Guosong Wang, Xidong Wang, Hui Wang, Min Hou, Yan Li, Wenjing Fan, Yulong Liu. Evaluation on monthly sea surface wind speed of four reanalysis data sets over the China seas after 1988[J]. Acta Oceanologica Sinica, 2020, 39(1): 83-90. doi: 10.1007/s13131-019-1525-0
Citation: Guosong Wang, Xidong Wang, Hui Wang, Min Hou, Yan Li, Wenjing Fan, Yulong Liu. Evaluation on monthly sea surface wind speed of four reanalysis data sets over the China seas after 1988[J]. Acta Oceanologica Sinica, 2020, 39(1): 83-90. doi: 10.1007/s13131-019-1525-0

Evaluation on monthly sea surface wind speed of four reanalysis data sets over the China seas after 1988

doi: 10.1007/s13131-019-1525-0
Funds:  The National Key R&D Program of China under contract No. 2016YFC1401905; the National Natural Science Foundation of China under contract No. 41776004; the Fundamental Research Funds for the Central Universities under contract No. 2016B12514.
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  • Corresponding author: E-mail: wh_cherry@126.com
  • Received Date: 2018-09-28
  • Accepted Date: 2019-05-05
  • Available Online: 2020-04-21
  • Publish Date: 2020-01-20
  • This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set (CCMP), NCEP climate forecast system reanalysis data set (CFSR), ERA-interim reanalysis data set (ERA-int) and Japanese 55-year reanalysis data set (JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the long-term and homogeneous observation wind speeds data recorded at ten stations. The results reveal that (1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively. The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s, respectively; (2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea; (3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.
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  • [1]
    Accadia C, Zecchetto S, Lavagnini A, et al. 2007. Comparison of 10-m wind forecasts from a regional area model and QuikSCAT scatterometer wind observations over the Mediterranean sea. Monthly Weather Review, 135(5): 1945–1960. doi: 10.1175/MWR3370.1
    [2]
    Alvarez I, Gomez-Gesteira M, Decastro M, et al. 2013. Comparison of different wind products and buoy wind data with seasonality and interannual climate variability in the southern Bay of Biscay (2000–2009). Deep Sea Research Part II: Topical Studies in Oceanography, 106: 38–48
    [3]
    Atlas D. 1987. Radar detection of hazardous small scale weather disturbances: U.S. Patent 4, 649, 388[P]. 1987–3–10
    [4]
    Atlas R, Hoffman R N, Ardizzone J, et al. 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. doi: 10.1175/2010BAMS2946.1
    [5]
    Atlas R, Hoffman R N, Bloom S C, et al. 1996. A multiyear global surface wind velocity dataset using SSM/I wind observations. Bulletin of the American Meteorological Society, 77(5): 869–882. doi: 10.1175/1520-0477(1996)077<0869:AMGSWV>2.0.CO;2
    [6]
    Atlas R, Wolfson N, Terry J. 1993. The effect of SST and soil moisture anomalies on GLA model simulations of the 1988 U. S. Summer drought. Journal of Climate, 6(11): 2034–2048
    [7]
    Azorin-Molina C, Vicente-Serrano S M, Mcvicar T R, et al. 2014. Homogenization and assessment of observed near-surface wind speed trends over Spain and Portugal, 1961–2011. Journal of Climate, 27(10): 3692–3712. doi: 10.1175/JCLI-D-13-00652.1
    [8]
    Barnes E A, Barnes R J. 2015. Estimating linear trends: simple linear regression versus epoch differences. Journal of Climate, 28(24): 9969–9976. doi: 10.1175/JCLI-D-15-0032.1
    [9]
    Berrisford P, Kållberg P, Kobayashi S, et al. 2011. Atmospheric conservation properties in ERA-Interim. Quarterly Journal of the Royal Meteorological Society, 137(659): 1381–1399. doi: 10.1002/qj.864
    [10]
    Boldina I, Beninger P G. 2016. Strengthening statistical usage in marine ecology: Linear regression. Journal of Experimental Marine Biology and Ecology, 474: 81–91. doi: 10.1016/j.jembe.2015.09.010
    [11]
    Carvalho D, Rocha A, Gómez-Gesteira M. 2012. Ocean surface wind simulation forced by different reanalyses: Comparison with observed data along the Iberian Peninsula coast. Ocean Modelling, 56: 31–42. doi: 10.1016/j.ocemod.2012.08.002
    [12]
    Dee D P, Balmaseda M, Balsamo G, et al. 2013. Toward a consistent reanalysis of the climate system. Bulletin of the American Meteorological Society, 95(8): 1235–1248
    [13]
    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
    [14]
    Ebita A, Kobayashi S, Ota Y, et al. 2011. The Japanese 55-year reanalysis “JRA-55”: an interim report. SOLA, 7(1): 149–152
    [15]
    Kobayashi C, Iwasaki T. 2016. Brewer-Dobson circulation diagnosed from JRA-55. Journal of Geophysical Research: Atmospheres, 121(4): 1493–1510. doi: 10.1002/2015JD023476
    [16]
    Kuang Fangfang, Zhang Youquan, Zhang Junpeng, et al. 2015. Comparison and evaluation of three sea surface wind products in Taiwan Strait. Haiyang Xuebao (in Chinese), 37(5): 44–53
    [17]
    Laapas M, Venäläinen A. 2017. Homogenization and trend analysis of monthly mean and maximum wind speed time series in Finland, 1959-2015. International Journal of Climatology, 37(14): 4803–4813. doi: 10.1002/joc.5124
    [18]
    Li D L, Von Storch H, Geyer B. 2016. Testing reanalyses in constraining dynamical downscaling. Journal of the Meteorological Society of Japan, Ser II, 94: 47–68
    [19]
    Li Yan, Wang Guosong, Fan Wenjing, et al. 2018. The homogeneity study of the sea surface temperature data along the coast of the China Seas. Haiyang Xuebao (in Chinese), 40(1): 17–28
    [20]
    Saha S, Moorthi S, Pan H L, et al. 2010. The NCEP climate forecast system reanalysis. Bulletin of the American Meteorological Society, 91(8): 1015–1057. doi: 10.1175/2010BAMS3001.1
    [21]
    Stephenson T S, Goodess C M, Haylock M R, et al. 2008. Detecting inhomogeneities in Caribbean and adjacent Caribbean temperature data using sea-surface temperatures. Journal of Geophysical Research: Atmospheres, 113(D21): D21116. doi: 10.1029/2007JD009127
    [22]
    Taylor K E. 2001. Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research: Atmospheres, 106(D7): 7183–7192. doi: 10.1029/2000JD900719
    [23]
    Trenberth K E, Fasullo J T, Mackaro J. 2010. Atmospheric moisture transports from ocean to land and global energy flows in reanalyses. Journal of Climate, 24(18): 4907–4924
    [24]
    Uppala S M, Kållberg P W, Simmons A J, et al. 2005. The ERA-40 re-analysis. Quarterly Journal of the Royal Meteorological Society: A journal of the atmospheric sciences, applied meteorology and physical oceanography, 131(612): 2961–3012
    [25]
    Wan Hui, Wang Xiaolan, Swail V R. 2010. Homogenization and trend analysis of Canadian Near-surface wind speeds. Journal of Climate, 23(5): 1209–1225. doi: 10.1175/2009JCLI3200.1
    [26]
    Wang Guosong, Gao Shanhong, Wu Bingui, et al. 2014. Distribution features of wind energy resources in the offshore areas of China. Advances in Marine Science (in Chinese), 32(1): 21–29
    [27]
    Wang Guosong, Li Yan, Hou Min, et al. 2017. Homogeneity Study of the sea surface temperature data over the South China Seas using PMT method. Journal of Tropical Meteorology (in Chinese), 33(5): 637–643
    [28]
    Wolfson R. 1987. The configuration of slow-mode shocks. Journal of Geophysical Research, 92(A9): 9875–9884. doi: 10.1029/JA092iA09p09875
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