383 research outputs found
Evaluation of the Lidar/Radiometer Inversion Code (LIRIC) to determine microphysical properties of volcanic and desert dust
© Author(s) 2013. This work is distributed under the Creative Commons Attribution 3.0 LicenseThe Lidar/Radiometer Inversion Code (LIRIC) combines the multiwavelength lidar technique with sun/sky photometry and allows us to retrieve vertical profiles of particle optical and microphysical properties separately for fine-mode and coarse-mode particles. After a brief presentation of the theoretical background, we evaluate the potential of LIRIC to retrieve the optical and microphysical properties of irregularly shaped dust particles. The method is applied to two very different aerosol scenarios: a strong Saharan dust outbreak towards central Europe and an Eyjafjallajökull volcanic dust event. LIRIC profiles of particle mass concentrations for the coarse-mode as well as for the non-spherical particle fraction are compared with results for the non-spherical particle fraction as obtained with the polarization-lidar- based POLIPHON method. Similar comparisons for fine-mode and spherical particle fractions are presented also. Acceptable agreement between the different dust mass concentration profiles is obtained. LIRIC profiles of optical properties such as particle backscatter coefficient, lidar ratio, Ångström exponent, and particle depolarization ratio are compared with direct Raman lidar observations. Systematic deviations between the LIRIC retrieval products and the Raman lidar measurements of the desert dust lidar ratio, depolarization ratio, and spectral dependencies of particle backscatter and lidar ratio point to the applied spheroidal-particle model as main source for these uncertainties in the LIRIC results.Peer reviewe
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Aerosol absorption over the clear-sky oceans deduced from POLDER-1 and AERONET observations
We estimate aerosol absorption over the clear-sky oceans using aerosol geophysical products from POLDER-1 space measurements and absorption properties from ground-based AERONET measurements. Our best estimate is 2.5 Wm-2 averaged over the 8-month lifetime of POLDER-1. Low and high absorption estimates are 2.2 and 3.1 Wm-2 based on the variability in aerosol single scattering albedo observed by AERONET. Main sources of uncertainties are the discrimation of the aerosol type from satellite measurements, and potential clear-sky bias induced
by the cloud-screening procedure
Remote sensing of aerosol optical characteristics in sub-Sahel, West Africa
We have determined the characteristics of sub-Sahelian aerosols from a 2-year record of continuous ground-based measurements, made at the University of Ilorin, Ilorin (08°19′N, 04°20′E), Nigeria, in cooperation with the Aerosol Robotic Network. Observations of spectral aerosol optical depths during the dusty harmattan season indicate more than a twofold increase, when compared to other seasons. Retrieved columnar volume size distributions show the existence of bimodality with a dominant coarse mode. The retrieved size distributions were grouped according to different ranges of aerosol optical depths to characterize the aerosols for this particular region. Monthly means of retrieved single-scattering albedos show a sharp decrease from ∼0.95 to ∼0.85 at 500 nm from the preharmattan to the harmattan season when biomass burning is also practiced, increasing the presence of absorbing aerosols. On the basis of these comprehensive observations, we propose to augment existing desert aerosol models, as presented in the literature, to better characterize the dust outbreak season in West Africa, which is quite prolonged and overlaps with the biomass burning seaso
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Modelling soil dust aerosol in the Bodélé depression during the BoDEx campaign
We present regional model simulations of the dust emission events during the Bodélé Dust Experiment (BoDEx) that was carried out in February and March 2005 in Chad. A box model version of the dust emission model is used to test different input parameters for the emission model, and to compare the dust emissions computed with observed wind speeds to those calculated with wind speeds from the regional model simulation. While field observations indicate that dust production occurs via self-abrasion of saltating diatomite flakes in the Bodélé, the emission model based on the assumption of dust production by saltation and using observed surface wind speeds as input parameters reproduces observed dust optical thicknesses well. Although the peak wind speeds in the regional model underestimate the highest wind speeds occurring on 10–12 March 2005, the spatio-temporal evolution of the dust cloud can be reasonably well reproduced by this model. Dust aerosol interacts with solar and thermal radiation in the regional model; it is responsible for a decrease in maximum daytime temperatures by about 5 K at the beginning the dust storm on 10 March 2005. This direct radiative effect of dust aerosol accounts for about half of the measured temperature decrease compared to conditions on 8 March. Results from a global dust model suggest that the dust from the Bodélé is an important contributor to dust crossing the African Savannah region towards the Gulf of Guinea and the equatorial Atlantic, where it can contribute up to 40% to the dust optical thickness
Retrieving global sources of aerosols from MODIS observations by inverting GOCART model
International audienceKnowledge of the global distribution of tropospheric aerosols is important for studying the effects of aerosols on global climate. Chemical transport models rely on archived meteorological fields, accounting for aerosol sources, transport and removal processes can simulate the global distribution of atmospheric aerosols. However, the accuracy of global aerosol modeling is limited. Uncertainty in location and strength of aerosol emission sources is a major factor in limiting modeling accuracy. This paper describes an effort to develop an algorithm for retrieving global sources of aerosol from satellite observations by inverting the GOCART aerosol transport model. To optimize inversion algorithm performance, the inversion was formulated as a generalized multi-term least-squares-type fitting. This concept uses the principles of statistical optimization and unites diverse retrieval techniques into a single flexible inversion procedure. It is particularly useful for choosing and refining a priori constraints in the retrieval algorithm. For example, it is demonstrated that a priori limitations on the partial derivatives of retrieved characteristics, which are widely used in atmospheric remote sensing, can also be useful in inverse modeling for constraining time and space variability of the retrieved global aerosol emissions. The similarities and differences with the standard "Kalman filter" inverse modeling approach and the "Phillips-Tikhonov-Twomey" constrained inversion widely used in remote sensing are discussed. In order to retain the originally high space and time resolution of the global model in the inversion of a long record of observations, the algorithm was expressed using adjoint operators in a form convenient for practical development of the inversion from codes implementing forward model simulations. The inversion algorithm was implemented using the GOCART aerosol transport model. The numerical tests we conducted showed successful retrievals of global aerosol emissions with a 2°×2.5° resolution by inverting the GOCART output. For achieving satisfactory retrieval from satellite sensors such as MODIS, the emissions were assumed constant within the 24 h diurnal cycle and aerosol differences in chemical composition were neglected. Such additional assumptions were needed to constrain the inversion due to limitations of satellite temporal coverage and sensitivity to aerosol parameters. As a result, the algorithm was defined for the retrieval of emission sources of fine and coarse mode aerosols from the MODIS fine and coarse mode aerosol optical thickness data respectively. Numerical tests showed that such assumptions are justifiable, taking into account the accuracy of the model and observations and that it provides valuable retrievals of the location and the strength of the aerosol emissions. The algorithm was applied to MODIS observations during two weeks in August 2000. The global placement of fine mode aerosol sources retrieved from inverting MODIS observations was coherent with available independent knowledge. This was particularly encouraging since the inverse method did not use any a priori information about the sources and it was initialized under a "zero aerosol emission" assumption. The retrieval reproduced the instantaneous global MODIS observations with a standard deviation in fitting of aerosol optical thickness of ~0.04. The optical thickness during high aerosol loading events was reproduced with a standard deviation of ~48%. Applications of the algorithm for the retrieval of coarse mode aerosol emissions were less successful, mainly due to the currently existing lack of MODIS data over high reflectance desert dust sources. Possibilities for enhancing the global satellite data inversion by using diverse a priori constraints on the retrieval are demonstrated. The potential and limitations of applying our approach for the retrieval of global aerosol sources from aerosol remote sensing are discussed
Development of a new data-processing method for SKYNET sky radiometer observations
In order to reduce uncertainty in the estimation of Direct Aerosol Radiative Forcing (DARF), it is important to improve the estimation of the single scattering albedo (SSA). In this study, we propose a new data processing method to improve SSA retrievals for the SKYNET sky radiometer network, which is one of the growing number of networks of sun-sky photometers, such as NASA AERONET and others. There are several reports that SSA values from SKYNET have a bias compared to those from AERONET, which is regarded to be the most accurate due to its rigorous calibration routines and data quality and cloud screening algorithms. We investigated possible causes of errors in SSA that might explain the known biases through sensitivity experiments using a numerical model, and also using real data at the SKYNET sites at Pune (18.616° N/73.800° E) in India and Beijing (39.586° N/116.229° E) in China. Sensitivity experiments showed that an uncertainty of the order of ±0.03 in the SSA value can be caused by a possible error in the ground surface albedo or solid view angle assumed for each observation site. Another candidate for possible error in the SSA was found in cirrus contamination generated by imperfect cloud screening in the SKYNET data processing. Therefore, we developed a new data quality control method to get rid of low quality or cloud contamination data, and we applied this method to the real observation data at the Pune site in SKYNET. After applying this method to the observation data, we were able to screen out a large amount of cirrus-contaminated data and to reduce the deviation in the SSA value from that of AERONET. We then estimated DARF using data screened by our new method. The result showed that the method significantly reduced the difference of 5 W m−2 that existed between the SKYNET and AERONET values of DARF before screening. The present study also suggests the necessity of preparing suitable a priori information on the distribution of coarse particles ranging in radius between 10 μm and 30 μm for the analysis of heavily dust-laden atmospheric case
Retrieval of spatio-temporal distributions of particle parameters from multiwavelength lidar measurements using the linear estimation technique and comparison with AERONET
The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3β + 1α lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement
Remote sensing of soot carbon – Part 2: Understanding the absorption Ångström exponent
Recently, some authors have suggested that the absorption Ångström
exponent (AAE) can be used to deduce the component aerosol
absorption optical depths (AAODs) of carbonaceous aerosols in the
AERONET database. This AAE approach presumes that AAE ≪ 1
for soot carbon, which contrasts the traditional small particle limit
of AAE = 1 for soot carbon. Thus, we provide an overview of the
AERONET retrieval, and we investigate how the microphysics of
carbonaceous aerosols can be interpreted in the AERONET AAE
product. We find that AAE ≪ 1 in the AERONET database requires
large coarse mode fractions and/or imaginary refractive indices that
increase with wavelength. Neither of these characteristics are
consistent with the current definition of soot carbon, so we explore
other possibilities for the cause of AAE ≪ 1. AAE
is related to particle size, and coarse mode particles have
a smaller AAE than fine mode particles for a given aerosol mixture
of species. We also note that the mineral goethite has an imaginary
refractive index that increases with wavelength, is very common in
dust regions, and can easily contribute to AAE ≪ 1. We find that
AAE ≪ 1 can not be caused by soot carbon, unless soot carbon has
an imaginary refractive index that increases with wavelength
throughout the visible and near-infrared spectrums. Finally, AAE is
not a robust parameter for separating carbonaceous absorption from
dust aerosol absorption in the AERONET database
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