Volume 40 Issue 3
Apr.  2021
Turn off MathJax
Article Contents
Jing Cha, Xinyu Lin, Xiaogang Guo, Xiaofang Wan, Dawei You. Evaluation of reanalysis surface wind products with quality-assured buoy wind measurements along the north coast of the South China Sea[J]. Acta Oceanologica Sinica, 2021, 40(3): 58-69. doi: 10.1007/s13131-021-1746-x
Citation: Jing Cha, Xinyu Lin, Xiaogang Guo, Xiaofang Wan, Dawei You. Evaluation of reanalysis surface wind products with quality-assured buoy wind measurements along the north coast of the South China Sea[J]. Acta Oceanologica Sinica, 2021, 40(3): 58-69. doi: 10.1007/s13131-021-1746-x

Evaluation of reanalysis surface wind products with quality-assured buoy wind measurements along the north coast of the South China Sea

doi: 10.1007/s13131-021-1746-x
Funds:  The Scientific Research Foundation of the Third Institute of Oceanography, Ministry of Natural Resources under contract Nos 2014028, 2017011 and 2017012; the State Oceanic Administration Program on Global Change and Air-Sea Interactions under contract Nos GASI-IPOVAI-02 and GASI-IPOVAI-03.
More Information
  • Corresponding author: Email: chajing@tio.org.cn
  • Received Date: 2020-10-22
  • Accepted Date: 2020-11-02
  • Available Online: 2021-04-07
  • Publish Date: 2021-04-30
  • Three archived reanalysis wind vectors at 10 m height in the wind speed range of 2–15 m/s, namely, the second version of the National Centres for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSv2), European Centre for Medium-Range Weather Forecasting Interim Reanalysis (ERA-I) and NCEP-Department of Energy (DOE) Reanalysis 2 (NCEP-2) products, are evaluated by a comparison with the winds measured by moored buoys in coastal regions of the South China Sea (SCS). The buoy data are first quality controlled by extensive techniques that help eliminate degraded measurements. The evaluation results reveal that the CFSv2 wind vectors are most consistent with the buoy winds (with average biases of 0.01 m/s and 1.76°). The ERA-I winds significantly underestimate the buoy wind speed (with an average bias of –1.57 m/s), while the statistical errors in the NCEP-2 wind direction have the largest magnitude. The diagnosis of the reanalysis wind errors shows the residuals of all three reanalysis wind speeds (reanalysis-buoy) decrease with increasing buoy wind speed, suggesting a narrower wind speed range than that of the observations. Moreover, wind direction errors are examined to depend on the magnitude of the wind speed and the wind speed biases. In general, the evaluation of three reanalysis wind products demonstrates that CFSv2 wind vectors are the closest to the winds along the north coast of the SCS and are sufficiently accurate to be used in numerical models.
  • loading
  • [1]
    Bourassa M A, Meissner T, Cerovecki I, et al. 2010. Remotely sensed winds and wind stresses for marine forecasting and ocean modeling. In: Hall J, Harrison D E, Stammer D, eds. Proceedings of the OceanObs’09: Sustained Ocean Observations and Information for Society Conference. Venice, Italy: Space Agency
    [2]
    Carvalho D, Rocha A, Gómez-Gesteira M, et al. 2013. Comparison between CCMP, QuikSCAT and buoy winds along the Iberian Peninsula coast. Remote Sensing of Environment, 137: 173–183. doi: 10.1016/j.rse.2013.06.005
    [3]
    Chelton D B. 2005. The impact of SST specification on ECMWF surface wind stress fields in the Eastern Tropical Pacific. Journal of Climate, 18(4): 530–550. doi: 10.1175/JCLI-3275.1
    [4]
    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. doi: 10.1175/MWR-2861.1
    [5]
    Chelton D B, Schlax M G, Freilich M H, et al. 2004. Satellite measurements reveal persistent small-scale features in ocean winds. Science, 303: 978–983. doi: 10.1126/science.1091901
    [6]
    Dee D P, Uppala S M, Simmons A J, et al. 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656): 553–597. doi: 10.1002/qj.828
    [7]
    Ebuchi N, Graber H C, Caruso M J. 2002. Evaluation of wind vectors observed by QuikSCAT/SeaWinds using ocean buoy data. Journal of Atmospheric and Oceanic Technology, 19(12): 2049–2062. doi: 10.1175/1520-0426(2002)019<2049:EOWVOB>2.0.CO;2
    [8]
    Gilhousen D B. 1998. Improved real-time quality control of NDBC measurements. In: 10th Symposium on Meteorological Observations and Instrumentation. Preprints. Phoenix, AZ: American Meteorological Society, 363–366
    [9]
    Josse P, Caniaux G, Giordani H, et al. 1999. Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations. Part I: Surface fluxes. Annales Geophysicae, 17(4): 566–576
    [10]
    Kanamitsu M, Ebisuzaki W, Woollen J, et al. 2002. NCEP–DOE AMIP-II reanalysis (R-2). Bulletin of the American Meteorological Society, 83(11): 1631–1644. doi: 10.1175/BAMS-83-11-1631
    [11]
    Large W G, Holland W R, Evans J C. 1991. Quasi-geostrophic ocean response to real wind forcing: the effects of temporal smoothing. Journal of Physical Oceanography, 21(7): 998–1017. doi: 10.1175/1520-0485(1991)021<0998:QGORTR>2.0.CO;2
    [12]
    Peng Ge. 2004. Validation of a global reanalysis model in representing synoptic-scale eddies using scatterometer data: A case study. Geophysical Research Letter, 31: L16201. doi: 10.1029/2004GL020297
    [13]
    Peng Ge, Zhang Huaimin, Frank H P, et al. 2013. Evaluation of various surface wind products with OceanSITES buoy measurements. Weather and Forecasting, 28(6): 1281–1303. doi: 10.1175/WAF-D-12-00086.1
    [14]
    Saha S, Moorthi S, Wu Xingren, et al. 2014. The NCEP climate forecast system version 2. Journal of Climate, 27(6): 2185–2208. doi: 10.1175/JCLI-D-12-00823.1
    [15]
    Schmidt K M, Swart S, Reason C, et al. 2017. Evaluation of satellite and reanalysis wind products with in situ wave glider wind observations in the southern Ocean. Journal of Atmospheric and Oceanic Technology, 34(12): 2551–2568. doi: 10.1175/JTECH-D-17-0079.1
    [16]
    Tang Wenqing, Liu W T, Stiles B W. 2004. Evaluation of high-resolution ocean surface vector winds measured by QuikSCAT scatterometer in coastal regions. IEEE Transactions on Geoscience and Remote Sensing, 42(8): 1762–1769. doi: 10.1109/TGRS.2004.831685
    [17]
    Yang Jungang, Zhang Jie. 2018. Evaluation of ISS-RapidScat wind vectors using buoys and ASCAT data. Remote Sensing, 10(4): 648. doi: 10.3390/rs10040648
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(13)  / Tables(5)

    Article Metrics

    Article views (591) PDF downloads(23) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return