比较ALADIN/Aeolus和CALIOP/CALIPSO观测反演的散射比产品:灵敏度、可比性和时间演变

A. Feofilov, H. Chepfer, V. Noel, R. Guzman, Cyprien Gindre, M. Chiriaco
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引用次数: 1

摘要

摘要自2006年CALIPSO(云-气溶胶激光雷达和红外探路者卫星观测)发射以来,星载主动探测器为大气光学特性提供了宝贵的垂直分辨率信息。为了确保气候研究和全球变化监测的连续性,必须了解不同波长、不同轨道、不同观测几何形状、接收路径和探测器之间的差异。在本文中,我们展示了ALADIN (Atmospheric Laser Doppler INstrument)和CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization)激光雷达在2019年6月28日至2019年12月31日期间散射比(SR)产品的对比研究结果。我们提出了一组最优的搭配标准(Δdist < 1º;Δtime < 6 h),这将给出一组具有代表性的并置配置文件,我们表明,对于这样一对仪器,与上述标准并置的数据理论上可实现的云检测一致性为0.77±0.17。对由约78000对夜间SR剖面组成的并置数据库的分析表明:(a)在无云区域,两种仪器的一致性较好,表明假阳性云检测的频率较低;(b)低层云检测一致性较好。在~7 km以上,ALADIN产品的灵敏度较低,因为355nm处的后向散射较低,信噪比较低;(c)当ALADIN报告了CALIOP未检测到的低云时,在50%的分析案例中,中层云阻碍了观测并干扰了ALADIN的检索,这表明需要对此类情景进行质量标志优化;(d)对低空云的高度敏感导致ALADIN的云峰向下倾斜~0.5±0.4 km,但这种影响并未改变极地平流层云峰高度;(e)在考虑的时间段内,云一致性质量的时间演变没有显示出任何异常,这表明ALADIN的热像元和激光退化效应至少已经减轻到以下云检测一致性值的不确定性:分别为61±16%、34±18%、24±10%、26±10%和22±12%,分别为0.75 km、2.25 km、6.75 km、8.75 km和10.25 km。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparing scattering ratio products retrieved from ALADIN/Aeolus and CALIOP/CALIPSO observations: sensitivity, comparability, and temporal evolution
Abstract. The spaceborne active sounders have been contributing invaluable vertically resolved information of atmospheric optical properties since the launch of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) in 2006. To ensure the continuity of climate studies and monitoring the global changes, one has to understand the differences between lidars operating at different wavelengths, flying at different orbits, and utilizing different observation geometries, receiving paths, and detectors. In this article, we show the results of an intercomparison study of ALADIN (Atmospheric Laser Doppler INstrument) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidars using their scattering ratio (SR) products for the period of 28/06/2019−31/12/2019. We suggest an optimal set of collocation criteria (Δdist < 1º; Δtime < 6 h), which would give a representative set of collocated profiles and we show that for such a pair of instruments the theoretically achievable cloud detection agreement for the data collocated with aforementioned criteria is 0.77 ± 0.17. The analysis of a collocated database consisting of ~78000 pairs of collocated nighttime SR profiles revealed the following: (a) in the cloud-free area, the agreement is good indicating low frequency of false positive cloud detections by both instruments; (b) the cloud detection agreement is better for the lower layers. Above ~7 km, the ALADIN product demonstrates lower sensitivity because of lower backscatter at 355 nm and because of lower signal-to-noise ratio; (c) in 50 % of the analyzed cases when ALADIN reported a low cloud not detected by CALIOP, the middle level cloud hindered the observations and perturbed the ALADIN’s retrieval indicating the need for quality flag refining for such scenarios; (d) large sensitivity to lower clouds leads to skewing the ALADIN’s cloud peaks down by ~0.5 ± 0.4 km, but this effect does not alter the polar stratospheric cloud peak heights; (e) temporal evolution of cloud agreement quality does not reveal any anomaly for the considered period, indicating that hot pixels and laser degradation effects in ALADIN have been mitigated at least down to the uncertainties in the following cloud detection agreement values: 61 ± 16 %, 34 ± 18 % 24 ± 10 %, 26 ± 10 %, and 22 ± 12 % at 0.75 km, 2.25 km, 6.75 km, 8.75 km, and 10.25 km, respectively.
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