Near real time processing of ceilometer network data: characterizing an extraordinary dust outbreak over the Iberian Peninsula

Abstract. The interest on the use of ceilometers for optical aerosol characterization has increased in the last few years. They operate continuously almost unattended and are also much less expensive than lidars, hence they can be distributed in dense networks over large areas. However, due to the low signal-to-noise-ratio it is not always possible to obtain particle 20 backscatter coefficient profiles, and the vast amount of data generated requires an automated and unsupervised method that ensures the quality of the profiles inversions. In this work a method that uses aerosol optical depth (AOD) measurements from the AERONET network is applied for the calibration and automated quality assurance of inversion of ceilometer profiles. The method is compared with Independent inversions obtained by co-located multiwavelength lidar measurements and a difference up to 15% in backscatter is found 25 between both instruments. This method is continuously and automatically applied to the Iberian Ceilometer Network (ICENET) and a case example during an unusually intense dust outbreak affecting the Iberian Peninsula on 20 February 2016 and lasted until 24 February 2016 is shown. Results reveal that it is possible to obtain a quantitative optical Aerosol characterization (particle backscatter coefficient) with ceilometers over large areas and this information has a great potential for alert systems and model assimilation and evaluation