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Nemesio & Beatriz
simply go to –> https://twitter.com/SMOS_satellite!
Nemesio & Beatriz
By J., Boutin, N. Martin, N. Kolodziejczyk and G. Reverdin from LOCEAN/IPSL, Paris
It has been shown by Durand et al. (2013), Reul et al. (2013), Hasson et al. (2014) that SMOS detects large scale interrannual variability of SSS.
The LOCEAN group check this again over 2010-2014. The monthly anomalies of SMOS SSS with respect to a SMOS SSS monthly climatology very well agree with SSS monthly anomalies derived from in situ SSS using the In Situ Analysis System (ISAS) optimal interpolation by F. Gaillard (LPO) and the Coriolis Center.
Animation (click to start) : Top: SST anomaly in Niño 3 box from http://www.cpc.ncep.noaa.gov/data/indices/sstoi.indices and corresponding Indian Ocean Dipole (IOD) Index (SST difference between eastern and western equatorial Indian Ocean) from the Australian bureau of Meteorology (BOM). Bottom: SSS monthly anomalies with respect to a monthly climatology (July 2010-June2014): Left)SMOS SSS anomalies; Right)ISAS SSS anomalies
By computing anomalies with respect to 4-year monthly means, SMOS SSS systematic biases are removed. This leads to rms differences between SMOS SSS monthly anomalies and ISAS SSS monthly anomalies the order of 0.2 over large regions, while rms difference of SMOS SSS minus ISAS SSS are on the order of 0.4 over large regions.
Figure: Bias (top right) and standard deviation (bottom right) of the differences between SMOS and ISAS monthly SSS (red) and between SMOS and ISAS SSSanomalies (Blue). 6 regions are considered (from left to right): 60°S-60°N; 45°S-45°N; 30°S-30°N; (45°S-5°S, 140°W-95°W); (15°N-30°N,45°W-30°W); (5°N-15°N,110°W-180°W)
Part of this rms difference is due to spatial structures at shorter scale than 300km not resolved by ISAS (Hernandez et al. 2014). Hence this result strongly suggests that SMOS has the potential of measuring SSS at monthly and 100×100km2 scale with a precision better than 0.2 (Hernandez et al. 2014 found 0.15 in the subtropical north Atlantic) provided that systematic biases are removed.
This study has been performed with CATDS CEC-LOCEAN maps built using ESA version 5 reprocessed SSS. Systematic latitudinal biases present in version 5 are expected to decrease in version 6.
Durand, F., G. Alory, R. Dussin, and N. Reul (2013), SMOS reveals the signature of Indian Ocean Dipole events, Ocean Dynamics, 63(11-12), 1203-1212.
Hasson, A., T. Delcroix, J. Boutin, R. Dussin, and J. Ballabrera-Poy (2014), Analyzing the 2010–2011 La Niña signature in the tropical Pacific sea surface salinity using in situ data, SMOS observations, and a numerical simulation, Journal of Geophysical Research: Oceans, 119(6), 3855-3867, doi:10.1002/2013JC009388.
Hernandez, O., J. Boutin, N. Kolodziejczyk, G. Reverdin, N. Martin, F. Gaillard, N. Reul, and J. L. Vergely (2014), SMOS salinity in the subtropical north Atlantic salinity maximum: 1. Comparison with Aquarius and in situ salinity, Journal of Geophysical Research: Oceans, in press.
Reul, N., et al. (2013), Sea Surface Salinity Observations from Space with the SMOS Satellite: A New Means to Monitor the Marine Branch of the Water Cycle, Surv Geophys, 1-42.
Analyzing the 2010-2011 La Niña signature in the tropical Pacific sea surface salinity using in situ data, SMOS observations and a numerical simulation
Audrey Hasson(1, *), Thierry Delcroix(1), Jacqueline Boutin(2),
Raphael Dussin(3), Joaquim Ballabrera-Poy(4)
The tropical Pacific Ocean remained in a La Niña phase from mid 2010 to mid-2012. The near-surface salinity signature of this cold El Niño-Southern Oscillation (ENSO) phase is shown in the figure below and analysed in Hasson et. al (2014) using a combination of numerical model output, in situ data and SMOS satellite salinity products.
Comparisons of all salinity products show a good agreement between them, with a RMS error of 0.2-0.3 between the thermosalinograph (TSG) and SMOS data and between the TSG and model data. The last 6 months of 2010 (La Niña) are characterized by an unusually strong tri-polar anomaly captured by the three salinity products in the western half of the tropical Pacific. A positive SSS anomaly sits north of 10ºS (>0.5), a negative tilted anomaly lies between 10ºS and 20ºS and a positive one south of 20ºS. In 2011, anomalies shift south and amplify up to 0.8, except for the one south of 20ºS. Equatorial SSS changes are mainly the result of anomalous zonal advection, resulting in negative anomalies during El Niño (early 2010), and positive ones thereafter during La Niña. The mean seasonal and interannual poleward drift then exports those anomalies toward the south in the southern hemisphere, resulting in the aforementioned tripolar anomaly. The vertical salinity flux at the bottom of the mixed layer tends to resist the surface salinity changes. The observed basin-scale La Niña SSS signal is then compared in Hasson et al. (2014) with the historical 1998-1999 La Niña event using both observations and modelling.
for more details see Hasson, A., T. Delcroix, J. Boutin, R. Dussin, and J. Ballabrera-Poy (2014), Analyzing the 2010–2011 La Niña signature in the tropical Pacific sea surface salinity using in situ data, SMOS observations, and a numerical simulation, Journal of Geophysical Research: Oceans, 119(6), 3855-3867, doi:10.1002/2013JC009388.
(1) LEGOS, UMR 5566, CNES, CNRS, IRD, Université de Toulouse 14 avenue Edouard Belin, 31400 Toulouse, France
(2) LOCEAN, UMR7159, CNRS, UPMC, IRD, MNHN, Paris, France
(3) LEGI, Grenoble, France
(4) ICM/CSIC, Barcelona, Spain
(*) Corresponding author,Audrey.Hasson@legos.obs-mip.fr. Currently at the Jet Propulsion Laboratory,California Institute of Technology, Pasadena, California, USA
By Christophe Maes
Retrievals of the Sea Surface Salinity from space-borne mission like SMOS or Aquarius SAC-D provide for the first time an essential variable in the determination of ocean mass. If the field will reveal a lot of new signal at the surface its influence on the ocean dynamics is even more important at depths where it participates to the stratification of the water column. Concomitant with temperature profiles, reliable in situ observations of salinity at depth are now available at the global ocean scales. Above the main pycnocline (50-250m in the Tropics), Maes and O’Kane (2014) have recently shown that the stabilizing effect due to salinity could be isolated from its thermal counterpart by separating its role in the computation of the buoyancy frequency. In addition, relationships between such salinity stratification at depths and the SSS are shown to be well defined and quasi-linear in the tropics (see figure), providing some indication that in the future, analyses that consider both satellite surface salinity measurements at the surface and vertical profiles at depth will result in a better determination of the role of the salinity stratification in climate prediction systems.
Maes, C., and T. J. O’Kane (2014), Seasonal variations of the upper ocean salinity stratification in the Tropics, J. Geophys. Res. Oceans, 119, 1706–1722, doi:10.1002/2013JC009366.