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国家自然科学基金(41006011)

作品数:3 被引量:12H指数:2
相关作者:舒业强武扬韩桂军王东晓程国胜更多>>
相关机构:国家海洋信息中心南京信息工程大学中国科学院更多>>
发文基金:国家自然科学基金国家重点基础研究发展计划更多>>
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基于CORA资料的中国海海表面温度季节和年际变化特征分析被引量:6
2013年
基于1986—2008年的中国近海及邻近海域再分析产品(CORA),采用经验正交函数分解方法(EOF)分析了海表面温度(SST)的季节及年际变化特征,并用相应的SODA、AVHRR以及Levitus资料对CORA做了对比评估。相比于AVHRR而言,CORA资料SST的偏差和均方根误差均小于SO-DA,相比Levitus资料而言CORA资料温度盐度的均方根误差随深度的变化皆小于SODA。CORA与SODA资料相比,两者前3个模态的时空分布大体一致,区别在于CORA资料能更好地反映参量的一些细微特征。结果表明,CORA资料能很好的刻画中国近海SST的季节、年际变化特征,尤其是黑潮流经区域SST的局地变化特征。季节EOF第二模态显示的是SST对由风引起的潜热释放的响应特征。第三模态刻画了冬夏转换季的分布特征,主要揭示了东北-西南走向的锋面特征。SST年际变化与ENSO密切相关,区域平均的南海SSTA与Nino指数的吻合程度CORA优于SODA。
武扬程国胜韩桂军舒业强王东晓
关键词:SSTEOF
Temperature Inversion in the Bay of Bengal Prior to the Summer Monsoon Onsets in 2010 and 2011被引量:4
2012年
Freshwater input such as runoff and rainfall can enhance stratification in the Bay of Bengal(BOB) through the formation of a "barrier layer",which can lead to the formation of a temperature inversion.The authors focused on the temperature inversion in spring,especially before the onset of the summer monsoon,because previous research has mainly focused on the temperature inversion in winter.Using the hydrographic data from two cruises performed during 24-30 April 2010 and 1-4 May 2011,the authors found that inversions appeared at two out of nine Conductivity-Temperature-Depth Recorder(CTD) stations across the 10°N section and at seven out of 13 CTD stations across the 6°N section in the BOB.In 2010,the inversions(at stations N02 and N05) occurred at depths of approximately 50-60 meters,and their formation was caused by the advection of cold water over warm water.In 2010,the N02 inversion was mainly influenced by the warm saline water from the east sinking below the cold freshwater from the west,while the N05 inversion was affected by the warm saline water from its west sinking below the cold freshwater from its east.In 2011,the inversions appeared at depths of 20-40 meters(at stations S01,S02,S07,S08,and S09) and near 50 m(S12 and S13).The inversions in 2011 were mainly caused by the net heat loss of the ocean along the 6°N section.
LI JianYANG LeiSHU Ye-QiangWANG Dong-Xiao
关键词:STRATIFICATIONFRESHWATER
Comparison of remote sensing data with in-situ wind observation during the development of the South China Sea monsoon被引量:2
2012年
Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms that QuikSCAT estimates of wind speed and direction are generally accurate, except for the extremes of high wind speeds (>13.8m/s) and very low wind speeds (<1.5m/s) where direction is poorly predicted. In-situ observations show that the summer monsoon in the northern SCS starts between May 6 and June 1. From March 13, 2010 to August 31, 2010, comparisons of sea surface temperature (SST) and rainfall from AMSR-E with data from a buoy located at Xisha Islands, as well as wind measurements derived from ASCAT and observations from an automatic weather station show that QuikSCAT, ASCAT and AMSR-E data are good enough for research. It is feasible to optimize the usage of remote-sensing data if validated with in-situ measurements. Remarkable changes were observed in wind, barometric pressure, humidity, outgoing longwave radiation (OLR), air temperature, rainfall and SST during the monsoon onset. The eastward shift of western Pacific subtropical high and the southward movement of continental cold front preceded the monsoon onset in SCS. The starting dates of SCS summer monsoon indicated that the southwest monsoon starts in the Indochinese Peninsula and forms an eastward zonal belt, and then the belt bifurcates in the SCS, with one part moving northeastward into the tropical western North Pacific, and another southward into western Kalimantan. This largely determined the pattern of the SCS summer monsoon. Wavelet analysis of zonal wind and OLR at Xisha showed that intra-seasonal variability played an important role in the summer. This work improves the accuracy of the amplitude of intra-seasonal and synoptic variation obtained from remote-sensed data.
李健王东晓陈举杨磊
关键词:QUIKSCATAMSR-E
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