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A method for random uncertainties validation and probing the natural variability with application to TROPOMI/Sentinel5P total ozone measurements
Atmospheric Measurement Techniques ( IF 3.2 ) Pub Date : 2020-10-28 , DOI: 10.5194/amt-2020-402
Viktoria F. Sofieva , Hei Shing Lee , Johanna Tamminen , Christophe Lerot , Fabian Romahn , Diego G. Loyola

Abstract. In this paper, we discuss the method for validation of random uncertainties in the remote sensing measurements based on evaluation of the structure function, i.e., root-mean-square differences as a function of increasing spatio-temporal separation of the measurements. The limit at the zero mismatch provides the experimental estimate of random noise in the data. At the same time, this method allows probing the natural variability of the measured parameter. As an illustration, we applied this method to the clear-sky total ozone measurements by TROPOMI/Sentinel-5P. We found that the random uncertainties reported by the TROPOMI inversion algorithm, which are in the range 1–2 DU, agree well with the experimental uncertainty estimated by the structure function. Our analysis of the structure function has shown the expected results on total ozone variability: it is significantly smaller in the tropics compared to mid-latitudes. At mid-latitudes, ozone variability is much larger in winter than in summer. The ozone structure function is anisotropic (being larger in latitudinal direction) at horizontal scales larger than 10–20 km. The structure function rapidly grows with the separation distance. At mid-latitudes in winter, the ozone values can differ by 5 % at separations 300–500 km. The discussed method is a powerful tool in experimental estimates of the random noise in data and studies of natural variability and it can be used in various applications.

中文翻译:

一种用于TROPOMI / Sentinel5P总臭氧测量的随机不确定性验证和探测自然变异性的方法

摘要。在本文中,我们讨论了基于结构函数评估(即,均方根差作为增加测量时空分离的函数)评估遥感测量中随机不确定性的方法。零失配时的极限值提供了数据中随机噪声的实验估计。同时,这种方法可以探测被测参数的自然变化。作为说明,我们将此方法应用于TROPOMI / Sentinel-5P在晴空总臭氧测量中的应用。我们发现TROPOMI反演算法报告的随机不确定性在1-2 DU范围内,与结构函数估计的实验不确定性非常吻合。我们对结构函数的分析已显示出臭氧总变化率的预期结果:与中纬度地区相比,热带地区的臭氧变化率要小得多。在中纬度地区,冬季的臭氧变异性比夏季大得多。臭氧结构函数在大于10–20 km的水平尺度上是各向异性的(在纬度方向上更大)。结构功能随着分离距离的增长而迅速增长。在冬季的中纬度,相距300-500公里,臭氧值可能相差5%。所讨论的方法是在实验中估计数据中的随机噪声和研究自然变异性的有力工具,可以用于各种应用中。臭氧结构函数在大于10–20 km的水平尺度上是各向异性的(在纬度方向上更大)。结构功能随着分离距离的增长而迅速增长。在冬季的中纬度,相距300-500公里,臭氧值可能相差5%。所讨论的方法是在实验中估计数据中的随机噪声和研究自然变异性的有力工具,可用于各种应用中。臭氧结构函数在大于10–20 km的水平尺度上是各向异性的(在纬度方向上更大)。结构功能随着分离距离的增长而迅速增长。在冬季的中纬度,相距300-500公里,臭氧值可能相差5%。所讨论的方法是在实验中估计数据中的随机噪声和研究自然变异性的有力工具,可用于各种应用中。
更新日期:2020-10-30
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