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Different strategies to retrieve aerosol properties at night-time with the GRASP algorithm

机译:用掌握算法在夜间检索气溶胶特性的不同策略

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This study evaluates the potential of the GRASP algorithm (Generalized Retrieval of Aerosol and Surface Properties) to retrieve continuous day-to-night aerosol properties, both column-integrated and vertically resolved. The study is focused on the evaluation of GRASP retrievals during an intense Saharan dust event that occurred during the Sierra Nevada Lidar aerOsol Profiling Experiment?I (SLOPE?I) field campaign. For daytime aerosol retrievals, we combined the measurements of the ground-based lidar from EARLINET (European Aerosol Research Lidar Network) station and sun–sky photometer from AERONET (Aerosol Robotic Network), both instruments co-located in Granada (Spain). However, for night-time retrievals three different combinations of active and passive remote-sensing measurements are proposed. The first scheme?(N0) uses lidar night-time measurements in combination with the interpolation of sun–sky daytime measurements. The other two schemes combine lidar night-time measurements with night-time aerosol optical depth obtained by lunar photometry either using intensive properties of the aerosol retrieved during sun–sky daytime measurements?(N1) or using the Moon aureole radiance obtained by sky camera images?(N2). Evaluations of the columnar aerosol properties retrieved by GRASP are done versus standard AERONET retrievals. The coherence of day-to-night evolutions of the different aerosol properties retrieved by GRASP is also studied. The extinction coefficient vertical profiles retrieved by GRASP are compared with the profiles calculated by the Raman technique at night-time with differences below 30% for all schemes at?355, 532?and 1064nm. Finally, the volume concentration and scattering coefficient retrieved by GRASP at 2500ma.s.l.?are evaluated by in situ measurements at this height at Sierra Nevada Station. The differences between GRASP and in situ measurements are similar for the different schemes, with differences below 30% for both volume concentration and scattering coefficient. In general, for the scattering coefficient, the GRASP?N0 and?N1 show better results than the GRASP?N2 schemes, while for volume concentration, GRASP N2 shows the lowest differences against in situ measurements (around 10%) for high aerosol optical depth values.
机译:本研究评估了掌握算法(广义检索气溶胶和表面性质)的潜力,以检索连续的日夜气溶胶特性,两者集成和垂直解决。该研究专注于在塞拉尼亚岛激光乐气溶胶分析实验期间发生的激烈的撒哈拉尘埃事件期间对掌握检索的评估?I(斜坡?i)场运动。对于白天气溶胶检索,我们将基于射击赛(欧洲气溶胶研究Lidar Network)的地面LIDAR的测量结果与AeroNet(气溶胶机器人网络),包括在格拉纳达(西班牙)的仪器(西班牙)。然而,对于夜间检索,提出了三种不同的主动和被动遥感测量的不同组合。第一个方案?(N0)使用LIDAR夜间测量与Sun-Sky日间测量的插值结合使用。另外两种方案将LIDAR夜间测量结合在夜间光度测量中,使用了在阳光天空日测量期间检索到的气溶胶的密集特性,或者使用天空相机图像获得的月亮阳光辐射的夜间光度测量。(n1) ?(n2)。通过掌握检索的柱状气溶胶特性的评估与标准的机动机构检索进行了完成。还研究了通过掌握检索的不同气溶胶特性的日常夜间演进的连贯性。通过掌握检索的消光系数垂直轮廓与拉曼技术在夜间计算的曲线进行比较,夜间在Δ355,532的所有方案的差异低于30%?和1064nm。最后,通过在Sierra Nevada站在这个高度的原位测量中掌握在2500ma.L.的体积浓度和散射系数。掌握和原位测量之间的差异类似于不同方案,差异低于体积浓度和散射系数的差异。通常,对于散射系数,掌握φn0和Δn1显示比掌握Δn2方案的更好的结果,而对于体积浓度,掌握N2显示出对高气溶胶光学深度的原位测量(约10%)的最低差异价值观。
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