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利用NCEP风场产品和dropsonde探测资料,对中国近海ASCAT全场和单点的风速反演精度进行验证分析.研究发现ASCAT反演风场与NCEP风场的风速、风向平均绝对偏差分别为2.06 m/s和21.98°;均方根误差分别为2.87 m/s和34.29°.两者风速反演精度较一致,风向误差相对偏大.ASCAT反演风场与dropsonde探测资料的风速、风向平均绝对偏差分别为1.55 m/s和3.43°;均方根误差分别为1.73 m/s和4.15°.ASCAT资料可以较好的反演台风风场. 相似文献
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热带太平洋-印度洋上层海温、热含量和混合层深度的年变化特征 总被引：2，自引：1，他引：2
根据1955~2003年次表层海温、海洋上层400m热含量和混合层深度资料,采用EOF分析方法,研究热带太平洋-印度洋上层海温、热含量和混合层深度的年变化特征及其与厄尔尼诺、印度洋偶极子、热带辐合带分布和活动的关系。结果表明:海表温度SST的分布和变化不能代表海洋上层热含量的分布和变化,热含量HST的分布与混合层MLD分布比较相似,尤其在热带印度洋和东太平洋,MLD季节变化比HST和SST提前2~3个月左右。太平洋10°N附近HST带状强扰动区和赤道地区HST反相变化是热带太平洋上层海水温度扰动最主要特征。HST的强扰动区主要由60~300m次表层海温距平的扰动引起,80m左右扰动最强,这种扰动沿着斜温层由上向下,自东向西传递,上半年增温,下半年降温,具有明显的年周期变化。这种变化对ENSO循环期间热含量异常信号传播的影响值得关注。热带太平洋HST的扰动变化和太平洋的ITCZ和SPCZ的移动和变化也有一定的关联。印度洋的西北部和东南部次表层海温距平呈年周期的反相振荡,但这种固有振荡和印度洋偶极子DMI振荡反相,这可能是导致印度洋大部分偶极子生命史都很短的原因之一。 相似文献
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南海QuikSCAT海面风场变化特征分析 总被引：4，自引：0，他引：4
基于QuikSCAT海面风场产品,对海面风场资料进行了EOF分析和随机动态分析,以此分析南海海面风场的变化特征。研究发现:海面原始风场风速季节变化最为明显,其变化占总变化方差的59.1%,黑潮的季节变化通过海气相互作用对南海局地风场有较明显的影响;原始风场第三模态及异常风场第二模态时间变化函数与SOI和PDO弱相关,且异常风场第二模态时间变化函数谱分析结果主要呈现5年的周期变化,南海海面风场变化与年际振荡有关;南海大部分海区风速呈现增长的趋势,但增长速率较小;风速增大最快的区域是台湾海峡以南海域和北部湾,增长速度达到0.05 ms-1a-1。 相似文献
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南海海面风场变分融合的初步研究 总被引：1，自引：0，他引：1
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2.59 m/s、2.76 m/s,明显好于模式风场(3.63 m/s、2.81 m/s)和散射计风场(2.79 m/s、2.80 m/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0.81,好于散射计风场(0.74和0.79),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。 相似文献
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The Statistical Significance Test of Regional Climate Change Caused by Land Use and Land Cover Variation in West China 总被引：1，自引：0，他引：1
The West Development Policy being implemented in China is causing significant land use and land cover （LULC） changes in West China. With the up-to-date satellite database of the Global Land Cover Characteristics Database （GLCCD） that characterizes the lower boundary conditions, the regional climate model RIEMS-TEA is used to simulate possible impacts of the significant LULC variation. The model was run for five continuous three-month periods from 1 June to 1 September of 1993, 1994, 1995, 1996, and 1997, and the results of the five groups are examined by means of a student t-test to identify the statistical significance of regional climate variation. The main results are： （1） The regional climate is affected by the LULC variation because the equilibrium of water and heat transfer in the air-vegetation interface is changed. （2） The integrated impact of the LULC variation on regional climate is not only limited to West China where the LULC varies, but also to some areas in the model domain where the LULC does not vary at all. （3） The East Asian monsoon system and its vertical structure are adjusted by the large scale LULC variation in western China, where the consequences are the enhancement of the westward water vapor transfer from the east oast and the relevant increase of wet-hydrostatic energy in the middle-upper atmospheric layers. （4） The ecological engineering in West China affects significantly the regional climate in Northwest China, North China and the middle-lower reaches of the Yangtze River; there are obvious effects in South, Northeast, and Southwest China, but minor effects in Tibet. 相似文献
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Previous studies showed that 4 D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4 D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4 D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously,and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4 D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation,which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4 D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper. 相似文献
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