Validation of Aquarius sea surface salinity with Argo: Analysis of error due to depth of measurement and vertical salinity stratification

Journal of Geophysical Research: Oceans

Volumn 119, Issue 7, 2014, Pages 4626-4637

  Drucker, Robert ^a   Riser, Stephen C ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Aquarius; Argo; salinity; sea surface salinity; SSS; vertical salinity stratification

Indexed keywords

NASA; RAIN; TROPICS;

AQUARIUS; ARGO; SALINITY; SALINITY STRATIFICATION; SEA SURFACE SALINITY; SSS;

MEASUREMENT ERRORS;

AQUARIUS; ARRAY; DATA SET; HYDROLOGICAL CYCLE; MEASUREMENT METHOD; PRECIPITATION (CLIMATOLOGY); SEA SURFACE SALINITY; TROPICAL ENVIRONMENT;

EID: 84906237118     PISSN: None     EISSN: 21699291     Source Type: Journal    
DOI: 10.1002/2014JC010045     Document Type: Article

References (26)

1. Boutin, J., and, N. Martin, (2006), Argo upper salinity measurements: Perspectives for L-band radiometers calibration and retrieved sea surface salinity validation, IEEE Geosci. Remote Sens. Lett., 3 (2), 202-206, doi: 10.1109/LGRS.2005.861930.
2. Boutin, J., N. Martin, G. Reverdin, X. Yin, and, F. Gaillard, (2013), Sea surface freshening inferred from SMOS and ARGO salinity: Impact of rain, Ocean Sci., 9, 183-192, doi: 10.5194/os-9-183-2013.
3. Bowman, K., (2005), Comparison of TRMM precipitation retrievals with rain gauge data from ocean buoys, J. Clim., 18, 178-190, doi: 10.1175/JCLI3259.1. (Pubitemid 40252357)
4. Chao, Y., and, C. Zhang, (2013), Upper ocean salinity stratification: Challenges to validate satellite-sensed sea surface salinity, paper presented at SMOS Aquarius Science Workshop, Unpublished oral presentation, National Aeronautics and Space Administration (NASA), Brest, France.
5. Durack, P., and, S. Wijffels, (2010), Fifty-year trends in global ocean salinities and their relationship to broad-scale warming, J. Clim., 23, 4342-4362, doi: 10.1175/2010jcli3377.1.
6. Durack, P., S. Wijffels, and, R. Matear, (2012), Ocean salinities reveal strong global water cycle intensification during 1950 to 2000, Science, 336, 455, doi: 10.1126/science.1212222.
7. Elliott, G. W., (1974), Precipitation signatures in sea surface layer conditions during BOMEX, J. Phys. Oceanogr., 4, 498-501, doi: 10.1175/1520-0485(1974)004 <0498:psissl>2.0.co;2.
8. Gordon, A. L., and, C. F. Giulivi, (2008), Sea surface salinity trends over fifty years within the subtropical North Atlantic, Oceanography, 21 (1), 20-29, doi: 10.5670/oceanog.2008.64.
9. Henocq, C., J. Boutin, F. Petitcolin, G. Reverdin, S. Arnault, and, P. Lattes, (2009), Vertical variability of near-surface salinity in the tropics: Consequences for L-band radiometer calibration and validation, J. Atmos. Oceanic Technol., 27, 192-209, doi: 10.1175/2009jtecho670.1.
10. Koblinsky, C., P. Hildebrand, D. LeVine, F. Pellerano, Y. Chao, W. Wilson, S. Yueh, and, G. Lagerloef, (2003), Sea surface salinity from space: Science goals and measurement approach, Radio Sci., 38 (4), 8064, doi: 10.1029/2001RS002584.
11. Lagerloef, G., R. Schmitt, J. Schanze, and, H.-Y. Kao, (2010a), The ocean and the global water cycle, Oceanography, 23 (4), 82-93, doi: 10.5670/oceanog.2010.07.
12. Lagerloef, G., et al. (2010b), Resolving the global surface salinity field and variations by blending satellite and in situ observations, in Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society, vol. 2, edited by J. Hall, D. E. Harrison, and D. Stammer, ESA Publication WPP-306, Venice, Italy, doi: 10.5270/OceanObs09.cwp.51.
13. Lagerloef, G., et al. (2013), Aquarius salinity validation analysis, Data Version 2.0, Aquarius Proj. Doc. AQ-014-PS-0016, Unpublished report, National Aeronautics and Space Administration (NASA).
14. Le Vine, D. M., G. Lagerloef, F. Colomb, S. Yueh, and, F. Pellerano, (2007), Aquarius: An instrument to monitor sea surface salinity from space, IEEE Trans. Geosci. Remote Sens., 45 (7), 2040-2050, doi: 10.1109/TGRS.2007.898092. (Pubitemid 47000272)
15. Meissner, T., F. Wentz, and, K. Hilburn, (2014), The Aquarius salinity retrieval algorithm: Challenges and recent progress, paper presented at the 2014 Ocean Sciences Meeting, Honolulu, Hawaii, 26 Feb 2014.
16. Oka, E., and, K. Ando, (2004), Stability of temperature and conductivity sensors of Argo profiling floats, J. Oceanogr., 60, 253-258, doi: 10.1023/B:JOCE.0000038331.10108.79.
17. Reverdin, G., S. Morisset, J. Boutin, and, N. Martin, (2012), Rain-induced variability of near sea-surface T and S from drifter data, J. Geophys. Res., 117, C02032, doi: 10.1029/2011JC007549.
18. Riser, S., L. Ren, and, A. Wong, (2008), Salinity in Argo: A modern view of a changing ocean, Oceanography, 21 (1), 56-67, doi: 10.5670/oceanog.2008.67.
19. Rudnick, D., and, S. Cole, (2011), On sampling the ocean using underwater gliders, J. Geophys. Res., 116, C08010, doi: 10.1029/2010JC006849.
20. Schmitt, R., (1995), The ocean component of the global water cycle, Rev. Geophys., 33 (Suppl., Pt. 2), 1395-1409.
21. SPURS Steering Committee (2010), Salinity Processes in the Upper-Ocean Regional Study (SPURS), Unpublished report, National Aeronautics and Space Administration (NASA). [Available at http://spurs.jpl.nasa.gov/SPURS/spurs.pdf.]
22. Wentz, F., and, R. Spencer, (1998), SSM/I rain retrievals within a unified all-weather ocean algorithm, J. Atmos. Sci., 55 (9), 1613-1627, doi: 10.1175/1520-0469(1998)055 <1613:sirrwa>2.0.co;2.
23. Yaremchuk, M., (2006), Sea surface salinity constrains rainfall estimates over tropical oceans, Geophys. Res. Lett., 33, L15605, doi: 10.1029/2006GL026582.
24. Yu, L., (2007), Global variations in oceanic evaporation (1958-2005): The role of the changing wind speed, J. Clim., 20, 5376-5390, doi: 10.1175/2007JCLI1714.1. (Pubitemid 350143094)
25. Yu, L., (2011), A global relationship between the ocean water cycle and near-surface salinity, J. Geophys. Res., 116, C10025, doi: 10.1029/2010JC006937.
26. Yueh, S., R. West, W. J. Wilson, F. K. Li, E. G. Njoku, and, Y. Rahmat-Samii, (2001), Error sources and feasibility for microwave remote sensing of ocean surface salinity, IEEE Trans. Geosci. Remote Sens., 39 (5), 1049-1060, doi: 10.1109/36.921423. (Pubitemid 32534351)