DT算法(暗像元法)在C6.1中的改进：Aerosol Dark Target (10km 3km) Collection 6.1 Changes

DT算法(暗像元法)在C6.1中的改进：

仅适用于陆地：如果10x10km网格中有50%以上的沿海像素或20%以上的水像素，则将反演质量降为零
仅适用于陆地：修正的陆地表面气溶胶反演算法，当城市百分比大于20%时，使用修正的地表特征描述（using a revised surface characterization）( Gupta et al. 2016)。MODIS土地覆盖类型数据集用于识别城市像素，使用MYD09光谱地表反射率产品获得城市区域的面积比。

摘要:在这项研究中，我们解决了由MODIS暗目标算法气溶胶光学厚度(AOD)在城市地区反演产生的不准确性，并通过修改算法中的地表反射率方案（surface reflectance scheme）提出了改进建议。通过将MODIS陆地地表反射率（Land Surface Reflectance）和陆地覆盖类型（ Land Cover Type）信息集成到城市地区气溶胶地表参数化方案（aerosol surface parameterization scheme）中，与标准算法相关的许多问题已经在我们的试验区域美国大陆(CONUS)得到缓解。

新的地表方案（surface scheme）考虑了下垫面类型的变化，仅适用于城市百分比（UP）大于20%的中分辨率成像光谱仪像素（MODIS pixels）。在应用了新方案的城市地区(UP> 20%)，在预期误差范围内的AOD反演次数增加了20%，消除了对地面太阳测光的强烈正偏差（the strong positive bias against ground-based sun photometry has been eliminated）。
然而，我们注意到，由于AOD反演对低大气气溶胶载荷下的地表参数（surface parameterization）的超敏感性，新反演对小于0.1的AOD值引入了小的负偏差。

我们在全球范围内应用并测试了这种方法，发现新的城市地表参数化能够纠正城市地区的AOD偏差。通过对新开发的全球区域方案以及MODIS高分辨率(3公里)气溶胶产品的更多研究和优化，这一点可以得到进一步改善。

C6 (a)、C6U(b)(顶部面板)检索到的0.55微米处的MODIS AOD 季节性(2011年3月-4月-5月)地图。QAF=3的三个月的MODIS AOD在0.1*0.1度网格上做平均生成这些地图。与C6气溶胶光学厚度相比，大城市气溶胶光学厚度的反演值较低，其改善与UP密切相关。

图1图2 使用QAF=3的所有并置数据集（collocated data sets），与AERONET AOD相比，MODIS气溶胶光学厚度中的面元偏差（Binned bias）是UP的函数。该分析使用了2003年1月至2013年6月期间全球(不包括美国本土地区)AERONET的数据。MODIS C6反演在左边，MODIS C6U反演在右边。每个箱（bin）代表100个点，误差线（error bars）在两个方向上为±1个标准偏差。本图比较了302个站的50948个MODIS-AERONET数据对。C6 AODs在城市化土地表面（urbanized land surfaces）的偏差增加，而C6U能够校正QAF=3的数据点所在区域的偏差。

以下是原文：

10 km Dark Target（MOD04_L2， MY D04_L2）

a bug fix was implemented, which created problems running the code on Centos. To fix this run -time issue, a few redundant subroutines were taken out
For Ocean only:Added reflectance, standard deviation, aerosol cloud fraction, and number of pixels for retrievals when optical depth is zero or very small. All earlier PGE04 Versions
（Collections) reported only optical depth in these cases
For Ocean only Modified the sediment mask to make it more robust
For Land only:Degraded the quality of retrievals to zero if there are more than 50% coastal pixels or 20%of water pixels in 10x10 km grid
For Land only: Modified algorithm for Aerosol retrieval over land surface when urban percentage is larger than 20% using a revised surface characterization( Gupta et al. 2016). MODIS land cover type data set is used to identify urban pixels. The revised surface ratios for urban regions were created using MYD09 spectral surface reflectance product

3 km Dark Target（MOD04 3K, MYDO4 3K)

a bug fix was implemented which created problems to run code on Centos. Few redundant subroutines were taken out.
For Ocean only:Added reflectance, standard deviati osol cloud fraction and number of pixels for retrievals when optical depth is zero or very small. All earlier PGE04 Versions（Collections） reported only optical depth in these cases.
For Ocean only:Modified the sediment mask to make it more robust.
For Land only:Degraded the quality of retrievals to zero if there are more than 50% coastal pixels or 20% of water pixels in 10x10 km grid or Land only:Modified algorithm for Aerosol retrieval over land surface when urban percentage is larger than 20% using a revised surface characterization （Gupta et al. 2016).

Summary :
In this study we address the inaccuracies produced by the MODIS dark target（MDT）algorithm aerosol optical depth（AOD）retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm.
By integrating MODIS Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas much of the issues associated with the standard algorithm have been mitigated for our test region the continental United States（CONUS）.

The new surface scheme takes to account the change in underlying surface type and is only applied for MODIS pixels with urban percentage（UP）larger than 20%.
Over the urban areas where the new scheme has been applied（UP>20%），the number of AOD retrievals falling within expected error（EE %）has increased by 20%，and the strong positive bias against ground-based sun photometry has been eliminated.
However we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings.

We have applied and tested this approach over global regions and found that the new urban surface parameterization is able to correct AOD biases over urban areas. This can be further improved with more research and optimization of the newly developed scheme for global region as well as for MODIS high-resolution（3km）aerosol product.

Seasonal（March-April-May, 2011 ）maps of MODIS AOD at 0.55 μm as retrieved by C6 （a）， c6u（b）（top panels）. MODIS AODs with QAF=3 for three months have been averaged over 0.1*0.1 degree grids to generate these maps. C6UMDT retrieved AODs are lower over large cities as compared to C6 AODs and the improvements are well correlated with UP.

Figure 1. Figure 2. Binned bias in MODIS AODs compared to AERONET AODs as a function of UP using all collocated data sets with QAF=3. This analysis used data from global（excluding CONUS region）AERONET network for the period of January 2003-June 2013.

MODIS C6 retrievals are on the left and MODIS C6U retrievals are on the right.
Each bin represents 100 points and the error bars are ±1 standard deviation in both directions.
There are a total of 50 948 MODIS-AERONET collocated points from 302 stations compared in this plot.

C6 AODs show increased in bias over urbanized land surfaces whereas C6U is able to correct the bias over the region for QAF=3 data points.

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