Retrieval Of Aerosol Microphysical Properties Research Articles

Satellite Aerosol Retrieval From Multiangle Polarimetric Measurements: Information Content and Uncertainty Analysis

The multi-angle polarimetric (MAP) instruments have been a focus of recent satellite missions dedicated to enhanced detection of global aerosol microphysical properties. Considering that satellite observations can hardly infer all the unknowns of atmosphere and surface, it’s crucial to know how many and which aerosol parameters can be accurately retrieved from these different MAP measurements as well as their uncertainties. In this study, we present a comprehensive insight into the information content of POLDER-3 and 3MI observations for aerosol retrievals and estimate posterior errors of corresponding parameters based on Bayesian theory. The total degree of freedom for signal (DFS) of aerosol retrievals is around 6-8 from POLDER-3, and is raised by ~1.8-3.5 with 3MI. The retrieval accuracy of volume concentration and effective radius are high (<4%) in the fine-dominant case for both POLDER-3 and 3MI, but get much lower (~8% and ~15%) in coarse-dominant conditions. Furthermore, the advanced 3MI measurements can upgrade the retrieval uncertainties of POLDER-3 by ~50%. Though additional shortwave infrared bands of 3MI provide more information regarding coarse particles, the influence of aerosols on surface BRDF leads to a decrease of the total DFS. With a prior assumption that variations of refractive index depending on wavelength, satellite retrieval accuracy of the real (<0.03) and imaginary part (<0.003) reaches close levels with that of ground-based Sun photometers. Our results can provide a fundamental reference for MAP satellite retrieval of aerosol microphysical properties.

Enhancing MAX-DOAS atmospheric state retrievals by multispectral polarimetry – studies using synthetic data

Abstract. Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a widely used measurement technique for the remote detection of atmospheric aerosol and trace gases. The technique relies on the analysis of ultra-violet and visible radiation spectra of scattered sunlight (skylight) to obtain information on different atmospheric parameters. From an appropriate set of spectra recorded under different viewing directions (typically a group of observations at different elevation angles) the retrieval of aerosol and trace gas vertical distributions is achieved through numerical inversion methods. It is well known that the polarisation state of skylight is particularly sensitive to atmospheric aerosol content as well as aerosol properties and that polarimetric measurements could therefore provide additional information for MAX-DOAS profile retrievals; however, such measurements have not yet been used for this purpose. To address this issue, we have developed the RAPSODI (Retrieval of Atmospheric Parameters from Spectroscopic Observations using DOAS Instruments) algorithm. In contrast to existing MAX-DOAS algorithms, it can process polarimetric information, and it can retrieve simultaneously profiles of aerosols and various trace gases at multiple wavelengths in a single retrieval step; a further advantage is that it contains a Mie scattering model, allowing for the retrieval of aerosol microphysical properties. The forward-model component in RAPSODI is based on a linearised vector radiative transfer model with Jacobian facilities, and we have used this model to create a database of synthetic measurements in order to carry out sensitivity analyses aimed at assessing the potential of polarimetric MAX-DOAS observations. We find that multispectral polarimetry significantly enhances the sensitivity, particularly to aerosol-related quantities. Assuming typical viewing geometries, the degrees of freedom for signal (DOFS) increase by about 50 % and 70 % for aerosol vertical distributions and aerosol properties, respectively, and by approximately 10 % for trace gas vertical profiles. For an idealised scenario with a horizontally homogeneous atmosphere, our findings predict an improvement in the inversion results' accuracy (root-mean-square deviations to the true values) of about 60 % for aerosol vertical column densities (VCDs) as well as for aerosol surface concentrations and by 40 % for aerosol properties. For trace gas VCDs, very little improvement is apparent, although the accuracy of trace gas surface concentrations improves by about 50 %.

Retrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaign

Abstract. This study presents an investigation of aerosol microphysical retrievals from high spectral resolution lidar (HSRL) measurements. Firstly, retrievals are presented for synthetically generated lidar measurements, followed by an application of the retrieval algorithm to real lidar measurements. Here, we perform the investigation for an aerosol state vector that is typically used in multi-angle polarimeter (MAP) retrievals, so that the results can be interpreted in relation to a potential combination of lidar and MAP measurements. These state vectors correspond to a bimodal size distribution, where column number, effective radius, and effective variance of both modes are treated as fit parameters, alongside the complex refractive index and particle shape. The focus is primarily on a lidar configuration based on that of the High Spectral Resolution Lidar-2 (HSRL-2), which participated in the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined project between NASA and SRON (Netherlands Institute for Space Research). The measurement campaign took place between October and November 2017, over the western region of the USA. Six different instruments were mounted on the aeroplane: four MAPs and two lidar instruments, HSRL-2 and the Cloud Physics Lidar (CPL). Most of the flights were carried out over land, passing over scenes with a low aerosol load. One of the flights passed over a prescribed forest fire in Arizona on 9 November, with a relatively higher aerosol optical depth (AOD), and it is the data from this flight that are focussed on in this study. A retrieval of the aerosol microphysical properties of the smoke plume mixture was attempted with the data from HSRL-2 and compared with a retrieval from the MAPs carried out in previous work pertaining to the ACEPOL data. The synthetic HSRL-2 retrievals resulted for the fine mode in a mean absolute error (MAE) of 0.038 (0.025) µm for the effective radius (with a mean truth value of 0.195 µm), 0.052 (0.037) for the real refractive index, 0.010 (7.20×10-3) for the imaginary part of the refractive index, 0.109 (0.071) for the spherical fraction, and 0.054 (0.039) for the AOD at 532 nm, where the retrievals inside brackets indicate the MAE for noise-free retrievals. For the coarse mode, we find the MAE is 0.459 (0.254) µm for the effective radius (with a mean truth value of 1.970 µm), 0.085 (0.075) for the real refractive index, 2.06×10-4 (1.90×10-4) for the imaginary component, 0.120 (0.090) for the spherical fraction, and 0.051 (0.039) for the AOD. A study of the sensitivity of retrievals to the choice of prior and first guess showed that, on average, the retrieval errors increase when the prior deviates too much from the truth value. These experiments revealed that the measurements primarily contain information on the size and shape of the aerosol, along with the column number. Some information on the real component of the refractive index is also present, with the measurements providing little on absorption or on the effective variance of the aerosol distribution, as both of these were shown to depend heavily on the choice of prior. Retrievals using the HSRL-2 smoke-plume data yielded, for the fine mode, an effective radius of 0.107 µm, a real refractive index of 1.561, an imaginary component of refractive index of 0.010, a spherical fraction of 0.719, and an AOD at 532 nm of 0.505. Additionally, the single-scattering albedo (SSA) from the HSRL-2 retrievals was 0.940. Overall, these results are in good agreement with those from the Spectropolarimeter for Planetary Exploration (SPEX) and Research Scanning Polarimeter (RSP) retrievals.

Ambient Aerosol Hygroscopic Growth From Combined Raman Lidar and HSRL

AbstractLidar retrievals of aerosol extinction and collocated relative humidity (RH) were acquired during the Department of Energy Combined High Spectral Resolution Lidar (HSRL) and Raman Measurement Study campaign in the summer of 2015 at the Southern Great Plains site in northern Oklahoma. Measurements of the hygroscopic properties of aerosols are crucial for accurately representing their relationship with clouds, which can be a significant source of uncertainty in assessing direct and indirect radiative effects. The ability for lidar to retrieve measurements of the vertically resolved f (RH), that is, the aerosol extinction at some wet RH normalized by the aerosol extinction at a dry reference RH, is investigated here and compared with nephelometer‐measured f (RH) at the surface. We introduce a modified approach to fitting the lidar measurements of aerosol extinction and our comparisons reveal that lidar and nephelometer measurements of f (RH) are consistent, both with each other and with reported values in the literature. The implications for this work present a path forward for global‐scale retrievals of remotely sensed aerosol hygroscopic properties. Most importantly, the efforts in this study could lead to closing the gap on uncertainties associated with the aerosol indirect radiative effect when combined with inversion retrievals of aerosol microphysical properties.

Optimized profile retrievals of aerosol microphysical properties from simulated spaceborne multiwavelength Lidar

This work is an expanded study of one previously published on retrievals of aerosol microphysical properties from space-borne multiwavelength lidar measurements. The earlier studies and this one were done in the framework of the NASA Aerosol-Clouds-Ecosystems (now the Aerosol Clouds Convection and Precipitation) NASA mission. The focus here is on the capabilities of a simulated spaceborne multiwavelength lidar system for retrieving aerosol complex refractive index (m = mr + imi) and spectral single scattering albedo (SSA(λ)), although other bulk parameters such as effective (reff) radius and particle volume (V) and surface (S) concentrations are also studied. The novelty presented here is the use of recently published, case-dependent optimized-constraints on the microphysical retrievals using three backscattering coefficients (β) at 355, 532 and 1064 nm and two extinction coefficients (α) at 355 and 532 nm, typically known as the stand-alone 3β + 2α lidar inversion. Case-dependent optimized-constraints (CDOC) limit the ranges of refractive index, both real (mr) and imaginary (mi) parts, and of radii that are permitted in the retrievals. Such constraints are selected directly from the 3β + 2α measurements through an analysis of the relationship between spectral dependence of aerosol extinction-to-backscatter ratios (LR) and the Ångström exponent of extinction. The analyses presented here for different sets of size distributions and refractive indices reveal that the direct determination of CDOC are only feasible for cases where the uncertainties in the input optical data are less than 15%. For the same simulated spaceborne system and yield than in Whiteman et al., (2018), we demonstrated that the use of CDOC as essential for the retrievals of refractive index and also largely improved retrieval of bulk parameters. A discussion of the global representativeness of CDOC is presented using simulated lidar data from a 24 h satellite track using GEOS model output to initialize the lidar simulator. We found that CDOC are representative of many aerosol mixtures in spite of some outliers (e.g. highly hydrated particles) associated with the assumptions of bimodal size distributions and of the same refractive index for fine and coarse modes. Moreover, sensitivity tests performed using synthetic data reveal that retrievals of imaginary refractive index (mi) and SSA are extremely sensitive to β(355).

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products.

We present an optimal-estimation-based retrieval framework, the microphysical aerosol properties from polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular total and polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High-Spectral-Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355 and 532 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ångstrøm exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio-Optical Research (SABOR) campaign. For the SABOR campaign, 73% RSP MAPP retrievals fall within ±0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.933 and root-mean-square deviation of 0.0372. For the TCAP campaign, 53% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.927 and root-mean-square deviation of 0.0673. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.959 and a root-mean-square deviation of 0.0694. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar+polarimeter retrieval using both HSRL and RSP measurements.

Effect of sea breeze circulation on aerosol mixing state and radiative properties in a desert setting

Abstract. Chemical composition, microphysical, and optical properties of atmospheric aerosol deep inland in the Negev Desert of Israel are found to be influenced by daily occurrences of sea breeze flow from the Mediterranean Sea. Abrupt increases in aerosol volume concentration and shifts of size distributions towards larger sizes, which are associated with increase in wind speed and atmospheric water content, were systematically recorded during the summertime at a distance of at least 80 km from the coast. Chemical imaging of aerosol samples showed an increased contribution of highly hygroscopic particles during the intrusion of the sea breeze. Besides a significant fraction of marine aerosols, the amount of internally mixed marine and mineral dust particles was also increased during the sea breeze period. The number fraction of marine and internally mixed particles during the sea breeze reached up to 88 % in the PM1–2. 5 and up to 62 % in the PM2. 5–10 size range. Additionally, numerous particles with residuals of liquid coating were observed by SEM/EDX analysis. Ca-rich dust particles that had reacted with anthropogenic nitrates were evidenced by Raman microspectroscopy. The resulting hygroscopic particles can deliquesce at very low relative humidity. Our observations suggest that aerosol hygroscopic growth in the Negev Desert is induced by the daily sea breeze arrival. The varying aerosol microphysical and optical characteristics perturb the solar and thermal infrared radiations. The changes in aerosol properties induced by the sea breeze, relative to the background situation, doubled the shortwave radiative cooling at the surface (from −10 to −20.5 W m−2) and increased by almost 3 times the warming of the atmosphere (from 5 to 14 W m−2), as evaluated for a case study. Given the important value of observed liquid coating of particles, we also examined the possible influence of the particle homogeneity assumption on the retrieval of aerosol microphysical characteristics. The tests suggest that sensitivity to the coating appears if backward scattering and polarimetric measurements are available for the inversion algorithm. This may have an important implication for retrievals of aerosol microphysical properties in remote sensing applications.

Information content and sensitivity of the 3&amp;lt;i&amp;gt;β&amp;lt;/i&amp;gt; + 2&amp;lt;i&amp;gt;α&amp;lt;/i&amp;gt; lidar measurement system for aerosol microphysical retrievals

Abstract. There is considerable interest in retrieving profiles of aerosol effective radius, total number concentration, and complex refractive index from lidar measurements of extinction and backscatter at several wavelengths. The combination of three backscatter channels plus two extinction channels (3β + 2α) is particularly important since it is believed to be the minimum configuration necessary for the retrieval of aerosol microphysical properties and because the technological readiness of lidar systems permits this configuration on both an airborne and future spaceborne instrument. The second-generation NASA Langley airborne High Spectral Resolution Lidar (HSRL-2) has been making 3β + 2α measurements since 2012. The planned NASA Aerosol/Clouds/Ecosystems (ACE) satellite mission also recommends the 3β + 2α combination.Here we develop a deeper understanding of the information content and sensitivities of the 3β + 2α system in terms of aerosol microphysical parameters of interest. We use a retrieval-free methodology to determine the basic sensitivities of the measurements independent of retrieval assumptions and constraints. We calculate information content and uncertainty metrics using tools borrowed from the optimal estimation methodology based on Bayes' theorem, using a simplified forward model look-up table, with no explicit inversion. The forward model is simplified to represent spherical particles, monomodal log-normal size distributions, and wavelength-independent refractive indices. Since we only use the forward model with no retrieval, the given simplified aerosol scenario is applicable as a best case for all existing retrievals in the absence of additional constraints. Retrieval-dependent errors due to mismatch between retrieval assumptions and true atmospheric aerosols are not included in this sensitivity study, and neither are retrieval errors that may be introduced in the inversion process. The choice of a simplified model adds clarity to the understanding of the uncertainties in such retrievals, since it allows for separately assessing the sensitivities and uncertainties of the measurements alone that cannot be corrected by any potential or theoretical improvements to retrieval methodology but must instead be addressed by adding information content.The sensitivity metrics allow for identifying (1) information content of the measurements vs. a priori information; (2) error bars on the retrieved parameters; and (3) potential sources of cross-talk or "compensating" errors wherein different retrieval parameters are not independently captured by the measurements. The results suggest that the 3β + 2α measurement system is underdetermined with respect to the full suite of microphysical parameters considered in this study and that additional information is required, in the form of additional coincident measurements (e.g., sun-photometer or polarimeter) or a priori retrieval constraints. A specific recommendation is given for addressing cross-talk between effective radius and total number concentration.

Retrieval of aerosol microphysical properties from AERONET photopolarimetric measurements: 2. A new research algorithm and case demonstration

AbstractA new research algorithm is presented here as the second part of a two‐part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new‐generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach. While the new algorithm has heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithm retrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarse modes, while the AERONET operational algorithm assumes a size‐independent aerosol refractive index. Mode‐resolved refractive indices can improve the estimate of the single‐scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode‐resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance‐only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10–30% in the refractive index, and 10–40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two‐part study.

Aerosol optical and microphysical retrievals from a hybrid multiwavelength lidar data set – DISCOVER-AQ 2011

Abstract. Retrievals of aerosol microphysical properties (effective radius, volume and surface-area concentrations) and aerosol optical properties (complex index of refraction and single-scattering albedo) were obtained from a hybrid multiwavelength lidar data set for the first time. In July 2011, in the Baltimore–Washington DC region, synergistic profiling of optical and microphysical properties of aerosols with both airborne (in situ and remote sensing) and ground-based remote sensing systems was performed during the first deployment of DISCOVER-AQ. The hybrid multiwavelength lidar data set combines ground-based elastic backscatter lidar measurements at 355 nm with airborne High-Spectral-Resolution Lidar (HSRL) measurements at 532 nm and elastic backscatter lidar measurements at 1064 nm that were obtained less than 5 km apart from each other. This was the first study in which optical and microphysical retrievals from lidar were obtained during the day and directly compared to AERONET and in situ measurements for 11 cases. Good agreement was observed between lidar and AERONET retrievals. Larger discrepancies were observed between lidar retrievals and in situ measurements obtained by the aircraft and aerosol hygroscopic effects are believed to be the main factor in such discrepancies.

Retrieval of aerosol microphysical properties by means of sun and star photometry at Granada, Spain

Knowledge of aerosol microphysical properties is essential to understand the role of atmospheric aerosols in radiative forcing. Passive remote-sensing techniques allow the retrieval of columnar aerosol size distribution from spectral measurements of aerosol optical depth by applying numerical methods. These methods are widely applied to sun photometers. For night-time retrievals of aerosol optical depth, the GFAT (Atmospheric Physics Group of the University of Granada), operates a star photometer with channels at 380, 436, 500, 670, 880, and 1020 nm in the city of Granada (southeastern Spain, 36.83° N, 3.58° W, 680 m a.s.l.). The GFAT also operates a Cimel CE-318 sun photometer with filters at the same wavelengths. To our knowledge, the variations between daytime and night-time columnar aerosol microphysical properties have not been studied until now. In this work, the applicability of an inversion code based only on direct irradiance measurements is presented to retrieve aerosol size distributions, for both daytime and night-time. From March 2007 to February 2009, statistical analyses and time evolutions of the effective radius and the properties of the fine mode such as mean radius, width, and particle volume concentration are analysed. Daytime effective radius values are large in summer and small in winter, whereas no clear seasonal pattern emerges at night-time. During daytime, the fine mode radius does not show any remarkable pattern, whereas at night-time, this parameter shows a clear seasonal pattern with large values in summer and small values in winter. On the other hand, fine mode widths do not show any pattern, neither daytime nor night-time, although large values of this parameter are found during daytime in all seasons. The fine-particle volume concentration presents no seasonal pattern during the daytime, whereas at night-time it shows larger values in summer than in other seasons.

Optimal estimation retrieval of aerosol microphysical properties from SAGE~II satellite observations in the volcanically unperturbed lower stratosphere

Abstract. Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003). An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE) method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths) with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities), even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal) size distributions naturally differ from the correct bimodal values, the associated surface area (A) and volume densities (V) are, nevertheless, fairly accurately retrieved, except at values larger than 1.0 μm2 cm−3 (A) and 0.05 μm3 cm−3 (V), where they tend to underestimate the true bimodal values. Due to the limited information content in the SAGE II spectral extinction measurements this kind of forward model error cannot be avoided here. Nevertheless, the retrieved uncertainties are a good estimate of the true errors in the retrieved integrated properties, except where the surface area density exceeds the 1.0 μm2 cm−3 threshold. When applied to near-global SAGE II satellite extinction measured in 1999 the retrieved OE surface area and volume densities are observed to be larger by, respectively, 20–50% and 10–40% compared to those estimates obtained by the SAGE~II operational retrieval algorithm. An examination of the OE algorithm biases with in situ data indicates that the new OE aerosol property estimates tend to be more realistic than previous estimates obtained from remotely sensed data through other retrieval techniques. Based on the results of this study we therefore suggest that the new Optimal Estimation retrieval algorithm is able to contribute to an advancement in aerosol research by considerably improving current estimates of aerosol properties in the lower stratosphere under low aerosol loading conditions.

EARLINET: the European aerosol research lidar network

Present knowledge concerning aerosols and their distribution patterns in the earth’s atmosphere is far from adequate to properly assess their role in changing climate and environmental conditions, both regionally and globally. Information about vertical concentrations is particularly lacking. Lidar (light detection and ranging) remote sensing is the most appropriate tool to close this observational gap, and networks that deploy this technology are fundamental to the scaled-up study of aerosol concentrations, transport, and modification.1 Established in 2000, the EuropeanAerosol Research LidarNetwork (EARLINET) currently comprises 25 stations and has as its main objective the development of a qualitatively and quantitatively significant database that details the horizontal, vertical, and temporal distribution of atmospheric aerosol over the entire continent (see Figure 1). Station observation capabilities vary. EARLINET currently includes 10 single backscatter stations and 8 stations with a UV Raman channel for independent measurements of aerosol extinction and backscatter. In addition, for retrieval of aerosol microphysical properties, 7 multiwavelength Raman stations include elastic channels at 1064, 532, and 355nm, with Raman channels at 532 and 355nm, and a depolarization channel at 532nm. Network-wide observations take place systematically on a fixed schedule. For collection of unbiased data, all stations perform measurements three fixed days per week. Lidar surveillance adheres to a regular timetable: once each week around noon when the boundary layer is usually well developed, and twice weekly at night under low background light conditions in order to perform Raman extinction measurements. Other network activities monitor special events such as Saharan dust outbreaks (see Figure 2), forest fires, photochemical smog, and volcanic eruptions. A rigorous quality assurance program applies to both instruments and evaluation algorithms,2–4 and a standardFigure 1. Stations in the European Aerosol Research Lidar Network (EARLINET).