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附加影响因子对红外遥感资料反演大气温湿廓线的辅助作用

蒋德明1,董超华2,曹思沁3

蒋德明1,董超华2,曹思沁3. 附加影响因子对红外遥感资料反演大气温湿廓线的辅助作用[J]. 热带气象学报, 2009, (S1): 79-84.
引用本文: 蒋德明1,董超华2,曹思沁3. 附加影响因子对红外遥感资料反演大气温湿廓线的辅助作用[J]. 热带气象学报, 2009, (S1): 79-84.

附加影响因子对红外遥感资料反演大气温湿廓线的辅助作用

  • 摘要:

    利用AIRS(Atmospheric Infrared Sounder)实际观测资料和采用特征向量反演方法,研究了非红外遥感因子对红外遥感大气温湿廓线反演的辅助作用。这些因子包括:微波探测通道、纬度、地形、表面高度、表面温度、表面气压等。试验结果表明,微波通道可以明显改善对流层中低层(800 hPa以下)温度和湿度的反演结果,对800 hPa以上没有明显的作用。划分纬度带有助于提高反演精度。在较平坦的地区温度反演的均方根误差远远小于地形起伏较大的地区。而水汽反演误差对地形变化不敏感。增加附加影响因子对改善对流层中低层温度反演精度有十分明显的作用,对中低层湿度反演精度有一定的改善。

     

  • [1] FETZER E, McMILLIN L M, TOBIN D, et al. AIRS/AMSU/HSB validation[J]. IEEE Trans Geosci Remote Sensing, 2003, 41:418–431.[2] SUSSKIND J, BARNET C D, BLAISDELL J M. Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds[J]. IEEE Trans Geosci Remote Sensing, 2003, 41: 390–409.[3] AUMANN H H, CHAHINE M T, GAUTIER C, et al. AIRS/AMSU/HSB on the Aqua mission: Design, science objectives, data products, and processing systems[J]. IEEE Trans Geosci Remote Sensing, 2003, 41: 253–264.[4] GOLDBERG M D, QU Y, McMILLIN L M, et al. AIRS near-real-time products and algorithms in support of operational numerical weather prediction[J]. IEEE Trans Geosci Remote Sensing, 2003, 41: 379–389.[5] 蒋德明,董超华,陆维松. AQUA/AIRS大气参数反演的敏感性试验[C]//2004环境遥感学术年会论文集,2004: 1-9.[6] DONG Chaohua,JIANG Deming,QI Chengli, et al. Experimental study on atmospheric parameters using new atmospheric sounding instrument data[C]//Multispectral and Hyperspectral Remote Sensing Instruments and Applications II, Proc. of SPIE, 2005: 24-32.[7] 张鹏,PASCAL Brunel,董超华,等. 卫星高光谱红外大气探测的正演模拟研究[J]. 红外与毫米波学报,2005, 24(6): 414-418.[8] WU Xuebao, LI Jun, ZHANG Wenjian, et al. Atmospheric Profile Retrieval with AIRS Data and Validation at the ARM CART Site[J]. Adv Atmos Sci, 2005, 22(5): 647–654.[9] GUAN Li ALLEN Huang, LI Jun. A Study on Retrieving Atmospheric Profiles from EOS/AIRS Observations[J]. ACTA METEOROLOGICA SINICA, 2005, 19(1): 112-119.[10] HUANG J, QIU C, MA G, et al. Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements[J]. Adv Atmos Sci, 2006, 23(2): 224-234.[11] JIANG Deming, DONG Chaohua, LU Weisong. Neural networks approach to high vertical resolution atmospheric temperature profiles retrieval from spaceborne high spectral resolution infrared sounder measurements[C]. Proc of SPIE, 2006, 6064.[12] 蒋德明,董超华,陆维松. 利用AIRS观测资料进行红外高光谱大气探测能力试验研究[J]. 遥感学报, 2006, 10(4): 586-592. [13] HUANG H -L, ANTONELLI P. Application of principal component analysis to high-resolution infrared measurement compression and retrieval[J]. J Appl Met, 2001, 40: 365-388.[14] SMITH W L, WOOLF H M. The Use of Eigenvectors of Statistical Covariance Matrices for Interpreting Satellite Sounding Radiometer Observations[J]. J Atmos Sci, 1976, 33: 1 127-1 140.
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