A method for correcting regional bias in SMOS global salinity products

Xiaolin Tong; Zhenzhan Wang; Qingxia Li

doi:10.1007/s00343-015-4196-5

Your Location：

Home >

Browse articles >

A method for correcting regional bias in SMOS global salinity products

Updated：2023-05-16

- A method for correcting regional bias in SMOS global salinity products
- Journal of Oceanology and Limnology Vol. 33, Issue 4, Pages: 1072-1084(2015)
- Affiliations：
  
  1. Department of Electronics and Information Engineering Huazhong University of Science and Technology
  2. Key Laboratory of Microwave Remote Sensing National Space Science Center/Center for Space Science and Applied Research Chinese Academy of Sciences
  3. School of Physics and Electronics Henan University
- Author bio：
- Funds：
- DOI：10.1007/s00343-015-4196-5
  CLC：
- Online First：04 January 2015，
  
  Published：2015
- Accepted：
Scan QR Code
Tong, X., Wang, Z. & Li, Q. A method for correcting regional bias in SMOS global salinity products., Chin. J. Ocean. Limnol. 33, 1072–1084 (2015). https://doi.org/10.1007/s00343-015-4196-5
DOI：

Tong, X., Wang, Z. & Li, Q. A method for correcting regional bias in SMOS global salinity products., Chin. J. Ocean. Limnol. 33, 1072–1084 (2015). https://doi.org/10.1007/s00343-015-4196-5 DOI：

摘要

Abstract

Soil Moisture and Ocean Salinity (SMOS) Level 3 (L3) sea surface salinity (SSS) products are provided by the Barcelona Expert Centre (BEC). Strong biases were observed on the SMOS SSS products

thus the data from the Centre Aval de Traitement des Données SMOS (CATDS) were adjusted for biases using a large-scale correction derived from observed differences between the SMOS SSS and World Ocean Atlas (WOA) climatology data. However

this large-scale correction method is not suitable for correcting the large gradient of salinity biases. Here

we present a method for the correction of SSS regional bias of the monthly L3 products. Based on the stable characteristics of the large SSS biases from month to month in some regions

corrected SMOS SSS maps can be obtained from the monthly mean values after removing the regional biases. The accuracy of the SMOS SSS measurements is greatly improved

especially near the coastline

at high latitudes

and in some open ocean regions. The SMOS and ISAS SSS data are also compared with Aquarius SSS to verify the corrected SMOS SSS data. The correction method presented here only corrects annual mean biases. The measurement accuracy of the SSS may be improved by considering the influence of atmospheric and ocean circulation in different seasons and years.

关键词

Keywords

references

Banks C J, Gommenginger C P, Srokosz M A, Snaith H M. 2012. Validating SMOS ocean surface salinity in the Atlantic with Argo and operational ocean model data. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1 688–1 702.

Boutin J, Martin N, Reverdin G, Yin X B, Gaillard F. 2012. Sea surface freshening inferred from SMOS and ARGO salinity: impact of rain. Ocean Science, 9: 3 331–3 357.

Chelton D B, Freilich M H. 2005. Scatterometer-based assessment of 10-m wind analyses from the operational ECMWF and NCEP numerical weather prediction models. Monthly Weather Review, 133(2): 409–429.

De Roo R D, Misra S. 2008. A Demonstration of the effects of digitization on the calculation of kurtosis for the detection of RFI in microwave radiometry. IEEE Transactions on Geoscience and Remote Sensing, 46(10): 3 129–3 136.

Drucker R, Riser S C. 2014. 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, 119(7): 4 626–4 637.

Font J, Boutin J, Reul N, Spurgeon P, Ballabrera-Poy J, Chuprin A, Hénocq C, Lavender S, Martin N, Martínez J, McCulloch M, Meirold-Mautner I, Mugerin C, Petitcolin F, Portabella M, Sabia R, Talone M, Tenerelli J, Turiel A, Vergely J L, Waldteufel P, Yin X B, Zine S, Delwart S. 2013. SMOS first data analysis for sea surface salinity determination. International Journal of Remote Sensing, 34(9–10): 3 654–3 670.

Font J, Camps A, Borges A, Martin-Neira M, Boutin J, Reul N, Kerr Y H, Hahne A, Mecklenburg S. 2010. SMOS: the challenging sea surface salinity measurement from space. Proceedings of the IEEE, 98(5): 649–665.

Font J, Lagerloef G S E, Le Vine D M, Camps A, Zanife O Z. 2004. The determination of surface salinity with the European SMOS space mission. IEEE Transactions on Geoscience and Remote Sensing, 42(10): 2 196–2 205.

Gaillard F, Autret E, Thierry V, Galaup P, Coatanoan C, Loubrieu T. 2009. Quality control of large argo datasets. Journal of Atmospheric Oceanic Technology, 26(2): 337–357.

Gourrion J, Sabia R, Portabella M, Tenerelli J, Guimbard S, Camps A. 2012. Characterization of the SMOS instrumental error pattern correction over the ocean. IEEE Geoscience and Remote Sensing Letters, 9(4): 793–797.

Guimbard S, Gourrion J, Portabella M, Turiel A, Gabarró C, Font J. 2012. SMOS semi-empirical ocean forward model adjustment. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1 676–1 687.

Hernandez O, Boutin J, Kolodziejczyk N, Reverdin G, Martin N, Gaillard F, Reul N, Vergely J L. 2014. SMOS salinity in the subtropical north Atlantic salinity maximum: 1. Comparison with Aquarius and in situ Salinity. Journal of Geophysical Research: Oceans, Published Online First, 26 December 2014. http://dx.doi.org/10.1002/2013JC009610.

Kainulainen J, Colliander A, Closa J, Martin-Neira M, Oliva R, Buenadicha G, Rubiales A P, Hakkarainen A, Hallikainen M T. 2012. Radiometric performance of the SMOS reference radiometers—assessment after one year of operation. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1 367–1 383.

Kerr Y H, Waldteufel P, Wigneron J P, Delwart S, Cabot F, Boutin J, Escorihuela M J, Font J, Reul N, Gruhier C, Juglea S E, Drinkwater M R, Hahne A, Martin-Neira M, Mecklenburg S. 2010. The SMOS mission: new tool for monitoring key elements of the global water cycle. Proceedings of the IEEE, 98(5): 666–687.

Kerr Y H, Waldteufel P, Wigneron J-P, Martinuzzi J, Font J, Berger M. 2001. Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission. IEEE Transactions on Geoscience and Remote Sensing, 39(8): 1 729–1 735.

Klemas V. 2011. Remote sensing of sea surface salinity: an overview with case studies. Journal of Coastal Research, 27(5): 830–838.

Lagerloef G. 2012. Satellite mission monitors ocean surface salinity. EOS, Transactions American Geophysical Union, 93(25): 233–234.

Latif M. 2001. Tropical Pacific/Atlantic Ocean interactions at multi-decadal time scales. Geophysical Research Letters, 28(3): 539–542.

Pinori S, Crapolicchio R, Mecklenburg S. 2008. Preparing the ESA-SMOS (soil moisture and ocean salinity) missionoverview of the user data products and data distribution strategy. In: Microwave Radiometry and Remote Sensing of the Environment, 2008. MICRORAD 2008. IEEE, Firenze. p.1–4.

Reul N, Tenerelli J, Boutin J, Chapron B, Paul F, Brion E, Brion E, Archer O. 2012. Overview of the first SMOS sea surface salinity products. Part I: quality assessment for the second half of 2010. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1 636–1 647.

Reul N, Tenerelli J, Chapron B, Waldteufel P. 2007. Modeling sun glitter at L-band for sea surface salinity remote sensing with SMOS. IEEE Transactions on Geoscience and Remote Sensing, 45(7): 2 073–2 087.

Ruf C S, Gross S M, Misra S. 2006. RFIdetection and mitigation for microwave radiometry with an agile digital detector. IEEE Transactions on Geoscience and Remote Sensing, 44(3): 694–706.

Sabia R, Camps A, Talone M, Vall-Llossera M, Font J. 2010. Determination of the sea surface salinity error budget in the soil moisture and ocean salinity mission. IEEE Transactions on Geoscience and Remote Sensing, 48(4): 1 684–1 693.

SMOS Team. 2014. SMOS L2 OS algorithm theoretical baseline document. http://www.argans.co.uk/smos/docs/deliverables/delivered/ATBD/SO-TN-ARG-GS-0007_L2OS-ATBD_v3.11_140905.pdf.

SMOS-BEC Team. 2014. SMOS-BEC ocean and land products description. http://cp34-bec.cmima.csic.es/doc/BECSMOS-0001-PD.pdf.

Tang W Q, Yueh S H, Fore A G, Hayashi A, Lee T, Lagerloef G. 2014. Uncertainty of Aquarius sea surface salinity retrieved under rainy conditions and its implication on the water cycle study. Journal of Geophysical Research: Oceans, 119(8): 4 821–4 839.

Wei E B, Liu S B, Wang Z Z, Tong X L, Dong S, Li B, Liu J Y. 2014. Emissivity measurements of foam-covered water surface at l-band for low water temperatures. Remote Sensing, 6(11): 10 913–10 930.

Yin X B, Boutin J, Martin N, Spurgeon P, Vergely J L, Gaillard F. 2014. Errors in SMOS Sea Surface Salinity and their dependency on a priori wind speed. Remote Sensing of Environment, 146: 159–171.

Yin X B, Boutin J, Martin N, Spurgeon P. 2012. Optimization of L-band sea surface emissivity models deduced from SMOS data. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1 414–1 426.

Zhang H F, Chen G, Qian C C, Jiang H Y. 2013. Assessment of two SMOS sea surface salinity level 3 products against argo upper salinity measurements. IEEE Geoscience and Remote Sensing Letters, 10: 1 434–1 438.

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

Preliminary validation of SMOS sea surface salinity measurements in the South China Sea

Analysis Procedure and Numerical Simulation of Failure Probability of Turbine Disk Caused by Defects

Performance Modelling of Geared Contra-RotatingPropfan Engine

Research on Aging Characterization of Solid Propellantsby Electro-Mechanical Impedance

Research on Air Turbo Ramjet Expander Performance Optimization Based on Diversity Improved NSGA II Algorithm

Related Author

Yongzheng Ren

Qing Dong

Mingxia He

Related Institution

Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences

Ocean Remote Sensing Institute Ocean University of China

Address：Editorial Office of JOL, 88 Haijun Rd. Qingdao, 266000, China
Tel：+86-532-82898754 Email：jol@qdio.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰