Are EARLINET and AERONET climatologies consistent? the case of Thessaloniki, Greece
Journal
Atmospheric Chemistry and Physics
Date Issued
August 21, 2018
DOI
10.5194/acp-18-11885-2018
Abstract
In this study we investigate the climatological behavior of the aerosol optical properties over Thessaloniki during the years 2003–2017. For this purpose, measurements of two independent instruments, a lidar and a sunphotometer, were used. These two instruments represent two individual networks, the European Lidar Aerosol Network (EARLINET) and the Aerosol Robotic Network (AERONET). They include different measurement schedules. Fourteen years of lidar and sunphotometer measurements were analyzed, independently of each other, in order to obtain the annual cycles and trends of various optical and geometrical aerosol properties in the boundary layer, in the free troposphere, and for the whole atmospheric column. The analysis resulted in consistent statistically significant and decreasing trends of aerosol optical depth (AOD) at 355 nm of ĝ'23.2 and ĝ'22.3 % per decade in the study period over Thessaloniki for the EARLINET and the AERONET datasets, respectively. Therefore, the analysis indicates that the EARLINET sampling schedule can be quite effective in producing data that can be applied to long-term climatological studies. It is also shown that the observed decreasing trend is mainly attributed to changes in the aerosol load inside the boundary layer. Seasonal profiles of the most dominant aerosol mixture types observed over Thessaloniki have been generated from the lidar data. The higher values of the vertically resolved extinction coefficient at 355 nm appear in summer, while the lower ones appear in winter. The dust component is more dominant in the free troposphere than in the boundary layer during summer. The biomass burning layers tend to arrive in the free troposphere during spring and summer. This kind of information can be quite useful for applications that require a priori aerosol profiles. For instance, they can be utilized in models that require aerosol climatological data as input, in the development of algorithms for satellite products, and also in passive remote-sensing techniques that require knowledge of the aerosol vertical distribution.