Highlights

High Latitudes

  • In the Arctic, salinity trends reveal water cycle variations.
    Salinity is an important - but poorly studied - component of the high-latitude ocean. In the rapidly changing Arctic salinity trends reveal water cycle variations.
  • Salinity is a key ingredient in the layering of high-latitude ocean waters.
    Salinity is a key ingredient in the layering of high-latitude ocean waters. Thus, it influences the formation of water masses and affects global ocean circulation.
  • Detecting cold-water salinity from space is challenging.
    Detecting cold-water salinity from space has been challenging. NASA is investigating how to monitor our polar oceans with improved sensors and computer models.
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"Let us love winter, for it is the spring of genius." - Pietro Aretino

Climate is changing. And nowhere is it more evident than near Earth's poles. Life that has adapted to these extreme regions – including sea ice-dependent species from tiny algae to huge polar bears – is being impacted. Salinity is a "key ingredient" for high-latitude ocean ecological communities. Why? It affects seawater density which, in turn, influences the movement of water, heat, and carbon.

A basin surrounded by land, the Arctic Ocean has a cap of frozen seawater (a.k.a. "sea ice") that waxes and wanes. For years, satellites have tracked sea ice growth each winter and the dramatic extent of sea ice melt each summer. In the Arctic Ocean, thermohaline (i.e., temperature- and salt-controlled) layering is vital to maintaining the cold, relatively fresh surface waters that support diverse ecosystems. However, measuring cold-water salinity from space is challenging.

Antarctica is a large continent surrounded by the Southern Ocean. Because of this geography, sea ice has more room to expand in the winter. So, sea ice – along with other ice that originated on land such as icebergs – can move into warmer latitudes and melt. Being the only place where our seas circle Earth without being slowed down by land, the Southern Ocean is prone to very high winds. Along with cold temperatures, a wind-roughened sea surface hampers the accurate measurement of salinity from satellite.

Use the tool below – based on studies by Lind et al. (2018) and Haumann et al. (2016) – to investigate the characteristics of salinity in the Arctic and Antarctic. Use the buttons to toggle between locations.

Study area
Antarctic and Arctic sea ice. Credit: NASA Goddard Space Flight Center

Related Publications

  • Trossman, D., and Bayler, E. (2022). An Algorithm to Bias-Correct and Transform Arctic SMAP-Derived Skin Salinities into Bulk Surface Salinities, Remote Sens., 14(6), 1418, doi: 10.3390/rs14061418.
    MDPI »
  • Zhao, J., Wang, Y., Liu, W., Bi, H., Cokelet, E., Mordy, C., Lawrence-Slavas, N., and Meinig, C. (2022). Sea Surface Salinity Variability in the Bering Sea in 2015-2020, Remote Sens., 14(3), 758, doi: 10.3390/rs14030758.
    MDPI »
  • Vazquez-Cuervo, J., Castro, S., Steele, M., Gentemann, C., Gomez-Valdes, J., and Tang, W. (2022). Comparison of GHRSST SST Analysis in the Arctic Ocean and Alaskan CoastalWaters Using Saildrones, Remote Sens., 14(3), 692, doi: 10.3390/rs14030692.
    MDPI »
  • Hall, S., Subrahmanyam, B., and Morison, H. (2022). Intercomparison of Salinity Products in the Beaufort Gyre and Arctic Ocean, Remote Sens., 14, 71, doi: 10.3390/rs14010071.
    MDPI »
  • Zhuk, V. and Kubryakov, A. (2021). Interannual Variability of the Lena River Plume Propagation in 1993–2020 during the Ice-Free Period on the Base of Satellite Salinity, Temperature, and Altimetry Measurements, Remote Sens., 13, 4252, doi: 10.3390/rs13214252.
    MDPI »
  • Martínez, J., Gabarró, C., Turiel, A., González-Gambau, V., Umbert, M., Hoareau, N., González-Haro, C., Olmedo, E., Arias, M., Catany, R., Bertino, L., Raj, R. P., Xie, J., Sabia, R., and Fernández, D. (2021). Improved BEC SMOS Arctic Sea Surface Salinity product v3.1, Earth Syst. Sci. Data Discuss., doi: 10.5194/essd-2021-334.
    ESSD »
  • Vreugdenhil, C. and Gayen, B. (2021). Ocean Convection, Fluids, 6(10), 360, doi: 10.3390/fluids6100360.
    MDPI »
  • Demir, O., Johnson, J., Jezek, K., Andrews, M., Ayotte, K., Hendricks, S., Kaleschke, L., Oggier, M., Granskog, M., Fong, A., Hoppmann, M., Matero, I., and Scholz, D. (2021). Measurements of 540-1740 MHz Brightness Temperatures of Sea Ice During the Winter of the MOSAiC Campaign, IEEE Trans. Geosci. Remote Sens., doi: 10.1109/TGRS.2021.3105360.
    IEEE »
  • Gibert, F., Boutin, J., Dierking, W., Granados, A., Li, Y., Makhoul, E., Meng, J., Supply, A., Vendrell, E., Vergely, J.-L., Wang, J., Yang, J., Xiang, K., Yin, X., and Zhang, X. (2021). Results of the Dragon 4 Project on New Ocean Remote Sensing Data for Operational Applications, Remote Sens., 13(14), 2847, doi: 10.3390/rs13142847.
    MDPI »
  • Garcia-Eidell, C., Comiso, J.C., Berkelhammer, M., and Stock, L. (2021). Interrelationships of Sea Surface Salinity, Chlorophyll-α Concentration, and Sea Surface Temperature Near the Antarctic Ice Edge, J. Clim., doi: 10.1175/JCLI-D-20-0716.1.
    AMS »
  • Miller, J.Z., Culberg, R., Long, D.G., Shuman, C.A., Schroeder, D.M., and Brodzik, M.J. (2021). An Empirical Algorithm to Map Perennial Firn Aquifers, Ice Slabs, and Perched Firn Aquifers Within the Greenland Ice Sheet Using Satellite L-Band Microwave Radiometry, The Cryosphere Discuss. [preprint], doi: 10.5194/tc-2021-116, in review.
    EGU »
  • Hall, S.B., Subrahmanyam, B., Nyadjro, E.S., and Samuelsen, A. (2021). Surface Freshwater Fluxes in the Arctic and Subarctic Seas During Contrasting Years of High and Low Summer Sea Ice Extent., Remote Sens., 13 (8), 1570, doi: 10.3390/rs13081570.
    MDPI »
  • Kolodziejczyk, N., Hamon, M., Boutin, J., Vergely, J-L., Reverdin, G., Supply, A., and Reul, N. (2021). Objective Analysis of SMOS and SMAP Sea Surface Salinity to Reduce Large Scale and Time Dependent Biases from Low to High Latitudes, J. Atmos. Ocean. Technol., 38 (3), 405-421, doi: 10.1175/JTECH-D-20-0093.1.
    AMS »
  • Vazquez-Cuervo, J., Gentemann, C., Tang, W., Carroll, D., Zhang, H., Menemenlis, D., Gomez-Valdes, J., Bouali, M., and Steele, M. (2021). Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models, Remote Sens. 2021, 13, 831, doi: 10.3390/rs13050831.
    MDPI »
  • Shiklomanov, A., Dery, S., Tretiakov, M., Yang, D., Magritsky, D., Georgiadi, A., and Tang, W. (2020). River Freshwater Flux to the Arctic Ocean, In Yang D., Kane D. (eds) Arctic Hydrology, Permafrost and Ecosystems, 703-738, Springer, Cham., doi: 10.1007/978-3-030-50930-9_24.
    Springer »
  • Yu, L. (2020). Variability and Uncertainty of Satellite Sea Surface Salinity in the Subpolar North Atlantic (2010–2019), Remote Sens., 12(13), 2092, doi: 10.3390/rs12132092.
    MDPI »
  • Drushka, K., Gaube, P., Armitage, T., Cerovecki, I., Fenty, I., Fournier, S., Gentemann, C., Girton, J., Haumann, A., Lee, T., Mazloff, M., Padman, L., Rainville, L., Schanze, J., Springer, S., Steele, M., Thomson, J., and Wilson, E. (2020). A NASA High-latitude Salinity Campaign, White paper, 20 pp., doi: 10.6084/m9.figshare.12469154.v1.
    Figshare »
To view all salinity publications, visit the publications page.
Sea ice concentration bar
Choose among four slideshows featuring minimum and maximum sea ice concentrations around the Arctic and Antarctica since 1990. Minima show the months of September and February for the Arctic and Antarctic, respectively. Maxima shows the months of March and September, for the Arctic and Antarctic, respectively. (Source: NASA Earth Observatory's World of Change – Arctic & Antarctic)

Featured Publications

Changes in Arctic freshwater distribution impacts ocean circulation, climate, and life. This study explores the use of satellite-derived sea surface salinity (SSS) as a proxy for Arctic freshwater changes. It builds on previous work that used satellite‐derived sea surface height (SSH) and ocean bottom pressure (OBP) to infer depth‐integrated freshwater content changes. This proof‐of‐concept study analyzes the output of an ocean‐ice state estimation product, finding that SSS variations are coherent with SSH-minus-OBP across much of the Arctic basin.

Reference

Fournier, S., Lee, T., Wang, X., Armitage, T., Wang, O., Fukumori, I., and Kwok, R. (2020). Read the full paper.

Hudson Bay, the largest semi-inland sea in the Northern Hemisphere, is completely covered by ice and snow in winter. About six months each year, however, satellite remote sensing of sea surface salinity (SSS) can be retrieved over open water. This provides some insight into freshwater cycles in the Arctic Ocean where SSS data are scarce. The study found that the main source of the year-to-year SSS variability in Hudson Bay is sea ice melting. The freshwater contribution from surface forcing precipitation minus evaporation (P-E) is smaller in magnitude but lasts through the entire open water season. River discharge is comparable with P-E in magnitude but peaks before ice melt.

Reference

Tang, W., Yueh, S., Yang, D., Mcleod, E., Fore, A., Hayashi, A., Olmedo, E., Martínez, J., and Gabarró, C. (2020). Read the full paper.

This study presents the first systematic analysis of six commonly used sea surface salinity (SSS) products from NASA and the European Space Agency in terms of their consistency among one another and with in-situ data. When averaged over the Arctic Ocean, the products show excellent consistency in capturing seasonal and year-to-year variations. The products also consistently identify regions with strong SSS variability over time. However, many challenges still exist in retrieving Arctic SSS because brightness temperature (TB) has lower sensitivity in colder waters at the frequency employed by today's SSS satellites (i.e., L-band). View the One-pager. Read about an evaluation and intercomparison of SMOS, Aquarius, and SMAP SSS products in our Research Insights.

Reference

Fournier, S., Lee, T., Tang, W., Steele, M., and Olmedo, E. (2019). Read the full paper.

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