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Tropospheric carbon monoxide variability from AIRS under clear and cloudy conditions

机译:在晴朗和多云的条件下,来自AIRS的对流层一氧化碳变异性

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We study the carbon monoxide (CO) variability in the last decade measured by NASA's Atmospheric InfraRed Sounder (AIRS) on the Earth Observing System (EOS)/Aqua satellite. The focus of this study is to analyze CO variability and short-term trends separately for background CO and fresh CO emissions based on a new statistical approach. The AIRS Level 2 (L2) retrieval algorithm utilizes cloud clearing to treat cloud contaminations in the signals, and this increases the data coverage significantly to a yield of more than 50% of the total measurements. We first study if the cloud clearing affects CO retrievals and the subsequent trend studies by using the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask to identify AIRS clear sky scenes. We then carry out a science analysis using AIRS CO data individually for the clear and cloud-cleared scenes to identify any potential effects due to cloud clearing. We also introduce a new technique to separate background and recently emitted CO observations, which aims to constrain emissions using only satellite CO data.We validate the CO variability of the recent emissions estimated from AIRS against other emission inventory databases (i.e., Global Fire Emissions Database - GFED3 and the MACC/CityZEN UE - MACCity) and calculate that the correlation coefficients between the AIRS CO recently emitted and the emission inventory databases are 0.726 for the Northern Hemisphere (NH) and 0.915 for the Southern Hemisphere (SH). The high degree of agreement between emissions identified using only AIRS CO and independent inventory sources demonstrates the validity of this approach to separate recent emissions from the background CO using one satellite data set.
机译:我们研究了近十年来由地球观测系统(EOS)/ Aqua卫星上的NASA大气红外探测仪(AIRS)测量的一氧化碳(CO)变异性。这项研究的重点是基于一种新的统计方法,分别分析背景CO和新鲜CO排放的CO变异性和短期趋势。 AIRS 2级(L2)检索算法利用云清除技术来处理信号中的云污染,这大大提高了数据覆盖率,其收率超过了总测量值的50%。我们首先通过使用并置的中等分辨率成像光谱仪(MODIS)云遮罩来识别AIRS晴朗的天空场景,来研究云清除是否会影响CO的获取以及随后的趋势研究。然后,我们使用AIRS CO数据分别对晴朗和多云的场景进行科学分析,以识别由于多云清除而产生的任何潜在影响。我们还引入了一种新技术来分离背景和最近发射的CO观测值,其目的是仅使用卫星CO数据来限制排放。我们对照其他排放清单数据库(例如,全球火灾排放数据库)验证了AIRS估算的最近排放的CO变异性-GFED3和MACC / CityZEN UE-MACCity),并计算出最近排放的AIRS CO与排放清单数据库之间的相关系数对于北半球(NH)为0.726,对于南半球(SH)为0.915。仅使用AIRS CO识别的排放量与独立清单资源之间的高度一致性证明了这种方法的有效性,即使用一个卫星数据集将最新排放量与背景CO分离。

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