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Comparison of sea surface wind field measured by HY-2A scatterometer and WindSat in global oceans

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Abstract

In this study, we present a comprehensive comparison of the sea surface wind field measured by scatterometer (Ku-band scatterometer) aboard the Chinese HY-2A satellite and the full-polarimetric radiometer WindSat aboard the Coriolis satellite. The two datasets cover a four-year period from October 2011 to September 2015 in the global oceans. For the sea surface wind speed, the statistical comparison indicates good agreement between the HY-2A scatterometer and WindSat with a bias of nearly 0 m/s and a root mean square error (RMSE) of 1.13 m/s. For the sea surface wind direction, a bias of 1.41° and an RMSE of 20.39° were achieved after excluding the data collocated with opposing directions. Furthermore, discrepancies in sea surface wind speed measured by the two sensors in the global oceans were investigated. It is found that the larger differences mainly appear in the westerlies in the both hemispheres. Both the bias and RMSE show latitude dependence, i.e., they have significant latitudinal fl uctuations.

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References

  • Atlas R, Hoffman R N, Ardizzone J, Leidner S M, Jusem J C, Smith D K, Gombos D. 2011. A cross–calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications. Bulletin of the American Meteorological Society, 92 (2): 157–174.

    Article  Google Scholar 

  • Bourassa M A, Legler D M, O’Brien J J, Smith S R. 2003. SeaWinds validation with research vessels. Journal of Geophysical Research: Oceans, 108 (C2): 3 019.

    Book  Google Scholar 

  • Freilich M H, Dunbar R S. 1999. The accuracy of the NSCAT 1 vector winds: comparisons with National Data Buoy Center buoys. Journal of Geophysical Research: Oceans, 104 (C5): 11 231–11 246.

    Google Scholar 

  • Gaiser P W, Germain K M S, Twarog E M, Poe G A, Purdy W, Richardson D, Grossman W, Jones W L, Spencer D, Golba G, Cleveland J, Choy L, Bevilacqua R M, Chang P S. 2004. The WindSat spaceborne polarimetric microwave radiometer: sensor description and early orbit performance. IEEE Transactions on Geoscience and Remote Sensing, 42 (11): 2 347–2 361.

    Article  Google Scholar 

  • Hasager B, Mouche A, Badger M, Bingöi F, Karagali I, Driesenaar T, Stoffelen A, Peña A, Longépé N. 2015. Offshore wind climatology based on synergetic use of Envisat ASAR, ASCAT and QuikSCAT. Remote Sensing of Environment, 156: 247–263.

    Article  Google Scholar 

  • Hersbach H, Stoffelen A, de Haan S. 2007. An improved Cband scatterometer ocean geophysical model function: CMOD5. Journal of Geophysical Research: Oceans, 112 (C3): C03006.

    Google Scholar 

  • Hersbach H. 2010. Comparison of C–band scatterometer CMOD5.N equivalent neutral winds with ECMWF. Journal of Atmospheric and Oceanic Technology, 27 (4): 721–736.

    Article  Google Scholar 

  • Jiang X W, Lin M S, Liu J Q, Zhang Y G, Xie X T, Peng H L, Zhou W. 2012. The HY–2 satellite and its preliminary assessment. International Journal of Digital Earth, 5 (3): 266–281.

    Article  Google Scholar 

  • Jiang X W, Song Q T. 2010. A climatology of sea surface wind speed and wind stress fields constructed from scatterometer observations. Acta Oceanologica Sinica, 32 (6): 83–90. (in Chinese with English abstract)

    Google Scholar 

  • Mears A, Smith D K, Wentz F J. 2001. Comparison of special sensor microwave imager and buoy–measured wind speeds from 1987 to 1997. Journal of Geophysical Research: Oceans, 106 (C6): 11 719–11 729.

    Book  Google Scholar 

  • Meissner T, Ricciardulli L, Wentz F. 2011. All–weather wind vector measurements from intercalibrated active and passive microwave satellite sensors. In: IEEE International Geoscience and Remote Sensing Symposium. IEEE, Vancouver, BC, Canada, p.1 509–1 511.

    Book  Google Scholar 

  • Meissner T, Wentz F. 2005. Ocean retrievals for WindSat: radiative transfer model, algorithm, validation. In: Proceedings of 2005 IEEE International Geoscience and Remote Sensing Symposium. IEEE, Seoul, South Korea, p.4 761–4 764.

    Google Scholar 

  • Monaldo F M, Thompson D R, Pichel W G, Clemente–Colón P. 2004. A systematic comparison of QuikSCAT and SAR ocean surface wind speeds. IEEE Transaction s o n Geoscience and Remote Sensing, 42 (2): 283–291. OSI SAF. 2014–10–02. NSCAT–4 geophysical model function. http://projects.knmi.nl/scatterometer/nscat_gmf/.

    Article  Google Scholar 

  • Quilfen Y, Chapron B, Elfouhaily T, Katsaros K, Tournadre J. 1998. Observation of tropical cyclones by high–resolution scatterometry. Journal of Geophysical Research: Oceans, 103 (C4): 7 767–7 786.

    Book  Google Scholar 

  • Ricciardulli L, Wentz F J. 2015. A scatterometer geophysical model function for climate–quality winds: quikSCAT Ku–2011. Journal of Atmospheric and Oceanic Technology, 32 (10): 1 829–1 846.

    Article  Google Scholar 

  • Ricciardulli L. 2016–04–04. ASCAT on MetOp–A data product update notes. 4 April 2016, http://images.remss.com/papers/rsstech/2016_040416_RSS_ASCAT_V2_update.pdf.

    Google Scholar 

  • Stoffelen A, Anderson D. 1997. Scatterometer data interpretation: measurement space and inversion. Journal of Atmospheric and Oceanic Technology, 14 (6): 1 298–1 313.

    Article  Google Scholar 

  • Stoffelen A, Verspeek J A, Vogelzang J, 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 (5): 2 123–2 134.

    Article  Google Scholar 

  • Valkonen T, Schyberg H, Figa–Saldaña J. 2017. Assimilating advanced scatterometer winds in a high–resolution limited area model over northern Europe. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 (5): 2 394–2 405.

    Article  Google Scholar 

  • Verhoef A, Vogelzang J, Verspeek J, Stoffelen A. 2017. Longterm scatterometer wind climate data records. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10 (5): 2 186–2 194.

    Article  Google Scholar 

  • Verspeek J, Stoffelen A, Portabella M, Bonekamp H, Anderson C, Saldana J F. 2010. Validation and Calibration of ASCAT Using CMOD5.n. IEEE Transaction s on Geoscience and Remote Sensing, 48 (1): 386–395.

    Article  Google Scholar 

  • Vogelzang J, Stoffelen A, Verhoef A, Figa–Saldaña J. 2011. On the quality of high–resolution scatterometer winds. Journal of Geophysical Research: Oceans, 116 (C10): C10033.

    Book  Google Scholar 

  • Wang H, Zhu J H, Lin M S, Huang X Q, Zhao Y L, Chen C T, Zhang Y G, Peng H L. 2013. First six months quality assessment of HY–2. SCAT wind products using in situ measurements. Acta Oceanologica Sinica, 32 (11): 27–33.

    Article  Google Scholar 

  • Wang Z X, Stoffelen A, Zhao C F, Vogelzang J, Verhoef A, Verspeek J, Lin M S, Chen G. 2017. An SST–dependent Ku–band geophysical model function for RapidScat. Journal of Geophysical Research: Oceans, 122 (4): 3 461–3 480.

    Google Scholar 

  • Wentz F J, Meissner T, Smith D. 2005. Evaluation of microwave scatterometers and radiometers as satellite anemometers. In: Proceedings of 2005 IEEE International Geoscience and Remote Sensing Symposium. IEEE, Seoul, South Korea, p.3 310–3 313.

    Book  Google Scholar 

  • Wentz F J. 1990. SBIR phase II report: west coast storm forecasting with SSM/I. Tech. Rep. 033190, Santa Rosa, CA: Remote Sensing Systems.

    Google Scholar 

  • Wentz F J. 2015. A 17–yr climate record of environmental parameters derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. Journal of Climate, 28 (17): 6 882–6 902.

    Article  Google Scholar 

  • Wu Q, Chen G. 2015. Validation and intercomparison of HY–2A/MetOp–A/Oceansat–2 scatterometer wind products. Chinese Journal of Oceanology and Limnology, 33 (5): 1 181–1 190.

    Article  Google Scholar 

  • Yang X F, Li X F, Pichel W G, Li Z W. 2011. Comparison of ocean surface winds from ENVISAT ASAR, Metop ASCAT scatterometer, buoy measurements, and NOGAPS model. IEEE Transactions on Geoscience and Remote Sensing, 49 (12): 4 743–4 750.

    Article  Google Scholar 

  • Yang X F, Liu G H, Li Z W, Yu Y. 2014. Preliminary validation of ocean surface vector winds estimated from China’s HY–2A scatterometer. International Journal of Remote Sensing, 35 (11–12): 4 532–4 543.

    Google Scholar 

  • Yuan X J. 2004. High–wind–speed evaluation in the Southern Ocean. Journal of Geophysical Research: Atmosphere s, 109 (D13): D13101.

    Book  Google Scholar 

Download references

Acknowledgement

We would like to thank the NSOAS (National Satellite Ocean Application Service, China) for providing us with the HY-2A SCAT data. WindSat data are produced by Remote Sensing Systems and sponsored by the NASA Earth Science MEASURES DISCOVER Project and the NASA Earth Science Physical Oceanography Program. RSS WindSat data are available at www.remss.com.

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Correspondence to Xiao-Ming Li.

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Supported by the Hainan Provincial Department of Science and Technology (No. ZDKJ2016015), the National Natural Science Foundation of China (No. 41406198), and the Special Project of Chinese High- Resolution Earth Observation System (No. 41-Y20A14-9001-15/16)

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Zheng, M., Li, XM. & Sha, J. Comparison of sea surface wind field measured by HY-2A scatterometer and WindSat in global oceans. J. Ocean. Limnol. 37, 38–46 (2019). https://doi.org/10.1007/s00343-019-7347-2

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