Synthetic aperture radar (SAR) is a suitable tool to obtain reliable wind retrievals with high spatial resolution. The geophysical model function (GMF), which is widely employed for wind speed retrieval from SAR data, describes the relationship between the SAR normalized radar cross-section (NRCS) at the copolarization channel (vertical-vertical and horizontal-horizontal) and a wind vector. SAR-measured NRCS at cross-polarization channels (horizontal-vertical and vertical-horizontal) correlates with wind speed. In this study, a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3 (GF-3) SAR data with noise-equivalent sigma zero correction using an empirical function. GF-3 SAR can acquire data in a quad-polarization strip mode, which includes cross-polarization channels. The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts. In particular, the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS. The accuracy of SAR-derived wind speed is around 2.10 m s-1 root mean square error, which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration. The results obtained by the proposed algorithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms. This work provides an alternative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direction.
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Alpers, W., and Brummer, B., 1994. Atmospheric boundary layer rolls observed by the synthetic aperture radar aboard the ERS-1 satellite. Journal of Geophysical Research, 99 (C6): 12613–12621.
Chapron, B., Johnsen, H., and Garello, R., 2001. Wave and wind retrieval from SAR images of the ocean. Annales des Telecommunications, 56 (11): 682–699.
Corcione, V., Grieco, G., Portabella, M., Nunziata, F., and Migliaccio, M., 2018. A novel azimuth cutoff implementation to retrieve sea surface wind speed from SAR imagery. IEEE Transactions on Geoscience and Remote Sensing, 57 (6): 3331–3340, DOI: https://doi.org/10.1109/TGRS.2018.2883364.
Duan, B. H., Zhang, W. M., Yang, X. F., Dai, H. J., and Yu, Y., 2017. Assimilation of typhoon wind field retrieved from scatterometer and SAR based on the Huber norm quality control. Remote Sensing, 9: 987.
Fois, F., Hoogeboom, P., Chevalier, F. L., and Stoffelen, A., 2015. Future ocean scatterometry: On the use of cross-polar scattering to observe very high winds. IEEE Transaction on Geoscience and Remote Sensing, 53: 5009–5020.
Hersbach, H., 2010. Comparison of C-Band scatterometer CMOD5.N equivalent neutral winds with ECMWF. Journal of Atmospheric and Oceanic Technology, 27: 721–736.
Hersbach, H., Stoffelen, A., and Haan, S. D., 2007. An improved C-band scatterometer ocean geophysical model function: CMOD5. Journal of Geophysical Research, 112: 225–237.
Huang, L. Q., Liu, B., Li, X. F., Zhang, Z. H., and Yu, W. X., 2017. Technical evaluation of Sentinel-1 IW mode cross-pol radar backscattering from the ocean surface in moderate wind condition. Remote Sensing, 9: 854.
Hwang, P. A., and Fois, F., 2015. Surface roughness and breaking wave properties retrieved from polarimetric microwave radar backscattering. Journal of Geophysical Research: Oceans, 120: 3640–3657.
Hwang, P. A., Stoffelen, A., Van Zadelhoff, G. J., Perrie, W., Zhang, B., Li, H., and Shen, H., 2012. Cross-polarization geophysical model function for C-band radar backscattering from the ocean surface and wind speed retrieval. Journal of Geophysical Research: Oceans, 120: 893–909.
Lehner, S., Horstmann, J., Koch, W., and Rosenthal, W., 1998. Mesoscale wind measurements using recalibrated ERS SAR images. Journal of Geophysical Research, 103: 7847–7856.
Lu, Y., Zhang, B., Perrie, W., Mouche, A. A., Li, X. F., and Wang, H., 2018. A C-band geophysical model function for determining coastal wind speed using synthetic aperture radar. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11: 2417–2428.
Masuko, H., Okamoto, K., Shimada, M., and Niwa, S., 1986. Measurement of microwave backscattering signatures of the ocean surface using X band and Ka band airborne scatterometers. Journal of Geophysical Research, 91: 13065–13083.
Monaldo, F., Jackson, C., Li, X. F., and Pichel, W. G., 2016. Preliminary evaluation of Sentinel-1A wind speed retrievals. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9: 2638–2642.
Mouche, A. A., and Chapron, B., 2015. Global C-Band Envisat, RADARSAT-2 and Sentinel-1 SAR measurements in copolarization and cross-polarization. Journal of Geophysical Research: Oceans, 120: 7195–7207.
Mouche, A. A., Hauser, D., Daloze, J. F., and Guerin, C., 2005. Dual polarization measurements at C-Band over the ocean: Results from airborne radar observations and comparison with ENVISAT ASAR data. IEEE Transaction on Geoscience and Remote Sensing, 43: 753–769.
Quilfen, Y., Bentamy, A., Elfouhaily, T., Katsaros, K., and Tournadre, J., 1998. Observation of tropical cyclones by highresolution scatterometry. Journal of Geophysical Research, 103: 7767–7786.
Ren, L., Yang, J. S., Mouche, A. A., Wang, H., Wang, J., Zheng, G., and Zhang, H., 2017. Preliminary analysis of Chinese GF-3 SAR quad-polarization measurements to extract winds in each polarization. Remote Sensing, 9: 1215.
Rivas, M. B., Stoffelen, A., Verspeek, J., Verhoef, A., Neyt, X., and Anderson, C., 2017. Cone metrics: A new tool for the intercomparison of scatterometer records. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10: 2195–2204.
Shao, W. Z., Hu, Y. Y., Yang, J. S., Nunziata, F., Sun, J., Li, H., and Zuo, J. C., 2018a. An empirical algorithm to retrieve significant wave height from Sentinel-1 synthetic aperture radar imagery collected under cyclonic conditions. Remote Sensing, 10: 1367.
Shao, W. Z., Li, X. F., Hwang, P. A., Zhang, B., and Yang, X. F., 2017a. Bridging the gap between cyclone wind and wave by C-band SAR measurements. Journal of Geophysical Research, 122: 6714–6724.
Shao, W. Z., Sheng, Y. X., and Sun, J., 2017b. Preliminary assessment of wind and wave retrieval from Chinese Gaofen-3 SAR imagery. Sensors, 17: 1705.
Shao, W. Z., Sun, J., Guan, C. L., and Sun, Z. F., 2014. A method for sea surface wind field retrieval from SAR image mode data. Journal of Ocean University of China, 13: 198–204.
Shao, W. Z., Yuan, X. Z., Sheng, Y., Sun, J., Zhou, W., and Zhang, Q. J., 2018b. Development of wind speed retrieval from crosspolarization Chinese Gaofen-3 synthetic aperture radar in typhoons. Sensors, 18: 412.
Shao, W. Z., Zhang, Z., Li, X. M., and Wang, W. L., 2016. Sea surface wind speed retrieval from TerraSAR-X HH-polarization data using an improved polarization ratio model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9: 4991–4997.
Shao, W. Z., Zhu, S., Sun, J., Yuan, X. Z., Sheng, Y. X., Zhang, Q. J., and Ji, Q. Y., 2019. Evaluation of wind retrieval from co-polarization Gaofen-3 SAR imagery around China seas. Journal of Ocean University of China, 18: 80–92.
Shen, H., Perrie, W., He, Y. J., and Liu, G., 2014. Wind speed retrieval from VH dual-polarization RADARSAT-2 SAR images. IEEE Geoscience and Remote Sensing, 52: 5820–5826.
Stoffelen, A., and Anderson, D., 1997. Scatterometer data interpretation: Estimation and validation of the transfer function: CMOD4. Journal of Geophysical Research, 102: 5767–5780.
Stoffelen, A., Verspeek, J. A., Vogelzang, J., and Verhoef, A., 2017. The CMOD7 geophysical model function for ASCAT and ERS wind retrievals. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10: 2123–2134.
Stopa, J. E., and Cheung, K. F., 2014. Intercomparison of wind and wave data from the ECMWF reanalysis interim and the NCEP climate forecast system reanalysis. Ocean Modelling, 75: 65–83.
Thompson, D. R., Elfouhaily, T. M., and Chapron, B., 1998. Polarization ratio for microwave backscattering from the ocean surface at low to moderate incidence angles. Geoscience and Remote Sensing Symposium Proceedings, 3: 1671–1673.
Vachon, P. W., and Dobson, F. W., 2000. Wind retrieval from RADARSAT SAR images selection of a suitable C-band HHpolarization wind retrieval model. Canadian Journal of Remote Sensing, 26: 306–313.
Vachon, P. W., and Wolfe, J., 2011. C-band cross-polarization wind speed retrieval. IEEE Geoscience and Remote Sensing Letters, 3: 456–459.
Vogelzang, J., and Stoffelen, A., 2017. ASCAT Ultrahigh-resolution wind products on optimized grids. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10: 2332–2339.
Vogelzang, J., Stoffelen, A., Verhoef, A., and Figa-Saldana, J., 2011. On the quality of high-resolution scatterometer winds. Journal of Geophysical Research: Oceans, 116: C10033.
Wackerman, C. C., Clemente-Colon, P., Pichel, W. G., and Li, X. F., 2002. A two-scale model to predict C-band VV and HH normalized radar cross section values over the ocean. Canadian Journal of Remote Sensing, 28: 367–384.
Wang, L., Han, B., Yuan, X. Z., Lei, B., Ding, C. B., Yao, Y. L., and Chen, Q., 2018. A preliminary analysis of wind retrieval, based on GF-3 wave mode data. Sensors, 18: 1004.
Yang, X. F., Li, X. F., Zheng, Q. A., Gu, X., Pichel, W. G., and Li, Z. W., 2011. Comparison of ocean-surface winds retrieved from Quikscat scatterometer and Radarsat-1 SAR in offshore waters of the U.S. West Coast. IEEE Geoscience and Remote Sensing Letters, 8: 163–167.
Zhang, B., Perrie, W., and He, Y. J., 2011. Wind speed retrieval from RADARSAT-2 quad-polarization images using a new polarization ratio model. Journal of Geophysical Research: Oceans, 116: 1318–1323.
Zhao, Y., Li, X. M., and Sha, J., 2016. Sea surface wind streaks in spaceborne synthetic aperture radar imagery. Journal of Geophysical Research, 121: 6731–6741.
GF-3 SAR images were accessed from http://ds.nsoas.org.cn as an authorized account issued by NSOAS. The updated calibration constants were collected from http://dds.nsoas.org.cn/business/document (in Chinese). We also thank ECMWF for providing wind data, which were downloaded from http://www.ecmwf.int. ASCAT winds were downloaded online from http://archive.eumetsat.int using an authorized account. Buoy data were downloaded from http://www.ndbc.noaa.gov.
The research is partly supported by the Fundamental Research Funds for Zhejiang Provincial Universities and Research Institutes (No. 2019J00010), the National Key Research and Development Program of China (No. 2017 YFA0604901), the National Natural Science Foundation of China (Nos. 41806005 and 41776183), the Public Welfare Technical Applied Research Project of Zhejiang Province of China (No. LGF19D060003), the New-Shoot Talented Man Plan Project of Zhejiang Province (No. 2018R 411065), and the Science and Technology Project of Zhoushan City (No. 2019C21008).
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Zhu, S., Shao, W., Marino, A. et al. Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data. J. Ocean Univ. China 19, 23–35 (2020) doi:10.1007/s11802-020-4215-9
- Gaofen-3 synthetic aperture radar