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Discussion papers | Copyright
https://doi.org/10.5194/amt-2018-79
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 05 Apr 2018

Research article | 05 Apr 2018

Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Atmospheric Measurement Techniques (AMT) and is expected to appear here in due course.

A multi-wavelength numerical model in support to quantitative retrievals of aerosol properties from automated-lidar-ceilometers and test applications for AOT and PM10 estimation

Davide Dionisi1, Francesca Barnaba1, Henri Diémoz2, Luca Di Liberto1, and Gian Paolo Gobbi1 Davide Dionisi et al.
  • 1Istituto di Scienze dell’Atmosfera e del Clima, Consiglio Nazionale delle Ricerche (ISAC-CNR), Roma, Italy
  • 2Aosta Valley Regional Environmental Protection Agency (ARPA Valle d'Aosta ), Saint-Christophe (Aosta), Italy

Abstract. Knowledge of the height-distribution of aerosol particles is a key factor in the study of climate, air pollution, and meteorological processes. The use of automated lidar-ceilometers (ALC) for the aerosol vertically-resolved characterization has increased in the recent years thanks to their low construction and operation costs, and to their capability in providing continuous, unattended measurements. The quantitative assessment of the aerosol properties from ALC measurements and the relevant assimilation in meteorological forecast models is amongst the main objectives of the EU COST Action TOPROF (Towards Operational ground-based PROFiling with ALCs, doppler lidars and microwave radiometers). Concurrently, the E-PROFILE program of the European Meteorological Services Network (EUMETNET) focuses on the harmonization of ALC measurements and data provision across Europe. Within these frameworks, we implemented a methodology to retrieve key aerosol properties (extinction coefficient, surface area and volume) from lidar and/or ALC measurements. The method is based on results from a large set of aerosol scattering simulations (Mie-theory) performed at UV, visible and near IR wavelengths using a Monte-Carlo approach to select the input aerosol microphysical properties. A continental aerosol type is addressed in this study. Based on the model results, we derived mean functional relationships linking the aerosol backscatter coefficients and the above-mentioned variables. Applied in the data inversion of single wavelength lidars/ALCs, these relationships allow quantitative determination of the vertically-resolved aerosols backscatter, extinction, volume and surface area, and in turn of the extinction-to-backscatter ratio (i.e., the lidar-ratio, LR) and of extinction-to-volume conversion factor (cv) at 355, 532, 1064nm. These variables provide valuable information for visibility, radiative transfer and air quality applications. This study also includes validation of the model results with real measurements, and test applications of the proposed model-based ALC inversion methodology. In particular, our model simulations were compared to backscatter and extinction coefficients retrieved by Raman lidar systems at different continental sites in Europe operating within the European Aerosol Research LIdar NETwork (EARLINET). This comparison showed good model-measurements agreement, with LR discrepancies below 20%. The model-assisted retrieval of both aerosol extinction and volume was then tested using raw data from three different ALCs systems (CHM15k-Nimbus), operating within the Italian Automated Lidar-ceilometer Network (ALICENET). To this purpose, a one-year-record of the ALCs-derived aerosol optical thickness (AOT) at each site was compared to direct AOT measurements performed by co-located sun-sky photometers. This comparison resulted into an overall AOT agreement within 30% at all sites. At one site, the model-assisted ALC estimation of the aerosol volume and mass (i.e., PM10) in the lowermost 75m was compared to values measured at the surface-level by co-located in situ instrumentation. This comparison showed rather good agreement too. In particular, the ALC-derived daily-mean mass concentration was found to well reproduce corresponding PM10 values measured by the local Air Quality agency in terms of both temporal variability and absolute values (mean relative difference around 15%). The good performances of the proposed approach in these preliminary tests suggest it could possibly represent a valid option to extend the capabilities of ALCs at providing quantitative information for operational air quality and meteorological monitoring.

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