南海海面风场变分融合的初步研究  被引量:5

PRELIMINARY STUDY ON VARIATIONAL BLENDING OF SURFACE VECTOR WINDS IN SOUTH CHINA SEA

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作  者:项杰[1] 王慧鹏[1] 王春明[1] 寇正[1] 施伟来[1] 刘春霞[2] 

机构地区:[1]解放军理工大学气象海洋学院 [2]中国气象局广州热带海洋气象研究所

出  处:《热带气象学报》2015年第2期153-160,共8页Journal of Tropical Meteorology

基  金:国家自然科学基金项目(41275113;41206163);行业专项"南海热带云团及其强风监测预警技术(GYHY201106036)";热带海洋环境国家重点实验室开放基金项目(LTO1205)共同资助

摘  要:利用二维变分同化(2DVar)方法,把南海海域(110.12~117.92°E,10.12~17.92°N)QuikSCAT散射计风场资料融合到区域高分辨率数值模式(华南中尺度天气预报模式GZMM)风场资料中,并利用独立的观测数据(西沙站海面风场观测值)对融合效果进行了检验。得到结论:(1)风场单点融合试验表明,风场融合设计方案基本合理;(2)与独立观测数据的偏差分析表明,融合后的风场在经向和纬向的均方根误差分别为2.59m/s、2.76m/s,明显好于模式风场(3.63m/s、2.81m/s)和散射计风场(2.79m/s、2.80m/s),这说明融合的风场优于模式风场和散射计风场;(3)与独立观测数据的相关性分析表明,融合后的风场在经向和纬向的相关系数分别为0.80和O.81,好于散射计风场(0.74和O.79),而比模式风场(0.91和0.94)的要差。最后讨论了均方根误差与相关系数不一致的可能原因。A 2-dimensional variational assimilation method is applied to blend the satellite scatterometer measurement (QuikSCAT) and surface vector winds simulated by a regional high-resolution mesoscale atmospheric model (GZMM) for an area (110.12-117.92°E, 10.12-17.92°N) in the South China Sea, and the validation is performed using the in situ observational surface wind speed from an automatic weather station located at the northern part of Yongxing Island in the South China Sea. The resulting conclusions are as follows: (1) The scheme of surface wind blending is feasible through single-point observation tests. (2) The RMS error in the longitudinal (latitudinal) component of the surface wind between the blended and in situ observations is 2.59 (2.76)m/s, which is superior to that simulated by the GZMM model and QuikSCAT surface wind. (3) The correlation of the longitudinal (latitudinal) component of the surface wind between the blended and in situ observational surface wind is 0.80 (0.81), which is larger than that of QuikSCAT surface wind, 0.74 (0.79), and less than that of GZMM model-simulated surface wind, 0.91 (0,94). The reasons why there exists this kind of disagreements are discussed.

关 键 词:南海 海面风场 QUIKSCAT 融合 2DVar 

分 类 号:P425[天文地球—大气科学及气象学]

 

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