塔克拉玛干沙漠地区气溶胶光学厚度卫星遥感产品验证
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摘要
基于塔克拉玛干沙漠地区地基太阳光度计数据,系统验证2007-2008年星载多角度成像光谱仪(MISR)、中分辨率成像光谱仪(MODIS)和臭氧监测仪(OMI)气溶胶反演产品,旨在定量评估这些产品在我国沙漠地区的气溶胶光学厚度(AOD)反演精度。此外,还利用云-气溶胶正交偏振激光雷达(CALIOP)气溶胶反演产品对气溶胶垂直分布进行了研究。以及利用辐射传输模式(SBDART)的模拟结果对OMI/UVAI效果较差的原因进行了敏感性试验分析,结果表明：
(1) MODIS/AOD的相关系数在四种产品中最高(0.91),OMI/AOD次之(0.87),其次为MISR/AOD (0.84), OMI/UVAI相关系数偏低(0.51)。MISR/AOD均方根误差(0.14),平均偏差(-0.06),在四种反演产品中最低。与地基观测相比,MISR/AOD, MODIS/AOD系统偏低,OMI/AOD, OMI/UVAI系统偏高。在相同比较条件下(地基观测气溶胶光学厚度值限定在2.0以内),MISR的均方根误差和平均偏差在四种反演产品中最低,且相关系数也较高(0.84)。尽管存在诸多不同,但三种探测器气溶胶反演产品均能较好的展示该地区的气溶胶季节变化。
(2)塔克拉玛干沙漠春夏季AOD较大,秋冬季AOD相对较小。Angstrom波长指数的结果表明,春季(3-5月)最小(均值为0.11),夏季(6-8月)次之,秋季(9-11月),冬季(12-2月)较大(均值达到0.61),这表明在春夏季气溶胶粒子偏大,秋冬季气溶胶粒子偏小。此外,通过研究2000-2010年AOD年际变化表明,由于塔克拉玛干沙漠地区属于沙尘源区,气溶胶类型较为单一,所以总的来说,变化趋势不是较为明显。从反演结果来看,2003年的气溶胶含量在这十年中最高,年均值达到0.32,2005年的气溶胶含量在这十年中最低,年均值为0.28。
(3)气溶胶消光系数随高度的增加而减小,对流层中上部的大气较为干净,气溶胶主要集中在对流层的中下层。就垂直递减率而言,冬季最小,这应该与冬季逆温层较低,导致对流不旺盛有关。与空气分子Rayleigh散射消光系数随高度的增加而单调递减不同,对流层气溶胶消光系数垂直分布的一个明显特点是具有多层结构,如春季1.5-2 km、3 km处分别存在着浓度较大的气溶胶层,层内气溶胶消光系数变大,它反映了气溶胶浓度垂直分布结构的复杂性。
(4)利用SBDART模式模拟大气层顶辐亮度,用于计算得出气溶胶指数(AI),从而进行一些对比研究。研究发现,AI对气溶胶层高度极其敏感,与气溶胶高度几乎成线性关系,它对1-2 km,尤其是1 km的边界层气溶胶不敏感,随着气溶胶层高度的增加,AI也随着增加。除此之外,AI还对气溶胶单次散射反照率以及观测角度的变化较为敏感,随着观测角度的增加,AI随之减小,尤其是大于15°后,减小趋势较大。由于CALIOP探测器扫描宽度较窄,所以不是所有区域的气溶胶高度资料均能获取,在这种情况下,可以通过模拟获取所要研究区域的气溶胶高度信息。
Using ground-based Aerosol Optical Depth (AOD) data at Tazhong, Taklimakan Desert, four sets of satellite aerosol data, i.e., multi-angle imaging spectrometer (MISR), Moderate Resolution Imaging Spectrometer (MODIS) and the Ozone Monitoring Instrument (OMI) from 2007 to 2008 were validated. Besides, data from CALIOP are used to investigate the vertical distribution of aerosol. Result from radiative transfer model (SBDART) is also used to compare with OMI/UVAI for sensitivity experiment. The main contents of the study and their primary results are summarized as follows:
(1)The correlation coefficient for MODIS/AOD is the largest (0.91), followed by OMI/AOD (0.87), MISR/AOD (0.84) and OMI/UVAI (0.51). MISR/AOD root mean square error (0.14) and the average deviation (-0.06) are the lowest in the four products. MISR/AOD and MODIS/AOD is relatively less than the ground-based AOD, however, OMI/AOD and OMI/UVAI exceed the ground-based ones. Under the same conditions (ground-based AOD is limited to less than 2.0), the root mean square error and the standard deviation of MISR is the lowest. Seasonal variation of aerosol loading is captured by satellite data.
(2)Spring and summer AOD is relatively larger and AOD is relatively lower in the autumn and winter. The result of Angstrom exponent reflects that the spring has the minimum(0.11), followed by summer and autumn, and winter has the maximum(0.61), which shows that the aerosol particle is larger in spring and summer while it is smaller in autumn and winter. Besides, Taklimakan belongs to the sand source where aerosol type is single. So in summary, the annual variability tendency of AOD from 2000 to 2010 is not that obvious. The result of the retrieval shows that 2003 has the maximal aerosol contents during the decade, the annual average is up to 0.32, while 2005 has the minimal aerosol contents, the annual average is 0.28.
(3) The extinction coefficient decreases with increasing altitude, the atmosphere in the upper troposphere is more clean, and aerosols mainly concentrated in the middle and lower troposphere. The value of the vertical lapse rate in winter is minimum, this attributes to the weak convection resulted from the relative low inversion layer in winter. Tropospheric vertical distribution of aerosol extinction coefficient is characterized by a multi-layer structure which is different from Rayleigh scattering of air molecules that decreases monotonically with increasing height. Large concentration of aerosol exists at 1.5-2 km and 3 km respectively in spring, the aerosol extinction coefficient becomes larger, which reflects the complexity of aerosols' vertical structure.
(4)Aerosol Index calculated from SBDART is used for comparison research. The results show that AI is extremely sensitive to the aerosol layer height and they are of almost linear relationship. AI is not sensitive to the boundary layer at 1-2 km,1 km particularly and increases with the aerosol layer height. In addition AI is also very sensitive to the single scattering albedo. Research shows that AI is more sensitive to the change of observation angle, AI decreases with the increasing observation angle, especially when the angle is greater than 15°, the decreasing trend is larger. Because of the narrow scanning width of CALIOP, not all region have the information of aerosol height. So we can get aerosol height in certain areas by simulating experiment.
(1) MODIS/AOD的相关系数在四种产品中最高(0.91),OMI/AOD次之(0.87),其次为MISR/AOD (0.84), OMI/UVAI相关系数偏低(0.51)。MISR/AOD均方根误差(0.14),平均偏差(-0.06),在四种反演产品中最低。与地基观测相比,MISR/AOD, MODIS/AOD系统偏低,OMI/AOD, OMI/UVAI系统偏高。在相同比较条件下(地基观测气溶胶光学厚度值限定在2.0以内),MISR的均方根误差和平均偏差在四种反演产品中最低,且相关系数也较高(0.84)。尽管存在诸多不同,但三种探测器气溶胶反演产品均能较好的展示该地区的气溶胶季节变化。
(2)塔克拉玛干沙漠春夏季AOD较大,秋冬季AOD相对较小。Angstrom波长指数的结果表明,春季(3-5月)最小(均值为0.11),夏季(6-8月)次之,秋季(9-11月),冬季(12-2月)较大(均值达到0.61),这表明在春夏季气溶胶粒子偏大,秋冬季气溶胶粒子偏小。此外,通过研究2000-2010年AOD年际变化表明,由于塔克拉玛干沙漠地区属于沙尘源区,气溶胶类型较为单一,所以总的来说,变化趋势不是较为明显。从反演结果来看,2003年的气溶胶含量在这十年中最高,年均值达到0.32,2005年的气溶胶含量在这十年中最低,年均值为0.28。
(3)气溶胶消光系数随高度的增加而减小,对流层中上部的大气较为干净,气溶胶主要集中在对流层的中下层。就垂直递减率而言,冬季最小,这应该与冬季逆温层较低,导致对流不旺盛有关。与空气分子Rayleigh散射消光系数随高度的增加而单调递减不同,对流层气溶胶消光系数垂直分布的一个明显特点是具有多层结构,如春季1.5-2 km、3 km处分别存在着浓度较大的气溶胶层,层内气溶胶消光系数变大,它反映了气溶胶浓度垂直分布结构的复杂性。
(4)利用SBDART模式模拟大气层顶辐亮度,用于计算得出气溶胶指数(AI),从而进行一些对比研究。研究发现,AI对气溶胶层高度极其敏感,与气溶胶高度几乎成线性关系,它对1-2 km,尤其是1 km的边界层气溶胶不敏感,随着气溶胶层高度的增加,AI也随着增加。除此之外,AI还对气溶胶单次散射反照率以及观测角度的变化较为敏感,随着观测角度的增加,AI随之减小,尤其是大于15°后,减小趋势较大。由于CALIOP探测器扫描宽度较窄,所以不是所有区域的气溶胶高度资料均能获取,在这种情况下,可以通过模拟获取所要研究区域的气溶胶高度信息。
Using ground-based Aerosol Optical Depth (AOD) data at Tazhong, Taklimakan Desert, four sets of satellite aerosol data, i.e., multi-angle imaging spectrometer (MISR), Moderate Resolution Imaging Spectrometer (MODIS) and the Ozone Monitoring Instrument (OMI) from 2007 to 2008 were validated. Besides, data from CALIOP are used to investigate the vertical distribution of aerosol. Result from radiative transfer model (SBDART) is also used to compare with OMI/UVAI for sensitivity experiment. The main contents of the study and their primary results are summarized as follows:
(1)The correlation coefficient for MODIS/AOD is the largest (0.91), followed by OMI/AOD (0.87), MISR/AOD (0.84) and OMI/UVAI (0.51). MISR/AOD root mean square error (0.14) and the average deviation (-0.06) are the lowest in the four products. MISR/AOD and MODIS/AOD is relatively less than the ground-based AOD, however, OMI/AOD and OMI/UVAI exceed the ground-based ones. Under the same conditions (ground-based AOD is limited to less than 2.0), the root mean square error and the standard deviation of MISR is the lowest. Seasonal variation of aerosol loading is captured by satellite data.
(2)Spring and summer AOD is relatively larger and AOD is relatively lower in the autumn and winter. The result of Angstrom exponent reflects that the spring has the minimum(0.11), followed by summer and autumn, and winter has the maximum(0.61), which shows that the aerosol particle is larger in spring and summer while it is smaller in autumn and winter. Besides, Taklimakan belongs to the sand source where aerosol type is single. So in summary, the annual variability tendency of AOD from 2000 to 2010 is not that obvious. The result of the retrieval shows that 2003 has the maximal aerosol contents during the decade, the annual average is up to 0.32, while 2005 has the minimal aerosol contents, the annual average is 0.28.
(3) The extinction coefficient decreases with increasing altitude, the atmosphere in the upper troposphere is more clean, and aerosols mainly concentrated in the middle and lower troposphere. The value of the vertical lapse rate in winter is minimum, this attributes to the weak convection resulted from the relative low inversion layer in winter. Tropospheric vertical distribution of aerosol extinction coefficient is characterized by a multi-layer structure which is different from Rayleigh scattering of air molecules that decreases monotonically with increasing height. Large concentration of aerosol exists at 1.5-2 km and 3 km respectively in spring, the aerosol extinction coefficient becomes larger, which reflects the complexity of aerosols' vertical structure.
(4)Aerosol Index calculated from SBDART is used for comparison research. The results show that AI is extremely sensitive to the aerosol layer height and they are of almost linear relationship. AI is not sensitive to the boundary layer at 1-2 km,1 km particularly and increases with the aerosol layer height. In addition AI is also very sensitive to the single scattering albedo. Research shows that AI is more sensitive to the change of observation angle, AI decreases with the increasing observation angle, especially when the angle is greater than 15°, the decreasing trend is larger. Because of the narrow scanning width of CALIOP, not all region have the information of aerosol height. So we can get aerosol height in certain areas by simulating experiment.
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