一种反演气溶胶光学厚度的改进方法

摘要

The algorithm to retrieve the aerosol optical depth over land has been completely restructured to produce the collection 005 products based on the algorithm by Levy et al. But the accuracy of the MODIS aerosol optical depth (AOD) products still has very large differences for different seasons and geographic locations in China. In order to improve the accuracy of aerosol retrieval products, an easier and faster algorithm for retrieval of aerosol optical depth over land with MODIS IB data is introduced. This algorithm deals with the surface reflectance relationships is the same way as MODIS V5. 2 algorithm. In order to better represent aerosol properties in China, the size distribution and refractive index of aerosol have been improved. Considering the fine structure of the aerosol size distribution has a little effect on satellite remote sensing of aerosol optical depth, this algorithm use the Junge aerosol size distribution to approximate the aerosol size distribution in an actual atmosphere. The real and imaginary index of refractive is 1. 5 and 0. 005, respectively. The complex refractive index is assumed for all wavelengths(0. 47,0. 55,0. 66 ^m and 2. 1 fjLm).In order to verify the accuracy and regional applicability of this algorithm, aerosol optical depth is derived with this algorithm using the MODIS IB data at Taihu and Xianghe, and this retrieval result is compared with equivalent measurements from AERONET (Aerosol Robotic NETwork) site (Level 2. 0 data). The MODIS/AOD product and IB data from September 2006 to June 2008 at Taihu (MODISI/AOD product and IB data from May 2008 to July 2009 at Xianghe) has been matched with L2. 0 AOD product from AERONET stations during the same period. Data from the AERONET are averaged within 30 min before and after the satellite's passing, and the MODIS data are averaged over a 10 km (15 km at Xianghe) area centered at the ground stations.The comparison results show that the standard deviation of the new algorithm inversion results and L2. 0 AOD product at Taihu is 0. 429. The standard deviation of the MODIS/AOD product and L2. 0 AOD product at Taihu is 0. 693. Accordingly, the standard deviations of two comparison experiment at Xianghe are 0. 493 and 0. 542, respectively. These results show that this algorithm retrieval results have good consistency with the sun photometer observational results at Taihu and Xianghe. The retrieval algorithm is more accurate than the current MODIS aerosol algorithm and its inversion results are reasonable. In addition, the settings for aerosol model and optical properties are simple and convenient in the new algorithm, which can effectively reduce the computational time for looking-up table and the iteration time for solving equations.%该文提出了一种简单快速反演气溶胶光学厚度的方法,该算法对地表反照率的处理与MODlS V5.2算法相同,但气溶胶谱分布假定为Junge谱,设置了新的气溶胶参数.应用2006年9月6日-2008年6月10日太湖MODIS观测资料和2008年5月20日-2009年7月6日香河MODIS观测资料进行反演,并将反演结果与AERONET(AErosol RObotic NETwork)站点资料进行对比,以检验算法的适用性和精度.对比结果显示:该算法在太湖的反演结果与AERONET太湖站反演结果对比的标准偏差为0.429,而MODIS卫星AOD产品与AERONET太湖站反演结果对比的标准偏差为0.693;相应在香河的两种反演结果与地面观测对比的标准偏差分别为0.493和0.542.该算法的反演误差小于MODIS现行算法,反演结果合理,具有较好的适用性,说明这种方法在这两个区域具有更高的反演精度.