽  
...  

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.


2020 ◽  
Vol 249 ◽  
pp. 112027
Author(s):  
Alexandre Supply ◽  
Jacqueline Boutin ◽  
Jean-Luc Vergely ◽  
Nicolas Kolodziejczyk ◽  
Gilles Reverdin ◽  
...  

2020 ◽  
Author(s):  
Estrella Olmedo ◽  
Cristina González-Haro ◽  
Nina Hoareau ◽  
Marta Umbert ◽  
Verónica González-Gambau ◽  
...  

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.


2021 ◽  
Vol 13 (16) ◽  
pp. 3224
Author(s):  
Joan Francesc Munoz-Martin ◽  
Adriano Camps

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.


2021 ◽  
Author(s):  
Aleksandr Konik ◽  
Alexey Zimin

<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>


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