利用卫星和AERONET观测资料对东亚地区吸收性气溶胶识别及其光学特征分析
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摘要
从沙尘源区产生的沙尘气溶胶、来自生物质燃烧和化石燃料燃烧的黑碳和有机碳气溶胶是最主要的三类吸收性气溶胶。由吸收性气溶胶产生的辐射强迫是全球和区域气候变化不确定性最大的来源之一。识别吸收性气溶胶并估计其光学特性能够深入了解和准确估计吸收性气溶胶的直接、半直接和间接效应,进而对气候变化研究都有着非常重要的意义。本文首先通过卫星观测对沙尘气溶胶长距离传输和垂直结构特征进行分析,并发展了一套结合多卫星识别沙尘气溶胶的新算法。同时通过对地面观测AERONET资料的分析发展了一套地面识别吸收性气溶胶的方法。
     在太平洋沙尘实验期间(PACDEX),用云-气溶胶偏振激光雷达(CALIOP)和地面标准数据来研究亚洲对流层中沙尘气溶胶的长距离传输和垂直分布特征。结果表明,在太平洋地区,气溶胶主要呈现两层结构,这主要同两个不同的沙尘源区有关系。从CALIOP观测的后向散射退偏比的垂直分布可以看出,从戈壁沙漠地区发生的沙尘一般都低于5千米,通常经过3天左右的时间到达太平洋,而从塔克拉玛干沙漠发生的沙尘有时能够达到9千米,这种情况一般需要5天或者更长的时间到达太平洋。说明进入到对流层上层西风急流的沙尘气溶胶可以被长距离传输达到更远。
     我们发展了一套结合主动CALIOP和被动红外成像仪(IIR)识别沙尘气溶胶的算法。这种结合激光雷达和红外观测(CLIM)的方法主要是用IIR三波段红外亮温来区分冰云和厚沙尘层并用激光雷达识别薄沙尘和水云层。一般来说厚沙尘层的10.6和12.05微米的亮温差(BTD11-12)是负值,冰云层的亮温差是正值,对于薄沙尘层来说,亮温差会从负值到正值之间变化,这种情况正好可以用CALIOP准确识别。塔克拉玛干沙漠在2008年春季的结果表明,美国国家航天局第二版CALIOP的沙尘层识别方法会误判43%的沙尘层(几乎所有的厚沙尘层)为云层,而我们的CLIM新方法会显著的减小这种误判到7%。
     我们用AERONET观测资料发展了一种获取吸收性气溶胶来源分类的方法。该方法主要是从AERONET观测资料得到散射和吸收Angstrom旨数,进而利用这些气溶胶光学参量把吸收性气溶胶来源分为以下六类:沙尘、生物质燃烧、化石燃料燃烧、沙尘和生物质燃烧混合、生物质和化石燃料燃烧混合和混合污染物。
     为了从AERONET观测数据识别吸收性气溶胶,我们发展了一套结合吸收Angstrom指数(AAE)来识别沙尘、黑碳和有机碳气溶胶的方法(三波段方法)。通过对吸收性气溶胶混合数据进行分析,我们估算出沙尘气溶胶AAE1(440和675nm)和AAE2(675和870nm)分别是2.24和1.29,黑碳气溶胶AAE1和AAE2是0.33和0.69,有机碳气溶胶的AAE1是4.21。把沙尘、黑碳和有机碳的AAEs代入三波段方程中,从而估计出它们的光学特征,并把这些结果同GOCART模式结果和外场实验结果作比较。结果表明:用三波段方法得到的550nm波段的有机碳和黑碳气溶胶的光学厚度比是1.33和吸收光学厚度比是0.26,GOCART模式得到的结果分别为1.94和0.05,而外场试验INDOEX和SAFARI的结果是1.4~1.5和0.27,对比分析可知三波段的结果同外场实验结果一致。因此,通过本文我们可以更加准确的估计沙尘、黑碳和有机碳气溶胶的对气候的影响。
Dust aerosol from dust source region, black carbon (BC) and organic carbon (OC) aerosols from biomass burning and fossil fuel are the three main types of light-absorbing aerosols. The radiative forcing due to light-absorbing aerosols is one of the largest sources of uncertainties in global and regional climate change. To identify the light-absorbing aerosols and estimate their optical properties have very important significance for understanding and estimating direct, semi-direct, and indirect effects by light-absorbing aerosols and climate change research. In this study, we use satellite observations to obtain the long-range transport and vertical distribution of dust aerosol, then, developed a new dust aerosol detection method. We also developed another new method to partition the light-absorbing aerosols using the AERONET observations.
     During the Pacific Dust Experiment (PACDEX), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and standard surface measurements are used to directly observe the long-range transport and vertical distribution of Asian dust aerosol in the free troposphere. The results show that two-layers dust aerosol structures in Pacific Ocean are often apparent, which may be associated with contributions from two major dust sources. The vertical distribution of the CALIOP backscattering/depolarization ratios indicate that non-spherically shaped dust aerosols floated from near the groud to an altitude of bellow5km in Gobi desert, which it usually takes three days to reach the Pacific Oceans and approximately9km around the Taklamakan desert, which need five or more days to arrive in the Pacific Oceans. This suggests the possible long-range transport of entrained dust aerosols via upper tropospheric westerly jets and it can be reached more distant.
     A new dust aerosol detection method was developed by combining the active CALIOP and passive Infrared Imaging Radiometer (IIR) measurements. This combined lidar and IR measurement (hereafter, CLIM) method uses the IIR tri-spectral IR brightness temperatures to discriminate between ice cloud and dense dust layers, and lidar measurements to detect thin dust and water cloud layers. The brightness temperature difference between10.60and12.05μm (BTD11-12) is typically negative for dense dust layer and generally positive for ice cloud layer, but it varies from negative to positive for thin dust layers, which the CALIOP correctly identifies. Results show that the CLIM method could significantly reduce misclassification rates to as low as-7%for the active dust season of spring2008over the Taklamakan Desert, which the National Aeronautics and Space Administration (NASA) version2CALIOP dust layer detection method misclassified about43%dust layers (almost dense dust layers) as cloud layers.
     Then, we developed a new method to partition the light-absorbing aerosols sources from AERONET observations. The aerosol spectral variations, scattering and absorption angstrom exponent from AERONET observations, are used to categorize6kinds of the absorption aerosols mixtures:Dust, Biomass Burning, Fossil Fuel, Mixed Dust with Biomass Burning, Mixed Biomass Burning with Fossil Fuel, and Mixed Pollution.
     For detecting the absorption aerosols from AERONET observations, another new method (three wavelengths method) was developed by using the absorption angstrom exponents (AAE) to indicate dust, black carbon, and organic carbon compositions. We found the dust AAE1(between440and675nm) and AAE2(between675and870nm) is2.24and1.29respectively, the black carbon AAE1is0.33and AAE2is0.69, and the organic carbon AAE1is4.21from the absorption aerosols mixtures data. Then we put the dust, black carbon, and organic carbon AAEs in the three wavelengths equations, to estimate their optical properties, and to compare the results with GOCART model results and field campaigns observations. The AODOC/AODBC and AAODOC/AAODBC ratios at550nm are1.33and0.26by using the three wavelengths method, and1.94and0.05from GOCART model. We found our results are more consistent with the field INDOEX and SAFARI campaigns, whose results show that the AODOC/AODBc at550nm is1.4-1.5, and AAODOC/AAODBC ratios is about0.27. These results allow a more accurate assessment of the effect of dust, black carbon, and organic carbon on climate.
引文
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