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首页> 外文期刊>Atmospheric Measurement Techniques >Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project
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Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project

机译:改进卫星No2检索的算法和不确定性估计:结果来自基本气候变量(QA4ECV)项目的质量保证

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摘要

Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities at the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information on how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best-practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2, a 1 degrees x 1 degrees TM5-MP data assimilation scheme to estimate the stratospheric background and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm to the most current level-1 data sets to produce a complete 22-year data record that includes GOME (1995-2003), SCIAMACHY (2002-2012), GOME-2(A) (2007 on-wards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40% over polluted scenes. The first validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai'an, China, in June 2006 suggest a small bias (-2 %) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale.
机译:全球对流层氮二氧化氮(NO2)柱的观察从空间中被证明是可行的,但尚未存在一致的多传感器记录,也不存在于国际一级的计划活动。协调的NO2列和他们相关的不确定性的多数截止纪录,可以提供关于如何随时间演变的排放和浓度发展的关键信息。在这里,我们描述了基于现有方法的合成的新的社区最佳实践No2检索算法的开发。这些方法的详细比较LED我们实现了NO2的增强频谱拟合方法,1度x 1度TM5-MP数据同化方案,以估计平流层背景并改善空气质量因子计算。通过数据用户,生产者和WMO GCOS指南表达的需求,我们在数据产品中纳入了详细的每个像素不确定性信息,以及有关检索相关质量方面的容易可追溯的信息。我们将改进的QA4ECV No2算法应用于最新的Level-1数据集,以产生包括Gome(1995-2003),Sciamachy(2002-2012),Gome-2(A)(2007年)的完整22年数据记录-Wards)和OMI(2004年)。 QA4ECV No2光谱配件推荐和TM5-MP平流层柱和空气质量因子方法目前也适用于S5P-Tropomi。 QA4ECV对流层NO2列中的不确定性通常在污染场景中的额定数量为40%。 QA4ECV OMI NO2列的第一个验证结果及其在2006年6月对泰安的不确定性建议偏见(-2%)和更好的精确度,而不是由于不确定性繁殖所建议。我们得出结论,我们改进的QA4ECV No2长期数据记录正在提供有价值的信息,以定量地限制在全球范围内氮氧化物中的排放,沉积和趋势。

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