Profiling aerosol optical, microphysical and hygroscopic properties in ambient conditions by combining in situ and remote sensing
Profiling aerosol optical, microphysical and hygroscopic properties in ambient conditions by combining in situ and remote sensing
复制标题
DOI：
10.5194/amt-10-83-2017
复制
发表时间：
2016-07
影响因子：
3.8
通讯作者：
A. Tsekeri;V. Amiridis;F. Marenco;A. Nenes;E. Marinou;S. Solomos;P. Rosenberg;J. Trembath;G. Nott;J. Allan;M. Breton;A. Bacak;H. Coe;C. Percival;N. Mihalopoulos
中科院分区：
文献类型：
--
作者：
A. Tsekeri;V. Amiridis;F. Marenco;A. Nenes;E. Marinou;S. Solomos;P. Rosenberg;J. Trembath;G. Nott;J. Allan;M. Breton;A. Bacak;H. Coe;C. Percival;N. Mihalopoulos
抽象的。我们提出了原位/遥感气溶胶反演算法（IRRA），结合机载原位和激光雷达遥感数据检索环境气溶胶光学，微物理和吸湿特性的垂直剖面，采用ISORROPIA II模型获取颗粒吸湿增长。在这里，我们应用的算法从空中大气测量设施（FAAM）的BAe-146研究飞机在东地中海的ACEMED活动期间收集的数据。对塞萨洛尼基市附近的一个老烟羽成功地导出了气溶胶微物理特性的垂直廓线，该烟羽在532 nm处的气溶胶光学厚度为0.4，在550 nm处的单次散射比为0.9-0.95，在532 nm处烟的典型激光雷达比为0.60 -80 sr。IRRA在陆地上方回收高度水合的颗粒，对于80%和90%的环境相对湿度，水体积含量分别为55%和80%。所提出的方法是非常有利的气溶胶特性在潮湿的条件下，可以找到有价值的应用气溶胶-云相互作用计划。此外，它还可用于验证有源星载传感器，如这里对CALIPSO的情况所示。
Abstract. We present the In situ/Remote sensing aerosol Retrieval Algorithm (IRRA) that combines airborne in situ and lidar remote sensing data to retrieve vertical profiles of ambient aerosol optical, microphysical and hygroscopic properties, employing the ISORROPIA II model for acquiring the particle hygroscopic growth. Here we apply the algorithm on data collected from the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft during the ACEMED campaign in the Eastern Mediterranean. Vertical profiles of aerosol microphysical properties have been derived successfully for an aged smoke plume near the city of Thessaloniki with aerosol optical depth of ∼ 0.4 at 532 nm, single scattering albedos of ∼ 0.9–0.95 at 550 nm and typical lidar ratios for smoke of ∼ 60–80 sr at 532 nm. IRRA retrieves highly hydrated particles above land, with 55 and 80 % water volume content for ambient relative humidity of 80 and 90 %, respectively. The proposed methodology is highly advantageous for aerosol characterization in humid conditions and can find valuable applications in aerosol–cloud interaction schemes. Moreover, it can be used for the validation of active space-borne sensors, as is demonstrated here for the case of CALIPSO.