Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation

Lihua Wang; Yunxuan Zhou; Jianrong Zhu; Fang Shen; Bo Tian

doi:10.1007/s00343-014-3253-9

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Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation

Updated：2023-05-16

- Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation
- Journal of Oceanology and Limnology Vol. 32, Issue 4, Pages: 946-957(2014)
- Affiliations：
  
  State Key Laboratory of Estuarine and Coastal Research East China Normal University
- Author bio：
- Funds：
- DOI：10.1007/s00343-014-3253-9
  CLC：
- Online First：11 July 2014，
  
  Published：2014
- Accepted：
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Wang, L., Zhou, Y., Zhu, J. et al. Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation., Chin. J. Ocean. Limnol. 32, 946–957 (2014). https://doi.org/10.1007/s00343-014-3253-9
DOI：

Wang, L., Zhou, Y., Zhu, J. et al. Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation., Chin. J. Ocean. Limnol. 32, 946–957 (2014). https://doi.org/10.1007/s00343-014-3253-9 DOI：

摘要

Abstract

Wind plays an important role in hydrodynamic processes such as the expansion of Changjiang (Yangtze) River Diluted Water (CDW)

and shelf circulation in the Changjiang estuary. Thus

it is essential to include wind in the numerical simulation of these phenomena. Synthetic aperture radar (SAR) with high resolution and wide spatial coverage is valuable for measuring spatially inhomogeneous ocean surface wind fields. We have collected 87 ERS-2 SAR images with wind-induced streaks that cover the Changjiang coastal area

to verify and improve the validity of wind direction retrieval using the 2D fast Fourier transform method. We then used these wind directions as inputs to derive SAR wind speeds using the C-band model. To demonstrate the applicability of the algorithms

we validated the SAR-retrieved wind fields using QuikSCAT measurements and the atmospheric Weather Research Forecasting model. In general

we found good agreement between the datasets

indicating the reliability and applicability of SAR-retrieved algorithms under different atmospheric conditions. We investigated the main error sources of this process

and conducted sensitivity analyses to estimate the wind speed errors caused by the effect of speckle

uncertainties in wind direction

and inaccuracies in the normalized radar cross section. Finally

we used the SAR-retrieved wind fields to simulate the salinity distribution off the Changjiang estuary. The findings of this study will be valuable for wind resource assessment and the development of future numerical ocean models based on SAR images.

关键词

Keywords

references

Argenti F, Alparone L. 2002. Speckle removal from SAR images in the undecimated wavelet domain. IEEE Trans. Geosci. Remote Sens., 40(11): 2 363–2 374.

Attema E P W. 1991. The Active Microwave Instrument onboard the ERS-1 satellite. Proceedings of the IEEE, 79(6): 791–799, http://dx.doi.org/10.1109/5.90158.

Blanton J, Wenner E, Werner F, Knott D. 1995. Effects of wind-generated coastal currents on the transport of blue crab megalopae on a shallow continental shelf. Bull. Mar. Sci., 57(3): 739–752.

Chang P H, Isobe A. 2003. A numerical study on the Changjiang diluted water in the Yellow and East China Seas. J. Geophys. Res-Oceans, 108(C9): 1–17, http://dx.doi.org/10.1029/2002JC001749.

Christiansen M B, Koch W, Horstmann J, Hasager C B, Nielsen M. 2006. Wind resource assessment from C-band SAR. Remote Sens. Environ., 105(1): 68–81.

Dankert H, Horstmann J, Rosenthal W. 2003. Ocean wind fields retrieved from radar-image sequences. J. Geophys. Res-Oceans, 108(C11): 2 150–2 152, http://dx.doi.org/10.1029/2003JC002056.

Done J, Davis C A, Weisman M. 2004. The next generation of N W P: explicit forecasts of convection using the weather research and forecasting (WRF) model. Atmos. Sci. Lett., 5(6): 110–117, http://dx.doi.org/10.1002/asl.72.

Donnelly W, Carswell R M, Chang P, Wilkerson J. 1999. Revised ocean backscatter models at C and Ku band under high wind conditions. J. Geophys. Res-Oceans, 104(C5): 11 485–11 497, http://dx.doi.org/10.1029/1998JC900030.

Elfouhaily T, Thompson D R, Vandemark D, Chapron B. 1999. A new bistatic model for electromagnetic scattering from perfectly conducting random surfaces. Waves in Random Media, 9(3): 281–294.

Fetterer F, Gineris D, Wackerman C C. 1998. Validating a scatterometer wind algorithm for ERS-1 SAR. IEEE Trans. Geosci. Remote Sens., 36(2): 479–492.

Fichaux N, Ranchin T. 2002. Combined extraction of high spatial resolution wind speed and wind direction from SAR images: a new approach using wavelet transform. Can. J. Remote Sens., 28(3): 510–516.

Freilich M H, Chelton D B. 1986. Wavenumber spectra of pacific winds measured by the Seasat scatterometer. J. Phys. Oceanogr., 16(4): 741–757.

Garratt J R. 1990. The internal boundary layer-a review. Boundary-Layer Meteorology, 50(1–4): 171–203.

Genovese S J, Witman J D. 2004. Wind-mediated diel variation in flow speed in a Jamaican back reef environment: Effects on ecological processes. Bull. Mar. Sci., 75(2): 281–293.

Gerling T W. 1986. Structure of the surface wind field from the Seasat SAR. J. Geophys. Res-Oceans, 91(C2): 2 308–2 320, http://dx.doi.org/10.1029/JC091iC02p02308.

Haarpaintner J. 1999. The Storfjorden polynya: ERS-2 SAR observations and overview. Polar Research, 18(8): 175–182, http://dx.doi.org/10.1111/j.1751-8369.1999.tb00290.x.

Hasager C B, Nielsen M, Astrup P, Barthelmie R, Dellwik E, Jensen N O, Jørgensen B H, Pryor S C, Rathmann O, Furevik B R. 2005. Offshore wind resource estimation from satellite SAR wind field maps. Wind Energy, 8(4): 403–419.

Horstmann J, Koch W, Lehner S, Tonboe R. 2000a. Mapping of mesoscale wind field using RADARSAT-1 ScanSAR images. IEEE Conference and Exhibition Oceans 2000MTS, 2: 1 321–1 327, http://dx.doi.org/10.1109/OCEANS.2000.881787.

Horstmann J, Koch W, Lehner S, Tonboe R. 2000b. Wind retrieval over the ocean using synthetic aperture radar with C-band HH polarization. IEEE Trans. Geosci. Remote Sens., 38(5): 2 122–2 131.

Horstmann J, Koch W, Lehner S, Tonboe R. 2002. Ocean winds from RADARSAT-1 ScanSAR. Can. J. Remote Sens., 28(3): 524–533.

Horstmann J, Koch W, Lehner S. 2004. Ocean wind field retrieved from the advanced synthetic aperture radar aboard ENVISAT. Ocean Dyn., 54(6): 570–576.

Horstmann J, Koch W. 2005. Measurement of ocean surface winds using synthetic aperture radars. IEEE J. Ocean Eng., 30(3): 508–515.

Horstmann J, Thompson D R, Monaldo F, Iris S, Graber H C. 2005. Can synthetic aperture radars be used to estimate hurricane force winds. Geophys. Res. Lett., 32(22): 1–5, http://dx.doi.org/10.1029/2005GL023992.

Johannessen J A. 2000. Coastal observing systems: the role of synthetic aperture radar. Johns Hopkins A PL Tech nical Dig est, 21: 7–14.

Katsaros K, Vachon P, Lio W, Black P. 2002. Microwave remote sensing of tropical cyclones from space. J. Oceanogr., 58: 137–151.

Kerbaol V, Chapron B, Vachon P W. 1998. Analysis of ERS-1/2 synthetic aperture radar wave mode imagettes. J. Geophys. Res-Oceans, 103(C4): 7 833–7 846, http://dx.doi.org/10.1029/97JC01579.

Kim D J, Moon W M. 2002. Estimation of sea surface wind vector using RADARSAT data. Remote Sens. Environ., 80(1): 55–64.

Koch W. 2004. Directional analysis of SAR images aiming at wind direction. IEEE Trans. Geosci. Remote Sens., 42(4): 702–710.

Korsbakken E, Johannessen J A, Johannessen O M. 1998. Coastal wind field retrievals from ERS synthetic aperture radar images. J. Geophys. Res-Oceans, 103(C4): 7 857–7 874, http://dx.doi.org/10.1029/97JC02580.

Laur H, Bally P, Meadows P, Sanchez J, Schaettler B, Lopinto E, Esteban D. 2004. Derivation of the Backscattering Coefficient in ESA ERS SAR PRI Products. European Space Agency, Frascati.

Lehner S, Schulz-Stellenfleth J, Schattler B, Breit H, Horstmann J. 2000. Wind and wave measurements using complex ERS-2 SAR wave mode data. IEEE Trans. Geosci. Remote Sens., 38(5): 2 246–2 257.

Lin H, Xu Q, Zheng Q. 2008. An overview on SAR measurements of sea surface wind. Progress in Natural Science, 18(8): 913–919.

Meadows P J, Rosich B, Fernandez D E. 2000. The performance of the ERS-2 Synthetic Aperture Radar. In Proc. of the ERSENVISAT Symposium. Goteborg, Sweden.

Monaldo F M, Thompson D R, Pichel W G, Clemente-Colon P. 2004. A systematic comparison of QuikSCAT and SAR ocean surface wind speeds. IEEE Trans. Geosci. Remote Sens., 42(2): 283–291.

Monaldo F M. 2000. The Alaska SAR demonstration and nearreal-time synthetic aperture radar winds. Johns Hopkins A PL Tech nical Dig est, 21: 75–84.

Moon J, Hirose N, Yoon J, Pang I. 2010. Offshore detachment process of the low-Salinity water around Changjiang bank in the East China Sea. J. Phys. Oceanogr., 5(40): 1 035–1 053.

Rung Z, Li M. 2012. Tidal effects on the bulge region of Changjiang River plume. Estuar. Coast. Shelf Sci., 97: 149–160.

Sikora T D, Young G S, Beal R C, Edson J B. 1995. Use of spaceborne synthetic aperture radar imagery of the sea surface in detecting the presence and structure of the convective marine atmospheric boundary layer. Mon. Wea. Rev., 123(12): 3 623–3 632.

Stoffelen A, Anderson D. 1997. Scatterometer data interpretation: estimation and validation of the transfer function CMOD4. J. Geophys. Res., 102(C3): 5 767–5 780, http://dx.doi.org/10.1029/96JC02860.

Stull R B. 1988. An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers, New York.

Thompson D R, Elfouhaily T M, Chapron B. 1999. Polarization ratio for microwave backscattering from the ocean surface at low to moderate incidence angles. IEEE International Geosci. Remote Sens. Symposium Proceedings, 3: 1 671–1 673.

Vachon P W, Dobson F W. 1996. Validation of wind vector retrieval from ERS-1 SAR images over the ocean. The Glob al Atmos phere and Ocean Sys tem, 5(2): 177–187.

Valenzuela G R. 1978. Theories for the interaction of electromagnetic and oceanic waves-a review. Bound-Layer Meteorol., 13(1–4): 61–85, http://dx.doi.org/10.1007/BF00913863.

Wackerman C C, Rufenach C L, Shuchman R A, Johannessen J A, Davidson K L. 1996. Wind vector retrieval using ERS-1 synthetic aperture radar imagery. IEEE Trans. Geosci. Remote Sens., 34(6): 1 343–1 352.

Wright J. 1966. Backscattering from capillary waves with application to sea clutter. IEEE Trans. Antennas Propag., 14(6): 749–754.

Wu H, Zhu J R, Shen J, Wang H. 2011. Tidal modulation on the Changjiang River plume in summer. J. Geophys. Res-Oceans, 116: C08017, http://dx.doi.org/10.1029/2011JC007209.

Wu H, Zhu J R. 2010. Advection scheme with 3rd high-order spatial interpolation at the middle temporal level and its application to saltwater intrusion in the Changjiang estuary. Ocean Model., 33(1–2): 33–51.

Young G S, Sikora T N, Winstead N S. 2005. Use of synthetic aperture radar in finescale surface analysis of synopticscale fronts at sea. Wea. Forecasting, 20(3): 311–327, http://dx.doi.org/10.1175/WAF853.1.

Zhu J R, Li Y P, Shen H T. 1997. Numerical simulation of the wind field’s impact on the expansion of the Changjiang River diluted water in summer. Oceanol. Limnol. Sin., 28(1): 72–79. (in Chinese with English abstract)

Zink M, Torres R, Buck C H, Rosich B, Closa J. 2002. The advanced SAR system on ENVISAT: mission status. Proceedings 4th European Conference on Synthetic Aperture Radar. p.175.

Zou Q, He Y, Perrie W, Vachon P W. 2007. Wind-vector estimation for RADARSAT-1 SAR images: validation of wind-direction estimates based upon geometry diversity. IEEE Trans. Geosci. Remote Sens. Lett., 4(1): 176–180.

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