Aerosols affect the meteorological and climate system in many ways: by interacting with solar radiation, by acting as cloud condensation nuclei (CCN) and ice nuclei (IN), and by carrying nutrients to oligotrophic ecosystems. Moreover, they also have a large impact on human health by causing or enhancing respiratory, cardiovascular, infectious, and allergic diseases and can affect air transport, as happened during the spring of 2010, when the Eyjafjallajökull volcano eruption in Iceland caused an enormous disruption to air traffic across western and northern Europe.
The aerosols effects and importance depend on their characteristics, such as size, origin and composition. In particular, giant and ultragiant particles (>5 µm diameter) can act as Giant CCN (GCCN) and IN. As GCCN, they determine the concentration of the initial cloud droplets, the clouds albedo and lifetime, and the precipitation formation, expediting especially warm rain processes. As IN, they can be very efficient, as for example mineral dust.
Lidar and sun photometer are used nowadays in measuring aerosols. However, they do not allow to retrieve aerosol microphysical properties for particles bigger than a few microns. Thus, giant and ultragiant aerosols are passed undetected and their importance and effects are still not well known.
Recent studies have demonstrated that cloud radars are able to detect ultragiant volcanic aerosols also at a large distance from the source. Therefore, the aim of this study is to enhance the size range in which aerosol microphysical properties can be retrieved taking advantage of the synergistic use of lidar and radar. The combined information offers the possibility to retrieve aerosol microphysical properties from ultrafine to ultragiant size range.
This study has been carried out at the CNR-IMAA (Consiglio Nazionale delle Ricerche Istituto di Metodologie per l'Analisi Ambientale) Atmospheric Observatory (CIAO), located in Tito Scalo, Potenza, Southern Italy, on the Apennine mountains (40.60°N, 15.72°E, 760 m a.s.l.).
The main instruments used are a 35 GHz Ka-band Doppler radar and two multi-wavelength Raman lidars, along with ancillary instruments data.
The methodology consists of three parts.
First of all, we developed a new methodology to detect aerosols with the cloud radar. The non-hydrometeorological targets are classified into aerosols or insects based on various criteria defined according to entomology studies.
Following, simultaneous aerosol lidar measurements were searched for and analyzed. The retrieved extensive (backscatter and extinction) and intensive lidar optical parameters (i.e. Ångström exponent and lidar ratio) together with depolarization allow to characterize the observed aerosols. In order to test if these parameters are different when the cloud radar observes aerosols or insects, their mean and standard deviation were computed accordingly and compared.
Finally, we retrieve the aerosol size independently for each instrument, since different scatterers enhance the lidar and cloud radar signals. For the lidar measurements, we use Veselovskii's inversion code to retrieve the aerosol size distribution from the extensive optical properties. For the radar measurements, the particle effective radius is inferred using look-up tables built using Mishchenko's T-matrix scattering code for different particle sizes and types.
The application of the novel methodology that we developed to the cloud radar dataset of approximately 4.5 years resulted in 66 aerosol and 136 insect layers. Figure 1 shows their evolution throughout the year. Two aerosol peaks are observed during spring and summer and a minimum during winter, in accordance to climatological studies of the site. Most likely, the peak during spring is caused by pollen and dust and the one during summer by dust. Other statistics such as the diurnal evolution, the height and the layer thickness, the temperature and the wind speed were likewise retrieved for aerosol and insects.
The non-continuous lidar measurements at the site limited the collected sample to 26 cases of concurrent lidar observations. The radar detected aerosols in 12 of the cases and insects in 14. Despite the small differences shown for the backscatter signals, extinction and depolarization showed a different behavior. Figure 2 shows the extinction spectral dependence: it is much more pronounced in presence of aerosols. Besides, the particle depolarization values are much higher when aerosols are also observed by the cloud radar.
The retrieval of aerosol effective radius using the lidar and cloud radar measurements is currently ongoing. Initial outcomes of the lidar inversion point to aerosol size distributions within the accumulation and coarse modes, while the effective radius observed by the cloud radar lies between 10 and 40 µm.
In this study, we developed a novel methodology for the study of giant and ultragiant aerosols observation. Our findings show a good seasonal agreement with the site climatology as well as the observational capability of aerosols up to the tenths of microns. Furthermore, depending on the cloud radar detected target, different lidar aerosol properties are retrieved. This might be explained by the differences of aerosols shape and composition and the insects tendency to avoid flying in high aerosol load regions.
This methodology can be very useful to better understand the role and processes of giant particles in the atmosphere, as well as to monitor dust, pollen and volcanic intrusions in near-real time. Nevertheless, the number of cases available in this study is limited, and an enlargement of the dataset will be considered.
The financial support from the European Union 7th Framework Programme, under the ACTRIS Grant Agreement n. 262254 and the ITaRS Grant Agreement n. 289923, and from the national project "Programma Operativo Nazionale (PON) Regione Basilicata 2000/2006" is gratefully acknowledged.