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The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future.

A 15-channel airborne sun tracking photometer has been developed. The instrument provides aerosol optical depths over a wide spectral range (0.34–2.25 μm) with an accuracy of ΔAOD from 0.005 to 0.01. Doing measurements at different altitudes allow us to derive the aerosol extinction vertical profile. Thanks to the wide spectral range of the instrument, information on the aerosol size distribution along the vertical is also available.

Currently most of experiments pursuing comprehensive characterization of atmosphere include coordinated observations by both lidar and radiometers in order to obtain important complimentary information about aerosol properties. The passive observations by radiometers from ground are mostly sensitive to the properties of aerosol in total atmospheric column and have very limited sensitivity to vertical structure of the atmosphere. Such observations are commonly used for measuring aerosol optical thickness and deriving the information about aerosol microphysics including aerosol particles shape, size distribution, and complex refractive index. In a contrast, lidar observations of atmospheric responses from different altitudes to laser pulses emitted from ground are designed to provide accurate profiling of the atmospheric properties. The interpretation of the lidar observation generally relies on some assumptions about aerosol type and loading. Here we present the GARRLiC algorithm (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data) that simultaneously inverts co-incident lidar and radiometer observations and derives a united set of aerosol parameters. Such synergetic retrieval is expected to result in additional enhancements in derived aerosol properties because the backscattering observations by lidar add some sensitivity to the columnar properties of aerosol, while radiometric observations provide sufficient constraints on aerosol type and loading that generally are missing in lidar signals. GARRLiC is based on AERONET algorithm for inverting combined observations by radiometer and multi-wavelength elastic lidar observations. It is expected that spectral changes of backscattering signal obtained by multi-wavelength lidar at different altitudes provide some sensitivity to the vertical variability of aerosol particle sizes. In order to benefit from this sensitivity the algorithm is set to derive not only the vertical profile of total aerosol concentration but it also differentiates between the contributions of fine and coarse modes of aerosol. The detailed microphysical properties are assumed height independent and different for each mode and expected to be derived as a part of the retrieval. Thus, the GARRLiC inversion algorithm retrieves vertical distribution of both fine and coarse aerosol concentrations as well as the size distribution, complex refractive index and single scattering albedo for each mode. The potential and limitations of the method are demonstrated by the series of sensitivity tests. The practical outcome of the approach is illustrated by applications of the algorithm to the real lidar and radiometer observations obtained over selected AERONET site.

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010–2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust).

West Africa and the adjacent oceanic regions are very important locations for studying dust properties and their influence on weather and climate. The SHADOW (Study of SaHAran Dust Over West Africa) campaign is performing a multi-scale and multi-laboratory study of aerosol properties and dynamics using a set of in situ and remote sensing instruments at an observation site located at IRD (Institute for Research and Development) Center, Mbour, Senegal (14° N, 17° W). In this paper, we present the results of lidar measurements performed during the first phase of SHADOW which occurred in March-April, 2015. The multiwavelength Mie-Raman lidar acquired 3β + 2α + 1δ measurements during this period. This set of measurements has permitted particle intensive properties such as extinction and backscattering Ångström exponents (BAE) for 355/532 nm wavelengths corresponding lidar ratios and depolarization ratio at 532 nm to be determined. The mean values of dust lidar ratios during the observation period were about 53 sr at both 532 nm and 355 nm, which agrees with the values observed during the SAMUM 1 and SAMUM 2 campaigns held in Morocco and Cape Verde in 2006, 2008. The mean value of particle depolarization ratio at 532 nm was 30 ± 4.5 %, however during strong dust episodes this ratio increased to 35 ± 5 %, which is also in agreement with the results of the SAMUM campaigns. The backscattering Ångström exponent during the dust episodes decreased to ~ −0.7, while the extinction Ångström exponent though being negative, was greater than −0.2. Low values of BAE can likely be explained by an increase in the imaginary part of the dust refractive index at 355 nm compared to 532 nm. The dust extinction and backscattering coefficients at multiple wavelengths were inverted to the particle microphysics using the regularization algorithm and the model of randomly oriented spheroids. The analysis performed has demonstrated that the spectral dependence of the imaginary part of the dust refractive index may significantly influence the inversion results and should be taken into account.

West Africa and the adjacent oceanic regions are very important locations for studying dust properties and their influence on weather and climate. The SHADOW (Study of SaHAran Dust Over West Africa) campaign is performing a multi-scale and multi-laboratory study of aerosol properties and dynamics using a set of in situ and remote sensing instruments at an observation site located at IRD (Institute for Research and Development) Center, Mbour, Senegal (14°N, 17°W). In this paper, we present the results of lidar measurements performed during the first phase of SHADOW which occurred in March-April, 2015. The multiwavelength Mie-Raman lidar acquired 3β+2α+1δ measurements during this period. This set of measurements has permitted particle intensive properties such as extinction and backscattering Angstrom exponents (BAE) for 355/532 nm wavelengths corresponding lidar ratios and depolarization ratio at 532 nm to be determined. The backscattering Angstrom exponent during the dust episodes decreased to ~-0.7, while the extinction Angstrom exponent though being negative, was greater than -0.2. Low values of BAE can likely be explained by an increase in the imaginary part of the dust refractive index at 355 nm compared to 532 nm.

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board of the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of the all available angular observations of total and polarized radiances obtained by POLDER sensor in the window spectral channels where absorption by gaseous is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed on retrieval of extended set of parameters affecting measured radiation. The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index). In order to achieve reliable retrieval from PARASOL observations even over very reflective desert surfaces, the algorithm was designed as simultaneous inversion of a large group of pixels within one or several images. Such, multi-pixel retrieval regime takes advantage from known limitations on spatial and temporal variability in both aerosol and surface properties. Specifically the variations of the retrieved parameters horizontally from pixel-to-pixel and/or temporary from day-to-day are enforced to be smooth by additional appropriately set a priori constraints. This concept is expected to provide satellite retrieval of higher consistency, because the retrieval over each single pixel will be benefiting from co-incident aerosol information from neighboring pixels, as well, from the information about surface reflectance (over land) obtained in preceding and consequent observations over the same pixel. The paper provides in depth description of the proposed inversion concept, illustrates the algorithm performance by a series of numerical tests and presents the examples of preliminary retrieval results obtained from actual PARASOL observations. It is should be noted that many aspects of the described algorithm design considerably benefited from experience accumulated in the preceding effort on developments of currently operating AERONET and PARASOL retrievals, as well as, several core software components were inherited from those earlier algorithms.

Remote sensing of aerosol from space is a challenging and typically underdetermined retrieval task, requiring many assumptions to be made with respect to the aerosol and surface models. Therefore, the quality of a priori information plays a central role in any retrieval process (apart from the cloud screening procedure and the forward radiative transfer model, which to be most accurate should include the treatment of light polarization and molecular-aerosol coupling). In this paper the performance of various algorithms with respect to the of spectral aerosol optical thickness determination from optical spaceborne measurements is studied. The algorithms are based on various types of measurements (spectral, angular, polarization, or some combination of these). It is confirmed that multiangular spectropolarimetric measurements provide more powerful constraints compared to spectral intensity measurements alone, particularly those acquired at a single view angle and which rely on a priori assumptions regarding the particle phase function in the retrieval process.

Here we review the methods presently available and expected in the near future for retrieving the tropospheric aerosol properties using remote sensing. Since all aerosol properties cannot be derived from space, measurements performed from the surface of the Earth are used to adjust the parameters that are not directly accessible and to limit the variability of the parameters that present a weaker sensitivity. The aerosol properties derived include the column concentration (expressed by the aerosol optical depth), the size (given by distribution of the aerosol in 2 to 3 size modes or measurement of the Angstrom coefficient), composition (expressed by the refractive index), shape and vertical profile. The article is restricted to aerosols that are within the troposphere since the techniques used for stratospheric aerosols are very specific.

We discuss the improvements in the aerosol properties characterization resulting from the additional multi-wavelength polarization measurements measured by a new CIMEL polarized sun/sky-photometer, CE318-DP. In order to process direct-sun, sky and polarization measurements in a wide spectral range (340–1640 nm), we developed new calibration methods and strategies, e.g. using the Langley plot method to calibrate both direct-sun irradiance and sky radiance, as well as combining laboratory facilities with a vicarious method to calibrate the polarized sky measurements. For studying the impact of new polarimetric measurements on the retrievals of aerosol properties, we have processed an extensive record of field measurements using an updated Dubovik and King retrieval algorithm [Dubovik O, Sinyuk A, Lapyonok T, Holben BN, Mishchenko MI, et al. Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. J Geophys Res 2006;111:D11208.]. A preliminary analysis shows that adding polarization in the inversion can reduce possible errors (notably for about 30% of our field cases) in the fine mode size distribution, real part of refractive index and particle shape parameter retrievals, especially for small particles.

The detection of aerosol above clouds is critical for the estimate of both the aerosol and cloud radiative impacts. In this study, the authors present a new method to retrieve the aerosol properties over clouds that uses the multiangle polarization measurements of the Polarization and Directionality of Earth Reflectances (POLDER)–Polarization and Anisotropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL) instrument. The method is illustrated and applied to a case study exploiting the coincident observations from other passive and active sensors of the NASA A-Train satellite constellation. The case study is relative to an elevated biomass burning aerosol layer that originates from southern Africa and is then transported over low-level clouds extending over the Atlantic Ocean. It is shown that the comparison between the cloud-top heights retrieved with the different passive techniques developed for the A-Train sensors can be used to detect the presence of aerosols above clouds. The analysis of the PARASOL observations showed that the aerosols significantly affect the polarized light reflected by the clouds over the 80°–120° scattering angle range and in the rainbow region. A single scattering model permitted the reproduction of the polarization observations and the retrieval of an estimate of the aerosol layer optical thickness of 0.225 at 0.865 μm. The retrieved aerosol optical thicknesses over clouds agree quantitatively with the closest ones retrieved over clear-sky ocean (±0.04 as a maximum departure), demonstrating the value of the method. This innovative technique based solely on passive measurements is expected to provide a better understanding of aerosol properties in regions where significant cloud cover usually prevents the retrieval of aerosol optical thickness. As such, this new retrieval method can provide significant and valuable information about the radiative impact of clouds and aerosols, especially where they can potentially interact strongly with each other.

The third POLDER (POLarization and Directionality of the Earth Reflectance) instrument, PARASOL (Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) was launched in December 2004 and started its operational life at the early beginning of March 2005. This study is devoted to the regional validation of PARASOL aerosol retrieval scheme over land surfaces against independent automatic sun-photometers located in the northeast part of China at the Beijing and Xianghe sites both included in AERONET (Aerosol Robotic Network). PARASOL Level 2 Aerosol Optical Thickness (AOT) is shown, thanks to the high quality sun-photometer dataset, to be quite consistent with the AERONET AOT of the fine fractional part of the size distribution (radius ≤ 0.3 μm). In other words, PARASOL retrieval over land is mainly sensitive to the anthropogenic aerosols which are known for influencing the climate, environment as well as human health. Moreover, analysis of polarization in the 490 nm band (Level 1 data) shows the possibility of dust type aerosol identification thus yielding to a potential algorithm improvement in the future.

This document outlines a practical strategy for achieving an observationally based quantification of direct climate forcing by anthropogenic aerosols. The strategy involves a four-step program for shifting the current assumption-laden estimates to an increasingly empirical basis using satellite observations coordinated with suborbital remote and in situ measurements and with chemical transport models. Conceptually, the problem is framed as a need for complete global mapping of four parameters: clear-sky aerosol optical depth δ, radiative efficiency per unit optical depth E, fine-mode fraction of optical depth ff, and the anthropogenic fraction of the fine mode faf. The first three parameters can be retrieved from satellites, but correlative, suborbital measurements are required for quantifying the aerosol properties that control E, for validating the retrieval of ff, and for partitioning fine-mode δ between natural and anthropogenic components. The satellite focus is on the “A-Train,” a constellation of six spacecraft that will fly in formation from about 2005 to 2008. Key satellite instruments for this report are the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) radiometers on Aqua, the Ozone Monitoring Instrument (OMI) radiometer on Aura, the Polarization and Directionality of Earth's Reflectances (POLDER) polarimeter on the Polarization and Anistropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL), and the Cloud and Aerosol Lider with Orthogonal Polarization (CALIOP) lidar on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). This strategy is offered as an initial framework—subject to improvement over time—for scientists around the world to participate in the A-Train opportunity. It is a specific implementation of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) program, presented earlier in this journal, which identified the integration of diverse data as the central challenge to progress in quantifying global-scale aerosol effects. By designing a strategy around this need for integration, we develop recommendations for both satellite data interpretation and correlative suborbital activities that represent, in many respects, departures from current practice

Understanding the impact of aerosols on the earth’s radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth’s Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product. This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved aerosol parameters (τ/α) and ambient cloud amount, with the dependence in the M product being more pronounced than in the A product.

The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard both NASA’s Terra and Aqua satellites is making near-global daily observations of the earth in a wide spectral range (0.41–15 μm). These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode, and several derived parameters including reflected spectral solar flux at the top of the atmosphere. Over the ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 to 2.13 μm. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral irradiance contributed by the aerosol, mass concentration, and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of Aerosol Robotic Network (AERONET) data gleaned from 132 AERONET stations. Eight thousand MODIS aerosol retrievals collocated with AERONET measurements confirm that one standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of Δτ = ±0.03 ±0.05τ over ocean and Δτ = ±0.05 ± 0.15τ over land. Two hundred and seventy-one MODIS aerosol retrievals collocated with AERONET inversions at island and coastal sites suggest that one standard deviation of MODIS effective radius retrievals falls within Δreff = ±0.11 μm. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.

For an 8-month period aerosol optical depth (AOD) is compared, derived over global oceans with five different retrieval algorithms applied to four satellite instruments flown on board three satellite platforms. The Advanced Very High Resolution Radiometer (AVHRR) was flown on board NOAA-14, the Ocean Color and Temperature Scanner (OCTS) and the Polarization and Directionality of the Earth’s Reflectances (POLDER) on board the Advanced Earth Observing Satellite(ADEOS), and the Total Ozone Mapping Spectrometer (TOMS) on board the Earth Probe satellites. The aerosol data are presented on the same format and converted to the same wavelength in the comparison and can therefore be a useful tool in validation of global aerosol models, in particular models that can be driven with meteorological data for the November 1996 to June 1997 period studied here. Large uncertainties in the global mean AOD are found. There is at least a factor of 2 difference between the AOD from the retrievals. The largest uncertainties are found in the Southern Hemisphere, and the smallest differences mostly near the continents in the Northern Hemisphere. The largest relative differences are probably caused by differences in cloud screening.

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spaceborne lidar, expected to be launched in 2004, will collect profiles of the lidar attenuated backscattering coefficients of aerosol and clouds at 0.53 and 1.06 /spl mu/m. The measurements are sensitive to the vertical distribution of aerosols. However, the information is insufficient to be mapped into unique aerosol physical properties and vertical distribution. Spectral radiances measured by the Moderate Resolution Imaging Spectrometer (MODIS) on the Aqua spacecraft, acquired simultaneously with the CALIPSO observations, can constrain the solutions. The combination of the MODIS and CALIPSO data can be used to derive extinction profiles of the fine and coarse modes of the aerosol size distribution for aerosol optical thickness of 0.1 and larger. Here we describe a new inversion method developed to invert simultaneously MODIS and CALIPSO data over glint-free ocean. The method is applied to aircraft lidar and MODIS data collected over a dust storm off the coast of West Africa during the Saharan Dust Experiment (SHADE). The backscattering-to-extinction ratio (BER) (BER=/spl omega//sub o/P(180)/4/spl pi/) can be retrieved from the synergism between measurements avoiding a priori hypotheses required for inverting lidar measurements alone. For dust, the resultant value of BER =0.016 sr/sup -1/ is over 50% smaller than what is expected using Mie theory, but in good agreement with recent results obtained from Raman lidar observations of dust episodes. The inversion is robust in the presence of 10% and 20% noise in the lidar signal at 0.53 and 1.06 /spl mu/m, respectively. Calibration errors of the lidar of 5% to 10% can cause an error in optical thickness of 20% to 40%, respectively, in the tested cases.

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an Earth-viewing sensor that flies on the Earth Observing System Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS scans a swath width of 2330 km that is sufficiently wide to provide nearly complete global coverage every two days from a polar-orbiting, Sun-synchronous, platform at an altitude of 705 km. MODIS provides images in 36 spectral bands between 0.415 and 14.235 /spl mu/m with spatial resolutions of 250 m (two bands), 500 m (five bands), and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric properties. Twenty-six bands are used to derive atmospheric properties such as cloud mask, atmospheric profiles, aerosol properties, total precipitable water, and cloud properties. We describe each of these atmospheric data products, including characteristics of each of these products such as file size, spatial resolution used in producing the product, and data availability.

Accurate measurements of the spectral solar flux reaching the surface in cloud-free conditions are required to determine the aerosol radiative impact and to test aerosol models that are used to calculate radiative forcing of climate. Spectral flux measurements are hampered in many locations by persistent broken cloud fields. Here a new technique is developed to derive the diffuse solar spectral flux reaching the surface from principal-plane measurements conducted in the last six years by the Aerosol Robotic Network (AERONET). This 50‐100 instrument global network measures the principal-plane radiances in four spectral bands (0.44‐1.02 mm) approximately every hour every day. These instruments also measure the spectral optical thickness and derive the aerosol size distribution and other properties from sky measurements. The advantage of the AERONET measurements is that collimated sky radiance is measured for each 1 83 18 field of view. Clouds and cloud shadows are rejected before the total sky brightness is reconstructed and the flux is derived. The results compare favorably with shadow band measurements and with aerosol models. Studied are smoke aerosol in Brazil; Saharan dust

Simultaneous spectral remote observations of dust properties from space and from the ground create a powerful tool for the determination of ambient dust properties integrated on the entire atmospheric column. The two measurement methods have a complementary sensitivity to variety of dust properties. The methodology is demonstrated using spectral measurements (0.47-2.21 mm) from Landsat TM over the bright Senegalian coast and dark ocean, and Aerosol Robotic Network (AERONET) radiances measured in several locations. We derive (1) the dust size distribution, showing a dominant coarse mode at 1-5 mm and a secondary mode around 0.5 mm effective radius; (2) dust absorption, which is found to be substantially smaller than reported from previous measurements; (3) the real part of the refractive index which varies within the range 1.53- 1.46; and we show that (4) the effect of the dust nonspherical shape on its optical properties is not significant for scattering angles ,1208.

Dust absorption of solar radiation is not well known due to limitations in the accuracy of in situ measurements. Here we report two new independent remote sensing techniques that provide sensitive measurements of dust absorption. One uses satellite spectral measurements, the second ground based sky measurements. Both techniques demonstrate that Saharan dust absorption of solar radiation is several times smaller than the current international standards. For example, at wavelength of 0.64 µm the dust single scattering albedo is reported here as 0.97±0.02 rather than 0.87±0.04 in recent review.

International audience; The polarization measurements achieved by the POLDER instrument on ADEOS-! are used for the remote sensing of aerosols over land surfaces. The key advantage of using polarized observations is their ability to systematically correct for the ground contribution, whereas the classical approach using natural light fails. The estimation of land surface polarizing properties from POLDER has been examined in a previous paper. Here we consider how the optical thickness 30 and ,•ngstr6m exponent a of aerosols are derived from the polarized light backscattered by the particles. The inversion scheme is detailed, and illustrative results are presented. Maps of the retrieved optical thickness allow for detection of large aerosol features, and in the case of small aerosols, the $0 and a retrievals are consistent with correlative ground-based measurements. However, because polarized light stems mainly from small particles, the results are biased for aerosol distributions containing coarser modes of particles. To overcome this limitation, an aerosol index defined as the product AI = •0a is proposed. Theoretical analysis and comparison with ground-based measurements suggest that AI is approximately the same when using •0, and a is related to the entire aerosol size distribution or derived from the polarized light originating from the small polarizing particles alone. This invariance is specially assessed by testing the continuity of AI across coastlines, given the unbiased properties of aerosol retrieval over ocean. Although reducing the information concerning the aerosols, this single parameter allows a link between the POLDER aerosol surveys over land and ocean. POLDER aerosol index global maps enable the monitoring of major aerosol sources over continental areas.

Dust is a dominant feature in satellite images and is suspected to extract large radiative forcing of climate. While remote sensing of dust over the dark oceans is feasible, adequate techniques for remote sensing over the land still have to be developed. Similar to remote sensing of aerosol over vegetated regions, the authors use a combination of visible and mid-IR solar channels to detect dust over the desert. Analysis of Landsat TM images over Senegal taken in 1987 show that the surface reflectance at 0.64 /spl mu/m is between 0.54/spl plusmn/0.05 of the reflectance at 2.1 /spl mu/m, and reflectance at 0.47 /spl mu/m is 0.26/spl plusmn/0.03 of that at 2.1 /spl mu/m, surprisingly similar to relationships in non-desert sites. They also found that dust have only a small effect on the surface+atmosphere reflectance at 2.1 /spl mu/m over the desert. Therefore, in the presence of dust, they use the Landsat TM data at 2.1 /spl mu/m channel to predict the surface reflectance at 0.64 and 0.47 /spl mu/m. The difference between the satellite-measured reflectances of surface+atmosphere and the predicted surface reflectances is used to derive the dust-optical thickness /spl tau/ at 0.64 and 0.47 /spl mu/m. Results show that /spl tau/ can be derived within /spl Delta//spl tau/=/spl plusmn/0.5 for the range of 0

Aerosol particles originate from man-made sources such as urban/industrial activities,rurning associated with land use processes, wind-blown dust, and natural sources. Their interaction with sunlight and their effect on cloud microphysics forms a major uncertainty in predicting climate change. Furthermore, the lifetime of only a few days causes high spatial variability in aerosol optical and radiative properties that requires global observations from space. Remote sensing of aerosol properties from space is reviewed both for present and planned national and international satellite sensors. Techniques that are being used to enhance our ability to characterize the global distribution of aerosol properties include well-calibrated multispectral radiometers, multispectral polarimeters, and multi-angle spectroradiometers. Though most of these sensor systems rely primarily on visible to mid-infrared spectral channels, the availability of of thermal channels to aid in cloud screening is an important additional piece of information that is not always incorporated into the sensor design. In this paper we describe the various satellite sensor systems being developed by Europe, Japan, and the U.S., and highlight the advantages and disadvantages of each of these systems for aerosol applications. An important underlying theme is that the remote sensing of aerosol properties, especially aerosol size distribution and single scattering albedo, is exceedingly difficult. As a consequence, no one sensor system is capable of providing totally unambiguous information, and hence a careful intercomparison of derived products from different sensors, together with a comprehensive network of ground-based sun-photometer and sky radiometer systems, are required to advance our quantitative understanding of global aerosol characteristics.

The concept and description of a remote sensing aerosol monitoring network initiated by NASA, developed to support NASA, CNES, and NASDA’s Earth satellite systems under the name AERONET and expanded by national and international collaboration, is described. Recent development of weather-resistant automatic sun and sky scanning spectral radiometers enable frequent measurements of atmospheric aerosol optical properties and precipitable water at remote sites. Transmission of automatic measurements via the geostationary satellites GOES and METEOSATS’ Data Collection Systems allows reception and processing in near real-time from approximately 75% of the Earth’s surface and with the expected addition of GMS, the coverage will increase to 90% in 1998. NASA developed a UNIX-based near real-time processing, display and analysis system providing internet access to the emerging global database. Information on the system is available on the project homepage, http://spamer.gsfc.nasa.gov . The philosophy of an open access database, centralized processing and a user-friendly graphical interface has contributed to the growth of international cooperation for ground-based aerosol monitoring and imposes a standardization for these measurements. The system’s automatic data acquisition, transmission, and processing facilitates aerosol characterization on local, regional, and global scales with applications to transport and radiation budget studies, radiative transfer-modeling and validation of satellite aerosol retrievals. This article discusses the operation and philosophy of the monitoring system, the precision and accuracy of the measuring radiometers, a brief description of the processing system, and access to the database.

Daily distribution of the aerosol optical thickness and columnar mass concentration will be derived over the continents, from the EOS moderate resolution imaging spectroradiometer (MODIS) using dark land targets. Dark land covers are mainly vegetated areas and dark soils observed in the red and blue channels; therefore the method will be limited to the moist parts of the continents (excluding water and ice cover). After the launch of MODIS the distribution of elevated aerosol concentrations, for example, biomass burning in the tropics or urban industrial aerosol in the midlatitudes, will be continuously monitored. The algorithm takes advantage of the MODIS wide spectral range and high spatial resolution and the strong spectral dependence of the aerosol opacity for most aerosol types that result in low optical thickness in the mid-IR (2.1 and 3.8 pm). The main steps of the algorithm are (1) identification of dark pixels in the mid-IR; (2) estimation of their reflectance at 0.47 and 0.66 pm; and (3) derivation of the optical thickness and mass concentration of the accumulation mode from the detected radiance. To differentiate between dust and aerosol dominated by accumulation mode particles, for example, smoke or sulfates, ratios of the aerosol path radiance at 0.47 and 0.66 pm are used. New dynamic aerosol models for biomass burning aerosol, dust and aerosol from industrial/urban origin, are used to determine the aerosol optical properties used in the algorithm. The error in the retrieved aerosol optical thicknesses, r,, is expected to be AT, = 0.05 5 0.27,. Daily values are stored on a resolution of 10 X 10 pixels (1 km nadir resolution). Weighted and gridded 8-day and monthly composites of the optical thickness, the aerosol mass concentration and spectral radiative forcing are generated for selected scattering angles to increase the accuracy. The daily aerosol information over land and oceans (Tunr& et al., this issue), combined with continuous aerosol remote sensing from the ground, will be used to study aerosol climatology, to monitor the sources and sinks of specific aerosol types, and to study the interaction of aerosol with water vapor and clouds and their radiative forcing of climate. The aerosol information will also be used for atmospheric corrections of remotely sensed surface reflectance. In this paper, examples of applications and validations are provided.

Spectral radiances measured at the top of the atmosphere in a wide spectral range (0.55–2.13 μm) are used to monitor the aerosol optical thickness and the aerosol size distribution (integrated on the vertical column) of the ambient (undisturbed) aerosol over the oceans. Even for the moderate resolution imaging spectrometer (MODIS) wide spectral range, only three parameters that describe the aerosol loading and size distribution can be retrieved. These three parameters are not always unique. For instance, the spectral radiance of an aerosol with a bilognormal size distribution can be simulated very well with a single lognormal aerosol with an appropriate mean radius and width of distribution. Preassumptions on the general structure of the size distribution are therefore required in the inversion of MODIS data. The retrieval of the aerosol properties is performed using lookup table computations. The volume size distribution in the lookup table is described with two lognormal modes: a single mode to describe the accumulation mode particles (radius 1.0 μm). Note that two accumulation modes may be present, one dominated by gas phase processes and a second dominated by cloud phase processes. The coarse mode can also be split into several partially overlapping modes describing maritime salt particles and dust. The aerosol parameters we expect to retrieve are η, the fractional contribution of the accumulation mode to scattering; τ, the spectral optical thickness; and rm, the mean particle size of the dominant mode. Additional radiative quantities such as asymmetry parameter and effective radius are derived subsequently. The impact of the surface conditions, wind speed and chlorophyll content on the retrieval is estimated, the impact of potential sources of error like the calibration of the instrument is also tested. The algorithm has been applied successfully to actual data sets provided by the Thematic Mapper on Landsat 5 and by the MODIS airborne simulator on the ER-2 and tested against ground and airborne measurements. A first estimate of the general accuracy is Δτ = ±0.05±0.05τ (at 550 nm), Δrm = 0.3rm, Δη = ±0.25.

The launch of ADEOS in August 1996 with POLDER, TOMS, and OCTS instruments on board and the future launch of EOS-AM 1 in mid-1998 with MODIS and MISR instruments on board start a new era in remote sensing of aerosol as part of a new remote sensing of the whole Earth system (see a list of the acronyms in the Notation section of the paper). These platforms will be followed by other international platforms with unique aerosol sensing capability, some still in this century (e.g., ENVISAT in 1999). These international spaceborne multispectral, multiangular, and polarization measurements, combined for the first time with international automatic, routine monitoring of aerosol from the ground, are expected to form a quantum leap in our ability to observe the highly variable global aerosol. This new capability is contrasted with present single-channel techniques for AVHRR, Meteosat, and GOES that although poorly calibrated and poorly characterized already generated important aerosol global maps and regional transport assessments. The new data will improve significantly atmospheric corrections for the aerosol effect on remote sensing of the oceans and be used to generate first real-time atmospheric corrections over the land. This special issue summarizes the science behind this change in remote sensing, and the sensitivity studies and applications of the new algorithms to data from present satellite and aircraft instruments. Background information and a summary of a critical discussion that took place in a workshop devoted to this topic is given in this introductory paper. In the discussion it was concluded that the anticipated remote sensing of aerosol simultaneously from several space platforms with different observation strategies, together with continuous validations around the world, is expected to be of significant importance to test remote sensing approaches to characterize the complex and highly variable aerosol field. So far, we have only partial understanding of the information content and accuracy of the radiative transfer inversion of aerosol information from the satellite data, due to lack of sufficient theoretical analysis and applications to proper field data. This limitation will make the anticipated new data even more interesting and challenging. A main concern is the present inadequate ability to sense aerosol absorption, from space or from the ground. Absorption is a critical parameter for climate studies and atmospheric corrections. Over oceans, main concerns are the effects of white caps and dust on the correction scheme. Future improvement in aerosol retrieval and atmospheric corrections will require better climatology of the aerosol properties and understanding of the effects of mixed composition and shape of the particles. The main ingredient missing in the planned remote sensing of aerosol are spaceborne and ground-based lidar observations of the aerosol profiles.

Remote sensing from satellite or airborne platforms of land or sea surfaces in the visible and near infrared is strongly affected by the presence of the atmosphere along the path from Sun to target (surface) to sensor. This paper presents 6S (Second Simulation of the Satellite Signal in the Solar Spectrum), a computer code which can accurately simulate the above problems. The 6S code is an improved version of 5S (Simulation of the Satellite Signal in the Solar Spectrum), developed by the Laboratoire d'Optique Atmospherique ten years ago. The new version now permits calculations of near-nadir (down-looking) aircraft observations, accounting for target elevation, non lambertian surface conditions, and new absorbing species (CH/sub 4/, N/sub 2/O, CO). The computational accuracy for Rayleigh and aerosol scattering effects has been improved by the use of state-of-the-art approximations and implementation of the successive order of scattering (SOS) algorithm. The step size (resolution) used for spectral integration has been improved to 2.5 nm. The goal of this paper is not to provide a complete description of the methods used as that information is detailed in the 6S manual, but rather to illustrate the impact of the improvements between 5S and 6S by examining some typical remote sensing situations. Nevertheless, the 6S code has still limitations. It cannot handle spherical atmosphere and as a result, it cannot be used for limb observations. In addition, the decoupling the authors are using for absorption and scattering effects does not allow to use the code in presence of strong absorption bands.

International audience; Spaceborne instruments such as POLDER (polarization and directionality of Earth's reflectances) provide multidirectional estimates of the surface reflectance (after atmospheric correction). A better description of the surface cover is needed for an improvement in climate modeling. This paper describes how the inversion of a three-parameter bidirectional model from the measurements yields some variables of interest such as the surface albedo, the leaf area index, the fraction of vegetation, and the daily integrated photosynthetically active radiation absorption. Airborne measurements of POLDER were made during the HAPEX-Sahel experiment over various surface types and for different atmospheric conditions. These measurements together with some "ground truth" allow a validation of the proposed method. The reflectance bidirectional signature of the Sahelian landscape shows some classical features such as a general increase toward backscattering and the hot spot phenomenon. The bidirectional model allows an accurate representation of the observed signatures. However, a large range of angular measurements is necessary to constrain the model inversion and to decrease the uncertainty in the three-parameter retrieval. The surface variables derived from these three parameters are found to be in agreement with the in situ measurements. Obviously, a validation on other landscapes with a higher vegetation coverage is now needed. The technique described in this paper will be applied to the spaceborne POLDER data sets.

We present an estimate of the yearly flux of total and black carbon aerosols emitted by savanna biomass burning in Africa from satellite data and ground-based measurements. Smoke plumes are identified using visible, near-infrared, and thermal infrared derived information. In the savanna region of our study, these structures could either decrease or increase the visible albedo of advanced very high resolution radiometer (AVHRR). It is hypothesized that variations of chemical composition and particulate size distribution may create such differences. The 5S model [Tanre et al., 1990] is used to simulate radiative transfer through smoke plumes and background atmosphere. The overall uncertainty of the derived aerosol optical depth (τa) is 75% and mainly due to the choice in particulate composition and size distribution aerosol. Impact of the aerosol mixture (internal versus external mixture) has been also tested. For smoke plumes a typical value of τa (at 0.55 μm) is 0.5, and 0.1 for the background atmosphere. Specific extinction cross sections are calculated using Mie theory applied to different representative aerosol models, allowing the retrieval of aerosol columnar concentrations from aerosol optical depth values and integrated aerosol mass loadings in fire plumes. The overall uncertainty on the determination of aerosol load is estimated to be lower than a factor of 5. The atmospheric carbonaceous aerosol flux from savanna burning in Africa was estimated to be 6.5 Tg C yr−1, which compares with that obtained from emission factor on-site measurements (13±5 Tg C yr−1).

The new algorithm that simultaneously inverts co-incident ground-based observations by AERONET radiometer and multi-wavelength lidar is presented. The retrieval uses an assumption that a mixture of fine and coarse aerosol modes with vertically constant spectral optical properties can satisfactorily describe the vertical variability of aerosol spectral optical properties. In this model the shape of size distribution and complex refractive index are assumed to be height independent for each mode, while the vertical profiles of aerosol concentrations can change arbitrarily for each mode. Consequently the inversion algorithm retrieves the size distribution, complex refractive index, single scattering albedo and vertical distribution of both fine and coarse aerosol modes. The concept of the method is presented and illustrated by the application of the developed method to the actual combined observations of lidar and radiometer.

This book gives a much needed explanation of the basic physical principles of radia5tive transfer and remote sensing, and presents all the instruments and retrieval algorithms in a homogenous manner. For the first time, an easy path from theory to practical algorithms is available in one easily accessible volume, making the connection between theoretical radiative transfer and individual practical solutions to retrieve aerosol information from remote sensing. In addition, the specifics and intercomparison of all current and historical methods are explained and clarified.

Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate. The Aerosol-cci project, part of the European Space Agency's Climate Change Initiative (CCI), was designed to provide essential climate variables for aerosols from satellite data. Eight algorithms, developed for the retrieval of aerosol properties using data from AATSR (4), MERIS (3) and POLDER, were evaluated to determine their suitability for climate studies. The primary result from each of these algorithms is the aerosol optical depth (AOD) at several wavelengths, together with the Ångström exponent (AE) which describes the spectral variation of the AOD for a given wavelength pair. Other aerosol parameters which are possibly retrieved from satellite observations are not considered in this paper. The AOD and AE (AE only for Level 2) were evaluated against independent collocated observations from the ground-based AERONET sun photometer network and against "reference" satellite data provided by MODIS and MISR. Tools used for the evaluation were developed for daily products as produced by the retrieval with a spatial resolution of 10 × 10 km2 (Level 2) and daily or monthly aggregates (Level 3). These tools include statistics for L2 and L3 products compared with AERONET, as well as scoring based on spatial and temporal correlations. In this paper we describe their use in a round robin (RR) evaluation of four months of data, one month for each season in 2008. The amount of data was restricted to only four months because of the large effort made to improve the algorithms, and to evaluate the improvement and current status, before larger data sets will be processed. Evaluation criteria are discussed. Results presented show the current status of the European aerosol algorithms in comparison to both AERONET and MODIS and MISR data. The comparison leads to a preliminary conclusion that the scores are similar, including those for the references, but the coverage of AATSR needs to be enhanced and further improvements are possible for most algorithms. None of the algorithms, including the references, outperforms all others everywhere. AATSR data can be used for the retrieval of AOD and AE over land and ocean. PARASOL and one of the MERIS algorithms have been evaluated over ocean only and both algorithms provide good results. © 2013 Elsevier Inc. All rights reserved.

Passive remote sensing of aerosol using the shortwave spectrum draws on a long heritage of experience that began with three main techniques described in Chapter 7: occultation methods, dark target approaches, and spectral ultra-violet (UV) algorithms. Beginning in the 1970s, these techniques have been applied to instruments flown on a series of different satellite platforms and have produced important time series of aerosol parameters that span decades. This heritage is especially valuable given the fact that the early downward-viewing sensors used for aerosol retrieval – the Advanced Very High Resolution Radiometer (AVHRR), the Total Ozone Mapping Spectrometer (TOMS) and even the Geostationary Operational Environmental satellites (GOES) – were designed for purposes other than retrieving aerosol. However, the success of using these instruments for aerosol characterization motivated the development of sensors designed with aerosol retrievals in mind. Improved spatial resolution, narrower spectral channels, increased spectral range and density, enhanced capability in terms of multiple angular views of the same scene and polarization are some of the specific improvements designed into the sensors flying during the 2000s that were intended to provide better aerosol retrievals than AVHRR and TOMS.

Aerosol scatters solar radiation before it reaches the surface and scatters and absorbs it again after it is reflected from the surface and before it reaches the satellite sensor. The effect is spectrally and spatially dependent. Therefore, atmospheric aerosol (dust, smoke, and air pollution particles) has a significant effect on remote sensing. Correction for the aerosol effect on remote sensing of land areas was never achieved on an operational basis though several case studies were demonstrated. We distinguish between direct correction, in which the aerosol loading is derived from the image itself (or supplied from external sources) followed by correction of the image using an appropriate radiative transfer model, and indirect correction, achieved by defining remote sensing functions that are less dependent on the aerosol loading. To some degree this was already achieved in global remote sensing of vegetation where a composite of several days of the normalized difference vegetation index (NDVI) measurements, choosing the maximal value, was used instead of a single cloud-screened value. The atmospheric resistant vegetation index (ARVI) introduced recently for the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) is the most appropriate example of indirect correction, where the index is defined in such a way that the atmospheric effect in a blue spectral channel cancels to a large degree the atmospheric effect in the red channel in computations of the vegetation index. Atmospheric corrections can also use aerosol climatology or simultaneous measurements with ground-based instrumentation. These aspects of aerosol studies and remote sensing are reviewed in this article. New advances in ground-based instrumentation and future satellite systems (including measurements of polarization) are discussed. In the conclusions a strategy is introduced for a combination of ground-based measurements, with direct and indirect corrections that is implemented for the EOS-MODIS and recommended for other similar platforms. Such strategy, planned in advance, is a first step to face the challenge and take advantage of the opportunities that the remote sensing community will face with the launch of EOS and ADEOS in the next several years.

Most of the current aerosol retrievals from passive sensors are restricted to cloud-free scenes, which strongly reduces our ability to monitor the aerosol properties at a global scale and to estimate their radiative forcing. The presence of aerosol above clouds (AAC) affects the polarized light reflected by the cloud layer, as shown by the spaceborne measurements provided by the POlarization and Directionality of Earth Reflectances (POLDER) instrument on the PARASOL satellite. In a previous work, a first retrieval method was developed for AAC scenes and evaluated for biomass-burning aerosols transported over stratocumulus clouds. The method was restricted to the use of observations acquired at forward scattering angles (90–120°) where polarized measurements are highly sensitive to fine-mode particle scattering. Non-spherical particles in the coarse mode, such as mineral dust particles, do not much polarize light and cannot be handled with this method. In this paper, we present new developments that allow retrieving also the properties of mineral dust particles above clouds. These particles do not much polarize light but strongly reduce the polarized cloud bow generated by the liquid cloud layer beneath and observed for scattering angles around 140°. The spectral attenuation can be used to qualitatively identify the nature of the particles (i.e. accumulation mode versus coarse mode, i.e. mineral dust particles versus biomass-burning aerosols), whereas the magnitude of the attenuation is related to the optical thickness of the aerosol layer. We also use the polarized measurements acquired in the cloud bow to improve the retrieval of both the biomass-burning aerosol properties and the cloud microphysical properties. We provide accurate polarized radiance calculations for AAC scenes and evaluate the contribution of the POLDER polarization measurements for the simultaneous retrieval of the aerosol and cloud properties. We investigate various scenes with mineral dust particles and biomass-burning aerosols above clouds. For clouds, our results confirm that the droplet size distribution is narrow in high-latitude ocean regions and that the droplet effective radii retrieved from both polarization measurements and from total radiance measurements are generally close for AAC scenes (departures smaller than 2 μm). We found that the magnitude of the primary cloud bow cannot be accurately estimated with a plane parallel transfer radiative code. The errors for the modeling of the polarized cloud bow are between 4 and 8% for homogenous cloudy scenes, as shown by a 3-D radiative transfer code. These effects only weakly impact the retrieval of the Aerosol Optical Thickness (AOT) performed with a mineral dust particle model for which the microphysical properties are entirely known (relative error smaller than 6%). We show that the POLDER polarization measurements allow retrieving the AOT, the fine-mode particle size, the Ångström exponent and the fraction of spherical particles. However, the complex refractive index and the coarse-mode particle size cannot be accurately retrieved with the present polarization measurements. Our complete and accurate algorithm cannot be applied to process large amounts of data, so a simpler algorithm was developed to retrieve the AOT and the Ångström exponent above clouds in an operational way. Illustrations are provided for July–August 2008 near the African coast. Large mean AOTs above clouds at 0.865 μm (>0.3) are retrieved for oceanic regions near the coasts of South Africa that correspond to biomass-burning aerosols, whereas even larger mean AOTs above clouds for mineral dust particles (>0.6) are also retrieved near the coasts of Senegal. For these regions and time period, the direct AAC radiative forcing is likely to be significant. The final aim of this work is the global monitoring of the AAC properties and the estimation of the direct aerosol radiative forcing in cloudy scenes.

This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was transported over desert, vegetated, and ocean surfaces. The aim is to identify the differences between current datasets. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as assumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, it is important to note that differences in sampling, related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset can be an important issue.

Lidar and sun-radiometer data of the EARLINET, CIS-LiNet and AERONET/PHOTONS stations in the East European area, space observations and local in-situ measurements were used to characterize long range aerosol transport over European regions. Brief description of technique and equipment for implementation of combined lidar and sun-radiometer approach to aerosol monitoring and results of five years observations are presented.

The aerosol remote sensing from space has started in the 1980's using observations provided by geostationary satellites or by polar orbiting platforms not specifically designed for observing aerosols. As a result, the number of retrieved parameters was limited and retrievals in the visible restricted over ocean. Over land, because of the important surface contribution, the aerosol detection was performed in the UV (or in the dark blue) where most of the earth surfaces are dark enough but with overlap of multiple aerosols parameters, content, altitude and absorption. Instruments dedicated to aerosol monitoring are recently available and the POLDER instrument on board the PARASOL mission is one of them. By measuring the wavelength, angular and polarization properties of the radiance at the top of the atmosphere, in coordination with the other A-Train instruments, PARASOL can better quantify aerosol optical depths (AOD) and improve the derivation of the radiative and physical properties. The instrument, the inversion schemes and the list of aerosol parameters are described. Examples of retrieved aerosol parameters are provided as well as innovative approaches and further inversion techniques.

An atmospherically resistant vegetation index (ARVI) is proposed and developed for remote sensing of vegetation from the Earth Observing System (EOS) MODIS sensor. The same index can be used for remote sensing from Landsat TM and the EOS-HIRIS sensor. The index takes advantage of the presence of the blue channel (0.47.+or-0.01 mu m) in the MODIS sensor, in addition to the red (0.66+or-0.025 mu m) and the near-IR (0.865+or-0.02 mu m) channels that compose the present normalized difference vegetation index (NDVI). The resistance of the ARVI to atmospheric effects (in comparison to the NDVI) is accomplished by a self-correction process for the atmospheric effect on the red channel, using the difference in the radiance between the blue and the red channels to correct the radiance in the red channel. Simulations using radiative transfer computations on arithmetic and natural surface spectra, for various atmospheric conditions, show that ARVI has a similar dynamic range to the NDVI, but is, on average, four times less sensitive to atmospheric effects than the NDVI. >

The problem of remotely sensing the amount of solar radiation absorbed and reflected by vegetated land surfaces was investigated with the aid of one- and three-dimensional radiative transfer models. Desert vegetation was modeled as clumps of leaves randomly distributed on a bright dry soil with a ground cover of generally less than 100%. Surface albedo (ALB), fraction of photosynthetically active radiation absorbed by the canopy (FAPAR), fractions of solar radiation absorbed by the canopy (FASOLAR) and soil (FASOIL), and normalized difference vegetation index (NDVI) were calculated for various illumination conditions. The magnitude of errors involved in the estimation of surface albedo from broadband monodirectional measurements was assessed. The nature of the relationships between NDVI vs. FASOLAR, FAPAR, FASOIL, and ALB and their sensitivity to all problem parameters were investigated in order to develop simple predictive models. The relationship between NDVI measured above the atmosphere and that sensed above the canopy at the ground surface was studied to characterize atmospheric effects. >

Correction of Advanced Very High Resolution Radiometer (AVHRR) imagery for the aerosol effect requires retrieval of the aerosol loading from the images. Two retrieval algorithms that were previously developed for Landsat are modified for the AVHRR. The methods determine the aerosol optical thickness over land surfaces from AVHRR band one data independently of ancillary information. The first method retrieves aerosols based on the atmospheric effect on the path radiance. This method requires the surface reflectance to be 0.02+or-0.01, which is found over forests in the red channel. Two techniques are used to screen an AVHRR scene for pixels that have this low reflectance. The qualifying requirements for these techniques are discussed, and the method is demonstrated to retrieve aerosol optical thicknesses to approximately +or-0.1. The second method uses the change in contrast for several scenes to determine the change in the optical thickness between the scenes. A reference scene allows absolute determination. The method has an rms error of approximately 0.1. >

Investigation of the effect of atmospheric constituents on NOAA Advanced Very High Resolution Radiometer (AVHRR) visible and near-infrared data is presented. The general remote sensing equation, including scattering, absorption, and bidirectional reflectance effects for the AVHRR solar bands, is described. The magnitude of the atmospheric effects for AVHRR solar bands with respect to their impact on the normalized difference vegetation index (NDVI) and the surface bidirection reflectance is examined. Possible approaches for acquiring atmospheric information are discussed, and examples of atmospheric correction of surface reflectance and NDVI are given. Invariant effects (ozone absorption and molecular scattering) and variant effects (water vapor absorption and aerosol scattering) are shown to dominate the atmospheric effects in the AVHRR solar bands. >

The authors describe the status of MODIS-N and its companion instrument MODIS-T (tilt), a tiltable cross-track scanning spectrometer with 32 uniformly spaced channels between 0.410 and 0.875 mu m. They review the various methods being developed for the remote sensing of atmospheric properties using MODIS, placing primary emphasis on the principal atmospheric applications of determining the optical, microphysical, and physical properties of clouds and aerosol particles from spectral reflection and thermal emission measurements. In addition to cloud and aerosol properties, MODIS-N will be used for determining the total precipitable water vapor and atmospheric stability. The physical principles behind the determination of each of these atmospheric products are described, together with an example of their application to aircraft and/or satellite measurements. >

Variable atmospheric conditions have a significant impact on satellite monitoring of vegetation in the Sahelian zone of Africa. The effects of atmospheric O3, H2O, and aerosols on spectral, directional reflectances and derived measures, such as the normalized difference vegetation index are discussed using a sensitivity study. An atmospheric correction scheme is presented based on measurements of optical thicknesses from the ground and is applied to NOAA AVHRR data. The use of the reflectance of the ocean surface close to the terrestrial target to estimate atmospheric effects on terrestrial reflectance is also discussed.

The aim of this project is to improve the characterization of radiative and microphysical properties of aerosols and clouds in the atmosphere. These two atmospheric components and their interactions are among the main sources of uncertainty in the numerical forecast of climate change. In this context, we have designed a new airborne polarimeter for measuring directional, total and polarized radiances in the 440 to 2200 nm spectral range. This instrument is based on the POLDER concept, instrument that is currently aboard the PARASOL microsatellite. This new sensor consists in two optical systems for the visible to near infrared range (440 to 940 nm) and the shortwave infrared (940 to 2200 nm). Each optical system is composed of a wide field-of-view optics (114° and 105° respectively) associated to two rotating wheels for interferential filters and analysers respectively, and a 2D array of detectors. For each channel, the total and polarized radiances are computed using the measurements performed with the three analysers shifted by an angle of 60°. Thanks to the large field of view of the optics, any target is seen under several viewing angles during the aircraft motion. This type of instrument has been designed for the retrieval of optical thickness and microphysical properties of aerosols as well as for the determination of microphysical, macrophysical and radiative properties of clouds. In this paper, we will present this new instrument design and some preliminary results recently obtained during the first field campaign in May 2008 over Europe.

[1] Reflectance differences among Multiangle Imaging Spectroradiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra and Polarization and Directionality of the Earth's Reflectances (POLDER2) are characterized, as functions of observation geometry and spectral bands. For observations having similar geometry, corresponding normalized reflectances from MISR and MODIS fall within 3% for all bands except the MISR red band, which is higher than MODIS and POLDER2 by about 3.5%. POLDER2 and MODIS are within less than about 1% in the blue and red, 4% in the near-infrared, and 5% in the green. Generally, MISR reflectances are at the high end of the reflectance envelope, whereas POLDER2 tends to be at the low end, yielding a spread of about 5% in the red, 5% in the near-infrared, and over 7% in the green. Reflectance differences were not quantitatively corrected for instrument-to-instrument spectral band pass differences because of the uncertainties associated with such calculations. However, these uncertainties are assessed, and the envelopes can be used to bound calibration contributions to derived geophysical quantity uncertainties, including aerosol amount and type. This is of particular importance when data from the three instruments are used together in geophysical applications.