Aerosol retrieval experiments in the ESA Aerosol_cci project
Aerosol retrieval experiments in the ESA Aerosol_cci project
复制标题
DOI：
10.5194/amt-6-1919-2013
复制
发表时间：
2013-08
影响因子：
3.8
通讯作者：
T. Holzer-Popp;G. Leeuw;J. Griesfeller;D. Martynenko;L. Klüser;S. Bevan;W. Davies;F. Ducos;
中科院分区：
文献类型：
--
作者：
T. Holzer-Popp;G. Leeuw;J. Griesfeller;D. Martynenko;L. Klüser;S. Bevan;W. Davies;F. Ducos;
抽象的。在欧空局气候变化举措项目Aerosol_cci（2010-2013年）内，开发了从欧洲地球观测传感器生成长期气溶胶总柱光学厚度数据集的算法。从八个现有的前体算法开始，进行三个分析步骤来改进和鉴定算法：（1）应用于一个月的全球数据的一系列实验，以理解由于潜在反演问题的不适定性质而需要的对假设的几个主要敏感性，（2）这些算法中的每一个的“最佳”版本的循环练习（使用步骤1结果定义）应用于四个月的全球数据，以识别成熟的算法，以及（3）应用于由基于循环试验选择为成熟的算法产生的一整年的全球数据的综合验证试验。测试的算法包括四个使用AATSR，三个使用MERIS和一个使用PARASOL。本文总结了第一步。进行了三个实验，以评估各种气溶胶反演算法的主要假设的潜在影响。在第一个实验中，一组共同的四个气溶胶成分被用来提供所有的算法相同的假设。第二个实验介绍了气溶胶特性气候学，来自模型和太阳光度计观测相结合，作为先验信息的检索出现的共同气溶胶成分。第三个实验评估了使用AATSR和MERIS算法的共同最低点云掩模的影响，以表征对基线数据集版本检索中剩余云污染的敏感性。算法变化的影响进行了评估一个月（2008年9月）的数据：定性检查每月平均气溶胶光学厚度图和定量比较每日网格化的卫星数据对每日平均AERONET太阳光度计观测的每种算法的不同版本的全球（陆地和沿海）和三个地区不同的气溶胶制度。该分析允许对所有算法的敏感性进行评估，这有助于为随后的循环试验确定最佳算法版本;所有算法（MERIS除外）都显示出一些部分显著的改进。特别是，使用共同的气溶胶成分和部分先验气溶胶型气候学是有益的。另一方面，使用基于AATSR的通用云掩模意味着MERIS标准产品的明显改进（尽管覆盖范围显著减少），但对使用AATSR的算法没有改进。值得注意的是，所有五项分析（全球陆地、全球沿海、三个区域）的所有这些观测结果基本一致，这一点可以很好地理解，因为第3.1节中定义的一套气溶胶成分明确旨在涵盖不同的全球气溶胶体系（低吸收和高吸收精细模式、海盐和尘埃）。
Abstract. Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010–2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust).