QA4EO NATALI is a project funded by the European Space Agency (ESA) in the frame of the Romanian Industry Incentive Scheme and the ESA/SPPA QA4EO activities -https://earth.esa.int/web/sppa/activities. The contract started on 1st of March 2014 and ends on 30th of September 2016.
Observations are fundamental to improve atmospheric models by advancing process understanding, evaluating model performance, and improving initial conditions via data assimilation. Today the most advanced observations of the atmosphere are achieved by remote-sensing instrumentation.
Aerosols, the small particles of various origins present in the atmosphere, can influence the microphysical and macro-physical properties of clouds and hence impact the energy balance, precipitation and the hydrological cycle (indirect aerosol effects).
The largest radiative contribution comes from aerosols with radii in the range 0.1 –1 µm (Satheesh S.K. et al., 2005). Aerosols have different scattering and absorption properties depending on their origin, and it is important to identify them in order to better quantify their radiative impact.
In particular lidars (optical active remote sensing instruments) are used to characterize aerosols and clouds.
Depending on the complexity of the system, a number of optical parameters (extensive and intensive) can be retrieved for the aerosol layers: aerosol optical depth, particle depolarization ratio, Angstrom exponent, color indexes and color ratios, lidar ratios. Comparing these values with the typical ones, the type of particles can be estimated. Lidars are nevertheless limited in terms of sounding wavelengths and dynamic range. For a full characterization of the aerosol distribution, lidar data have to be complemented by in situ (more physical information content) and integrated column (more spatial information content). This increases the level of confidence in the aerosol typing decisions and/or validates the lidar retrievals.
AERONET-Aerosol Robotic Network
is a global network of sun/sky radiometers that is monitoring AOD (Aerosol Optical Depth) and aerosol optical properties for AOD trend analysis, optical properties characterization, and for validation of satellite retrievals (Dubovik O et.al 2002). Dubovik O. et al. (2000) ascertain aerosol features from extensively measured solar transmission and sky radiation (in AERONET), but results of such passive measurements are averaged over the entire atmospheric column and cannot provide information regarding the vertical distribution of particles.
An important advance in the remote sensing of aerosols is the development of continental-scale ground based lidar networks, which provide quality assured optical profiles on a large temporal and spatial scale. EARLINET, the European Aerosol Research Lidar Network
(Pappalardo G. et al., 2004) data are relevant for climatology, but also for special events, with strong aerosol influence: Saharan dust outbreaks, forest-fire smoke plumes transported over large areas, photochemical smog and volcano eruptions (e.g. Mona L. et al., 2012; Nicolae D. et al., 2013, Tesche M et al. 2009, 2011).
Presently efforts are underway to make complementary use of different measurement techniques such as lidar and sun-sky photometry at combined EARLINET and AERONET stations.
The main purpose of these techniques is the retrieval of height distributions of optical and microphysical properties of fine-mode and coarse-mode particles (Wagner J et al. 2013) and therefore provides a classification of the aerosols depicted. The recently developed Lidar/Radiometer Inversion Code (LIRIC) analyses profiles of elastic-backscatter signals measured with multiwavelength lidar and spectrally-resolved column-integrated particle optical properties from photometer observations in a synergistic way (Chaikovsky A. et al., 2008, 2012). LIRIC was designed as a universal code for processing of lidar/photometer network data, applicable to many different instrumental conditions and technical approaches. Another procedure is the Polarization Lidar Photometer Networking (POLIPHON) method (Ansmann A. et al. 2012). The POLIPHON technique allows the separation of the contributions of spherical particles (mostly fine-mode particles) and non-spherical particles (mostly coarse-mode particles) to the measured optical effects. This method is based on directly measured linear particle depolarization ratios.
A major step forward in earth observation has been made by the successful implementation of active remote sensing from space (CALIPSO, ADM-AEOLUS, EarthCARE).
Although having multiple advantages (high dynamic range, high spatial and temporal resolution), lidar data suffer by a limited physical content. Both the problems of retrieving optical profiles and microphysical properties from lidar data are ill-posed, needing advanced mathematical algorithms. This is even more pronounced for space-based lidars, which have multiple constraints in terms of emitted / detected wavelengths.
One step forward made in NATALI is to use Artificial Neural Networks in order to classify the aerosols based on optical data provided by multiwavelength Raman lidars and advanced aerosol models.
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Dr. Phys. Doina Nicolae
Remote Sensing Department
National Institute of R&D for Optoelectronics
409 Atomistilor Str., Magurele, Ilfov, Romania
Tel. +40-31-4053303
Fax +40-21-4574522
http://environment.inoe.ro
E-mail: nnicol@inoe.ro
E-mail: doina.nicolae@gmail.com
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Bojan Bojkov
ESA- ESRIN
Via Galileo Galilei
00044 Frascati
Italy
Tel. 0039 06 941 80
Fax 0039 06 941 80
E-Mail: Bojan.Bojkov@esa.int
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