28 research outputs found

    Satellite retrieval of aerosol microphysical and optical parameters using neural networks: a new methodology applied to the Sahara desert dust peak

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    In order to exploit the full-earth viewing potential of satellite instruments to globally characterise aerosols, new algorithms are required to deduce key microphysical parameters like the particle size distribution and optical parameters associated with scattering and absorption from space remote sensing data. Here, a methodology based on neural networks is developed to retrieve such parameters from satellite inputs and to validate them with ground-based remote sensing data. For key combinations of input variables available from the MODerate resolution Imaging Spectro-radiometer (MODIS) and the Ozone Measuring Instrument (OMI) Level 3 data sets, a grid of 100 feed-forward neural network architectures is produced, each having a different number of neurons and training proportion. The networks are trained with principal components accounting for 98% of the variance of the inputs together with principal components formed from 38 AErosol RObotic NETwork (AERONET) Level 2.0 (Version 2) retrieved parameters as outputs. Daily averaged, co-located and synchronous data drawn from a cluster of AERONET sites centred on the peak of dust extinction in Northern Africa is used for network training and validation, and the optimal network architecture for each input parameter combination is identified with reference to the lowest mean squared error. The trained networks are then fed with unseen data at the coastal dust site Dakar to test their simulation performance. A neural network (NN), trained with co-located and synchronous satellite inputs comprising three aerosol optical depth measurements at 470, 550 and 660 nm, plus the columnar water vapour (from MODIS) and the modelled absorption aerosol optical depth at 500 nm (from OMI), was able to simultaneously retrieve the daily averaged size distribution, the coarse mode volume, the imaginary part of the complex refractive index, and the spectral single scattering albedo – with moderate precision: correlation coefficients in the range 0.368 ≤ R ≤ 0.514. The network failed to recover the spectral behaviour of the real part of the complex refractive index. This new methodological approach appears to offer some potential for moderately accurate daily retrieval of the total volume concentration of the coarse mode of aerosol at the Saharan dust peak in the area of Northern Africa

    Optimizing CALIPSO Saharan dust retrievals

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    We demonstrate improvements in CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations) dust extinction retrievals over northern Africa and Europe when corrections are applied regarding the Saharan dust lidar ratio assumption, the separation of the dust portion in detected dust mixtures, and the averaging scheme introduced in the Level 3 CALIPSO product. First, a universal, spatially constant lidar ratio of 58 sr instead of 40 sr is applied to individual Level 2 dust-related backscatter products. The resulting aerosol optical depths show an improvement compared with synchronous and collocated AERONET (Aerosol Robotic Network) measurements. An absolute bias of the order of −0.03 has been found, improving on the statistically significant biases of the order of −0.10 reported in the literature for the original CALIPSO product. When compared with the MODIS (Moderate-Resolution Imaging Spectroradiometer) collocated aerosol optical depth (AOD) product, the CALIPSO negative bias is even less for the lidar ratio of 58 sr. After introducing the new lidar ratio for the domain studied, we examine potential improvements to the climatological CALIPSO Level 3 extinction product: (1) by introducing a new methodology for the calculation of pure dust extinction from dust mixtures and (2) by applying an averaging scheme that includes zero extinction values for the non-dust aerosol types detected. The scheme is applied at a horizontal spatial resolution of 1×1 degrees for ease of comparison with the instantaneous and collocated dust extinction profiles simulated by the BSC-DREAM8b dust model. Comparisons show that the extinction profiles retrieved with the proposed methodology reproduce the well-known model biases per subregion examined. The very good agreement of the proposed CALIPSO extinction product with respect to AERONET, MODIS and the BSC-DREAM8b dust model makes this dataset an ideal candidate for the provision of an accurate and robust multiyear dust climatology over northern Africa and Europe

    Aerosol microphysical retrievals from precision filter radiometer direct solar radiation measurements and comparison with AERONET

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    Synchronized sun-photometric measurements from the AERONET-CIMEL (AErosol RObotic NETwork) and GAW-PFR (Global Atmospheric Watch–Precision Filter Radiometer) aerosol networks are used to compare retrievals of the aerosol optical depth (AOD), effective radius, and volume concentration during a high-temporal-resolution measurement campaign at the Athens site in the Mediterranean Basin from 14 to 22 July 2009. During this period, direct-sun AOD retrievals from both instruments exhibited small differences in the range 0.01–0.02. The AODs measured with CIMEL and PFR instruments were inverted to retrieve particle microphysical properties using the linear estimation (LE) technique. For low aerosol loads (AOD < 0.2), measurements of the effective radius by the PFR were found to be −20% to +30% different from CIMEL values for both direct-sun data and inversion data. At higher loads (AOD > 0.4), measurements of the effective radius by the PFR are consistently 20% lower than CIMEL for both direct sun and inversion data. Volume concentrations at low aerosol loads from the PFR are up to 80% higher than the CIMEL for direct-sun data but are up to 20% lower when derived from inversion data under these same conditions. At higher loads, the percentage difference in volume concentrations from the PFR and CIMEL is systematically negative, with inversion data predicting differences 30% lower than those obtained from direct-sun data. An assessment of the effect of errors in the AOD retrieval on the estimation of PFR bulk parameters was performed and demonstrates that it is possible to estimate the particle volume concentration and effective radius with an uncertainty < 65% when AOD < 0.2 and when input errors are as high as 10%

    Application of a synergetic lidar and sunphotometer algorithm for the characterization of a dust event over Athens, Greece

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    We present first retrievals of the Lidar-Radiometer Inversion Code (LIRIC), applied on combined lidar and sunphotometer data during a Saharan dust episode over Athens, Greece, on July 20, 2011. A full lidar dataset in terms of backscatter signals at 355, 532 and 1064 nm, as well as depolarization at 532 nm was acquired from the European Aerosol Research Network (EARLINET) station of Athens and combined with Aerosol Robotic Network (AERONET) data, in order to retrieve the concentration and extinction coefficient profiles of dust. The lidar measurements showed a free tropospheric layer between 1-5 km above Athens, with low Ångström exponent of ~0.5 and high particle depolarization ratio, ~25-30%, both values characteristic of dust particles. The application of LIRIC revealed high concentration profiles of non-spherical coarse particles in the layer, in the range of 0.04-0.07 ppb and a smaller fine particle component with concentrations of ~0.01 ppb. The extinction coefficients at 532 nm ranged between 50 and 90 Mm-1 for coarse non-spherical particles and between 25 and 50Mm-1 for fine particles. The retrievals were compared with modeled dust concentration and extinction coefficient profiles from the Dust Regional Atmospheric Modeling (BSC-DREAM8b), showing good agreement, especially for the coarse modePostprint (published version

    Profiling aerosol optical, microphysical and hygroscopic properties in ambient conditions by combining in situ and remote sensing

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    We present the In situ/Remote sensing aerosol Retrieval Algorithm (IRRA) that combines airborne in situ and lidar remote sensing data to retrieve vertical profiles of ambient aerosol optical, microphysical and hygroscopic properties, employing the ISORROPIA II model for acquiring the particle hygroscopic growth. Here we apply the algorithm on data collected from the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft during the ACEMED campaign in the Eastern Mediterranean. Vertical profiles of aerosol microphysical properties have been derived successfully for an aged smoke plume near the city of Thessaloniki with aerosol optical depth of ∼0.4 at 532 nm, single scattering albedos of ∼0.9-0.95 at 550 nm and typical lidar ratios for smoke of ∼60-80 sr at 532 nm. IRRA retrieves highly hydrated particles above land, with 55 and 80% water volume content for ambient relative humidity of 80 and 90%, respectively. The proposed methodology is highly advantageous for aerosol characterization in humid conditions and can find valuable applications in aerosol-cloud interaction schemes. Moreover, it can be used for the validation of active space-borne sensors, as is demonstrated here for the case of CALIPSO

    Linear polarization signatures of atmospheric dust with the SolPol direct-sun polarimeter

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    Dust particles in lofted atmospheric layers may present a preferential orientation, which could be detected from the resulting dichroic extinction of the transmitted sunlight. The first indications were provided relatively recently on atmospheric dust layers using passive polarimetry, when astronomical starlight observations of known polarization were found to exhibit an excess in linear polarization, during desert dust events that reached the observational site. We revisit the previous observational methodology by targeting dichroic extinction of transmitted sunlight through extensive atmospheric dust layers utilizing a direct-sun polarimeter, which is capable to continuously monitor the polarization of elevated aerosol layers. In this study, we present the unique observations from the Solar Polarimeter (SolPol) for different periods within 2 years, when the instrument was installed in the remote monitoring station of PANGEA – the PANhellenic GEophysical observatory of Antikythera – in Greece. SolPol records polarization, providing all four Stokes parameters, at a default wavelength band centred at 550 nm with a detection limit of 10−7. We, overall, report on detected increasing trends of linear polarization, reaching up to 700 parts per million, when the instrument is targeting away from its zenith and direct sunlight propagates through dust concentrations over the observatory. This distinct behaviour is absent on measurements we acquire on days with lack of dust particle concentrations and in general of low aerosol content. Moreover, we investigate the dependence of the degree of linear polarization on the layers' optical depth under various dust loads and solar zenith angles and attempt to interpret these observations as an indication of dust particles being preferentially aligned in the Earth's atmosphere.</p

    A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals

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    Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research Infra-Structure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAM-ABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1-6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 mu g m(-3) at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies

    Aerosol absorption profiling from the synergy of lidar and sun-photometry : The ACTRIS-2 campaigns in Germany, Greece and Cyprus

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    © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).Aerosol absorption profiling is crucial for radiative transfer calculations and climate modelling. Here, we utilize the synergy of lidar with sun-photometer measurements to derive the absorption coefficient and single scattering albedo profiles during the ACTRIS-2 campaigns held in Germany, Greece and Cyprus. The remote sensing techniques are compared with in situ measurements in order to harmonize and validate the different methodologies and reduce the absorption profiling uncertainties.Peer reviewe

    Lidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: development and distribution in EARLINET

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    The financial support by the European Union's Horizon 2020 research and innovation programme (ACTRIS-2, grant agreement no. 654109) is gratefully acknowledged. The background of LIRIC algorithm and software was developed under the ACTRIS Research Infrastructure project, grant agreement no. 262254, within the European Union Seventh Framework Programme, which financial support is gratefully acknowledged.r I. Binietoglou received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under the grant agreement no. 289923 - ITARS.This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code) algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar/radiometric input data we use measurements from European Aerosol Research Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data. The algorithm starts with the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode. The LIRIC software package was implemented and tested at a number of EARLINET stations. Intercomparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLINET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.European Union (EU) 654109ACTRIS Research Infrastructure project within the European Union 262254European Union (EU) 289923 - ITAR
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