Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.
The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.
Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.
The aerosol products retrieved using the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semiarid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and nonvegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of precalculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semiarid regions to the entire land areas. In this paper, the changes made in the enhanced Deep Blue algorithm regarding the surface reflectance estimation, aerosol model selection, and cloud screening schemes for producing the MODIS collection 6 aerosol products are discussed. A similar approach has also been applied to the algorithm that generates the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue products. Based upon our preliminary results of comparing the enhanced Deep Blue aerosol products with the Aerosol Robotic Network (AERONET) measurements, the expected error of the Deep Blue aerosol optical thickness (AOT) is estimated to be better than 0.05 + 20%. Using 10 AERONET sites with long-term time series, 79% of the best quality Deep Blue AOT values are found to fall within this expected error.
de Leeuw, G.; Holzer-Popp, T.; Aerosol-cci Team
The Climate Change Initiative (cci) of the European Space Agency (ESA) has brought together a team of European Aerosol retrieval groups working on the development and improvement of aerosol retrieval algorithms. The goal of this cooperation is the development of methods to provide the best possible information on climate and climate change based on satellite observations. To achieve this, algorithms are characterized in detail as regards the retrieval approaches, the aerosol models used in each algorithm, cloud detection and surface treatment. A round-robin intercomparison of results from the various participating algorithms serves to identify the best modules or combinations of modules for each sensor. Annual global datasets including their uncertainties will then be produced and validated. The project builds on 9 existing algorithms to produce spectral aerosol optical depth (AOD and Ångström exponent) as well as other aerosol information; two instruments are included to provide the absorbing aerosol index (AAI) and stratospheric aerosol information. The algorithms included are: - 3 for ATSR (ORAC developed by RAL / Oxford university, ADV developed by FMI and the SU algorithm developed by Swansea University ) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for OMI retreival of the absorbing aerosol index with averaging kernel information (KNMI) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) The first seven algorithms aim at the retrieval of the AOD. However, each of the algorithms used differ in their approach, even for algorithms working with the same instrument such as ATSR or MERIS. To analyse the strengths and weaknesses of each algorithm several tests are made. The starting point for comparison and measurement of improvements is a retrieval run for 1 month, September 2008. The data from the same month are subsequently used for
Kosmale, Miriam; Popp, Thomas
Ensemble techniques are widely used in the modelling community, combining different modelling results in order to reduce uncertainties. This approach could be also adapted to satellite measurements. Aerosol_cci is an ESA funded project, where most of the European aerosol retrieval groups work together. The different algorithms are homogenized as far as it makes sense, but remain essentially different. Datasets are compared with ground based measurements and between each other. Three AATSR algorithms (Swansea university aerosol retrieval, ADV aerosol retrieval by FMI and Oxford aerosol retrieval ORAC) provide within this project 17 year global aerosol records. Each of these algorithms provides also uncertainty information on pixel level. Within the presented work, an ensembles of the three AATSR algorithms is performed. The advantage over each single algorithm is the higher spatial coverage due to more measurement pixels per gridbox. A validation to ground based AERONET measurements shows still a good correlation of the ensemble, compared to the single algorithms. Annual mean maps show the global aerosol distribution, based on a combination of the three aerosol algorithms. In addition, pixel level uncertainties of each algorithm are used for weighting the contributions, in order to reduce the uncertainty of the ensemble. Results of different versions of the ensembles for aerosol optical depth will be presented and discussed. The results are validated against ground based AERONET measurements. A higher spatial coverage on daily basis allows better results in annual mean maps. The benefit of using pixel level uncertainties is analysed.
Wang, Y.; Lyapustin, A.; Marshak, A.; Korkin, S.; Herman, J. R.
EPIC is a multi-spectral imager onboard planned Deep Space Climate ObserVatoRy (DSCOVR) designed for observations of the full illuminated disk of the Earth with high temporal and coarse spatial resolution (10 km) from Lagrangian L1 point. During the course of the day, EPIC will view the same Earth surface area in the full range of solar and view zenith angles at equator with fixed scattering angle near the backscattering direction. This talk will describe a new aerosol retrieval/atmospheric correction algorithm developed for EPIC and tested with EPIC Simulator data. This algorithm uses the time series approach and consists of two stages: the first stage is designed to periodically re-initialize the surface spectral bidirectional reflectance (BRF) on stable low AOD days. Such days can be selected based on the same measured reflectance between the morning and afternoon reciprocal view geometries of EPIC. On the second stage, the algorithm will monitor the diurnal cycle of aerosol optical depth and fine mode fraction based on the known spectral surface BRF. Testing of the developed algorithm with simulated EPIC data over continental USA showed a good accuracy of AOD retrievals (10-20%) except over very bright surfaces.
Wang, Yujie; Lyapustin, Alexei; Marshak, Alexander; Korkin, Sergey; Herman, Jay
EPIC is a multi-spectral imager onboard planned Deep Space Climate ObserVatoRy (DSCOVR) designed for observations of the full illuminated disk of the Earth with high temporal and coarse spatial resolution (10 km) from Lagrangian L1 point. During the course of the day, EPIC will view the same Earth surface area in the full range of solar and view zenith angles at equator with fixed scattering angle near the backscattering direction. This talk will describe a new aerosol retrieval/atmospheric correction algorithm developed for EPIC and tested with EPIC Simulator data. This algorithm uses the time series approach and consists of two stages: the first stage is designed to periodically re-initialize the surface spectral bidirectional reflectance (BRF) on stable low AOD days. Such days can be selected based on the same measured reflectance between the morning and afternoon reciprocal view geometries of EPIC. On the second stage, the algorithm will monitor the diurnal cycle of aerosol optical depth and fine mode fraction based on the known spectral surface BRF. Testing of the developed algorithm with simulated EPIC data over continental USA showed a good accuracy of AOD retrievals (10-20%) except over very bright surfaces.
Wahab, A. M.; Sarker, M. L. R.
Atmospheric aerosol plays an important role in radiation budget, climate change, hydrology and visibility. However, it has immense effect on the air quality, especially in densely populated areas where high concentration of aerosol is associated with premature death and the decrease of life expectancy. Therefore, an accurate estimation of aerosol with spatial distribution is essential, and satellite data has increasingly been used to estimate aerosol optical depth (AOD). Aerosol product (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) data is available at global scale but problems arise due to low spatial resolution, time-lag availability of AOD product as well as the use of generalized aerosol models in retrieval algorithm instead of local aerosol models. This study focuses on the aerosol retrieval algorithm for the characterization of local aerosol in Hong Kong for a long period of time (2006-2011) using high spatial resolution MODIS level 1B data (500 m resolution) and taking into account the local aerosol models. Two methods (dark dense vegetation and MODIS land surface reflectance product) were used for the estimation of the surface reflectance over land and Santa Barbara DISORT Radiative Transfer (SBDART) code was used to construct LUTs for calculating the aerosol reflectance as a function of AOD. Results indicate that AOD can be estimated at the local scale from high resolution MODIS data, and the obtained accuracy (ca. 87%) is very much comparable with the accuracy obtained from other studies (80%-95%) for AOD estimation.
Limbacher, J. A.; Kahn, R. A.
We explore systematically the cumulative effect of many assumptions made in the Multi-angle Imaging SpectroRadiometer (MISR) research aerosol retrieval algorithm with the aim of quantifying the main sources of uncertainty over ocean, and correcting them to the extent possible. A total of 1129 coincident, surface-based sun photometer spectral aerosol optical depth (AOD) measurements are used for validation. Based on comparisons between these data and our baseline case (similar to the MISR standard algorithm, but without the "modified linear mixing" approximation), for 558 nm AOD < 0.10, a high bias of 0.024 is reduced by about one-third when (1) ocean surface under-light is included and the assumed whitecap reflectance at 672 nm is increased, (2) physically based adjustments in particle microphysical properties and mixtures are made, (3) an adaptive pixel selection method is used, (4) spectral reflectance uncertainty is estimated from vicarious calibration, and (5) minor radiometric calibration changes are made for the 672 and 866 nm channels. Applying (6) more stringent cloud screening (setting the maximum fraction not-clear to 0.50) brings all median spectral biases to about 0.01. When all adjustments except more stringent cloud screening are applied, and a modified acceptance criterion is used, the Root-Mean-Square-Error (RMSE) decreases for all wavelengths by 8-27% for the research algorithm relative to the baseline, and is 12-36% lower than the RMSE for the Version 22 MISR standard algorithm (SA, with no adjustments applied). At 558 nm, 87% of AOD data falls within the greater of 0.05 or 20% of validation values; 62% of the 446 nm AOD data, and > 68% of 558, 672, and 866 nm AOD values fall within the greater of 0.03 or 10%. For the Ångström exponent (ANG), 67% of 1119 validation cases for AOD > 0.01 fall within 0.275 of the sun photometer values, compared to 49% for the SA. ANG RMSE decreases by 17% compared to the SA, and the median absolute error drops by
Nelson, R.; O'Dell, C. W.; Frankenberg, C.; Oshchepkov, S.; Bril, A.; Yokota, T.; Yoshida, Y.; Butz, A.; Guerlet, S.; Boesch, H.; Parker, R.
Spaced-based near-infrared measurements of greenhouse gases such as carbon dioxide and methane are now routinely made from the Greenhouse Gases Observing Satellite (GOSAT) via an assortment of retrieval algorithms. The measurements are based on assumed knowledge of the light paths followed by the measured solar photons, paths which can be altered in the presence of clouds and aerosols. Most algorithms therefore attempt to simultaneously retrieval aerosol information alongside the desired gas concentrations, in an attempt to mitigate errors caused by atmospheric scattering. However, recent studies have hinted that most algorithms tend to retrieve biased aerosol information over certain surface types (such as bright surfaces), leading in particular to biased estimates of the column-averaged dry air mole fraction of carbon dioxide (XCO2). In this work, we compare GOSAT-retrieved AEROSOL properties from multiple XCO2 retrieval algorithms with those of the well-validated AERONET sun photometer network. We present a correlation analysis of retrieved aerosol errors and their effect on retrieved XCO2, as a function of multiple variables such as surface type and viewing geometry, with the goal of providing critical information on how best to deal with aerosols in the context of these challenging greenhouse gas retrievals.
Mao, Jiandong; Li, Jinxuan
Particle size distribution is essential for describing direct and indirect radiation of aerosols. Because the relationship between the aerosol size distribution and optical thickness (AOT) is an ill-posed Fredholm integral equation of the first type, the traditional techniques for determining such size distributions, such as the Phillips-Twomey regularization method, are often ambiguous. Here, we use an approach based on an improved particle swarm optimization algorithm (IPSO) to retrieve aerosol size distribution. Using AOT data measured by a CE318 sun photometer in Yinchuan, we compared the aerosol size distributions retrieved using a simple genetic algorithm, a basic particle swarm optimization algorithm and the IPSO. Aerosol size distributions for different weather conditions were analyzed, including sunny, dusty and hazy conditions. Our results show that the IPSO-based inversion method retrieved aerosol size distributions under all weather conditions, showing great potential for similar size distribution inversions.
Russell, Philip B.; Kacenelenbogen, Meloe; Livingston, John M.; Hasekamp, Otto P.; Burton, Sharon P.; Schuster, Gregory L.; Johnson, Matthew S.; Knobelspiesse, Kirk D.; Redemann, Jens; Ramachandran, S.; Holben, Brent
In this presentation, we demonstrate application of a new aerosol classification algorithm to retrievals from the POLDER-3 polarimter on the PARASOL spacecraft. Motivation and method: Since the development of global aerosol measurements by satellites and AERONET, classification of observed aerosols into several types (e.g., urban-industrial, biomass burning, mineral dust, maritime, and various subtypes or mixtures of these) has proven useful to: understanding aerosol sources, transformations, effects, and feedback mechanisms; improving accuracy of satellite retrievals and quantifying assessments of aerosol radiative impacts on climate.
Kim, Woogyung; kim, Jhoon; Jung, Yeonjin; lee, Hanlim; Boesch, Hartmut
Human activities have resulted in increasing atmospheric CO2 concentration since the beginning of Industrial Revolution to reaching CO2 concentration over 400 ppm at Mauna Loa observatory for the first time. (IPCC, 2007). However, our current knowledge of carbon cycle is still insufficient due to lack of observations. Satellite measurement is one of the most effective approaches to improve the accuracy of carbon source and sink estimates by monitoring the global CO2 distributions with high spatio-temporal resolutions (Rayner and O'Brien, 2001; Houweling et al., 2004). Currently, GOSAT has provided valuable information to observe global CO2 trend, enables our extended understanding of CO2 and preparation for future satellite plan. However, due to its physical limitation, GOSAT CO2 retrieval results have low spatial resolution and cannot cover wide area. Another obstruction of GOSAT CO2 retrieval is low data availability mainly due to contamination by clouds and aerosols. Especially, in East Asia, one of the most important aerosol source areas, it is hard to have successful retrieval result due to high aerosol concentration. The main purpose of this study is to improve data availability of GOSAT CO2 retrieval. In this study, current state of CO2 retrieval algorithm development is introduced and preliminary results are shown. This algorithm is based on optimal estimation method and utilized VLIDORT the vector discrete ordinate radiative transfer model. This proto type algorithm, developed from various combinations of state vectors to find accurate CO2 concentration, shows reasonable result. Especially the aerosol retrieval algorithm using GOSAT-CAI measurements, which provide aerosol information for the same area with GOSAT-FTS measurements, are utilized as input data of CO2 retrieval. Other CO2 retrieval algorithms use chemical transport model result or climatologically expected values as aerosol information which is the main reason of low data availability. With
Lyapustin, Alexei; Wang, Yujie
Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the
Nelson, R. R.; O'Dell, C.; Crisp, D.; Eldering, A.; Frankenberg, C.; Gunson, M. R.; Natraj, V.; Fu, D.
An effective parameterization of clouds and aerosols in retrieval algorithms is essential for reducing measurement errors and biases in estimates of the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from space-based measurements of near-infrared reflected sunlight. The NASA Atmospheric CO2 Observations from Space (ACOS) XCO2 retrieval algorithm has evolved significantly over the past several years in an effort to more accurately represent the impact of clouds and aerosols on XCO2. Recent ACOS algorithm versions up to build 3.4 used a water cloud type, ice cloud type, and two generic aerosol types for each sounding. ACOS build 3.5 uses the same cloud parameterization, but was modified to replace the "one-size-fits-all" aerosol scheme. Build 3.5 uses a monthly aerosol climatology based on the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis to choose the two most likely aerosol types for a given measurement location, along with typical optical depths. The five MERRA types available for selection are sulfate, dust, sea salt, organic carbon, and black carbon. The algorithm then uses a pre-assigned Gaussian width and height and fits for the aerosol amount and peak height based on information from the 760 nm O2 A-band and the CO2 bands centered near 1610 and 2060 nm. Here we compare ACOS builds 3.4 and build 3.5 to quantify the impact of the aerosol scheme update. Two types of tests were performed. Simulated Orbiting Carbon Observatory 2 (OCO-2) retrievals and their associated aerosol and cloud profiles were compared to the "true" aerosol and cloud profiles used to create the simulated environment for a given measurement. The retrieval algorithms were also run on Greenhouse gases Observing SATellite (GOSAT) observations and compared to AErosol RObotic NETwork (AERONET) aerosol optical depth measurements in order to quantify the ability of the algorithms to retrieve information about aerosol optical depths. XCO2 errors
Sogacheva, Larisa; De Leeuw, Gerrit; Kolmonen, Pekka; Virtanen, Timo H.; Saponaro, Giulia; Kokhanovsky, Alexander
Aerosols and clouds play an important role in radiative transfer and are key elements of the water and energy cycles. The interactions between aerosol particles and cloud drops are critical to identifying the earth radiation budget. Accurate evaluation of the effects of aerosols and clouds on climate requires global information on aerosol properties which can only be provided using satellite remote sensing. Among the satellite instruments used for aerosol and cloud retrieval is the (Advanced) Along-Track Scanning Radiometer ((A)ATSR) on board the European Space Agency (ESA) satellite ENVISAT (1997-2012). (A)ATSR measures top-of-the-atmosphere (TOA) radiances at 7 wavelengths in the spectral range from the visible to the thermal infrared. It has two views, one at nadir and the other one at 55o forward view; conical scan covers a swath of 512 km. The (A)ATSR resolution is 1 km at nadir. The aerosol retrieval algorithm (dual-view over land and single-view over ocean) was constructed for ATSR-2 data (e.g. Veefkind et al. 1998). The most recent version of ADV (AATSR Dual View) is described in Kolmonen et al. (2013). The (A)ATSR dual-view allows retrieval without prior information about land surface reflectance. A semi-analytical cloud retrieval algorithm using backscattered radiation in 0.4-2.4 μm spectral region has been implemented to ADV for the determination of the optical thickness, the liquid water path, and the effective size of droplets from spectral measurements of the intensity of light reflected from water clouds with large optical thickness. In AacDV ((A)ATSR aerosol and cloud Dual View) aerosol and cloud retrievals are combined. Cloud retrieval starts when cloud tests for aerosol retrieval show the presence of clouds. The algorithm was early introduced in Kokhanovsky et al. (2003). It works well for thick clouds. In addition to cloud properties, cloud top height is estimated using information from both nadir and forward views. AacDV has been successfully
Gupta, Pawan; Levy, Robert C.; Mattoo, Shana; Remer, Lorraine A.; Munchak, Leigh A.
The MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aboard the two Earth Observing System (EOS) satellites Terra and Aqua, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 and 3 km). Almost 15 years of aerosol data records are now available from MODIS that can be used for various climate and air-quality applications. However, the application of MODIS aerosol products for air-quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. This is largely because the urban surface reflectance behaves differently than that assumed for natural surfaces. In this study, we address the inaccuracies produced by the MODIS Dark Target (MDT) algorithm aerosol optical depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating MODIS Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the continental United States (CONUS). The new surface scheme takes into account the change in underlying surface type and is only applied for MODIS pixels with urban percentage (UP) larger than 20 %. Over the urban areas where the new scheme has been applied (UP > 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sun photometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation.
Choi, M.; Kim, J.; Lee, J.; Kim, M.; Park, Y. Je; Jeong, U.; Kim, W.; Holben, B.; Eck, T. F.; Lim, J. H.; Song, C. K.
The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorology Satellites (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm over ocean and land together with validation results during the DRAGON-NE Asia 2012 campaign. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type from selected aerosol models in calculating AOD. Assumed aerosol models are compiled from global Aerosol Robotic Networks (AERONET) inversion data, and categorized according to AOD, FMF, and SSA. Nonsphericity is considered, and unified aerosol models are used over land and ocean. Different assumptions for surface reflectance are applied over ocean and land. Surface reflectance over the ocean varies with geometry and wind speed, while surface reflectance over land is obtained from the 1-3 % darkest pixels in a 6 km × 6 km area during 30 days. In the East China Sea and Yellow Sea, significant area is covered persistently by turbid waters, for which the land algorithm is used for aerosol retrieval. To detect turbid water pixels, TOA reflectance difference at 660 nm is used. GOCI YAER products are validated using other aerosol products from AERONET and the MODIS Collection 6 aerosol data from "Dark Target (DT)" and "Deep Blue (DB)" algorithms during the DRAGON-NE Asia 2012 campaign from March to May 2012. Comparison of AOD from GOCI and AERONET gives a Pearson correlation coefficient of 0.885 and a linear regression equation with GOCI AOD =1.086 × AERONET AOD - 0.041. GOCI and MODIS AODs are more highly correlated
Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.; Song, Chul H.; Lim, Jae-Hyun; Song, Chang-Keun
The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGON-NE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 × AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better
Jeong, U; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.
An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional lookup tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OEbased estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.
Jeong, U.; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.
An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional look-up tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OE-based estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.
He, Zhenzong; Qi, Hong; Yao, Yuchen; Ruan, Liming
The Ant Colony Optimization algorithm based on the probability density function (PDF-ACO) is applied to estimate the bimodal aerosol particle size distribution (PSD). The direct problem is solved by the modified Anomalous Diffraction Approximation (ADA, as an approximation for optically large and soft spheres, i.e., χ≫1 and |m-1|≪1) and the Beer-Lambert law. First, a popular bimodal aerosol PSD and three other bimodal PSDs are retrieved in the dependent model by the multi-wavelength extinction technique. All the results reveal that the PDF-ACO algorithm can be used as an effective technique to investigate the bimodal PSD. Then, the Johnson's SB (J-SB) function and the modified beta (M-β) function are employed as the general distribution function to retrieve the bimodal PSDs under the independent model. Finally, the J-SB and M-β functions are applied to recover actual measurement aerosol PSDs over Beijing and Shanghai obtained from the aerosol robotic network (AERONET). The numerical simulation and experimental results demonstrate that these two general functions, especially the J-SB function, can be used as a versatile distribution function to retrieve the bimodal aerosol PSD when no priori information about the PSD is available.
Mukai, Sonoyo; Sano, Itaru; Yasumoto, Masayoshi; Fujito, Toshiyuki; Nakata, Makiko; Kokhanovsky, Alexander
The Japan Aerospace Exploration Agency (JAXA) has been developing the new Earth observing system, GCOM (Global Change Observation Mission) project, which consists of two satellite series of GCOM-W1 and GCOM-C1. The 1st GCOM-C satellite will board the SGLI (second generation global imager) which also includes polarimetric sensor and be planed to launch in early of 2017. The SGLI has multi (19)-channels including near UV channel (380 nm) and two polarization channels at red and near-infrared wavelengths of 670 and 870 nm. EUMETSAT plans to collect polarization measurements with a POLDER follow on 3MI / EPS-SG in 2021. Then the efficient retrieval algorithms for aerosol and/or cloud based on the combination use of radiance and polarization are strongly expected. This work focuses on serious biomass burning episodes in East Asia. It is noted that the near UV measurements are available for detection of the carbonaceous aerosols. The biomass burning aerosols (BBA) generated by forest fire and/or agriculture biomass burning have influenced on the severe air pollutions. It is known that the forest fire increases due to global warming and a climate change, and has influences on them vice versa. It is well known that this negative cycle decreases the quality of global environment and human health. We intend to consider not only retrieval algorithms of remote sensing for severe air pollutions but also detection and/or distinction of aerosols and clouds, because mixture of aerosols and clouds are often occurred in the severe air pollutions. Then precise distinction of aerosols and clouds, namely aerosols in cloudy scenes and/or clouds in heavy aerosol episode, is desired. Aerosol retrieval in the hazy atmosphere has been achieved based on radiation simulation method of successive order of scattering 1,2. In this work, we use both radiance and polarization measurements observed by GLI and POLDER-2 on Japanese ADEOS-2 satellite in 2003 as a simulated data. As a result the
Nanda, Swadhin; Sanders, Abram; Veefkind, Pepijn
The Sentinel-4 mission is a part of the European Commission's Copernicus programme, the goal of which is to provide geo-information to manage environmental assets, and to observe, understand and mitigate the effects of the changing climate. The Sentinel-4/UVN instrument design is motivated by the need to monitor trace gas concentrations and aerosols in the atmosphere from a geostationary orbit. The on-board instrument is a high resolution UV-VIS-NIR (UVN) spectrometer system that provides hourly radiance measurements over Europe and northern Africa with a spatial sampling of 8 km. The main application area of Sentinel-4/UVN is air quality. One of the data products that is being developed for Sentinel-4/UVN is the Aerosol Layer Height (ALH). The goal is to determine the height of aerosol plumes with a resolution of better than 0.5 - 1 km. The ALH product thus targets aerosol layers in the free troposphere, such as desert dust, volcanic ash and biomass during plumes. KNMI is assigned with the development of the Aerosol Layer Height (ALH) algorithm. Its heritage is the ALH algorithm developed by Sanders and De Haan (ATBD, 2016) for the TROPOMI instrument on board the Sentinel-5 Precursor mission that is to be launched in June or July 2016 (tentative date). The retrieval algorithm designed so far for the aerosol height product is based on the absorption characteristics of the oxygen-A band (759-770 nm). The algorithm has heritage to the ALH algorithm developed for TROPOMI on the Sentinel 5 precursor satellite. New aspects for Sentinel-4/UVN include the higher resolution (0.116 nm compared to 0.4 for TROPOMI) and hourly observation from the geostationary orbit. The algorithm uses optimal estimation to obtain a spectral fit of the reflectance across absorption band, while assuming a single uniform layer with fixed width to represent the aerosol vertical distribution. The state vector includes amongst other elements the height of this layer and its aerosol optical
Dubovik, Oleg; Litvinov, Pavel; Lapyonok, Tatyana; Ducos, Fabrice; Aspetsberger, Michael; Planer, Wolfgang; Federspiel, Christian; Fuertes, David
The GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm has been developed for enhanced characterization of the properties of both aerosol and land surface from diverse remote sensing observations. The concept of the algorithm is described in details by Dubovik et al. (2011). The algorithm is based on highly advanced statistically optimized fitting implemented as Multi-Term Least Square minimization (Dubovik, 2004) and deduces nearly 50 unknowns for each observed site. The algorithm derives a set of aerosol parameters similar to that derived by AERONET including detailed particle size distribution, the spectral dependence on the complex index of refraction and the fraction of non-spherical particles. The algorithm uses detailed aerosol and surface models and fully accounts for all multiple interactions of scattered solar light with aerosol, gases and the underlying surface. All calculations are done on-line without using traditional look-up tables. In addition, the algorithm can use the new multi-pixel concept - a simultaneous fitting of a large group of pixels with additional constraints limiting the time variability of surface properties and spatial variability of aerosol properties. This principle provides a possibility to improve retrieval for multiple observations even if the observations are not exactly co-incident or co-located. Significant efforts have been spent for optimization and speedup of the GRASP computer routine and retrievals from satellite observations. For example, the routine has been adapted for running at GPGPUs accelerators. Originally GRASP has been developed for POLDER/PARASOL multi-viewing imager and later adapted to a number of other satellite sensors such as MERIS at polar-orbiting platform and COCI/GOMS geostationary observations. The results of numerical tests and results of applications to real data will be presented. REFERENCES: Dubovik, et al.,“Statistically optimized inversion algorithm for enhanced
Lee, Jaehwa; Hsu, Nai-Yung Christina; Sayer, Andrew Mark; Bettenhausen, Corey
A strategy for retrieving aerosol optical depth (AOD) under conditions of thin cirrus coverage from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. We adopt an empirical method that derives the cirrus contribution to measured reflectance in seven bands from the visible to shortwave infrared (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 µm, commonly used for AOD retrievals) by using the correlations between the top-of-atmosphere (TOA) reflectance at 1.38 micron and these bands. The 1.38 micron band is used due to its strong absorption by water vapor and allows us to extract the contribution of cirrus clouds to TOA reflectance and create cirrus-corrected TOA reflectances in the seven bands of interest. These cirrus-corrected TOA reflectances are then used in the aerosol retrieval algorithm to determine cirrus-corrected AOD. The cirrus correction algorithm reduces the cirrus contamination in the AOD data as shown by a decrease in both magnitude and spatial variability of AOD over areas contaminated by thin cirrus. Comparisons of retrieved AOD against Aerosol Robotic Network observations at Nauru in the equatorial Pacific reveal that the cirrus correction procedure improves the data quality: the percentage of data within the expected error +/-(0.03 + 0.05 ×AOD) increases from 40% to 80% for cirrus-corrected points only and from 80% to 86% for all points (i.e., both corrected and uncorrected retrievals). Statistical comparisons with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals are also carried out. A high correlation (R = 0.89) between the CALIOP cirrus optical depth and AOD correction magnitude suggests potential applicability of the cirrus correction procedure to other MODIS-like sensors.
Gupta, P.; Levy, R. C.; Mattoo, S.
Urban air quality in many parts of the globe has reached at dangerous level (5 to 10 times higher than WHO guidelines) as urbanization and industrialization have amplified many folds during the last few decades. More than half of the world's population now lives in urban areas and their number will increase 60% by 2030. Therefore it is very critical to monitor air quality (aerosol or PM) on a daily basis; especially in populated regions (urban areas) around the world. The new version (C6) of MODIS Dark Target Land Aerosol Algorithm (MDT) provides aerosol optical depth (AOD) retrievals at 10km2 and 3km2 spatial resolutions over dark vegetated regions. Initial validation efforts during DISCOVER-AQ field campaign over Baltimore-DC area shows that MDT overestimates AOD over urban areas, mainly because the bright and complex urban surface is not characterized properly. Accurate estimation of the surface signal within satellite-measured radiance is essential for aerosol retrieval. Surface characterization can be challenging and small error (~0.01) can produce large errors in retrieved AOD (~0.1). In this new approach, we have modified the surface characterization for urban areas, using the urban percentage information from the MODIS Land Product. We used the MODIS land surface spectral reflectance product to redefine the relationship between shortwave-IR and visible wavelengths over urban areas. We derived new surface characterization for urban area and used the DRAGON network measurements, during DISCOVER-AQ field campaigns, to validate the new AOD retrievals both in 10km and 3km spatial resolution. Initial inter-comparison with AERONET data over US shows significant improvement in AOD retrieval over urban areas. This improved AOD retrieval will be an important step toward utilization of satellite based particulate matter estimation for surface air quality monitoring. We also evaluate whether the new 3km product can enable studies of small-scale gradients in aerosol
Wang, J.; Zhu, J.; Xia, X.; Chen, H.; Zhang, J.; Xu, X.; Oo, M. M.; Holz, R.; Levy, R. C.
After the launch of Suomi National Polar-orbiting Partnership (S-NPP) equipped with the Visible Infrared Imaging Radiometer Suit (VIIRS) instrument in late 2011, the aerosol products of VIIRS have received much attention. Currently there are two aerosol products of VIIRS by using different algorithms: VIIRS Environment Data Record data (VIIRS_EDR) and aerosol products by applying MODIS-like algorithm to VIIRS (VIIRS_ML). In this study, the aerosol optical depth (AOD) at 550nm and properties of aerosol models used in the two VIIRS algorithms (VIIRS_EDR and VIIRS_ML) are compared respectively with their corresponding quantities retrieved from the ground-based Sunphotometer measurements (CE318) during May 2012-March 2014 at three sites over North China Plain (NCP): metropolis-Beijing, suburban-XiangHe and regional background site-Xinglong. The results show that the VIIRS_EDR AOD has a positive mean bias (MB) of 0.04-0.06 and the root mean square error (RMSE) of 0.22-0.24 in NCP region. Among three sites, the largest MB (0.10-0.15) and RMSE (0.27-0.30) are observed in Beijing. The results of evaluation of VIIRS_ML for each site and quality flags analysis are similar to VIIRS_EDR, but in general the VIIRS_ML AOD shows better than VIIRS_EDR except for the MB (0.13-0.14). The model comparisons show that the occurrence percentages of both dust and clean urban aerosol in VIIRS_EDR (82% for Beijing, 73% for XiangHe and 50% for Xinglong) are significantly larger than that for CE318, the latter shows the polluted urban aerosol is the dominant aerosol especially for Beijing (67%) and XiangHe (59%) sites. The values of Single Scattering albedo (SSA) from VIIRS_EDR are higher than from CE318 in all aerosol modes, with a positive bias of 0.03-0.06 for fine mode, 0.18-0.22 for coarse model and 0.03-0.08 for total modes and the aerosol microphysical properties used in the VIIRS_EDR algorithm for AOD retrieval show a large difference with the counterparts from CE318 inversion results
Russell, P. B.; Kacenelenbogen, M. S.; Livingston, J. M.; Hasekamp, O.; Burton, S. P.; Schuster, G. L.; Redemann, J.; Ramachandran, S.; Holben, B. N.
In this presentation we demonstrate application of a new aerosol classification algorithm to retrievals from the POLDER-3 polarimeter on the PARASOL spacecraft. Motivation and method: Since the development of global aerosol measurements by satellites and AERONET, classification of observed aerosols into several types (e,g., urban-industrial, biomass burning, mineral dust, maritime, and various subtypes or mixtures of these) has proven useful to: understanding aerosol sources, transformations, effects, and feedback mechanisms; improving accuracy of satellite retrievals; and quantifying assessments of aerosol radiative impacts on climate. With ongoing improvements in satellite measurement capability, the number of aerosol parameters retrieved from spaceborne sensors has been growing, from the initial aerosol optical depth at one or a few wavelengths to a list that now includes complex refractive index, single scattering albedo (SSA), and depolarization of backscatter, each at several wavelengths; wavelength dependences of extinction, scattering, absorption, SSA, and backscatter; and several particle size and shape parameters. Making optimal use of these varied data products requires objective, multi-dimensional analysis methods. We describe such a method, which uses a modified Mahalanobis distance to quantify how far a data point described by N aerosol parameters is from each of several prespecified classes. The method makes explicit use of uncertainties in input parameters, treating a point and its N-dimensional uncertainty as an extended data point or pseudo-cluster E. It then uses a modified Mahalanobis distance, DEC, to assign that observation to the class (cluster) C that has minimum DEC from the point (equivalently, the class to which the point has maximum probability of belonging). The method also uses Wilks' overall lambda to indicate how well the input data lend themselves to separation into classes and Wilks' partial lambda to indicate the relative
Zhang, H.; Lyapustin, A.; Wang, Y.; Kondragunta, S.; Laszlo, I.; Ciren, P.; Hoff, R. M.
Aerosol optical depth (AOD) retrievals from geostationary satellites have high temporal resolution compared to the polar orbiting satellites and thus enable us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosols and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) in the channel 1 of GOES is proportional to seasonal average MODIS BRDF in the 2.1 μm channel. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of AOD and surface reflectance retrievals are evaluated through comparisons against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US with correlation coefficients ranges from 0.71 to 0.85 at five out of six sites. At the two western sites Railroad Valley and UCSB, the MAIAC AOD retrievals have correlations of 0.8 and 0.85 with AERONET AOD, and are more accurate than GASP retrievals, which have correlations of 0.7 and 0.74 with AERONET AOD. At the three eastern sites, the correlations with AERONET AOD are from 0.71 to 0.81, comparable to the GASP retrievals. In the western US where surface reflectance is higher than 0.15, the new algorithm also produces larger AOD retrieval coverage
Xu, Xiaoguang; Wang, Jun; Zeng, Jing; Spurr, Robert; Liu, Xiong; Dubovik, Oleg; Li, Li; Li, Zhengqiang; Mishchenko, Michael I.; Siniuk, Aliaksandr; Holben, Brent N.
A 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 algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves 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 coarsemodes,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.
Zhang, H.; Lyapustin, A.; Wang, Y.; Kondragunta, S.; Laszlo, I.; Ciren, P.; Hoff, R. M.
Aerosol optical depth (AOD) retrieval from geostationary satellites has high temporal resolution compared to the polar orbiting satellites and thus enables us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosol and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified multi-angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) at channel 1 of GOES is proportional to seasonal average BRDF in the 2.1 μm channel from MODIS. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of the AOD and surface reflectance retrievals are evaluated through comparison against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US. They are comparable to the GASP retrievals in the eastern-central sites and are more accurate than GASP retrievals in the western sites. In the western US where surface reflectance is high, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.
Levy, Robert C.; Remer, Lorraine A.; Mattoo, Shana; Vermote, Eric F.; Kaufman, Yoram J.
Since first light in early 2000, operational global quantitative retrievals of aerosol properties over land have been made from MODIS observed spectral reflectance. These products have been continuously evaluated and validated, and opportunities for improvements have been noted. We have replaced the original algorithm by improving surface reflectance assumptions, the aerosol model optical properties and the radiative transfer code used to create the lookup tables. The new algorithm (known as Version 5.2 or V5.2) performs a simultaneous inversion of two visible (0.47 and 0.66 micron) and one shortwave-IR (2.12 micron) channel, making use of the coarse aerosol information content contained in the 2.12 micron channel. Inversion of the three channels yields three nearly independent parameters, the aerosol optical depth (tau) at 0.55 micron, the non-dust or fine weighting (eta) and the surface reflectance at 2.12 micron. Finally, retrievals of small magnitude negative tau values (down to -0.05) are considered valid, thus normalizing the statistics of tau in near zero tau conditions. On a 'test bed' of 6300 granules from Terra and Aqua, the products from V5.2 show marked improvement over those from the previous versions, including much improved retrievals of tau, where the MODIS/AERONET tau (at 0.55 micron) regression has an equation of: y = 1.01+0.03, R = 0.90. Mean tau for the test bed is reduced from 0.28 to 0.21.
Jeong, U.; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.
An online version of the OMI (Ozone Monitoring Instrument) near-ultraviolet (UV) aerosol retrieval algorithm was developed to retrieve aerosol optical thickness (AOT) and single scattering albedo (SSA) based on the optimal estimation (OE) method. Instead of using the traditional look-up tables for radiative transfer calculations, it performs online radiative transfer calculations with the Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model to eliminate interpolation errors and improve stability. The OE-based algorithm has the merit of providing useful estimates of uncertainties simultaneously with the inversion products. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in Northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved AOT and SSA. The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The estimated retrieval noise and smoothing error perform well in representing the envelope curve of actual biases of AOT at 388 nm between the retrieved AOT and AERONET measurements. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface albedo at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for future studies.
Jäkel, E.; Mey, B.; Levy, R.; Gu, X.; Yu, T.; Li, Z.; Althausen, D.; Heese, B.; Wendisch, M.
MODIS (MOderate-resolution Imaging Spectroradiometer) retrievals of aerosol optical depth (AOD) are biased over urban areas, primarily because the reflectance characteristics of urban surfaces are different than that assumed by the retrieval algorithm. Specifically, the operational "dark-target" retrieval is tuned towards vegetated (dark) surfaces and assumes a spectral relationship to estimate the surface reflectance in blue and red wavelengths. From airborne measurements of surface reflectance over the city of Zhongshan, China, were collected that could replace the assumptions within the MODIS retrieval algorithm. The subsequent impact was tested upon two versions of the operational algorithm, Collections 5 and 6 (C5 and C6). AOD retrieval results of the operational and modified algorithms were compared for a specific case study over Zhongshan to show minor differences between them all. However, the Zhongshan-based spectral surface relationship was applied to a much larger urban sample, specifically to the MODIS data taken over Beijing between 2010 and 2014. These results were compared directly to ground-based AERONET (AErosol RObotic NETwork) measurements of AOD. A significant reduction of the differences between the AOD retrieved by the modified algorithms and AERONET was found, whereby the mean difference decreased from 0.27±0.14 for the operational C5 and 0.19±0.12 for the operational C6 to 0.10±0.15 and -0.02±0.17 by using the modified C5 and C6 retrievals. Since the modified algorithms assume a higher contribution by the surface to the total measured reflectance from MODIS, consequently the overestimation of AOD by the operational methods is reduced. Furthermore, the sensitivity of the MODIS AOD retrieval with respect to different surface types was investigated. Radiative transfer simulations were performed to model reflectances at top of atmosphere for predefined aerosol properties. The reflectance data were used as input for the retrieval methods. It
Bilal, Muhammad; Nichol, Janet E.
This study evaluates the performance of different MODerate resolution Imaging Spectroradiometer (MODIS) aerosol algorithms during fine particle pollution events over the Beijing-Tianjin-Hebei region using Aerosol Robotic Network aerosol optical depth (AOD). These algorithms include the Deep Blue (DB) Collection 5.1 (C5) and Collection 6 (C6) algorithms at 10 km resolution, the Dark Target (DT) C5 and C6 algorithms at 10 km, the DT C6 algorithm at 3 km, and the Simplified Aerosol Retrieval Algorithm (SARA) at 500 m, 3 km, and 10 km resolutions. The DB C6 retrievals have 34-39% less uncertainties, 2-3 times smaller root-mean-square error (RMSE), and 3-4 times smaller mean absolute error (MAE) than DB C5 retrievals. The DT C6 has 4-8% lower bias, 4-12% less overestimation, and smaller RMSE and MAE errors than DT C5. Due to underestimation of surface reflectance and the use of inappropriate aerosol schemes, 87-89% of the collocations of the DT C6 at 3 km fall above the expected error (EE), with overestimation of 64-79% which is 15-27% higher than that for the DT C6 at 10 km. The results suggest that the DT C6 at 3 km resolution is less reliable than that at 10 km. The SARA AOD has small RMSE and MAE errors with 90-96% of the collocations falling within the EE. Overall, the SARA showed 15-16% less uncertainty than the DB C6 (10 km), 69-72% less than the DT C6 (10 km), and 79-83% less than the DT C6 (3 km) retrievals.
Träger-Chatterjee, Christine; Müller, Richard W.; Trentmann, Jörg
The Satellite Application Facility on Climate Monitoring (CM SAF) provides long-term climate datasets of surface solar radiation for more than 30 years retrieved from MVIRI and SEVIRI instruments on board the METEOSAT first and second generation satellites, respectively. The surface solar radiation is retrieved using the SPECMAGIC algorithm. The SPECMAGIC method is composed of the Heliosat approach to calculate the cloud transmission and a clear sky model. The Heliosat approach as well as the SPECMAGIC method will be described in the presentation "The SPECMAGIC algorithm for the retrieval of spectrally resolved surface radiation, overview and applications" by R. Müller in this session. The clear sky model SPECMAGIC consists of look-up tables calculated with the radiative transfer model libradtran for the consideration of aerosol as well as water vapour and ozone. The effect of four different state of the art aerosol data sources on the accuracy of surface solar radiation derived with SPECMAGIC is evaluated. The respective results are compared with calculations assuming constant aerosol (0.15) and zero optical depth. The SPECMAGIC calculations using the different aerosol information are compared to measurements of stations of the Baseline Surface Radiation Network (BSRN). The results indicate that in regions with a low frequency of clouds and enhanced variability of aerosol optical depth the climatologies investigated lead to large underestimations of the surface solar radiation, indicating that high aerosol optical depth provided by these climatologies are overestimated. As a consequence the best performing aerosol climatology investigated is modified in such a way very high AODs are cut down, which leads to promising results in the surface solar radiation retrieval.
Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.
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 the PARASOL microsatellite 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 all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas 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 at retrieval of extended set of parameters affecting measured radiation.
de Leeuw, G.; Robles Gonzalez, C.; Kusmierczyk-Michulec, J.; Decae, R.
SATELLITE RETRIEVAL of AEROSOL PROPERTIES G. de Leeuw, C. Robles Gonzalez, J. Kusmierczyk-Michulec and R. Decae TNO Physics and Electronics Laboratory, The Hague, The Netherlands; firstname.lastname@example.org Methods to retrieve aerosol properties over land and over sea were explored. The dual view offered by the ATSR-2 aboard ERS-2 was used by Veefkind et al., 1998. The retrieved AOD (aerosol optical depth) values compare favourably with collocated sun photometer measurements, with an accuracy of 0.06 +/- 0.05 in AOD. An algorithm developed for GOME on ERS-2 takes advantage of the low surface reflection in the UV (Veefkind et al., 2000). AOD values retrieved from ATSR-2 and GOME data over western Europe are consistent. The results were used to produce a map of mean AOD values over Europe for one month (Robles-Gonzalez et al., 2000). The ATSR-2 is al- gorithm is now extended with other aerosol types with the aim to apply it over the In- dian Ocean. A new algorithm is being developed for the Ozone Monitoring Instrument (OMI) to be launched in 2003 on the NASA EOS-AURA satellite. It is expected that, based on the different scattering and absorption properties of various aerosol types, five major aerosol classes can be distinguished. The experience with the retrieval of aerosol properties by using several wavelength bands is used to develop an algorithm for Sciamachy to retrieve aerosol properties both over land and over the ocean which takes advantage of the wavelengths from the UV to the IR. The variation of the AOD with wavelength is described by the Angstrom parameter. The AOD and the Angstrom parameter together yield information on the aerosol size distribution, integrated over the column. Analysis of sunphotometer data indicates a relation between the Angstrom parameter and the mass ratio of certain aerosols (black carbon, organic carbon and sea salt) to the total particulate matter. This relation has been further explored and was applied to satellite data over land to
Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.
To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångstrom Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in
Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.
To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in
Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Mattoo, Shana; Levy, Robert; Chu, D. Allen; Holben, Brent N.; Dubovik, Oleg; Ahmad, Ziauddin; Einaudi, Franco (Technical Monitor)
The MODerate resolution Imaging Spectroradiometer (MODIS) algorithm for determining aerosol characteristics over ocean is performing with remarkable accuracy. A two-month data set of MODIS retrievals co-located with observations from the AErosol RObotic NETwork (AERONET) ground-based sunphotometer network provides the necessary validation. Spectral radiation measured by MODIS (in the range 550 - 2100 nm) is used to retrieve the aerosol optical thickness, effective particle radius and ratio between the submicron and micron size particles. MODIS-retrieved aerosol optical thickness at 660 nm and 870 nm fall within the expected uncertainty, with the ensemble average at 660 nm differing by only 2% from the AERONET observations and having virtually no offset. MODIS retrievals of aerosol effective radius agree with AERONET retrievals to within +/- 0.10 micrometers, while MODIS-derived ratios between large and small mode aerosol show definite correlation with ratios derived from AERONET data.
Newchurch, Michael J.
We have developed a new algorithm for the retrieval of aerosol and gases from SAGE It1 solar transmission measurements. This algorithm improves upon the NASA operational algorithm in several key aspects, including solving the problem non-linearly and incorporating a new methodology for separating the contribution of aerosols and gases. In order to extract aerosol information we have built a huge database of aerosol models for both stratospheric and tropospheric aerosols, and polar stratospheric cloud particles. This set of models allows us to calculate a vast range of possible extinction spectra for aerosols. and from these, derive a set of eigenvectors which then provide the basis set used in our inversion algorithm. Our aerosol algorithm and retrievals are described in several articles (listed in References Section) published under this grant. In particular they allow us to analyze the spectral properties of aerosols and PSCs and ultimately derive their microphysical properties. We have found some considerable differences between our spectra and the ones derived from the SAGE III operational algorithm. These are interesting as they provide an independent check on the validity of published aerosol data and, in particular, on their associated uncertainties. In order to understand these differences, we are assembling independent aerosol data from other sources with which to make comparisons. We have carried out extensive comparisons of our ozone retrievals with both SAGE III and independent lidar, ozonesonde, and satellite measurements (Polyakov et al., 2004). These show very good agreement throughout the stratosphere and help to quantify differences which can be attributed to natural variation in ozone versus that produced by algorithmic differences. In the mid - upper stratosphere, agreement with independent data was generally within 5 - 20%. but in the lower stratosphere the differences were considerably larger. We believe that a large proportion of this
Remer, Lorraine A.; Kaufman, Yoram J.; Tanre, Didier
The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, operationally, on a nearly global basis every day. The three years of Terra-MODIS data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the MODIS aerosol optical thickness retrievals are accurate to within the pre-launch expectations. However, the validation in regions dominated by desert dust is less accurate than in regions dominated by fine mode aerosol or background marine sea salt. The discrepancy is most apparent in retrievals of aerosol size parameters over ocean. In dust situations, the MODIS algorithm tends to under predict particle size because the reflectances at top of atmosphere measured by MODIS exhibit the stronger spectral signature expected by smaller particles. This pattern is consistent with the angular and spectral signature of non-spherical particles. All possible aerosol models in the MODIS Look-Up Tables were constructed from Mie theory, assuming a spherical shape. Using a combination of MODIS and AERONET observations, in regimes dominated by desert dust, we construct phase functions, empirically, with no assumption of particle shape. These new phase functions are introduced into the MODIS algorithm, in lieu of the original options for large dust-like particles. The results will be analyzed and examined.
Kim, Jhoon; Choi, Myungje; Lee, Jaehwa
Aerosol optical properties (AOPs) over East Asia are retrieved hourly from the first Geostationary Ocean Color Imager (GOCI). GOCI Yonsei aerosol retrieval (YAER) algorithm was developed and improved continuously. Final products of GOCI YAER are aerosol optical depth (AOD), fine-mode fraction (FMF), single scattering albedo (SSA), Angstrom exponent (AE) and aerosol type in high spatial and temporal resolution. Previous aerosol retrieval algorithm over ocean adopts surface reflectance using cox and munk technique as fixed wind speed or the minimum reflectivity technique for continuous characteristics between ocean and land. This study adopt cox and munk technique using real time ECMWF wind speed data over clear water and the minimum reflectivity technique over turbid water. For detecting turbid water, TOA reflectance of 412, 660, and 865nm was used. Over the turbid water, TOA reflectance at 660nm increases more than 412 and 865nm. It also shows more sensitivity over turbid water than dust aerosol. We evaluated the accuracy of GOCI aerosol products using ground-based AERONET Level 2.0 products from total 38 East Asia sites and satellite-based MODIS-Aqua aerosol C6 products. The period of assessment is 3 months from March to May, 2012. Comparison results show that a correlation coefficient between the AODs at 550 nm of AERONET and GOCI is 0.884. Comparison results over ocean between GOCI and MODIS DT algorithm shows good agreement as R = 0.915.
Sanders, A. F. J.; de Haan, J. F.; Sneep, M.; Apituley, A.; Stammes, P.; Vieitez, M. O.; Tilstra, L. G.; Tuinder, O. N. E.; Koning, C. E.; Veefkind, J. P.
An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterized by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo. From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i
Sanders, A. F. J.; de Haan, J. F.; Sneep, M.; Apituley, A.; Stammes, P.; Vieitez, M. O.; Tilstra, L. G.; Tuinder, O. N. E.; Koning, C. E.; Veefkind, J. P.
An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterised by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies, and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo. From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i
Sanders, A. F. J.; de Haan, J. F.; Veefkind, J. P.
The Tropospheric Monitoring Instrument (TROPOMI), to be launched in 2015, will feature a new aerosol product providing the height of aerosol layers. Aerosol Layer Height will be one of two aerosol products, the other one being the Absorbing Aerosol Index. TROPOMI is a UV-VIS-NIR imaging spectrometer with daily global coverage. It will be part of ESA's Sentinel-5 Precursor mission. Algorithm development for the aerosol height product is currently underway at KNMI. In this presentation we will introduce the algorithm, highlight some of the development issues and discuss possible applications and example aerosol cases. Aerosol height observations from the near-infrared wavelength range will improve retrieval of other aerosol properties, particularly retrieval of absorption optical thickness. An increase in absorption in the ultraviolet wavelength range can be due to a higher imaginary part of the refractive index or to the aerosol layer being at a higher altitude. Independent height observations will therefore further constrain retrieval of the single scattering albedo. Furthermore, aerosol profile information is an important parameter when estimating radiative forcings and climate impacts of aerosol, it is a significant source of uncertainty in trace gas retrieval and it helps in understanding atmospheric transport mechanisms. Finally, timely available, global observations of aerosol height will be of interest to aviation safety agencies. The retrieval algorithm for aerosol height will be based on absorption by oxygen in the A-band (759-770 nm). Aerosols are assumed to be contained in a single layer. A spectral fit of reflectance (resolution 0.5 nm) across the absorption band provides layer height. The retrieval method will be optimal estimation to ensure a proper error analysis. Sensitivity studies have indicated that accuracy and precision of retrieved height for cloud-free scenes will be well below the TROPOMI science requirements (1 km). They have also shown that
Sogacheva, Larisa; Kolmonen, Pekka; Virtanen, Timo; Saponaro, Giulia; Kokhanovsky, Alexander; de Leeuw, Gerrit
Aerosols and clouds play an important role in terrestrial atmospheric dynamics, thermodynamics, chemistry, and radiative transfer and are key elements of the water and energy cycles. Accurate evaluation of the effects of aerosols and clouds on climate requires global information on aerosol properties. Such global information can only be provided using satellite remote sensing. Among the satellite instruments used for aerosol and cloud retrieval is the Advanced Along-Track Scanning Radiometer (AATSR) on board the European Space Agency (ESA) satellite ENVISAT. Many instruments and retrieval techniques have been developed and applied to satellite data to derive cloud data products (Kokhanonsky et al., 2009). However, many problems still remain to be solved. They are mostly related to the usage of homogeneous, single-layered cloud model. Further issues exist for studies of thin clouds, where both cloud inhomogeniety, cloud fraction and the underlying surface bi-directional reflectance must be accounted for in the retrieval process. The aerosol retrieval algorithm (dual-view over land and single-view over ocean) was constructed for ATSR-2 data (e.g. Veefkind et al. 1998). The most recent version of ADV (AATSR Dual View) is described in Kolmenen et al. (2012). The ATSR dual-view allows retrieval without prior information about land surface reflectance. A semi-analytical cloud retrieval algorithm using backscattered radiation in 0.4-2.4 μm spectral region has recently been implemented to ADV for the determination of the optical thickness, the liquid water path, and the effective size of droplets from spectral measurements of the intensity of light reflected from water clouds with large optical thickness. In AacDV (AATSR aerosol and cloud Dual View) aerosol and cloud retrievals are combined. Cloud retrieval starts when cloud tests for aerosol retrieval show the presence of clouds. The algorithm was early introduced in Kokhanovsky et al. (2003). It works well for thick
Tsekeri, Alexandra; Gross, Barry; Moshary, Fred; Ahmed, Samir
Quantifying aerosols on a global scale is extremely important due to their strong but anomalous impact on the global climate. Traditionally, the aerosols retrievals use only the intensity measurements of the scattered light. However, these measurements are less sensitive to aerosol type and also suffer contamination from ground surfaces. It is with these limitations in mind that we plan to improve the quality and scope of aerosol retrieval by making use of soon to be available polarimetric sensors such as the Aerosol Polarimetry Sensor (APS) on the GLORY satellite and combine them with other available datasets such as lidar data from the CALIPSO satellite for vertical profiling, and high-spatialcoverage intensity measurements from MODIS. To handle these extremely large sensor data sets, we will explore the capabilities of various statistical methods and even combine them to create inversion algorithms that will work best. Up to now, we worked with the simplest case, the single-scattering approximation and built a retrieval algorithm using multi-angular, multi-wavelength simulated measurements of intensity and polarization. The inversion techniques we used are the optimal estimator and the neural networks.
Chemyakin, E.; Sawamura, P.; Mueller, D.; Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Scarino, A. J.; Hair, J. W.; Berkoff, T.; Cook, A. L.; Harper, D. B.; Seaman, S. T.
Although aerosols are only a fairly minor constituent of Earth's atmosphere they are able to affect its radiative energy balance significantly. Light detection and ranging (lidar) instruments have the potential to play a crucial role in atmospheric research as only these instruments provide information about aerosol properties at a high vertical resolution. We are exploring different algorithmic approaches to retrieve microphysical properties of aerosols using lidar. Almost two decades ago we started with inversion techniques based on Tikhonov's regularization that became a reference point for the improvement of retrieval capabilities of inversion algorithms. Recently we began examining the potential of the "arrange and average" scheme, which relies on a look-up table of optical and microphysical aerosol properties. The future combination of these two different inversion schemes may help us to improve the accuracy of the microphysical data products.The novel arrange and average algorithm was applied to retrieve aerosol optical and microphysical parameters using NASA Langley Research Center (LaRC) High Spectral Resolution Lidar (HSRL-2) data. HSRL-2 is the first airborne HSRL system that is able to provide advanced datasets consisting of backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm as input information for aerosol microphysical retrievals. HSRL-2 was deployed on-board NASA LaRC's King Air aircraft during the Deriving Information on Surface Conditions from Column and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaigns over the California Central Valley and Houston. Vertical profiles of aerosol optical properties and size distributions were obtained from in-situ instruments on-board the NASA's P-3B aircraft. As HSRL-2 flew along the same flight track of the P-3B, synergistic measurements and retrievals were obtained by these two independent platforms. We will present an
Chu, W. P.; Mccormick, M. P.; Lenoble, J.; Brogniez, C.; Pruvost, P.
The operational Stratospheric Aerosol and Gas Experiment II multichannel data inversion algorithm is described. Aerosol and ozone retrievals obtained with the algorithm are discussed. The algorithm is compared to an independently developed algorithm (Lenoble, 1989), showing that the inverted aerosol and ozone profiles from the two algorithms are similar within their respective uncertainties.
The Meteosat satellites play an important role for the generation of consistent long time series of aerosol properties. This importance relies on (i) the long duration of past (Meteosat First Generation, MFG) starting in 1982, present (Meteosat Second Generation, MSG) and future (Meteosat Third Generation, MTG) missions and (ii) their frequent cycle of acquisition that can be used to document the anisotropy of the surface and therefore the lower boundary condition for aerosol retrieval over land surfaces. Hence, a similar approach is used for the processing of each Meteosat generation based on a joint retrieval of surface reflectance and aerosol properties using an Optimal Estimation approach. Daily accumulation of the frequent Meteosat observations is used to discriminate the radiative effects that result from the surface anisotropy, from those caused by the aerosol scattering. The inverted forward model explicitly accounts for the surface anisotropy and the multiple scattering for the coupled surface-atmosphere system. Pinty et al. (2000) pioneered with the development of an original method to characterise simultaneously surface anisotropy and atmospheric scattering properties for the processing of MFG. Although these observations are limited to one single large VIS band poorly characterised, the main advantage of MFG relies in the duration of the archive (1982 - 2006), knowing that prior to 2000 space observations were very scarce. Despite these radiometric limitations, it is possible to detect major aerosol events like dust storms, fire plumes or pollution events, even over land surfaces. SEVIRI, on-board MSG, offers additional capabilities with its three solar channels and 15 min repeat cycle. AOD retrieval is much more accurate than with MFG and it is possible to discriminate among various aerosol classes. The additional FCI solar channels on-board MTG will offer improved capabilities with respect to MSG/SEVIRI for the retrieval of aerosol concentration and
Picón, A. J.; Wu, Y.; Gross, B.; Moshary, F.; Ahmed, S. A.
Aerosol retrieval over urban areas is complicated since surface models in the operational algorithms are based on vegetation models such as the case of MODIS. To improve satellite retrieval of aerosols in urban areas, we use simultaneous AERONET radiometer and MODIS measurements in combination to refine surface albedo models. Refined surface models have been implemented for NYC and Mexico City demonstrating significant improvement in AOD in terms of accuracy and spatial resolution. Based on these direct retrievals of the surface reflection for the MODIS Land Aerosol Bands, we were able to show that current parameterizations of the surface as a function of the Modified Vegetation Index are not in good agreement either quantitatively or qualitatively. Further comparisons in other urban areas (eg. Beijing) show that for cases with surface reflectance ratios sufficiently high at the AERONET site, similar over biases can be observed. On the other hand, other cities such as Kanpur, Buenos Aires and Rome do not show any significant bias which can be traced to the fact that these sites are located in regions with less urban surface correlations. Further comparisons in these urban centers are also made with other satellites aerosol retrievals such as POLDER, MISR and OMI.
Dubovik, Oleg; litvinov, Pavel; Huang, Xin; Aspetsberger, Michael; Fuertes, David; Brockmann, Carsten; Fischer, Jürgen; Bojkov, Bojan
The CAWA "Advanced Clouds, Aerosols and WAter vapour products for Sentinel-3/OLCI" ESA-SEOM project aims on the development of advanced atmospheric retrieval algorithms for the Sentinel-3/OLCI mission, and is prepared using Envisat/MERIS and Aqua/MODIS datasets. This presentation discusses mainly CAWA aerosol product developments and results. CAWA aerosol retrieval uses recently developed GRASP algorithm (Generalized Retrieval of Aerosol and Surface Properties) algorithm described by Dubovik et al. (2014). GRASP derives extended set of atmospheric parameters using multi-pixel concept - a simultaneous fitting of a large group of pixels under additional a priori constraints limiting the time variability of surface properties and spatial variability of aerosol properties. Over land GRASP simultaneously retrieves properties of both aerosol and underlying surface even over bright surfaces. GRAPS doesn't use traditional look-up-tables and performs retrieval as search in continuous space of solution. All radiative transfer calculations are performed as part of the retrieval. The results of comprehensive sensitivity tests, as well as results obtained from real Envisat/MERIS data will be presented. The tests analyze various aspects of aerosol and surface reflectance retrieval accuracy. In addition, the possibilities of retrieval improvement by means of implementing synergetic inversion of a combination of OLCI data with observations by SLSTR are explored. Both the results of numerical tests, as well as the results of processing several years of Envisat/MERIS data illustrate demonstrate reliable retrieval of AOD (Aerosol Optical Depth) and surface BRDF. Observed retrieval issues and advancements will be discussed. For example, for some situations we illustrate possibilities of retrieving aerosol absorption - property that hardly accessible from satellite observations with no multi-angular and polarimetric capabilities.
instruments/algorithms using simulated data. Such retrievals should give the same AOT, although in practice, this is often not the case. Then there is a problem with the selection of the best performing algorithm/instrument for lack of a single reference measurement. In this presentation, we inter-compare several aerosol retrieval algorithms using synthetic radiative transfer calculations for a given (and known) atmospheric state for an assumed spectral surface reflectance. In particular, the retrievals are performed using synthetic double-view AATSR and multi-view MISR radiometric observations, and multi-view POLDER radio-polarimetric observations. It is found that other things being equal the most accurate retrievals are achieved, if not only the intensity but also the polarization of the reflected solar light is measured at several angles and spectral channels. This finding strongly endorses the launch of multi-angular polarimeters such as the planned 3MI instrument to be developed by European Space Agency for the EUMETSAT Polar System Second Generation (EPS-SG).
Sicard, Michaël; Comerón, Adolfo; Rocadenbosch, Francisco; Rodríguez, Alejandro; Muñoz, Constantino
The elastic, two-component algorithm is the most common inversion method for retrieving the aerosol backscatter coefficient from ground- or space-based backscatter lidar systems. A quasi-analytical formulation of the statistical error associated to the aerosol backscatter coefficient caused by the use of real, noise-corrupted lidar signals in the two-component algorithm is presented. The error expression depends on the signal-to-noise ratio along the inversion path and takes into account "instantaneous" effects, the effect of the signal-to-noise ratio at the range where the aerosol backscatter coefficient is being computed, as well as "memory" effects, namely, both the effect of the signal-to-noise ratio in the cell where the inversion is started and the cumulative effect of the noise between that cell and the actual cell where the aerosol backscatter coefficient is evaluated. An example is shown to illustrate how the "instantaneous" effect is reduced when averaging the noise-contaminated signal over a number of cells around the range where the inversion is started. PMID:19137026
The Multi-Filter Rotating Shadowband Radiometer (MFRSR) makes precise simultaneous measurements of the solar direct normal and diffuse horizontal irradiances at six wavelengths (nominally 415, 500, 615, 673, 870, and 940 nm) at short intervals (20 sec for ARM instruments) throughout the day. Time series of spectral optical depth are derived from these measurements. Besides water vapor at 940 nm, the other gaseous absorbers within the MFRSR channels are NO2 (at 415, 500, and 615 nm) and ozone (at 500, 615, and 670 nm). Aerosols and Rayleigh scattering contribute atmospheric extinction in all MFRSR channels. Our recently updated MFRSR data analysis algorithm allows us to partition the spectral aerosol optical depth into fine and coarse modes and to retrieve the fine mode effective radius. In this approach we rely on climatological amounts of NO2 from SCIAMACHY satellite retrievals and use daily ozone columns from TOMS.
Aerosol optical properties derived from the DRAGON-NE Asia campaign, and implications for a single-channel algorithm to retrieve aerosol optical depth in spring from Meteorological Imager (MI) on-board the Communication, Ocean, and Meteorological Satellite (COMS)
Kim, M.; Kim, J.; Jeong, U.; Kim, W.; Hong, H.; Holben, B.; Eck, T. F.; Lim, J. H.; Song, C. K.; Lee, S.; Chung, C.-Y.
An aerosol model optimized for northeast Asia is updated with the inversion data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-northeast (NE) Asia campaign which was conducted during spring from March to May 2012. This updated aerosol model was then applied to a single visible channel algorithm to retrieve aerosol optical depth (AOD) from a Meteorological Imager (MI) on-board the geostationary meteorological satellite, Communication, Ocean, and Meteorological Satellite (COMS). This model plays an important role in retrieving accurate AOD from a single visible channel measurement. For the single-channel retrieval, sensitivity tests showed that perturbations by 4 % (0.926 ± 0.04) in the assumed single scattering albedo (SSA) can result in the retrieval error in AOD by over 20 %. Since the measured reflectance at the top of the atmosphere depends on both AOD and SSA, the overestimation of assumed SSA in the aerosol model leads to an underestimation of AOD. Based on the AErosol RObotic NETwork (AERONET) inversion data sets obtained over East Asia before 2011, seasonally analyzed aerosol optical properties (AOPs) were categorized by SSAs at 675 nm of 0.92 ± 0.035 for spring (March, April, and May). After the DRAGON-NE Asia campaign in 2012, the SSA during spring showed a slight increase to 0.93 ± 0.035. In terms of the volume size distribution, the mode radius of coarse particles was increased from 2.08 ± 0.40 to 2.14 ± 0.40. While the original aerosol model consists of volume size distribution and refractive indices obtained before 2011, the new model is constructed by using a total data set after the DRAGON-NE Asia campaign. The large volume of data in high spatial resolution from this intensive campaign can be used to improve the representative aerosol model for East Asia. Accordingly, the new AOD data sets retrieved from a single-channel algorithm, which uses a precalculated look-up table (LUT) with the new aerosol model, show an
Jeong, U.; Ahn, C.; Kim, J.; Bhartia, P. K.; Torres, O.; Spurr, R. J. D.; Liu, X.; Chance, K.; Holben, B. N.
One of the representative advantages of using ultraviolet channel to retrieve aerosol optical property is that the results are less affected by the uncertainty of surface reflectance database. The retrieved aerosol products have relatively uniform quality at both land and ocean except the ice-snow surface. The near UV technique of aerosol remote sensing has additional merit that it has long period database since TOMS (Total Ozone Mapping Spectrometer) including aerosol absorption properties. Thus the retrieved product using the near UV technique using TOMS and OMI (Ozone Monitoring Instrument) measurement is quite appropriate for climatological research. For such purposes, assessment of accuracy of the retrieved product is essential to evaluate the radiative forcing of the aerosols. In this study, the error characterizations of the near UV technique using OMI measurements have been performed with the optimal estimation method during the DRAGON-NE Asia 2012 campaign. In order to avoid the interpolation error, we developed the on-line retrieval scheme based on the traditional near UV method. The retrieval noise and smoothing error of retrieved AOT (Aerosol Optical Thickness) were compared with the biases between 380 nm AOT from AERONET and retrieved 388 nm AOT. They showed positive correlations which infer the possibility of the estimated errors using the optimal estimation method to be used to evaluate the error of retrieved products. Forward model parameter errors were analyzed separately which depends on the quality of the used database, thus can be reduced by improving the database.
Chen, Zhong; Bhartia, Pawan K.; Loughman, Robert
The Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) on board the Suomi National Polar-orbiting Partnership (SNPP) satellite was launched on Oct. 28, 2011. Limb profilers measures the radiance scattered from the Earth's atmospheric in limb viewing mode from 290 to 1000 nm and infer ozone profiles from tropopause to 60 km. The recently released OMPS-LP Version 2 data product contains the first publicly released ozone profiles retrievals, and these are now available for the entire OMPS mission, which extends from April, 2012. The Version 2 data product retrievals incorporate several important improvements to the algorithm. One of the primary changes is to turn off the aerosol retrieval module. The aerosol profiles retrieved inside the ozone code was not helping the ozone retrieval and was adding noise and other artifacts. Aerosols including polar stratospheric cloud (PSC) and polar mesospheric clouds (PMC) have a detectable effect on OMPS-LP data. Our results show that ignoring the aerosol contribution would produce an ozone density bias of up to 10 percent in the region of maximum aerosol extinction. Therefore, aerosol correction is needed to improve the quality of the retrieved ozone concentration profile. We provide Aerosol Scattering Index (ASI) for detecting aerosols-PMC-PSC, defined as ln(Im-Ic) normalized at 45km, where Im is the measured radiance and Ic is the calculated radiance assuming no aerosols. Since ASI varies with wavelengths, latitude and altitude, we can start by assuming no aerosol profiles in calculating the ASIs and then use the aerosol profile to see if it significantly reduces the residuals. We also discuss the effect of aerosol size distribution on the ozone profile retrieval process. Finally, we present an aerosol-PMC-PSC correction scheme.
Kahn, Ralph A.; Gaitley, Barbara J.
In addition to aerosol optical depth (AOD), aerosol type is required globally for climate forcing calculations, constraining aerosol transport models and other applications. However, validating satellite aerosol-type retrievals is more challenging than testing AOD results, because aerosol type is a more complex quantity, and ground truth data are far less numerous and generally not as robust. We evaluate the Multiangle Imaging Spectroradiometer (MISR) Version 22 aerosol-type retrievals by assessing product self-consistency on a regional basis and by making comparisons with general expectation and with the Aerosol Robotic Network aerosol-type climatology, as available. The results confirm and add detail to the observation that aerosol-type discrimination improves dramatically where midvisible AOD exceeds about 0.15 or 0.2. When the aerosol-type information content of the observations is relatively low, increased scattering-angle range improves particle-type sensitivity. The MISR standard, operational product discriminates among small, medium, and large particles and exhibits qualitative sensitivity to single-scattering albedo (SSA) under good aerosol-type retrieval conditions, providing a categorical aerosol-type classification. MISR Ångström exponent deviates systematically from ground truth where particle types missing from the algorithm climatology are present, or where cloud contamination is likely to occur, and SSA tends to be overestimated where absorbing particles are found. We determined that the number of mixtures passing the algorithm acceptance criteria (#SuccMix) represents aerosol-type retrieval quality effectively, providing a useful aerosol-type quality flag.
Chemyakin, Eduard; Müller, Detlef; Burton, Sharon; Kolgotin, Alexei; Hostetler, Chris; Ferrare, Richard
We present the results of a feasibility study in which a simple, automated, and unsupervised algorithm, which we call the arrange and average algorithm, is used to infer microphysical parameters (complex refractive index, effective radius, total number, surface area, and volume concentrations) of atmospheric aerosol particles. The algorithm uses backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm as input information. Testing of the algorithm is based on synthetic optical data that are computed from prescribed monomodal particle size distributions and complex refractive indices that describe spherical, primarily fine mode pollution particles. We tested the performance of the algorithm for the "3 backscatter (β)+2 extinction (α)" configuration of a multiwavelength aerosol high-spectral-resolution lidar (HSRL) or Raman lidar. We investigated the degree to which the microphysical results retrieved by this algorithm depends on the number of input backscatter and extinction coefficients. For example, we tested "3β+1α," "2β+1α," and "3β" lidar configurations. This arrange and average algorithm can be used in two ways. First, it can be applied for quick data processing of experimental data acquired with lidar. Fast automated retrievals of microphysical particle properties are needed in view of the enormous amount of data that can be acquired by the NASA Langley Research Center's airborne "3β+2α" High-Spectral-Resolution Lidar (HSRL-2). It would prove useful for the growing number of ground-based multiwavelength lidar networks, and it would provide an option for analyzing the vast amount of optical data acquired with a future spaceborne multiwavelength lidar. The second potential application is to improve the microphysical particle characterization with our existing inversion algorithm that uses Tikhonov's inversion with regularization. This advanced algorithm has recently undergone development to allow automated and
Mei, L.; Rozanov, V. V.; Vountas, M.; Burrows, J. P.; Levy, R. C.; Lotz, W.
Retrieval of aerosol properties for satellite instruments without shortwave-IR spectral information, multi-viewing, polarization and/or high-temporal observation ability is a challenging problem for spaceborne aerosol remote sensing. However, space based instruments like the MEdium Resolution Imaging Spectrometer (MERIS) and the successor, Ocean and Land Colour Instrument (OLCI) with high calibration accuracy and high spatial resolution provide unique abilities for obtaining valuable aerosol information for a better understanding of the impact of aerosols on climate, which is still one of the largest uncertainties of global climate change evaluation. In this study, a new Aerosol Optical Thickness (AOT) retrieval algorithm (XBAER: eXtensible Bremen AErosol Retrieval) is presented. XBAER utilizes the global surface spectral library database for the determination of surface properties while the MODIS collection 6 aerosol type treatment is adapted for the aerosol type selection. In order to take the surface Bidirectional Reflectance Distribution Function (BRDF) effect into account for the MERIS reduce resolution (1km) retrieval, a modified Ross-Li mode is used. The AOT is determined in the algorithm using lookup tables including polarization created using Radiative Transfer Model SCIATRAN3.4, by minimizing the difference between atmospheric corrected surface reflectance with given AOT and the surface reflectance calculated from the spectral library. The global comparison with operational MODIS C6 product, Multi-angle Imaging SpectroRadiometer (MISR) product, Advanced Along-Track Scanning Radiometer (AATSR) aerosol product and the validation using AErosol RObotic NETwork (AERONET) show promising results. The current XBAER algorithm is only valid for aerosol remote sensing over land and a similar method will be extended to ocean later.
Bovchaliuk, Valentyn; Goloub, Philippe; Podvin, Thierry; Veselovskii, Igor; Tanre, Didier; Chaikovsky, Anatoli; Dubovik, Oleg; Mortier, Augustin; Lopatin, Anton; Korenskiy, Mikhail; Victori, Stephane
Aerosol particles are important and highly variable components of the terrestrial atmosphere, and they affect both air quality and climate. In order to evaluate their multiple impacts, the most important requirement is to precisely measure their characteristics. Remote sensing technologies such as lidar (light detection and ranging) and sun/sky photometers are powerful tools for determining aerosol optical and microphysical properties. In our work, we applied several methods to joint or separate lidar and sun/sky-photometer data to retrieve aerosol properties. The Raman technique and inversion with regularization use only lidar data. The LIRIC (LIdar-Radiometer Inversion Code) and recently developed GARRLiC (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data) inversion methods use joint lidar and sun/sky-photometer data. This paper presents a comparison and discussion of aerosol optical properties (extinction coefficient profiles and lidar ratios) and microphysical properties (volume concentrations, complex refractive index values, and effective radius values) retrieved using the aforementioned methods. The comparison showed inconsistencies in the retrieved lidar ratios. However, other aerosol properties were found to be generally in close agreement with the AERONET (AErosol RObotic NETwork) products. In future studies, more cases should be analysed in order to clearly define the peculiarities in our results.
Remer, Lorraine A.; Mattoo, Shana; Levy, Robert C.; Heidinger, Andrew; Pierce, R. Bradley; Chin, Mian
The challenge of using satellite observations to retrieve aerosol properties in a cloudy environment is to prevent contamination of the aerosol signal from clouds, while maintaining sufficient aerosol product yield to satisfy specific applications. We investigate aerosol retrieval availability at different instrument pixel resolutions, using the standard MODIS aerosol cloud mask applied to MODIS data and a new GOES-R cloud mask applied to GOES data for a domain covering North America and surrounding oceans. Aerosol availability is not the same as the cloud free fraction and takes into account the technqiues used in the MODIS algorithm to avoid clouds, reduce noise and maintain sufficient numbers of aerosol retrievals. The inherent spatial resolution of each instrument, 0.5x0.5 km for MODIS and 1x1 km for GOES, is systematically degraded to 1x1 km, 2x2 km, 4x4 km and 8x8 km resolutions and then analyzed as to how that degradation would affect the availability of an aerosol retrieval, assuming an aerosol product resolution at 8x8 km. The results show that as pixel size increases, availability decreases until at 8x8 km 70% to 85% of the retrievals available at 0.5 km have been lost. The diurnal pattern of aerosol retrieval availability examined for one day in the summer suggests that coarse resolution sensors (i.e., 4x4 km or 8x8 km) may be able to retrieve aerosol early in the morning that would otherwise be missed at the time of current polar orbiting satellites, but not the diurnal aerosol properties due to cloud cover developed during the day. In contrast finer resolution sensors (i.e., 1x1 km or 2x2 km) have much better opportunity to retrieve aerosols in the partly cloudy scenes and better chance of returning the diurnal aerosol properties. Large differences in the results of the two cloud masks designed for MODIS aerosol and GOES cloud products strongly reinforce that cloud masks must be developed with specific purposes in mind and that a generic cloud mask
Nicolae, Doina; Vasilescu, Jeni; Talianu, Camelia; Dandocsi, Alexandru
This paper presents an algorithm for aerosol typing from multiwavelength lidar data, based on Artificial Neural Networks. The aerosol model used to simulate optical properties for the training of the network is described. The algorithm is tested on real observations from ESA-CALIPSO database.
Wang, P.; Tuinder, O. N. E.; Tilstra, L. G.; de Graaf, M.; Stammes, P.
Cloud and aerosol information is needed in trace gas retrievals from satellite measurements. The Fast REtrieval Scheme for Clouds from the Oxygen A band (FRESCO) cloud algorithm employs reflectance spectra of the O2 A band around 760 nm to derive cloud pressure and effective cloud fraction. In general, clouds contribute more to the O2 A band reflectance than aerosols. Therefore, the FRESCO algorithm does not correct for aerosol effects in the retrievals and attributes the retrieved cloud information entirely to the presence of clouds, and not to aerosols. For events with high aerosol loading, aerosols may have a dominant effect, especially for almost cloud free scenes. We have analysed FRESCO cloud data and Absorbing Aerosol Index (AAI) data from the Global Ozone Monitoring Experiment (GOME-2) instrument on the Metop-A satellite for events with typical absorbing aerosol types, such as volcanic ash, desert dust and smoke. We find that the FRESCO effective cloud fractions are correlated with the AAI data for these absorbing aerosol events and that the FRESCO cloud pressure contains information on aerosol layer pressure. For cloud free scenes, the derived FRESCO cloud pressure is close to the aerosol layer pressure, especially for optically thick aerosol layers. For cloudy scenes, if the strongly absorbing aerosols are located above the clouds, then the retrieved FRESCO cloud pressure may represent the height of the aerosol layer rather than the height of the clouds. Combining FRESCO and AAI data, an estimate for the aerosol layer pressure can be given.
Lumpe, Jerry D.
This effort addresses the comparison and validation of currently operational solar occultation retrieval algorithms, and the development of generalized algorithms for future application to multiple platforms. initial development of generalized forward model algorithms capable of simulating transmission data from of the POAM II/III and SAGE II/III instruments. Work in the 2" quarter will focus on: completion of forward model algorithms, including accurate spectral characteristics for all instruments, and comparison of simulated transmission data with actual level 1 instrument data for specific occultation events.
Huttunen, Jani; Kokkola, Harri; Mielonen, Tero; Esa Juhani Mononen, Mika; Lipponen, Antti; Reunanen, Juha; Vilhelm Lindfors, Anders; Mikkonen, Santtu; Erkki Juhani Lehtinen, Kari; Kouremeti, Natalia; Bais, Alkiviadis; Niska, Harri; Arola, Antti
In order to have a good estimate of the current forcing by anthropogenic aerosols, knowledge on past aerosol levels is needed. Aerosol optical depth (AOD) is a good measure for aerosol loading. However, dedicated measurements of AOD are only available from the 1990s onward. One option to lengthen the AOD time series beyond the 1990s is to retrieve AOD from surface solar radiation (SSR) measurements taken with pyranometers. In this work, we have evaluated several inversion methods designed for this task. We compared a look-up table method based on radiative transfer modelling, a non-linear regression method and four machine learning methods (Gaussian process, neural network, random forest and support vector machine) with AOD observations carried out with a sun photometer at an Aerosol Robotic Network (AERONET) site in Thessaloniki, Greece. Our results show that most of the machine learning methods produce AOD estimates comparable to the look-up table and non-linear regression methods. All of the applied methods produced AOD values that corresponded well to the AERONET observations with the lowest correlation coefficient value being 0.87 for the random forest method. While many of the methods tended to slightly overestimate low AODs and underestimate high AODs, neural network and support vector machine showed overall better correspondence for the whole AOD range. The differences in producing both ends of the AOD range seem to be caused by differences in the aerosol composition. High AODs were in most cases those with high water vapour content which might affect the aerosol single scattering albedo (SSA) through uptake of water into aerosols. Our study indicates that machine learning methods benefit from the fact that they do not constrain the aerosol SSA in the retrieval, whereas the LUT method assumes a constant value for it. This would also mean that machine learning methods could have potential in reproducing AOD from SSR even though SSA would have changed during
Thompson, Robert E.; Gordley, Larry L.
The Halogen Occultation Experiment (HALOE) on the Upper Atmosphere Research Satellite (UARS) provided high quality measurements of key middle atmosphere constituents, aerosol characteristics, and temperature for 14 years (1991-2005). This report is an outline of the Level 2 retrieval algorithms, and it also describes the great care that was taken in characterizing the instrument prior to launch and throughout its mission life. It represents an historical record of the techniques used to analyze the data and of the steps that must be considered for the development of a similar experiment for future satellite missions.
Quijano, Ana Lía; Sokolik, Irina N.; Toon, Owen B.
We investigate the importance of the layered vertical distribution of absorbing and non-absorbing tropospheric aerosols for the retrieval of the aerosol optical depth from satellite radiances measured at visible wavelengths at a single viewing angle. We employ lidar and in-situ measurements of aerosol extinction coefficients and optical depths to model radiances which would have been observed by a satellite. Then, we determine the aerosol optical depth that would produce the observed radiance under various sets of assumptions which are often used in current retrieval algorithms. We demonstrate that, in the presence of dust or other absorbing aerosols, the retrieved aerosol optical depth can underestimate or overestimate the observed optical depth by a factor of two or more depending on the choice of an aerosol optical model and the relative position of different aerosol layers. The presence of undetected clouds provides a further complication.
Grzegorski, Michael; Munro, Rosemary; Lang, Ruediger; Poli, Gabriele; Holdak, Andriy
The retrieval of aerosol optical properties is an important task for industry and climate forecasting. An ideal instrument should include observations with moderate spectral and high spatial resolutions for a wide range of wavelengths (from the UV to the TIR), measurements of the polarization state at different wavelengths and measurements of the same scene for different observation geometries. As such an ideal instrument is currently unavailable the usage of different instruments on one satellite platform is an alternative choice. Since February 2014, the Polar Multi sensor Aerosol product (PMAp) is delivered as operational GOME product to our customers. The algorithms retrieve aerosol optical properties over ocean (AOD, volcanic ash, aerosol type) using a multi-sensor approach (GOME, AVHRR, IASI). The next releases of PMAp will provide an extended set of aerosol and cloud properties which include AOD over land and an improved volcanic ash retrieval combining AVHRR and IASI. This presentation gives an overview on the existing product and the prototypes in development. The major focus is the discussion of the AOD retrieval over land implemented in the upcoming PMAp2 release. In addition, the results of our current validation studies (e.g. comparisons to AERONET, other satellite platforms and model data) are shown.
Li, S.; Kahn, R.; Chin, M.; Garay, M. J.; Chen, L.; Liu, Y.
The Multi-Angle Imaging Spectro-Radiometer (MISR) instrument on NASA's Terra satellite can provide more reliable Aerosol Optical Depth (AOD, τ) and more particle information, such as constraints on particle size (Angström exponent or ANG, α), particle shape, and single-scattering albedo (SSA, ω), than many other satellite instruments. However, MISR's ability to retrieve aerosol properties is weakened at low AOD levels. When aerosol-type information content is low, many candidate aerosol mixtures can match the observed radiances. We propose an algorithm to improve MISR aerosol retrievals by constraining MISR mixtures' ANG and absorbing AOD (AAOD) with Goddard Chemistry Aerosol Radiation and Transport (GOCART) model-simulated aerosol properties. To demonstrate this approach, we calculated MISR aerosol optical properties over the contiguous US from 2006 to 2009. Sensitivities associated with the thresholds of MISR-GOCART differences were analyzed according to the agreement between our results (AOD, ANG, and AAOD) and AErosol RObotic NETwork (AERONET) observations. Overall, our AOD has a good agreement with AERONET because the MISR AOD retrieval is not sensitive to different mixtures under many retrieval conditions. The correlation coefficient (r) between our ANG and AERONET improves to 0.45 from 0.29 for the MISR Version 22 standard product and 0.43 for GOCART when all data points are included. However, when only cases having AOD > 0.2, the MISR product itself has r ~ 0.40, and when only AOD > 0.2 and the best-fitting mixture are considered, r ~ 0.49. So as expected, the ANG improvement occurs primarily when the model constraint is applied in cases where the particle type information content of the MISR radiances is low. Regression analysis for AAOD shows that MISR Version 22 and GOCART misestimate AERONET by a ratio (mean retrieved AAOD to mean AERONET AAOD) of 0.5; our method improves this ratio to 0.74. Large discrepancies are found through an inter
Lee, Jaehwa; Hsu, Nai-Yung Christina; Bettenhausen, Corey; Sayer, Andrew Mark.
Retrieval of aerosol optical properties using shortwave bands from passive satellite sensors, such as MODIS, is typically limited to cloud-free areas. However, if the clouds are thin enough (i.e. thin cirrus) such that the satellite-observed reflectance contains signals under the cirrus layer, and if the optical properties of this cirrus layer are known, the TOA reflectance can be corrected for the cirrus layer to be used for retrieving aerosol optical properties. To this end, we first correct the TOA reflectances in the aerosol bands (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 micron for ocean algorithm and 0.412, 0.47, and 0.65 micron for deep blue algorithm) for the effects of thin cirrus using 1.38 micron reflectance and conversion factors that convert cirrus reflectance in 1.38 micron band to those in aerosol bands. It was found that the conversion factors can be calculated by using relationships between reflectances in 1.38 micron band and minimum reflectances in the aerosol bands (Gao et al., 2002). Refer to the example in the figure. Then, the cirrus-corrected reflectance can be calculated by subtracting the cirrus reflectance from the TOA reflectance in the optically thin case. A sensitivity study suggested that cloudy-sky TOA reflectances can be calculated with small errors in the form of simple linear addition of cirrus-only reflectances and clear-sky reflectances. In this study, we correct the cirrus signals up to TOA reflectance at 1.38 micron of 0.05 where the simple linear addition is valid without extensive radiative transfer simulations. When each scene passes the set of tests shown in the flowchart, the scene is corrected for cirrus contamination and passed into aerosol retrieval algorithms.
Lyapustin, A.; Wang, Y.; Laszlo, I.; Kahn, R.; Korkin, S.; Remer, L.; Levy, R.; Reid, J. S.
An aerosol component of a new multiangle implementation of atmospheric correction (MAIAC) algorithm is presented. MAIAC is a generic algorithm developed for the Moderate Resolution Imaging Spectroradiometer (MODIS), which performs aerosol retrievals and atmospheric correction over both dark vegetated surfaces and bright deserts based on a time series analysis and image-based processing. The MAIAC look-up tables explicitly include surface bidirectional reflectance. The aerosol algorithm derives the spectral regression coefficient (SRC) relating surface bidirectional reflectance in the blue (0.47 micron) and shortwave infrared (2.1 micron) bands; this quantity is prescribed in the MODIS operational Dark Target algorithm based on a parameterized formula. The MAIAC aerosol products include aerosol optical thickness and a fine-mode fraction at resolution of 1 km. This high resolution, required in many applications such as air quality, brings new information about aerosol sources and, potentially, their strength. AERONET validation shows that the MAIAC and MOD04 algorithms have similar accuracy over dark and vegetated surfaces and that MAIAC generally improves accuracy over brighter surfaces due to the SRC retrieval and explicit bidirectional reflectance factor characterization, as demonstrated for several U.S. West Coast AERONET sites. Due to its generic nature and developed angular correction, MAIAC performs aerosol retrievals over bright deserts, as demonstrated for the Solar Village Aerosol Robotic Network (AERONET) site in Saudi Arabia.
Mukai, S.; Sano, I.; Nakata, M.
Aerosol retrieval is achieved by radiative transfer simulation in the Earth atmosphere model. This work intends to propose an algorithm for multiple light scattering simulations in the hazy polarized radiation field. We have already solved the scalar radiative transfer problem in the case of haze episodes with dense concentrations of atmospheric aerosols by the method of successive order of scattering, which is named scalar-MSOS. The term "scalar" indicates radiance alone in the treatment of radiative transfer problem against "vector" involving polarized radiation field. The satellite polarimetric sensor POLDER-1, 2, 3 has shown that the spectro-photopolarimetry of terrestrial atmosphere is very useful for observation of the Earth, especially for aerosols. JAXA has been developing the new Earth observing system, GCOM satellite. GCOM-C will board the polarimetric sensor SGLI in 2017. It is highly likely that large-scale aerosol episodes will continue to occur, because the air pollution becomes to be severe due to both the increasing emissions of the anthropogenic aerosols and the complicated behavior of natural aerosols. Then many potential applications for the kind of radiation simulation by MSOS considering the polarization information denoted by Stokes parameters (I, Q, U, V), named vector-MSOS, are desired. It is shown here that dense aerosol episodes can be well simulated by a semi-infinite radiation model composed of the proposed aerosol models. In addition our vector-MSOS is examined in practice by combination use of PARASOL/POLDER, GOSAT/CAI and Aqua/MODIS data.
Mei, Linlu; Rozanov, Vladimir; Vountas, Marco; Burrows, John P.
Surface reflectance determination and aerosol type selection are the two main challenges for space-borne aerosol remote sensing, especially for those instruments lacking of near-infrared channels, high-temporal observations, multi-angles abilities and/or polarization information. However, space based instruments like the MEdium Resolution Imaging Spectrometer (MERIS) and the successor, Ocean and Land Colour Instrument (OLCI) with high calibration accuracy and high spatial resolution provide unique abilities for obtaining valuable aerosol information for a better understanding of the impact of aerosols on climate, which is still one of the largest uncertainties of global climate change evaluation. In this study, a new Aerosol Optical Depth (AOD) retrieval algorithm is presented. Global aerosol type and surface spectral dataset were used for the aerosol type selection and surface reflectance determination. A modified Ross-Li mode is used to describe the surface Bidirectional Reflectance Distribution Function (BRDF) effect. The comparison with operational MODIS C6 product and the validation using AErosol RObotic NETwork (AERONET) show promising results.
KIM, M.; Kim, W.; Jung, Y.; Lee, S.; Kim, J.; Lee, H.; Boesch, H.; Goo, T. Y.
In the satellite remote sensing of CO2, incorrect aerosol information could induce large errors as previous studies suggested. Many factors, such as, aerosol type, wavelength dependency of AOD, aerosol polarization effect and etc. have been main error sources. Due to these aerosol effects, large number of data retrieved are screened out in quality control, or retrieval errors tend to increase if not screened out, especially in East Asia where aerosol concentrations are fairly high. To reduce these aerosol induced errors, a CO2 retrieval algorithm using the simultaneous TANSO-CAI aerosol information is developed. This algorithm adopts AOD and aerosol type information as a priori information from the CAI aerosol retrieval algorithm. The CO2 retrieval algorithm based on optimal estimation method and VLIDORT, a vector discrete ordinate radiative transfer model. The CO2 algorithm, developed with various state vectors to find accurate CO2 concentration, shows reasonable results when compared with other dataset. This study concentrates on the validation of retrieved results with the ground-based TCCON measurements in East Asia and the comparison with the previous retrieval from ACOS, NIES, and UoL. Although, the retrieved CO2 concentration is lower than previous results by ppm's, it shows similar trend and high correlation with previous results. Retrieved data and TCCON measurements data are compared at three stations of Tsukuba, Saga, Anmyeondo in East Asia, with the collocation criteria of ±2°in latitude/longitude and ±1 hours of GOSAT passing time. Compared results also show similar trend with good correlation. Based on the TCCON comparison results, bias correction equation is calculated and applied to the East Asia data.
Zhai, P.; Winker, D. M.; Hu, Y.; Trepte, C. R.; Lucker, P. L.
Aerosol absorption plays an important role in the climate by modulating atmospheric radiative forcing processes. Unfortunately aerosol absorption is very difficult to obtain via satellite remote sensing techniques. In this work we have built an algorithm to obtain aerosol absorption optical depth using both measurements from a passive O2 A-band spectrometer and an active lidar. The instrument protocols for these two satellite instruments are the O2 A-band spectrometer onboard the Orbiting Carbon Observatory (OCO-2) and the CALIOP onboard CALIPSO. The aerosol height and typing information is obtained from the CALIOP measurement. The aerosol extinction and absorption optical depths are then retrieved by fitting the forward model simulations to the O2 A-band spectrometer measurements. The forward model simulates the scattering and absorption of solar light at high spectral resolution in the O2 A-band region. The O2 and other gas absorption coefficients near 0.76 micron are calculated by either the line-by-line code (for instance, the Atmospheric Radiative Transfer Simulator) or the OCO2 ABSCO Look-Up-Table. The line parameters used are from the HITRAN 2008 database (http://www.cfa.harvard.edu/hitran/). The multiple light scattering by molecules, aerosols, and clouds is handled by the radiative transfer model based on the successive order of scattering method (Zhai et al, JQSRT, Vol. 111, pp. 1025-1040, 2010). The code is parallelized with Message Passing Interface (MPI) for better efficiency. The aerosol model is based on Shettle and Fenn (AFGL-TR 790214, 1979) with variant relative humidity. The vertical distribution of the aerosols and clouds will be read in from the CALIPSO product (http://www-calipso.larc.nasa.gov). The surface albedo is estimated by the continuum of the three bands of OCO2 payloads. Sensitivity study shows that the Gaussian quadrature (stream) number should be at least 12 to ensure the reflectance error is within 0.5% at the top of the atmosphere
Drury, Easan Evans
Atmospheric aerosols are of major concern for public health and climate change, but their sources and atmospheric distributions remain poorly constrained. Satellite-borne radiometers offer a new constraint on aerosol sources and processes by providing global aerosol optical depth (AOD) retrievals. However, quantitative evaluation of chemical transport models (CTMs) with AOD products retrieved from satellite backscattered reflectances can be compromised by inconsistent assumptions of aerosol optical properties and errors in surface reflectance estimates. We present an improved AOD retrieval algorithm for the MODIS satellite instrument using locally derived surface reflectances and CTM aerosol optical properties. Assuming negligible atmospheric reflectance at 2.13 in cloud-free conditions, we derive 0.47/2.13 and 0.65/2.13 surface reflectance ratios at 1°x1.25° horizontal resolution for the continental United States in summer 2004 from the subset of top-of-atmosphere (TOA) reflectance data with minimal aerosol reflectance. We find higher ratios over arid regions than those assumed in the operational MODIS AOD retrieval algorithm, explaining the high AOD bias found in these regions. We simulate TOA reflectances for each MODIS scene using local aerosol optical properties from the GEOS-Chem CTM, and fit these reflectances to the observed MODIS TOA reflectances for a best estimate of AODs for each scene. Comparison with coincident ground-based (AERONET) AOD observations in the western and central United States during the summer of 2004 shows considerable improvement over the operational MODIS AOD products in this region. We find the AOD retrieval is more accurate at 0.47 than at 0.65 mum because of the higher signal to noise ratio, and that the correlation between MODIS and AERONET AODs improves as averaging time increases. We further improve the AOD retrieval method using an extensive ensemble of aircraft, ground-based, and satellite aerosol observations during the
Saito, M.; Iwabuchi, H.
Twilight sky, one of the most beautiful sights seen in our daily life, varies day by day, because atmospheric components such as ozone and aerosols also varies day by day. Recent studies have revealed the effects of tropospheric aerosols on twilight sky. In this study, we develop a new algorithm for aerosol retrievals from twilight photographs taken by a digital single reflex-lens camera in solar zenith angle of 90-96˚ with interval of 1˚. A radiative transfer model taking spherical-shell atmosphere, multiple scattering and refraction into account is used as a forward model, and the optimal estimation is used as an inversion calculation to infer the aerosol optical and radiative properties. The sensitivity tests show that tropospheric (stratospheric) aerosol optical thickness is responsible to the distribution of twilight sky color and brightness near the horizon (in viewing angles of 10˚ to 20˚) and aerosol size distribution is responsible to the angular distribution of brightness near the solar direction. The AOTs are inferred with small uncertainties and agree very well with that from the Skyradiometer. In this conference, several case studies using the algorithm will be shown.
Lee, Sanghee; Kim, Jhoon; Kim, Mijin; Choi, Myungje; Go, Sujung; Lim, HyunKwang; Ou, Mi-Lim; Goo, Tae-Young; Yokota, Tatsuya
Aerosol is a significant component on air quality and climate change. In particular, spatial and temporal distribution of aerosol shows large variability over East Asia, thus has large effect in retrieving carbon dioxide from Greenhouse Gases Observing Satellite (GOSAT) Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer (TANSO-FTS). An aerosol retrieval algorithm was developed from TANSO- Cloud and Aerosol Imager (CAI) onboard the GOSAT. The algorithm retrieves aerosol optical depth (AOD), size distribution of aerosol, and aerosol type in 0.1 degree grid resolution and surface reflectance was estimated using the clear sky composite method. To test aerosol absorptivity, the reflectance difference method was considered using channels of TANSO-CAI. In this study, the retrieved aerosol optical depth (AOD) was compared with those of Aerosol Robotic NETwork (AERONET) and MODerate resolution Imaging Sensor (MODIS) dataset from September 2011 and August 2014. Comparisons of AODs between AERONET and CAI show the reasonably good correlation with correlation coefficient of 0.77 and regression slope of 0.87 for the whole period. Moreover, those between MODIS and CAI for the same period show correlations with correlation coefficient of 0.7 ~ 0.9 and regression slope of 0.7 ~ 1.2, depending on season and comparison regions however, the largest error source in aerosol retrieval has been surface reflectance. Over ocean and some Land, surface reflectance tends to be overestimated, and thereby CAI-AOD tends to be underestimated. Based on the results with CAI algorithm developed, the algorithm is continuously improved for better performance.
Meissner, Thomas; Wentz, Frank; Hilburn, Kyle; Lagerloef, Gary; Le Vine, David
The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration  converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water ,  and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step.
Istomina, Larysa; von Hoyningen-Huene, Wolfgang; Rozanov, Vladimir; Kokhanovsky, Alexander; Burrows, John P.
Remote sensing of aerosols experiences lack of products over very bright surfaces, such as deserts and snow, due to difficulties with the subtraction of the surface reflection contribution, when a small error in accounting for surface reflectance can cause a large error in retrieved aerosol optical thickness (AOT). Cloud screening over bright surface is also not easy because of low contrast between clouds and surface in visible range of spectrum, and additional infrared chan-nels are not always available. Luckily, AATSR instrument onboard ENVISAT has necessary features to solve both of these problems. In current work we present an improved version of discussed earlier [1,2] dual-view algorithm to retrieve AOT over snow. The retrieval algorithm still consists of cloud screening, based on spectral shape analysis of AATSR pixel in order to extract clear snow pixels, and of AOT retrieval over snow and water. Current version of AOT retrieval over open ocean now contains improved accounting for ocean reflectance (in previous version the ocean was assumed to be absolutely black). The AOT retrieval over snow has been improved to account more accurately for the bidirectional features of the surface reflection function. For this we now use the approach described in  instead of , which has been used in the previous version of the retrieval. The accuracy of both approaches  and  has been evaluated via comparison to forward radiative-transfer model for the case of a very bright surface. The new algorithm has been applied to various scenes in European Arctic and Alaska in different scales, up to global AOT maps. The correspondence of AOT over snow to AOT over water is quite good, which proves the reliability of the retrieval. The algorithm has been validated against AERONET and other Arctic ground based AOT data and shows reasonably good correlation. The presented cloud screening method has been validated via comparison to MODIS cloud mask and Micro Pulse Lidar data
Petrenko, Maksym; Ichoku, Charles
Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.
Toledano, Carlos; Torres, Benjamin; Althausen, Dietrich; Groß, Silke; Freudenthaler, Volker; Weinzierl, Bernadett; Gasteiger, Josef; Ansmann, Albert; Wiegner, Matthias; González, Ramiro; Cachorro, Victoria
The Saharan Aerosol Long-range Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE), aims at investigating the long-range transport of Saharan dust across the Atlantic Ocean. A large set of ground-based and airborne aerosol and meteorological instrumentation was used for this purpose during a 5-week campaign that took place during June-July 2013. Several Sun photometers were deployed at Barbados Island during this campaign. Two Cimels included in AERONET and the Sun and Sky Automatic Radiometer (SSARA) were co-located with the ground-based lidars BERTHA and POLIS. A set of optical and microphysical aerosol properties derived from Sun and Sky spectral observations (principal plane and almucantar configurations) in the range 340-1640nm are analyzed, including aerosol optical depth (AOD), volume size distribution, complex refractive index, sphericity and single scattering albedo. The Sun photometers include polarization capabilities, therefore apart from the inversion of sky radiances as it is routinely done in AERONET, polarized radiances are also inverted. Several dust events are clearly identified in the measurement period, with moderated AOD (500nm) in the range 0.3 to 0.6. The clean marine background was also observed during short periods. The retrieved aerosol properties are compared with the lidar and in-situ observations carried out within SALTRACE, as well as with data collected during the SAMUM campaigns in Morocco and Cape Verde, in order to investigate possible changes in the dust plume during the transport.
Wang, P.; Tuinder, O. N. E.; Tilstra, L. G.; Stammes, P.
Cloud and aerosol information is needed in trace gas retrievals from satellite measurements. The Fast REtrieval Scheme for Clouds from the Oxygen A band (FRESCO) cloud algorithm employs reflectance spectra of the O2 A band around 760 nm to derive cloud pressure and effective cloud fraction. In general, clouds contribute more to the O2 A band reflectance than aerosols. Therefore, the FRESCO algorithm does not correct for aerosol effects in the retrievals and attributes the retrieved cloud information entirely to the presence of clouds, and not to aerosols. For events with high aerosol loading, aerosols may have a dominant effect, especially for almost cloud-free scenes. We have analysed FRESCO cloud data and Absorbing Aerosol Index (AAI) data from the Global Ozone Monitoring Experiment (GOME-2) instrument on the Metop-A satellite for events with typical absorbing aerosol types, such as volcanic ash, desert dust and smoke. We find that the FRESCO effective cloud fractions are correlated with the AAI data for these absorbing aerosol events and that the FRESCO cloud pressures contain information on aerosol layer pressure. For cloud-free scenes, the derived FRESCO cloud pressures are close to those of the aerosol layer for optically thick aerosols. For cloudy scenes, if the strongly absorbing aerosols are located above the clouds, then the retrieved FRESCO cloud pressures may represent the height of the aerosol layer rather than the height of the clouds. Combining FRESCO cloud data and AAI, an estimate for the aerosol layer pressure can be given, which can be beneficial for aviation safety and operations in case of e.g. volcanic ash plumes.
Kim, J.; Lee, S.; KIM, M.; Choi, M.; Go, S.; Lim, H.; Goo, T. Y.; Nakajima, T.; Kuze, A.; Shiomi, K.; Yokota, T.
An aerosol retrieval algorithm was developed from Thermal And Near infrared Sensor for carbon Observation-Cloud and Aerosol Imager (TANSO-CAI) onboard the Greenhouse Gases Observing Satellite (GOSAT). The algorithm retrieves aerosol optical depth (AOD), size distribution of aerosol, and aerosol type in 0.1 degree grid resolution by look-up tables, which is used in retrieving optical properties of aerosol using inversion products from Aerosol Robotic NETwork (AERONET) sun-photometer observation. To improve the accuracy of aerosol algorithm, first, this algorithm considered the annually estimated radiometric degradation factor of TANSO-CAI suggested by Kuze et al. (2014). Second, surface reflectance was determined by two methods: one using the clear sky composite method from CAI measurements and the other the database from MODerate resolution Imaging Sensor (MODIS) surface reflectance data. At a given pixel, the surface reflectance is selected by using normalized difference vegetation index (NDVI) depending on season (Hsu et al., 2013). In this study, the retrieved AODs were compared with those of AERONET and MODIS dataset for different season over five years. Comparisons of AODs between AERONET and CAI show reasonable agreement with correlation coefficients of 0.65 ~ 0.97 and regression slopes between 0.7 and 1.2 for the whole period, depending on season and sites. Moreover, those between MODIS and CAI for the same period show agreements with correlation coefficients of 0.7 ~ 0.9 and regression slopes between 0.7 and 1.0, depending on season and regions. The results show reasonably good correlation, however, the largest error source in aerosol retrieval has been surface reflectance of TANSO-CAI due to its 3-days revisit orbit characteristics.
Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae
The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.
Lim, H. Q.; Kanniah, K. D.; Lau, A. M. S.
Monitoring of atmospheric aerosols over the urban area is important as tremendous amounts of pollutants are released by industrial activities and heavy traffic flow. Air quality monitoring by satellite observation provides better spatial coverage, however, detailed aerosol properties retrieval remains a challenge. This is due to the limitation of aerosol retrieval algorithm on high reflectance (bright surface) areas. The aim of this study is to retrieve aerosol optical depth over urban areas of Iskandar Malaysia; the main southern development zone in Johor state, using Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m resolution data. One of the important steps is the aerosol optical depth retrieval is to characterise different types of aerosols in the study area. This information will be used to construct a Look Up Table containing the simulated aerosol reflectance and corresponding aerosol optical depth. Thus, in this study we have characterised different aerosol types in the study area using Aerosol Robotic Network (AERONET) data. These data were processed using cluster analysis and the preliminary results show that the area is consisting of coastal urban (65%), polluted urban (27.5%), dust particles (6%) and heavy pollution (1.5%) aerosols.
Zhuravleva, Tatiana B.; Bedareva, Tatiana V.; Sviridenkov, Mikhail A.
This study focuses on the results of testing an algorithm for retrieval of aerosol optical and microphysical characteristics in the total atmospheric column from ground-based measurements of direct and diffuse solar radiation. Clear-sky photometric measurements carried out under moderate aerosol loading of the atmosphere in summer for 2003-2009 at Tomsk station of AERONET network were used. The retrieved aerosol optical and microphysical parameters are compared with AERONET data, an empirical model of the vertical profiles of aerosol optical characteristics over Western Siberia, well-known OPAC (Optical Properties of Aerosol and Clouds) model and model recommended by the World Meteorological Organization (WMO) (continental aerosol). In the visible spectral range, the mean value of single scattering albedo is 0.9-0.92, in good agreement with other data. It is shown, however, that asymmetry factor of aerosol scattering phase function disagrees with the WMO and OPAC values. A short description of the inversion strategy is also presented.
Samaras, Stefanos; Nicolae, Doina; Böckmann, Christine; Vasilescu, Jeni; Binietoglou, Ioannis; Labzovskii, Lev; Toanca, Florica; Papayannis, Alexandros
In this work we extract the microphysical properties of aerosols for a collection of measurement cases with low volume depolarization ratio originating from fire sources captured by the Raman lidar located at the National Institute of Optoelectronics (INOE) in Bucharest. Our algorithm was tested not only for pure smoke but also for mixed smoke and urban aerosols of variable age and growth. Applying a sensitivity analysis on initial parameter settings of our retrieval code was proved vital for producing semi-automatized retrievals with a hybrid regularization method developed at the Institute of Mathematics of Potsdam University. A direct quantitative comparison of the retrieved microphysical properties with measurements from a Compact Time of Flight Aerosol Mass Spectrometer (CToF-AMS) is used to validate our algorithm. Microphysical retrievals performed with sun photometer data are also used to explore our results. Focusing on the fine mode we observed remarkable similarities between the retrieved size distribution and the one measured by the AMS. More complicated atmospheric structures and the factor of absorption appear to depend more on particle radius being subject to variation. A good correlation was found between the aerosol effective radius and particle age, using the ratio of lidar ratios (LR: aerosol extinction to backscatter ratios) as an indicator for the latter. Finally, the dependence on relative humidity of aerosol effective radii measured on the ground and within the layers aloft show similar patterns.
Stap, F. A.; Hasekamp, O. P.; Röckmann, T.
An important problem in satellite remote sensing of aerosols is related to the need to perform an adequate cloud screening. If a cloud screening is applied that is not strict enough, the ground scene has the probability of residual cloud cover which causes large errors on the retrieved aerosol parameters. On the other hand, if the cloud-screening procedure is too strict, too many clear sky cases, especially near-cloud scenes, will falsely be flagged cloudy. The detrimental effects of cloud contamination as well as the importance of aerosol cloud interactions that can be studied in these near-cloud scenes call for new approaches to cloud screening. Multi-angle multi-wavelength photopolarimetric measurements have a unique capability to distinguish between scattering by (liquid) cloud droplets and aerosol particles. In this paper the sensitivity of aerosol retrievals from multi-angle photopolarimetric measurements to cloud contamination is investigated and the ability to intrinsically filter the cloud-contaminated scenes based on a goodness-of-fit criteria is evaluated. Hereto, an aerosol retrieval algorithm is applied to a partially clouded over-ocean synthetic data set as well as non-cloud-screened over-ocean POLDER-3/PARASOL observations. It is found that a goodness-of-fit filter, together with a filter on the coarse mode refractive index (mrcoarse > 1.335) and a cirrus screening, adequately rejects the cloud-contaminated scenes. No bias or larger SD are found in the retrieved parameters for this intrinsic cloud filter compared to the parameters retrieved in a priori cloud-screened data set (using MODIS/AQUA cloud masks) of PARASOL observations. Moreover, less high-aerosol load scenes are misinterpreted as cloud contaminated. The retrieved aerosol optical thickness, single scattering albedo and Ångström exponent show good agreement with AERONET observations. Furthermore, the synthetic retrievals give confidence in the ability of the algorithm to correctly
Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Shinozuka, Y.; Schmid, B.
Absorbing smoke or mineral dust aerosols above clouds (AAC) are a frequent occurrence in certain regions and seasons. Operational aerosol retrievals from sensors like MODIS omit AAC because they are designed to work only over cloud-free scenes. However, AAC can in principle be quantified by these sensors in some situations (e.g. Jethva et al., 2013; Meyer et al., 2013). We present a summary of some analyses of the potential of MODIS-like instruments for this purpose, along with two case studies using airborne observations from the Ames Airborne Tracking Sunphotometer (AATS; http://geo.arc.nasa.gov/sgg/AATS-website/) as a validation data source for a preliminary AAC algorithm applied to MODIS measurements. AAC retrievals will eventually be added to the MODIS Deep Blue (Hsu et al., 2013) processing chain.
KIM, M.; Kim, J.; Jeong, U.; Kim, W. V.; Kim, S. K.; Lee, S. D.; Moon, K. J.
An algorithm to retrieve aerosol optical depth (AOD), single scattering albedo (SSA), and aerosol loading height is developed for GEMS (Geostationary Environment Monitoring Spectrometer) measurement. The GEMS is planned to be launched in geostationary orbit in 2018, and employs hyper-spectral imaging with 0.6 nm resolution to observe solar backscatter radiation in the UV and Visible range. In the UV range, the low surface contribution to the backscattered radiation and strong interaction between aerosol absorption and molecular scattering can be advantageous in retrieving aerosol information such as AOD and SSA [Torres et al., 2007; Torres et al., 2013; Ahn et al., 2014]. However, the large contribution of atmospheric scattering results in the increase of the sensitivity of the backward radiance to aerosol loading height. Thus, the assumption of aerosol loading height becomes important issue to obtain accurate result. Accordingly, this study focused on the simultaneous retrieval of aerosol loading height with AOD and SSA by utilizing the optimal estimation method. For the RTM simulation, the aerosol optical properties were analyzed from AERONET inversion data (level 2.0) at 46 AERONET sites over ASIA. Also, 2-channel inversion method is applied to estimate a priori value of the aerosol information to solve the Lavenberg Marquardt equation. The GEMS aerosol algorithm is tested with OMI level-1B dataset, a provisional data for GEMS measurement, and the result is compared with OMI standard aerosol product and AERONET values. The retrieved AOD and SSA show reasonable distribution compared with OMI products, and are well correlated with the value measured from AERONET. However, retrieval uncertainty in aerosol loading height is relatively larger than other results.
Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Mattoo, S.; Chu, D. A.; Martins, J. V.; Li, R.-R.; Ichoku, C.; Levy, R. C.; Kleidman, R. G.
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. 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 top of atmosphere. Over ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 microns to 2.13 microns. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral aerosol flux, 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 AERONET data gleaned from 133 AERONET stations. 8000 MODIS aerosol retrievals colocated with AERONET measurements confirm that one-standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of delta tauapproximately equal to plus or minus 0.03 plus or minus 0.05 tau over ocean and delta tay equal to plus or minus 0.05 plus or minus 0.15 tau over land. 271 MODIS aerosol retrievals co-located with AERONET inversions at island and coastal sites suggest that one-standard deviation of MODIS effective radius retrievals falls within delta r_eff approximately equal to 0.11 microns. 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.
McGarragh, Gregory; Poulsen, Caroline; Povey, Adam; Thomas, Gareth; Christensen, Matt; Sus, Oliver; Schlundt, Cornelia; Stapelberg, Stefan; Stengel, Martin; Grainger, Don
The Optimal Retrieval of Aerosol and Cloud (ORAC) is a generalized optimal estimation system that retrieves cloud, aerosol and volcanic ash parameters using satellite imager measurements in the visible to infrared. Use of the same algorithm for different sensors and parameters leads to consistency that facilitates inter-comparison and interaction studies. ORAC currently supports ATSR, AVHRR, MODIS and SEVIRI. In this proceeding we discuss the ORAC retrieval algorithm applied to ATSR data including the retrieval methodology, the forward model, uncertainty characterization and discrimination/classification techniques. Application of ORAC to SLSTR data is discussed including the additional features that SLSTR provides relative to the ATSR heritage. The ORAC level 2 and level 3 results are discussed and an application of level 3 results to the study of cloud/aerosol interactions is presented.
Liu, X.; Ferrare, R. A.; Hostetler, C. A.; Burton, S. P.; Stamnes, S.; Mueller, D.; Chemyakin, E.; Sawamura, P.; Cairns, B.
Knowledge of the vertical profile, composition, concentration, and size distribution of aerosols is required to quantify the impacts of aerosols on human health, global and regional climate, clouds and precipitation, and ocean ecosystems. We will describe an Optimal Estimation (OE) retrieval method that will use three wavelengths of aerosol backscattering (3β) and two wavelengths of aerosol extinction (2α). We will also describe how to use the OE framework to retrieve vertical profiles simultaneously using altitude resolved HSRL data. Finally, we will describe how to include additional measurements (e.g. polarimeter or Sun photometer) for improved aerosol microphysical property retrievals. In a traditional aerosol retrieval algorithm, one solves for aerosol size distributions under various parameter space (rmin, rmax, real and imaginary refractive index) using Tikhonov (or other) regularization and then selects physically and mathematically meaningful solutions from hundreds of thousand retrievals. In an attempt to speed up the retrieval and to provide retrieval error estimates, the OE method solves for all related aerosol microphysical parameters (e.g. number concentrations, particle size distribution, real and imaginary part of refractive indices) simultaneously in a maximum-likelihood sense by fitting the observed data. Other quantities such as effective particle radius, surface area concentration, volume concentration, and single scattering albedo are also derived from the retrieved size distribution and the number concentrations. We will show preliminary results using both simulated data and airborne measurements from HSRL-2. Coincident airborne in-situ and surface remote sensing datasets will be used to evaluate the performance of the new OE algorithm.
Kalashnikova, Olga V.; Diner, David J.; Kahn, Ralph; Gaitley, Barbara
Satellite measurements provide important tools for understanding the effect of mineral dust aerosols on past and present climate and climate predictions. Multi-angle instruments such as Multi-angle Imaging Spectro- Radiometer (MISR) provide independent constraints on aerosol properties based on their sensitivity to the shape of aerosol scattering phase functions. The current MISR operational retrieval algorithm (version 16 and higher) was modified by incorporating new non-spherical dust models that account for naturally occurring dust shapes and compositions. We present selected examples of MISR version 16 retrievals over AERONET sunphotometer land and ocean sites during the passage of dust fronts. Our analysis shows that during such events MISR retrieves Angstrom exponents characteristic of large particles, having little spectral variation in extinction over the MISR wavelength range (442, 550, 672 and 866 nm channels), as expected. The retrieved fraction of non-spherical particles is also very high. This quantity is not retrieved by satellite instruments having only nadir-viewing cameras. Our comparison of current (version 16) MISR-retrieved aerosol optical thickness (AOT) with AERONET instantaneous AOT shows better coverage and stronger correlations than when making identical comparisons with previous AOT retrievals (version 15). The MISR algorithm successful mixtures include a non-spherical dust component with high frequency in retrievals over dark water and slightly lower frequency over land. Selection frequencies of non-spherical dust models also decrease in dusty regions affected by pollution.
Wang, Han; Sun, Xiaobing; Hou, Weizhen; Chen, Cheng; Hong, Jin
New developed sensor was called Atmosphere Multi-angle Polarization Radiometer (AMPR). It provides airborne multi-spectral, multi-angular and polarized measurements. Based on the measurements, a method to retrieve aerosol optical thickness (AOT) was developed. To reduce the ambiguity in retrieval algorithm, the key characteristics of aerosol model over East Asia are constrained. Initial surface reflectance was estimated from measurements at 1640 nm. With iteration the surface polarized reflectance tends to the real value together with AOT. Retrieved cases were selected from measurements in Tianjin. Validation between AOTs from AMPR and CE318 is encouraging. The AOTs along the track shows reasonable temporal and spatial variation.
Mei, L.; Xue, Y.; Kokhanovsky, A. A.
IPCC fourth assessment report demonstrated that aerosol is the least understood with highest uncertainty (The uncertainty of aerosol radiative forcing is even larger than radiative forcing itself) factor compared to other component in the climate system (IPCC, 2007). The mainly reason is due to the high variability in space and temporary of aerosol and it is really difficult for us to obtain enough information for understanding aerosol effect. Even we obtain sufficient information; there is still a problem to get the aerosol properties with high accuracy because almost all the aerosol properties are coupled. Many different aerosol monitoring schemes using different satellite data are available, the original stem is based on at least one assumption; that is except the retrieval aerosol properties, all the other properties (both aerosol and surface) can be obtained first. For instance, DeepBlue method is supported by a reflectance database (Hsu et al., 2004) while DDV algorithm need much prior knowledge about other aerosol properties (Levy et al., 2007) in order to retrieve aerosol optical depth (AOD). However, the retrieval methods are not always capable of reproducing the AOD spectral slope in a correct way because the correspondent aerosol model (Kokhanovsky et al, 2009) and other factors are not retrieved but rather prescribed. Is it possible for us to retrieve several aerosol or surface properties simultaneously? A novel approach for the joint retrieval of AOD, aerosol type and surface reflectance, using Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imagers (MSG/SEVIRI) observations in two solar channels, is presented in this paper. MSG/SEVIRI combines the advantages of a multi-spectral sensor as well as high-temporary satellite. The paper confined the consideration only to one approximate method of reducing the problem to solving a set of differential equations in the application to the case of shortwave radiation transfer. After
Nowlan, C. R.; Liu, X.; Leitch, J. W.; Chance, K.; González Abad, G.; Liu, C.; Zoogman, P.; Cole, J.; Delker, T.; Good, W.; Murcray, F.; Ruppert, L.; Soo, D.; Follette-Cook, M. B.; Janz, S. J.; Kowalewski, M. G.; Loughner, C. P.; Pickering, K. E.; Herman, J. R.; Beaver, M. R.; Long, R. W.; Szykman, J. J.; Judd, L. M.; Kelley, P.; Luke, W. T.; Ren, X.; Al-Saadi, J. A.
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a testbed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas in September 2013. Measurements of backscattered solar radiation between 420-465 nm collected on four days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 molecules cm-2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.91 for the most polluted day). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.84, slope = 0.94). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.
Nowlan, Caroline R.; Liu, Xiong; Leitch, James W.; Chance, Kelly; González Abad, Gonzalo; Liu, Cheng; Zoogman, Peter; Cole, Joshua; Delker, Thomas; Good, William; Murcray, Frank; Ruppert, Lyle; Soo, Daniel; Follette-Cook, Melanie B.; Janz, Scott J.; Kowalewski, Matthew G.; Loughner, Christopher P.; Pickering, Kenneth E.; Herman, Jay R.; Beaver, Melinda R.; Long, Russell W.; Szykman, James J.; Judd, Laura M.; Kelley, Paul; Luke, Winston T.; Ren, Xinrong; Al-Saadi, Jassim A.
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 molecules
Munchak, L. A.; Levy, R. C.; Mattoo, S.; Patadia, F.; Wilcox, E. M.; Marshak, A.
Passive satellite remote sensing has become essential for obtaining global information about aerosol properties, including aerosol optical depth (AOD) and aerosol fine mode fraction (FMF). However, due to the spatial resolution of satellite aerosol products (typically 3 km and larger), observing aerosol within dense partly cloudy fields is difficult from space. Here, we apply an adapted version of the MODIS Collection 6 dark target algorithm to the 50-meter MODIS airborne simulator retrieved reflectances measured during the SEAC4RS campaign during 2013 to robustly retrieve aerosol with a 500 m resolution. We show good agreement with AERONET and MODIS away from cloud, suggesting that the algorithm is working as expected. However, closer to cloud, significant AOD increases are observed. We investigate the cause of these AOD increases, including examining the potential for undetected cloud contamination, reflectance increases due to unconsidered 3D radiative effects, and the impact of humidification on aerosol properties. In combination with other sensors that flew in SEAC4RS, these high-resolution observations of aerosol in partly cloudy fields can be used to characterize the radiative impact of the "twilight zone" between cloud and aerosol which is typically not considered in current estimates of direct aerosol radiative forcing.
Rose, C. R.; Chandrasekar, V.
System engineering principles and methods are very useful in large-scale complex systems for developing the engineering requirements from end-user needs. Integrating research into system engineering is a challenging task. The proposed Global Precipitation Mission (GPM) satellite will use a dual-wavelength precipitation radar to measure and map global precipitation with unprecedented accuracy, resolution and areal coverage. The satellite vehicle, precipitation radars, retrieval algorithms, and ground validation (GV) functions are all critical subsystems of the overall GPM system and each contributes to the success of the mission. Errors in the radar measurements and models can adversely affect the retrieved output values. Ground validation (GV) systems are intended to provide timely feedback to the satellite and retrieval algorithms based on measured data. These GV sites will consist of radars and DSD measurement systems and also have intrinsic constraints. One of the retrieval algorithms being studied for use with GPM is the dual-wavelength DSD algorithm that does not use the surface reference technique (SRT). The underlying microphysics of precipitation structures and drop-size distributions (DSDs) dictate the types of models and retrieval algorithms that can be used to estimate precipitation. Many types of dual-wavelength algorithms have been studied. Meneghini (2002) analyzed the performance of single-pass dual-wavelength surface-reference-technique (SRT) based algorithms. Mardiana (2003) demonstrated that a dual-wavelength retrieval algorithm could be successfully used without the use of the SRT. It uses an iterative approach based on measured reflectivities at both wavelengths and complex microphysical models to estimate both No and Do at each range bin. More recently, Liao (2004) proposed a solution to the Do ambiguity problem in rain within the dual-wavelength algorithm and showed a possible melting layer model based on stratified spheres. With the No and Do
Dörner, Steffen; Penning de Vries, Marloes; Pukite, Janis; Beirle, Steffen; Wagner, Thomas
Techniques for retrieving height resolved information on stratospheric aerosol improved significantly in the past decade with the availability of satellite measurements in limb geometry. Instruments like OMPS, OSIRIS and SCIAMACHY provide height resolved radiance spectra with global coverage. Long term data sets of stratospheric aerosol extinction profiles are important for a detailed investigation of spatial and temporal variation and formation processes (e.g. after volcanic eruptions or in polar stratospheric clouds). Resulting data sets contain vital information for climate models (radiative effect) or chemistry models (reaction surface for heterogeneous chemistry). This study focuses on the SCIAMACHY instrument which measured scattered sunlight in the ultra-violet, visible and near infra-red spectral range since the launch on EnviSat in 2002 until an instrumental error occurred in April 2012. SCIAMACHY's unique method of alternating measurements in limb and nadir geometry provides co-located profile and column information respectively that can be used to characterize plumes with small horizontal extents. The covered wavelength range potentially provides information on effective micro-physical properties of the aerosol particles. However, scattering on background aerosol constitutes only a small fraction of detected radiance and assumptions on particle characteristics (e.g. size distribution) have to be made which results in large uncertainties especially for wavelengths below 700nm and for measurements in backscatter geometry. Methods to reduce these uncertainties are investigated and applied to our newly developed retrieval algorithm. In addition, so called spatial straylight contamination of the measured signal was identified as a significant error source and an empirical correction scheme was developed. A large scale comparison study with SAGE II for the temporal overlap of both instruments (2002 to 2005) shows promising results.
Remer, L. A.; Mattoo, S.; Levy, R. C.; Munchak, L.
After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community.
Stap, F. A.; Hasekamp, O. P.; Emde, C.
Most satellite measurements of the microphysical and radiative properties of aerosol near clouds are either strictly screened for, or hindered by sub-pixel cloud contamination. This may change with the advent of a new generation of aerosol retrieval algorithms,intended for multi-angle, multi-wavelength photo-polarimetric instruments such as POLDER3on board PARASOL, which show ability to separate between aerosol and cloud particles.In order to obtain the required computational efficiency these algorithms typically make use of 1D radiative transfer models and are thus unable to account for the 3D effects that occur in actual, partially clouded scenes.Here, we apply an aerosol retrieval algorithm, which employs a 1D radiative transfer code and the independent pixel approximation, on synthetic, 3D, partially cloudedscenes calculated with the Monte Carlo radiative transfer code MYSTIC.The influence of the 3D effects due to clouds on the retrieved microphysical and optical aerosol properties is presented and the ability of the algorithm to retrieve these properties in partially clouded scenes will be discussed.
Li, Chi; Xue, Yong; Yang, Leiku; Guang, Jie
by straightforwardly utilizing Mie theory in dust aerosol retrieval. As expected we find that the uncertainties mainly result from the obvious difference of phase functions (Pspheric and Pspheroid). Errors may be positive or negative, depending on the specific geometry. In scattering angle (θ) regions where Psphericis greater (30°~85° & 145°~180°), we generally get positive Δ?TOA and negative Δ?, and vice versa (85°~145°). For low aerosol loading (? ~0.25) and black surface, |Δ?TOA| could be greater than 0.004 and 0.012 around θ ~120° and θ ~170°, with |Δ?| of ~0.04 and ~0.12 respectively. In most back scattering cases (θ >100°), the magnitude of Δ? is about ten times that of Δ?TOA, while this ratio (|Δ?|/|Δ?TOA|) significantly reduces to as low as ~0.5 for forward scattering, and can reach ~20 at θ ~145°. Moreover, this errors and |Δ?|/|Δ?TOA| can increase more than ten times as aerosol loading gets higher and surface gets brighter. Therefore we conclude that the neglect of non-sphericity introduces substantial errors on radiative transfer simulation and AOD retrieval. As a result of this study, a representative aspheric aerosol model other than Mie calculation is recommended for inversion algorithms related with dust-like non-spherical aerosols. References Dubovik, O., Holben, B. N., Lapyonok, T., Sinyuk, A., Mishchenko, M. I., Yang, P., and Slutsker, I. (2002). Non-spherical aerosol retrieval method employing light scattering by spheroids. Geophyscal Research Letters, 29(10), 1415, doi:10.1029/2001GL014506. Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J., Leon, J.-F., Sorokin, M., and Slutsker, I. (2006). Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. Journal of Geophysical Research, 111, D11208, doi:10.1029/2005JD006619. Mishchenko, M. I., Lacis, A. A., Carlson, B. E., and
Thomas, Gareth; Poulsen, Caroline; Povey, Adam; McGarragh, Greg; Jerg, Matthias; Siddans, Richard; Grainger, Don
The Optimal Retrieval of Aerosol and Cloud (ORAC) - formally the Oxford-RAL Aerosol and Cloud retrieval - offers a framework that can provide consistent and well characterised properties of both aerosols and clouds from a range of imaging satellite instruments. Several practical issues stand in the way of achieving the potential of this combined scheme however; in particular the sometimes conflicting priorities and requirements of aerosol and cloud retrieval problems, and the question of the unambiguous identification of aerosol and cloud pixels. This presentation will present recent developments made to the ORAC scheme for both aerosol and cloud, and detail how these are being integrated into a single retrieval framework. The implementation of a probabilistic method for pixel identification will also be presented, for both cloud detection and aerosol/cloud type selection. The method is based on Bayesian methods applied the optimal estimation retrieval output of ORAC and is particularly aimed at providing additional information in the so-called "twilight zone", where pixels can't be unambiguously identified as either aerosol or cloud and traditional cloud or aerosol products do not provide results.
Guo, Changliang; Liu, Shi; Sheridan, John T
Two modified Gerchberg-Saxton (GS) iterative phase retrieval algorithms are proposed. The first we refer to as the spatial phase perturbation GS algorithm (SPP GSA). The second is a combined GS hybrid input-output algorithm (GS/HIOA). In this paper (Part I), it is demonstrated that the SPP GS and GS/HIO algorithms are both much better at avoiding stagnation during phase retrieval, allowing them to successfully locate superior solutions compared with either the GS or the HIO algorithms. The performances of the SPP GS and GS/HIO algorithms are also compared. Then, the error reduction (ER) algorithm is combined with the HIO algorithm (ER/HIOA) to retrieve the input object image and the phase, given only some knowledge of its extent and the amplitude in the Fourier domain. In Part II, the algorithms developed here are applied to carry out known plaintext and ciphertext attacks on amplitude encoding and phase encoding double random phase encryption systems. Significantly, ER/HIOA is then used to carry out a ciphertext-only attack on AE DRPE systems. PMID:26192504
Gupta, Pawan; Torres, Omar; Jethva, Hiren; Ahn, Changwoo
Ozone Monitoring Instrument (OMI) onboard Aura satellite retrieved aerosols properties using UV part of solar spectrum. The OMI near UV aerosol algorithm (OMAERUV) is a global inversion scheme which retrieves aerosol properties both over ocean and land. The current version of the algorithm makes use of TOMS derived Lambertian Equivalent Reflectance (LER) climatology. A new monthly climatology of surface LER at 354 and 388 nm have been developed. This will replace TOMS LER (380 nm and 354nm) climatology in OMI near UV aerosol retrieval algorithm. The main objectives of this study is to produce high resolution (quarter degree) surface LER sets as compared to existing one degree TOMS surface LERs, to product instrument and wavelength consistent surface climatology. Nine years of OMI observations have been used to derive monthly climatology of surface LER. MODIS derived aerosol optical depth (AOD) have been used to make aerosol corrections on OMI wavelengths. MODIS derived BRDF adjusted reflectance product has been also used to capture seasonal changes in the surface characteristics. Finally spatial and temporal averaging techniques have been used to fill the gaps around the globes, especially in the regions with consistent cloud cover such as Amazon. After implementation of new surface data in the research version of algorithm, comparisons of AOD and single scattering albedo (SSA) have been performed over global AERONET sites for year 2007. Preliminary results shows improvements in AOD retrievals globally but more significance improvement were observed over desert and bright locations. We will present methodology of deriving surface data sets and will discuss the observed changes in retrieved aerosol properties with respect to reference AERONET measurements.
Rault, Didier F.
The upcoming Ozone Mapper and Profiler Suite (OMPS), which will be launched on the NPOESS Preparatory Project (NPP) platform in early 2011, will continue monitoring the global distribution of the Earth's middle atmosphere ozone and aerosol. OMPS is composed of three instruments, namely the Total Column Mapper (heritage: TOMS, OMI), the Nadir Profiler (heritage: SBUV) and the Limb Profiler (heritage: SOLSE/LORE, OSIRIS, SCIAMACHY, SAGE III). The ultimate goal of the mission is to better understand and quantify the rate of stratospheric ozone recovery. The focus of the paper will be on the Limb Profiler (LP) instrument. The LP instrument will measure the Earth's limb radiance (which is due to the scattering of solar photons by air molecules, aerosol and Earth surface) in the ultra-violet (UV), visible and near infrared, from 285 to 1000 nm. The LP simultaneously images the whole vertical extent of the Earth's limb through three vertical slits, each covering a vertical tangent height range of 100 km and each horizontally spaced by 250 km in the cross-track direction. Measurements are made every 19 seconds along the orbit track, which corresponds to a distance of about 150km. Several data analysis tools are presently being constructed and tested to retrieve ozone and aerosol vertical distribution from limb radiance measurements. The primary NASA algorithm is based on earlier algorithms developed for the SOLSE/LORE and SAGE III limb scatter missions. All the existing retrieval algorithms rely on a spherical symmetry assumption for the atmosphere structure. While this assumption is reasonable in most of the stratosphere, it is no longer valid in regions of prime scientific interest, such as polar vortex and UTLS regions. The paper will describe a two-dimensional retrieval algorithm whereby the ozone distribution is simultaneously retrieved vertically and horizontally for a whole orbit. The retrieval code relies on (1) a forward 2D Radiative Transfer code (to model limb
Schoemaker, R. M.
During the months of August and September 2004 the United Arabic Emirates Unified Aerosol Experiment (UAE2) mission took place in the marine and desert region of the United Arabic Emirates. One of the primary goals of the mission was to evaluate and improve scientific based satellite aerosol and ocean retrieval products. Important aspect was the calibration and validation of remote sensing systems in order to gain more insight in space-based retrievals over this part of the region. This paper contributes to part of the space-based mission objectives and governs the retrieval of atmospheric aerosol properties over water through data from the AATSR instrument on board the European ENVISAT satellite. At TNO Defence, Security and Safety the retrieval of aerosol properties from AATSR is performed by means of the dual view algorithm for application over land and the single view algorithm for application over ocean. Both algorithms have been merged into a fast and efficient algorithm that allows for near real-time processing and which is suitable for semi-operational use. Data from retrievals over water have been compared with ground-truth measurements from the AERONET sun photometers present for the three water sites in the Persian Gulf during the campaign. The properties retrieved are a) aerosol optical depth for the visible wavelengths of AATSR and b) the Ångström wavelength coefficient α as an indicator for the size distribution. Different aerosol types have been pre-modeled by means of AERONET phase function information, and saved as look-up tables for the retrieval procedure. By comparing the satellite retrieved information with the ground-truth data for each of the modeled aerosol type more insight in the retrieval procedure and in the aerosol make-up in this region is obtained.
Rodgers, C.; Bhartia, P. K.; Chu, W. P.; Curran, R.; Deluisi, J.; Gille, J. C.; Hudson, R.; Mateer, C.; Rusch, D.; Thomas, R. J.
The algorithms are characterized that were used for production processing by the major suppliers of ozone data to show quantitatively: how the retrieved profile is related to the actual profile (This characterizes the altitude range and vertical resolution of the data); the nature of systematic errors in the retrieved profiles, including their vertical structure and relation to uncertain instrumental parameters; how trends in the real ozone are reflected in trends in the retrieved ozone profile; and how trends in other quantities (both instrumental and atmospheric) might appear as trends in the ozone profile. No serious deficiencies were found in the algorithms used in generating the major available ozone data sets. As the measurements are all indirect in someway, and the retrieved profiles have different characteristics, data from different instruments are not directly comparable.
Yilmaz, Selami; Frieß, Udo; Apituley, Arnoud; Henzing, Bas; Baars, Holger; Heese, Birgit; Althausen, Dietrich; Adam, Mariana; Putaud, Jean-Philippe; Zieger, Paul; Platt, Ulrich
Multi Axis Differential Absorption Spectroscopy (MAX-DOAS) is a well established measurement technique to derive atmospheric trace gas profiles. Using MAX-DOAS measurements of trace gases with a known vertical profile, like the oxygen-dimer O4, it is possible to retrieve information on atmospheric aerosols. Based on the optimal estimation method, we have developed an algorithm which fits simultaneously measured O4 optical densities and relative intensities at several wavelengths and elevation angles to values simulated by a radiative transfer model. Retrieval parameters are aerosol extinction profile and optical properties such as single scattering albedo, phase function and Angström exponent. In 2008 and 2009 several intercomparison campaigns with established aerosol measurement techniques took place in Cabauw/Netherlands, Melpitz/Germany, Ispra/Italy and Leipzig/Germany, where simultaneous DOAS, lidar, Sun photometer and Nephelometer measurements were performed. Here we present results of the intercomparisons for cloud free conditions. The correlation of the aerosol optical thickness retrieved by the DOAS technique and the Sun photometer shows coefficients of determination from 0.96 to 0.98 and slopes from 0.94 to 1.07. The vertical structure of the DOAS retrieved aerosol extinction profiles compare favourably with the structures seen by the backscatter lidar. However, the vertical spatial development of the boundary layer is reproduced with a lower resolution by the DOAS technique. Strategies for the near real-time retrieval of trace gas profiles, aerosol profiles and optical properties will be discussed as well.
Määttä, A.; Laine, M.; Tamminen, J.; Veefkind, J. P.
We study uncertainty quantification in remote sensing of aerosols in the atmosphere with top of the atmosphere reflectance measurements from the nadir-viewing Ozone Monitoring Instrument (OMI). Focus is on the uncertainty in aerosol model selection of pre-calculated aerosol models and on the statistical modelling of the model inadequacies. The aim is to apply statistical methodologies that improve the uncertainty estimates of the aerosol optical thickness (AOT) retrieval by propagating model selection and model error related uncertainties more realistically. We utilise Bayesian model selection and model averaging methods for the model selection problem and use Gaussian processes to model the smooth systematic discrepancies from the modelled to observed reflectance. The systematic model error is learned from an ensemble of operational retrievals. The operational OMI multi-wavelength aerosol retrieval algorithm OMAERO is used for cloud free, over land pixels of the OMI instrument with the additional Bayesian model selection and model discrepancy techniques. The method is demonstrated with four examples with different aerosol properties: weakly absorbing aerosols, forest fires over Greece and Russia, and Sahara dessert dust. The presented statistical methodology is general; it is not restricted to this particular satellite retrieval application.
Sanders, A. F. J.; de Haan, J. F.
We have investigated the precision of retrieved aerosol parameters for a generic aerosol retrieval algorithm over vegetated land using the O2 A band. Chlorophyll fluorescence is taken into account in the forward model. Fluorescence emissions are modeled as isotropic contributions to the upwelling radiance field at the surface and they are retrieved along with aerosol parameters. Precision is calculated by propagating measurement errors and a priori errors, including model parameter errors, using the forward model's derivatives. Measurement errors consist of noise and calibration errors. The model parameter errors considered are related to the single scattering albedo, surface pressure and temperature profile. We assume that measurement noise is dominated by shot noise; thus, results apply to grating spectrometers in particular. We describe precision for various atmospheric states, observation geometries and spectral resolutions of the instrument in a number of retrieval simulations. These precision levels can be compared with user requirements. A comparison of precision estimates with the literature and an analysis of the dependence on the a priori error in the fluorescence emission indicate that aerosol parameters can be retrieved in the presence of chlorophyll fluorescence: if fluorescence is present, fluorescence emissions should be included in the state vector to avoid biases in retrieved aerosol parameters.
Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.
Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.
Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.
Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty ˜25-50% (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty ˜10-20%, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.
Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae
This study extends the application of the previously developed Aerosol Single-scattering albedo and layer Height Estimation (ASHE) algorithm, which was originally applied to smoke aerosols only, to both smoke and dust aerosols by including nonspherical dust properties in the retrieval process. The main purpose of the algorithm is to derive aerosol height information over wide areas using aerosol products from multiple satellite sensors simultaneously: aerosol optical depth (AOD) and Ångström exponent from the Visible Infrared Imaging Radiometer Suite (VIIRS), UV aerosol index from the Ozone Mapping and Profiler Suite (OMPS), and total backscatter coefficient profile from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The case studies suggest that the ASHE algorithm performs well for both smoke and dust aerosols, showing root-mean-square error of the retrieved aerosol height as compared to CALIOP observations from 0.58 to 1.31 km and mean bias from -0.70 to 1.13 km. In addition, the algorithm shows the ability to retrieve single-scattering albedo to within 0.03 of Aerosol Robotic Network inversion data for moderate to thick aerosol loadings (AOD of ~1.0). For typical single-layered aerosol cases, the estimated uncertainty in the retrieved height ranges from 1.20 to 1.80 km over land and from 1.15 to 1.58 km over ocean when favorable conditions are met. Larger errors are observed for multilayered aerosol events, due to the limited sensitivities of the passive sensors to such cases.
Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.
The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to
Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.
This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.
Gassó, Santiago; Torres, Omar
Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD < 0.3, 30 % for AOD > 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm ˜ < 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (< 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the
Wang, Menghua; Gordon, Howard R.
Based on the fact that the part of downward radiance that depends on the optical properties of the aerosol in the atmosphere can be extracted from the measured sky radiance, a new scheme for retrieval of the aerosol phase function and the single-scattering albedo over the ocean is developed. This retrieval algorithm is tested with simulations for several cases. It is found that the retrieved aerosol phase function and the single-scattering albedo are virtually error-free if the vertical structure of the atmosphere is known and if the sky radiance and the aerosol optical thickness can be measured accurately. The robustness of the algorithm in realistic situations, in which the measurements are contaminated by calibration errors or noise, is examined. It is found that the retrieved value of omega(0) is usually in error by less than about 10 percent, and the phase function is accurately retrieved for theta less than about 90 deg. However, as the aerosol optical thickness becomes small, e.g., less than about 0.1, errors in the sky radiance measurement can lead to serious problems with the retrieval algorithm, especially in the blue. The use of the retrieval scheme should be limited to the red and near IR when the aerosol optical thickness is small.
Petrenko, M.; Smirnov, A.; Ichoku, C. M.
Complementary global aerosol products have been routinely available from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, SeaWiFS, and VIIRS. However, a variety of studies suggest that individual aerosol products have significant differences in the geographic distribution of their retrieval uncertainties. Nonetheless, it can be difficult or impractical to track down relevant product validation studies and invest time in mastering the proprietary file formats of these aerosol products. As a result, many studies are performed using data from one or two most familiar products that, oftentimes, may not be optimal for a given region of interest. In this presentation, we will use Aerosol Robotic Network (AERONET) and Maritime Aerosol Network (MAN) data within the framework of the Multi-sensor Aerosol Products Sampling System (MAPSS) to catalog the accuracy of aerosol retrievals from the spaceborne sensors listed above. We will report our findings in analyzing the spatial and temporal distributions of the uncertainties in the global over-land and maritime retrievals of aerosols based on inter-comparing spaceborne data with coincident ground-based measurements from both AERONET and MAN. We will also explain our vision of how this analysis can be used as a base for a multi-sensor aerosol product package that would help end users to make a more informed choice when selecting data for their regions of interest.
Albayrak, A.; Wei, J. C.; Petrenko, M.; Lary, D. J.; Leptoukh, G. G.
Over the past decade, global aerosol observations have been conducted by space-borne sensors, airborne instruments, and ground-base network measurements. Unfortunately, quite often we encounter the differences of aerosol measurements by different well-calibrated instruments, even with a careful collocation in time and space. The differences might be rather substantial, and need to be better understood and accounted for when merging data from many sensors. The possible causes for these differences come from instrumental bias, different satellite viewing geometries, calibration issues, dynamically changing atmospheric and the surface conditions, and other "regressors", resulting in random and systematic errors in the final aerosol products. In this study, we will concentrate on the subject of removing biases and the systematic errors from MODIS (both Terra and Aqua) aerosol product, using Machine Learning algorithms. While we are assessing our regressors in our system when comparing global aerosol products, the Aerosol Robotic Network of sun-photometers (AERONET) will be used as a baseline for evaluating the MODIS aerosol products (Dark Target for land and ocean, and Deep Blue retrieval algorithms). The results of bias adjustment for MODIS Terra and Aqua are planned to be incorporated into the AeroStat Giovanni as part of the NASA ACCESS funded AeroStat project.
The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA F...
Kahn, Ralph A.; Sayer, Andrew M.; Ahmad, Ziauddin; Franz, Bryan A.
As atmospheric reflectance dominates top-of-the-atmosphere radiance over ocean, atmospheric correction is a critical component of ocean color retrievals. This paper explores the operational Sea-viewing Wide Field-of-View Sensor (SeaWiFS) algorithm atmospheric correction with approximately 13 000 coincident surface-based aerosol measurements. Aerosol optical depth at 440 nm (AOD(sub 440)) is overestimated for AOD below approximately 0.1-0.15 and is increasingly underestimated at higher AOD; also, single-scattering albedo (SSA) appears overestimated when the actual value less than approximately 0.96.AOD(sub 440) and its spectral slope tend to be overestimated preferentially for coarse-mode particles. Sensitivity analysis shows that changes in these factors lead to systematic differences in derived ocean water-leaving reflectance (Rrs) at 440 nm. The standard SeaWiFS algorithm compensates for AOD anomalies in the presence of nonabsorbing, medium-size-dominated aerosols. However, at low AOD and with absorbing aerosols, in situ observations and previous case studies demonstrate that retrieved Rrs is sensitive to spectral AOD and possibly also SSA anomalies. Stratifying the dataset by aerosol-type proxies shows the dependence of the AOD anomaly and resulting Rrs patterns on aerosol type, though the correlation with the SSA anomaly is too subtle to be quantified with these data. Retrieved chlorophyll-a concentrations (Chl) are affected in a complex way by Rrs differences, and these effects occur preferentially at high and low Chl values. Absorbing aerosol effects are likely to be most important over biologically productive waters near coasts and along major aerosol transport pathways. These results suggest that future ocean color spacecraft missions aiming to cover the range of naturally occurring and anthropogenic aerosols, especially at wavelengths shorter than 440 nm, will require better aerosol amount and type constraints.
Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae
Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height as well as single scattering albedo (SSA) for biomass burning smoke aerosols. One of the advantages of this algorithm was that the aerosol layer height can be retrieved over broad areas, which had not been available from lidar observations only. The algorithm utilized aerosol properties from three different satellite sensors, i.e., aerosol optical depth (AOD) and Ångström exponent (AE) from Moderate Resolution Imaging Spectroradiometer (MODIS), UV aerosol index (UVAI) from Ozone Monitoring Instrument (OMI), and aerosol layer height from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Here, we extend the application of the algorithm to Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) data. We also now include dust layers as well as smoke. Other updates include improvements in retrieving the AOD of nonspherical dust from VIIRS, better determination of the aerosol layer height from CALIOP, and more realistic input aerosol profiles in the forward model for better accuracy.
Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.
An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.
Pahlow, Markus; Müller, Detlef; Tesche, Matthias; Eichler, Heike; Feingold, Graham; Eberhard, Wynn L.; Cheng, Ya-Fang
Simulation studies were carried out with regard to the feasibility of using combined observations from sunphotometer (SPM) and lidar for microphysical characterization of aerosol particles, i.e., the retrieval of effective radius, volume, and surface-area concentrations. It was shown that for single, homogeneous aerosol layers, the aerosol parameters can be retrieved with an average accuracy of 30% for a wide range of particle size distributions. Based on the simulations, an instrument combination consisting of a lidar that measures particle backscattering at 355 and 1574 nm, and a SPM that measures at three to four channels in the range from 340 to 1020 nm is a promising tool for aerosol characterization. The inversion algorithm has been tested for a set of experimental data. The comparison with the particle size distribution parameters, measured with in situ instrumentation at the lidar site, showed good agreement.
Martonchik, J.; Diner, D.; Kahn, R.
Retrieval of aerosol optical depth over ocean is routinely performed by many different single-view satellite instruments. Because most of the ocean surface is sufficiently black in the red and near-IR, its reflectance at these wavelengths can be conveniently ignored, which greatly simplifies the retrieval process. Once the aerosol properties are determined using these wavelengths, the scene can then be atmospherically corrected to determine the amount of water-leaving radiance in all the visible spectral bands of the instrument (i.e., the ocean color). It is this particular surface information which can be analyzed to determine aspects of the biological and chemical content of the water. However, there are many regions where this black water criterion is not met, particularly in coastal waters with continental runoff and areas with heavy phytoplankton bloom. In these situations, aerosol retrievals become much more difficult and the ocean color more uncertain. Preliminary studies indicate that simultaneous (or near-simultaneous) multiangle satellite observations (e.g., by MISR) of the ocean can help to provide more robust aerosol and ocean color retrievals. Here, the directional properties of the ocean color radiances (and not the lack of ocean color in the red and near-IR) can potentially supply the necessary surface constraint needed to perform a reasonably accurate aerosol and ocean color retrieval. As such, the applicability of this retrieval algorithm could extend over a much wider range of water conditions than is currently routinely attempted. An additional benefit of this approach is that it allows all spectral bands of the the multiangle instrument to be used by the algorithm, thus providing a more robust determination of aerosol properties. We will show some results of case studies using MISR data, performed over different water conditions (open ocean, coastal waters, blooms), and will assess the potential of using surface constraints based on the
Zhang, H.; Hoff, R. M.; Kondragunta, S.; Laszlo, I.; Lyapustin, A.
Aerosol Optical Depth (AOD) in the Western United States is observed independently by both the GOES-East and GOES-West imagers. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm treats each satellite as a unique sensor and thus NOAA obtains two separate aerosol optical depth values at the same time for the same location. The TOA radiances and the associated derived optical depths can be quite different due to the different viewing geometries with large difference in solar-scattering angles. In order to fully exploit the simultaneous observations and generate consistent AOD retrievals from the two satellites, the authors develop a new aerosol optical depth retrieval algorithm that uses data from both satellites. The algorithm uses combined GOES-East and GOES-West visible channel TOA reflectance and daily average AOD from GOES Multi-Angle Implementation of Atmospheric Correction (GOES-MAIAC) on clear days (AOD less than 0.3), when diurnal variation of AOD is low, to retrieve surface BRDF. The known BRDF shape is applied on subsequent days to retrieve BRDF and AOD. The algorithm is validated at three AERONET sites over the Western US. The AOD retrieval accuracy from the hybrid technique using the two satellites is similar to that from one satellite over UCSB and Railroad Valley. Improvement of the accuracy is observed at Boulder. The correlation coefficients between the GOES AOD and AERONET AOD are in the range of 0.67 to 0.81 over the three sites. The hybrid algorithm has more data coverage compared to the single satellite retrievals over surfaces with high reflectance. The number of coincidences with AERONET observations increases from the use of two-single satellite algorithms by 5-80% for the three sites. With the application of the new algorithm, consistent AOD retrievals and better retrieval coverages can be obtained using the data from the two GOES satellite imagers.
Kleidman, Richard G.; Smirnov, Alexander; Levy, Robert C.; Mattoo, Shana; Tanre, Didier
The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the MODIS aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing MODIS Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that MODIS is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and Aqua, respectively. Angstrom Exponent comparisons show a high correlation between MODIS retrievals and shipboard measurements (R= 0.85 Terra, 0.83 Aqua), although the MODIS aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and Aqua ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that Aqua agreement with AERONET is marginally better. However we cannot claim based on the current study that the better Aqua comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and Aqua retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process.
Lyapustin, A.; Wang, Y.; Hsu, C.; Terres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, S.
MODIS is a wide field-of-view sensor providing daily global observations of the Earth. Currently, global MODIS aerosol retrievals over land are performed with the main Dark Target algorithm complimented with the Deep Blue (DB) Algorithm over bright deserts. The Dark Target algorithm relies on surface parameterization which relates reflectance in MODIS visible bands with the 2.1 micrometer region, whereas the Deep Blue algorithm uses an ancillary angular distribution model of surface reflectance developed from the time series of clear-sky MODIS observations. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has been developed for MODIS. MAIAC uses a time series and an image based processing to perform simultaneous retrievals of aerosol properties and surface bidirectional reflectance. It is a generic algorithm which works over both dark vegetative surfaces and bright deserts and performs retrievals at 1 km resolution. In this work, we will provide a comparative analysis of DB, MAIAC, MISR and OMI aerosol products over bright deserts of northern Africa.
Ottaviani, M.; Knobelspiesse, K.; Cairns, B.; Mishchenko, M.
We exploit quantitative metrics to investigate the information content in retrievals of atmospheric aerosol parameters (with a focus on single-scattering albedo), contained in multi-angle and multi-spectral measurements with sufficient dynamical range in the sunglint region. The simulations are performed for two classes of maritime aerosols with optical and microphysical properties compiled from measurements of the Aerosol Robotic Network. The information content is assessed using the inverse formalism and is compared to that deriving from observations not affected by sunglint. We find that there indeed is additional information in measurements containing sunglint, not just for single-scattering albedo, but also for aerosol optical thickness and the complex refractive index of the fine aerosol size mode, although the amount of additional information varies with aerosol type.
Bassani, Cristiana; Cavalli, Rosa Maria; Pignatti, Stefano
Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness. PMID:22163558
Bassani, Cristiana; Cavalli, Rosa Maria; Pignatti, Stefano
Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550 nm (τ(550)) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ(550) with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ(550) and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ(550) retrieved by Module A (r(2) = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r(2) ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness. PMID:22163558
North, P. R.; Bevan, S. L.; Grey, W.; Heckel, A.; Brockmann, C.; Fischer, J.; Gomez-Chova, L.; Preusker, R.; Regner, P.
We present results of global aerosol retrieval from the ESA ATSR instrument series on ERS-2 and ENVISAT (1995-2010), and initial testing of a new algorithm developed for Sentinel-3, with planned operation 2014-2030. The ATSR instruments on ERS-2 and ENVISAT together provide one of the longest available, well-calibrated datasets of satellite radiance measurements. The dual-angle viewing capability gives two near-simultaneous images at differing slant paths though the atmosphere, allowing global retrieval of aerosol optical thickness without assumptions on surface spectral properties. We present the global ATSR time series and analysis of trends, and give comparison with AERONET and with MODIS and MISR global datasets. The algorithm has been developed for application to Sentinel-3 to make use of synergistic retrieval from two sensors, OLCI and SLSTR. The research explores the gain by using information from both instruments simultaneously to constrain atmospheric profile, characterise cloud, and provide improved atmospheric correction to surface reflectance. The algorithm has been implemented on the ESA BEAM system and tested on MERIS and AATSR data, and compared with existing algorithms. Preliminary results show agreement with AERONET to optical thickness of 0.04 mean absolute error at 550nm, and suggest improved estimation of aerosol properties compared to single-instrument retrievals. References Bevan, S.L., North, P.R.J., Grey, W.M.F., Los, S.O. and Plummer, S.E. (2009). Impact of atmospheric aerosol from biomass burning on Amazon dry-season drought. Journal of Geophysical Research, 114, D09204, doi:10.1029/2008JD011112. Bevan, S.L., et al. (2010). Global atmospheric aerosol optical depth retrievals over land and ocean from AATSR, Remote Sensing of Environment, submitted. North, P.R.J. et al. (2010) Sentinel-3 L2 Products and Algorithm Definition: OLCI/SLSTR Level 2 and 3 Synergy Products, S3-L203S2-SU-ATBD. Composite of global aerosol optical thickness derived
Levy, Robert C.; Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Holben, Brent N.; Livingston, John M.; Russell, Philip B.; Maring, Hal
The Puerto Rico Dust Experiment (PRIDE) took place in Roosevelt Roads, Puerto Rico from June 26 to July 24,2000 to study the radiative and physical properties of African dust aerosol transported into the region. PRIDE had the unique distinction of being the first major field experiment to allow direct comparison of aerosol retrievals from the MODerate Imaging Spectro-radiometer (MODIS) with sunphotometer and in-situ aerosol measurements. Over the ocean, the MODIS algorithm retrieves aerosol optical depth (AOD) as well as information about the aerosols size distribution. During PRIDE, MODIS derived AODs in the red wavelengths (0.66 micrometers) compare closely with AODs measured from sunphotometers, but, are too large at blue and green wavelengths (0.47 and 0.55 micrometers) and too small in the infrared (0.87 micrometers). This discrepancy of spectral slope results in particle size distributions retrieved by MODIS that are small compared to in-situ measurements, and smaller still when compared to sunphotometer sky radiance inversions. The differences in size distributions are, at least in part, associated with MODIS simplification of dust as spherical particles. Analysis of this PRIDE data set is a first step towards derivation of realistic non-spherical models for future MODIS retrievals.
Li, Yingjie; Xue, Yong; He, Xingwei; Guang, Jie
Satellite aerosol remote sensing over urban areas is still a difficult task because of the high reflectance of the underlying surface. Many aerosol retrieval algorithms are appropriate for 'dark' pixels and provide aerosol products with low resolutions. In this paper, we present a new aerosol retrieval algorithm that applies the synergetic use of small satellite data and Moderate Resolution Imaging Spectroradiometer (MODIS) data. The algorithm was applied to data from the China HJ-1A/1B of the Environment and Disasters Monitoring Microsatellite Constellation Charge-Coupled Device (CCD) camera and Terra MODIS data. To downscale 500 m MODIS data, a new method based on mutual information was developed. By applying this algorithm to aerosol retrieval over Beijing City, we obtain the aerosol optical depth (AOD) with a 100 m × 100 m resolution. A comparison of our results to the ground measurement data from Aerosol Robotic Network (AERONET) sites and Huailai Remote Sensing Test Field, which are measured by CE318 automatic sun tracking photometer, shows a correlation coefficient of approximately 0.89 and a root-mean-square error (RMSE) of about 0.24. The uncertainty for AOD ( τ) is found to be Δ τ = ±0.05 ± 0.20 τ. The algorithm could potentially be useful for other small satellite constellation data. High-resolution AOD is very useful and powerful for urban air quality monitoring and other applications.
Hsu, N. Christina
Mineral dust and smoke aerosols play an important role in both climate forcing and oceanic productivity throughout the entire year. Due to the relatively short lifetime (a few hours to about a week), the distributions of these airborne particles vary extensively in both space and time. Consequently, satellite observations are needed over both source and sink regions for continuous temporal and spatial sampling of dust and smoke properties. However, despite their importance, the high spatial resolution satellite measurements of these aerosols near their sources have been lacking, In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as MODIS and SeaWiFS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over land, including desert and semi-desert regions. The comparisons show reasonable agreements between these two. Our results show that the dust plumes lifted from the deserts near India/Pakistan border, and over Afghanistan, and the Arabian Peninsula are often observed by MODIS to be transported along the Indo-Gangetic Basin and mixed with the fine mode pollution particles generated by anthropogenic activities in this region, particularly during the pre-monsoon season (April-May). These new satellite products will allow scientists to determine
Zhang, H.; Hoff, R. M.; Kondragunta, S.; Laszlo, I.; Lyapustin, A.
The western United States is observed by both GOES-East and GOES-West imagers. The TOA reflectance measured from the two satellites has different sensitivity to AOD variations due to the different observation geometries. The GASP (GOES Aerosol/Smoke Product) aerosol optical depth retrieval algorithm only applies to single satellite data and thus obtains two separate aerosol optical depth values at the same time for the same location. In order to fully exploit the simultaneous observations and generate consistent AOD retrievals from the two satellites, we develop a new aerosol optical depth retrieval algorithm that uses data from both satellites. The algorithm uses combined GOES-East and GOES-West visible channel TOA reflectance and daily average AOD from GOES Multi-Angle Implementation of Atmospheric Correction (MAIAC) on clear days (AOD less than 0.3), when diurnal variation of AOD is low, to retrieve surface BRDF. The known BRDF shape is applied on the follow-on days to retrieve BRDF and AOD. The algorithm is validated at three AERONET sites over the western US. The AOD retrieval accuracy from two satellites is similar to that from one satellite, with correlation coefficients ranging from 0.71 to 0.81 for the three sites. However, the new algorithm has more data coverage compared to the single satellite retrievals. The number of coincidences with AERONET observations increases from the single satellite algorithm by 20 - 70% for the three sites. With the application of the new algorithm, we can provide consistent AOD retrievals with better retrieval coverage using the two GOES satellite imagers.
Nelson, D.L.; Garay, M.J.; Kahn, Ralph A.; Dunst, Ben A.
The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the Terra satellite acquires imagery at 275-m resolution at nine angles ranging from 0deg (nadir) to 70deg off-nadir. This multi-angle capability facilitates the stereoscopic retrieval of heights and motion vectors for clouds and aerosol plumes. MISR's operational stereo product uses this capability to retrieve cloud heights and winds for every satellite orbit, yielding global coverage every nine days. The MISR INteractive eXplorer (MINX) visualization and analysis tool complements the operational stereo product by providing users the ability to retrieve heights and winds locally for detailed studies of smoke, dust and volcanic ash plumes, as well as clouds, at higher spatial resolution and with greater precision than is possible with the operational product or with other space-based, passive, remote sensing instruments. This ability to investigate plume geometry and dynamics is becoming increasingly important as climate and air quality studies require greater knowledge about the injection of aerosols and the location of clouds within the atmosphere. MINX incorporates features that allow users to customize their stereo retrievals for optimum results under varying aerosol and underlying surface conditions. This paper discusses the stereo retrieval algorithms and retrieval options in MINX, and provides appropriate examples to explain how the program can be used to achieve the best results.
Guo, Q.; Palanisamy, B.; Karimi, H. A.
The burst of large-scale spatial terrain data due to the proliferation of data acquisition devices like 3D laser scanners poses challenges to spatial data analysis and computation. Among many spatial analyses and computations, polygon retrieval is a fundamental operation which is often performed under real-time constraints. However, existing sequential algorithms fail to meet this demand for larger sizes of terrain data. Motivated by the MapReduce programming model, a well-adopted large-scale parallel data processing technique, we present a MapReduce-based polygon retrieval algorithm designed with the objective of reducing the IO and CPU loads of spatial data processing. By indexing the data based on a quad-tree approach, a significant amount of unneeded data is filtered in the filtering stage and it reduces the IO overhead. The indexed data also facilitates querying the relationship between the terrain data and query area in shorter time. The results of the experiments performed in our Hadoop cluster demonstrate that our algorithm performs significantly better than the existing distributed algorithms.
Xu, F.; Diner, D. J.; Davis, A. B.; Latyshev, S.; Garay, M. J.; Kalashnikova, O.; Ge, C.; Wang, J.
A vector Markov chain (MarCh) radiative transfer (RT) code developed at JPL that includes forward modeling of radiance and polarization fields and linearization (analytical estimation of Jacobians) was incorporated into an aerosol and surface retrieval package for a plane-parallel atmosphere/surface system. The RT computation by MarCh is based on matrix operations. To improve the code's computational efficiency, the forward model is currently undergoing acceleration through the exploration of different strategies for matrix operation and inversion, including numerical optimization, multi-threading/multi-processing techniques on a CPU. Implementation on a graphics processing unit (GPU) is also planned. Following a benchmarking study of the forward model, the performance of MarCh in aerosol and surface retrieval is being tested. With an optimized algorithm, we started from aerosol optical depth and surface retrieval using imagery acquired by Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) over Fresno, CA. Aerosol properties including concentration and size distribution of different species provided by the Weather Research and Forecasting (WRF)-Chem model were used to constrain the retrieval and reduce the parameter space. The assumptions of spectral invariance in the angular shape of surface bidirectional reflectance factors (BRFs) and the magnitude of polarized surface BRFs were tested. The aerosol and surface properties are then relaxed in a stepwise way to refine the aerosol retrieval results and enable comparison with independent retrievals obtained from a collocated AErosol RObotic NETwork (AERONET) station.
Kassianov, Evgueni I.; Ovchinnikov, Mikhail; Berg, Larry K.; Flynn, Connor J.
There are lots of interesting and intriguing features of aerosols near clouds – many of which can be quite engaging, as well being useful and climate-related. Exploring aerosol with the aid of the remote sensing, in situ observations and numerical modeling has piqued our curiosity and led to improve insights into the nature of aerosol and clouds and their complex relationship. This chapter conveys the outstanding issues of cloudy-sky aerosol retrievals of important climate properties and outlines their fruitful connections to other research areas such as in situ measurements and model simulations. The chapter focuses mostly on treating the inverse problems in the context of the passive satellite remote sensing and how they can improve our understanding of the cloud-aerosol interactions. The presentation includes a basis in the inverse problem theory, reviews available approaches and discusses their applications to partly cloudy situations. Potential synergy of observations and model simulations is described as well.
Jin, Yoshitaka; Kai, Kenji; Kawai, Kei; Nagai, Tomohiro; Sakai, Tetsu; Yamazaki, Akihiro; Uchiyama, Akihiro; Batdorj, Dashdondog; Sugimoto, Nobuo; Nishizawa, Tomoaki
Ceilometers are durable compact backscatter lidars widely used to detect cloud base height. They are also useful for measuring aerosols. We introduced a ceilometer (CL51) for observing dust in a source region in Mongolia. For retrieving aerosol profiles with a backscatter lidar, the molecular backscatter signal in the aerosol free heights or system constant of the lidar is required. Although the system constant of the ceilometer is calibrated by the manufacturer, it is not necessarily accurate enough for the aerosol retrieval. We determined a correction factor, which is defined as the ratio of true attenuated backscattering coefficient to the measured attenuated backscattering coefficient, for the CL51 ceilometer using a dual-wavelength Mie-scattering lidar in Tsukuba, Japan before moving the ceilometer to Dalanzadgad, Mongolia. The correction factor determined by minimizing the difference between the ceilometer and lidar backscattering coefficients was approximately 1.2±0.1. Applying the correction to the CL51 signals, the aerosol optical depth (AOD) agreed well with the sky-radiometer AOD during the observation period (13-17 February 2013) in Tsukuba (9 ×10-3 of mean square error). After moving the ceilometer to Dalanzadgad, however, the AOD observed with the CL51 (calibrated by the correction factor determined in Tsukuba) was approximately 60% of the AErosol RObotic NETwork (AERONET) sun photometer AOD. The possible causes of the lower AOD results are as follows: (1) the limited height range of extinction integration (< 3 km); (2) change in the correction factor during the ceilometer transportation or with the window contamination in Mongolia. In both cases, on-site calibrations by dual-wavelength lidar are needed. As an alternative method, we showed that the backward inversion method was useful for retrieving extinction coefficients if the AOD was larger than 1.5. This retrieval method does not require the system constant and molecular backscatter signals
Dörner, S.; Kühl, S.; Pukite, J.; Penning de Vries, M.; Hörmann, C.; von Savigny, C.; Wagner, T.
Balloon-borne and aircraft measurements of stratospheric aerosol properties have been supplemented by satellite measurements since 1975 (Stratospheric Aerosol Measurement program). Ever since, the technological possibilities of satellite measurements increased steadily. Nowadays the large number of satellites provides global data sets of trace gases, clouds and aerosols. Stratospheric aerosol properties are usually determined from observations in occultation or limb geometry. Stratospheric aerosol has an important influence on the global radiation budget (e.g. after strong volcanic eruptions) and stratospheric ozone chemistry (e.g. the chlorine activation inside the polar vortex). Since the launch of SCIAMACHY on ENVISAT in 2002 measurements in limb geometry for the UV/VIS/NIR spectral range with a vertical resolution of 3.3 km at the tangent point are available. By using these measurements, profile information of stratospheric trace gases (e.g. NO2, BrO or OClO) can be retrieved. From the broad band spectral dependence of the SCIAMACHY limb measurements, also information on stratospheric aerosol properties can be derived. Pioneering studies (e.g. von Savigny et al., 2005) showed that signatures of polar stratospheric clouds and also stratospheric aerosols can be retrieved from color indices (including the near IR spectral range). In our study we make use of the color index method and additionally investigate the effects of aerosols on the whole UV/VIS/NIR spectral range. Aerosol properties are estimated by comparisons of the measured values with radiative transfer simulations. We investigate different atmospheric phenomena, e.g. volcanic eruptions (e.g. Kasatochi, 2008) or large biomass burning events (e.g. Australia, 2009). We also have a look at the spatio-temporal variation of Polar Stratospheric Clouds in the polar regions and stratospheric aerosol properties on a global scale.
Zhang, Qiong; Natraj, Vijay; Li, King-Fai; Shia, Run-Lie; Fu, Dejian; Pongetti, Thomas J.; Sander, Stanley P.; Roehl, Coleen M.; Yung, Yuk L.
The California Laboratory for Atmospheric Remote Sensing Fourier transform spectrometer (CLARS-FTS) deployed at Mount Wilson, California, has been measuring column abundances of greenhouse gases in the Los Angeles (LA) basin in the near-infrared spectral region since August 2011. CLARS-FTS measures reflected sunlight and has high sensitivity to absorption and scattering in the boundary layer. In this study, we estimate the retrieval biases caused by aerosol scattering and present a fast and accurate approach to correct for the bias in the CLARS column averaged CO2 mixing ratio product, XCO2. The high spectral resolution of 0.06 cm-1 is exploited to reveal the physical mechanism for the bias. We employ a numerical radiative transfer model to simulate the impact of neglecting aerosol scattering on the CO2 and O2 slant column densities operationally retrieved from CLARS-FTS measurements. These simulations show that the CLARS-FTS operational retrieval algorithm likely underestimates CO2 and O2 abundances over the LA basin in scenes with moderate aerosol loading. The bias in the CO2 and O2 abundances due to neglecting aerosol scattering cannot be canceled by ratioing each other in the derivation of the operational product of XCO2. We propose a new method for approximately correcting the aerosol-induced bias. Results for CLARS XCO2 are compared to direct-Sun XCO2 retrievals from a nearby Total Carbon Column Observing Network (TCCON) station. The bias-correction approach significantly improves the correlation between the XCO2 retrieved from CLARS and TCCON, demonstrating that this approach can increase the yield of useful data from CLARS-FTS in the presence of moderate aerosol loading.
Doerner, S.; Kühl, S.; Pukite, J.; Penning de Vries, M. J.; Hoermann, C.; von Savigny, C.; Deutschmann, T.; Wagner, T.
Since the start of the Stratospheric Aerosol Measurement program in 1975 satellites have been improving our understanding of the global distribution of trace gases, clouds and aerosols. Observations in occultation and limb geometry provide profile information on stratospheric aerosol, which have an important influence on the global radiation budget (e.g., after strong volcanic eruptions) and the stratospheric ozone chemistry (e.g., the chlorine activation inside the polar vortex). The Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) on ENVISAT performed measurements in limb geometry for almost ten years between 2002 and 2012. Its vertical resolution of about 3.3 km at the tangent point and the broad spectral range (UV/VIS/NIR) allow to retrieve profile information of stratospheric trace gases (e.g., O3, NO2, BrO or OClO) and stratospheric aerosol properties. Pioneering studies (e.g., Savigny et al., 2005) showed that in particular from color indices (including the near IR spectral range) signatures of stratospheric aerosols and polar stratospheric clouds (PSCs) can be retrieved. In our study we investigate the sensitivity of SCIAMACHY's broad spectral range to aerosol particle properties by comparing measured spectra with simulated results from the 3D full spherical Monte Carlo Atmospheric Radiative Transfer Model McArtim. In particular, we focus on the absorption properties in the UV spectral range, the extinction coefficient and the Angström exponent. The final aim of our study is to use SCIAMACHY limb measurements for the profile retrieval of optical parameters (e.g., absorption and phase function) from which microphysical properties (e.g., mean aerosol particle diameter) of the stratospheric aerosol particles can be deduced.
Torres, Omar; Bhartia, Pawan K.; Jethva, H.; Ahn, Chang-Woo
The Angstrom Absorption Exponent (AAE) is a parameter commonly used to characterize the wavelength-dependence of aerosol absorption optical depth (AAOD). It is closely related to aerosol composition. Black carbon (BC) containing aerosols yield AAE values near unity whereas Organic carbon (OC) aerosol particles are associated with values larger than 2. Even larger AAE values have been reported for desert dust aerosol particles. Knowledge of spectral AAOD is necessary for the calculation of direct radiative forcing effect of aerosols and for inferring aerosol composition. We have developed a satellitebased method of determining the spectral AAOD of absorbing aerosols. The technique uses multi-spectral measurements of upwelling radiation from scenes where absorbing aerosols lie above clouds as indicated by the UV Aerosol Index. For those conditions, the satellite measurement can be explained, using an approximations of Beer's Law (BL), as the upwelling reflectance at the cloud top attenuated by the absorption effects of the overlying aerosol layer. The upwelling reflectance at the cloud-top in an aerosol-free atmospheric column is mainly a function of cloud optical depth (COD). In the proposed method of AAE derivation, the first step is determining COD which is retrieved using a previously developed color-ratio based approach. In the second step, corrections for molecular scattering effects are applied to both the observed ad the calculated cloud reflectance terms, and the spectral AAOD is then derived by an inversion of the BL approximation. The proposed technique will be discussed in detail and application results making use of OMI multi-spectral measurements in the UV-Vis. will be presented.
Zhang, J.; Miller, S. D.; Reid, J. S.; Hyer, E. J.; McHardy, T. M.
Compared to abundant daytime satellite-based observations of atmospheric aerosol, observations at night are relatively scarce. In particular, conventional satellite passive imaging radiometers, which offer expansive swaths of spatial coverage compared to non-scanning lidar systems, lack sensitivity to most aerosol types via the available thermal infrared bands available at night. In this talk, we make the fundamental case for the importance of nighttime aerosol information in forecast models, and the need to mitigate the existing nocturnal gap. We review early attempts at estimating nighttime aerosol optical properties using the modulation of stable artificial surface lights. Initial algorithm development using DMSP Operational Linescan System (OLS) has graduated to refined techniques based on the Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB). We present examples of these retrievals for selected cases and compare the results to available surface-based point-source validation data.
Levy, Robert C.; Remer, Loraine A.; Dubovik, Oleg
Since 2000, MODIS has been deriving aerosol properties over land from MODIS observed spectral reflectance, by matching the observed reflectance with that simulated for selected aerosol optical models, aerosol loadings, wavelengths and geometrical conditions (that are contained in a lookup table or 'LUT'). Validation exercises have showed that MODIS tends to under-predict aerosol optical depth (tau) in cases of large tau (tau greater than 1.0), signaling errors in the assumed aerosol optical properties. Using the climatology of almucantur retrievals from the hundreds of global AERONET sunphotometer sites, we found that three spherical-derived models (describing fine-sized dominated aerosol), and one spheroid-derived model (describing coarse-sized dominated aerosol, presumably dust) generally described the range of observed global aerosol properties. The fine dominated models were separated mainly by their single scattering albedo (omega(sub 0)), ranging from non-absorbing aerosol (omega(sub 0) approx. 0.95) in developed urban/industrial regions, to neutrally absorbing aerosol (omega(sub 0) approx.90) in forest fire burning and developing industrial regions, to absorbing aerosol (omega(sub 0) approx. 0.85) in regions of savanna/grassland burning. We determined the dominant model type in each region and season, to create a 1 deg. x 1 deg. grid of assumed aerosol type. We used vector radiative transfer code to create a new LUT, simulating the four aerosol models, in four MODIS channels. Independent AERONET observations of spectral tau agree with the new models, indicating that the new models are suitable for use by the MODIS aerosol retrieval.
Naeger, A. R.; Gupta, P.; Zavodsky, B.; McGrath, K. M.
The primary goal of this study was to generate a near-real time (NRT) aerosol optical depth (AOD) product capable of providing a comprehensive understanding of the aerosol spatial distribution over the Pacific Ocean in order to better monitor and track the trans-Pacific transport of aerosols. Therefore, we developed a NRT product that takes advantage of observations from both low-earth orbiting and geostationary satellites. In particular, we utilize AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) satellites. Then, we combine these AOD products with our own retrieval algorithms developed for the NOAA Geostationary Operational Environmental Satellite (GOES-15) and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT-2) to generate a NRT daily AOD composite product. We present examples of the daily AOD composite product for a case study of trans-Pacific transport of Asian pollution and dust aerosols in mid-March 2014. Overall, the new product successfully tracks this aerosol plume during its trans-Pacific transport to the west coast of North America. However, we identify several areas across the domain of interest from Asia to North America where the new product can encounter significant uncertainties due to the inclusion of the geostationary AOD retrievals. The uncertainties associated with geostationary AOD retrievals are expected to be minimized after the successful launch of the next-generation advanced NOAA GOES-R and recently launched JMA Himawari satellites. Observations from these advanced satellites will ultimately provide an enhanced understanding of the spatial and temporal distribution of aerosols over the Pacific.
Knobelspiesse, K.; Cairns, B.; Ottaviani, M.; Ferrare, R.; Haire, J.; Hostetler, C.; Obland, M.; Rogers, R.; Redemann, J.; Shinozuka, Y.; Clarke, A.; Freitag, S.; Howell, S.; Kapustin, V.; McNaughton, C.
independent observations. The convergence to an unrealistic local minimum by the optimal estimator is related to the relatively low sensitivity to particles smaller than 0.1 ( m) at large optical thicknesses. Thus, optimization algorithms used for operational aerosol retrievals of the fine mode size distribution, when the total optical depth is large, will require initial values generated from table look-ups that exclude unrealistic size/complex index mixtures. External constraints from lidar on initial values used in the optimal estimation methods will also be valuable in reducing the likelihood of obtaining spurious retrievals.
Ahn, C.; Torres, O.; Jethva, H. T.
Global observations of aerosol properties from space are critical for understanding climate change and air quality applications. The Ozone Monitoring Instrument (OMI) onboard the EOS-Aura satellite provides information on aerosol optical properties by making use of the large sensitivity to aerosol absorption and dark surface albedo in the UV spectral region. These unique features enable us to retrieve both aerosol extinction optical depth (AOD) and single scattering albedo (SSA) successfully from radiance measurements at 354 and 388 nm by the OMI near UV aerosol algorithm (OMAERUV). Recent improvements to algorithms in conjunction with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Atmospheric Infrared Sounder (AIRS) carbon monoxide data also reduce uncertainties due to aerosol layer heights and types significantly in retrieved products. We present validation results of OMI AOD against space and time collocated Aerosol Robotic Network (AERONET) measured AOD values over multiple stations representing major aerosol episodes and regimes. We also compare the OMI SSA against the inversion made by AERONET as well as an independent network of ground-based radiometer called SKYNET in Japan, China, South-East Asia, India, and Europe. The outcome of the evaluation analysis indicates that in spite of the "row anomaly" problem, affecting the sensor since mid-2007, the long-term aerosol record shows remarkable sensor stability. The OMAERUV 10-year global aerosol record is publicly available at the NASA data service center web site (http://disc.sci.gsfc.nasa.gov/Aura/data-holdings/OMI/omaeruv_v003.shtml).
Sayer, A. M.; Hsu, N. C.; Eck, T. F.; Smirnov, A.; Holben, B. N.
Smoke aerosols from biomass burning are an important component of the global aerosol cycle. Analysis of Aerosol Robotic Network (AERONET) retrievals of size distribution and refractive index reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke transported to coastal/island AERONET sites also mostly lie within the range of variability at near-source sites. Two broad families of aerosol properties are found, corresponding to sites dominated by boreal forest burning (larger, broader fine mode, with midvisible SSA 0.95), and those influenced by grass, shrub, or crop burning with additional forest contributions (smaller, narrower particles with SSA 0.88-0.9 in the midvisible). The strongest absorption is seen in southern African savanna at Mongu (Zambia), with average SSA 0.85 in the midvisible. These can serve as candidate sets of aerosol microphysicaloptical properties for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean are often insufficiently absorbing to represent these biomass burning aerosols. A corollary of this is an underestimate of AOD in smoke outflow regions, which has important consequences for applications of these satellite datasets.
Cattrall, Christopher; Carder, Kendall L.; Gordon, Howard R.
The single-scattering albedo and phase function of African mineral dust are retrieved from ground-based measurements of sky radiance collected in the Florida Keys. The retrieval algorithm employs the radiative transfer equation to solve by iteration for these two properties which best reproduce the observed sky radiance using an assumed aerosol vertical structure and measured aerosol optical depth. Thus, no assumptions regarding particle size, shape, or composition are required. The single-scattering albedo, presented at fourteen wavelengths between 380 and 870 nm, displays a spectral shape expected of iron-bearing minerals but is much higher than current dust models allow. This indicates the absorption of light by mineral dust is significantly overestimated in climate studies. Uncertainty in the retrieved albedo is less than 0.02 due to the small uncertainty in the solar-reflectance-based calibration (12.2%) method employed. The phase function retrieved at 860 nm is very robust under simulations of expected experimental errors, indicating retrieved phase functions at this wavelength may be confidently used to describe aerosol scattering characteristics. The phase function retrieved at 443 nm is very sensitive to expected experimental errors and should not be used to describe aerosol scattering. Radiative forcing by aerosol is the greatest source of uncertainty in current climate models. These results will help reduce uncertainty in the absorption of light by mineral dust. Assessment of the radiative impact of aerosol species is a key component to NASA's Earth System Enterprise.
Hsu, N. Christina; Tsay, Si-Cee; King, Michael D.; Herman, Jay R.
During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, the newly developed satellite aerosol algorithm called "Deep Blue" was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the ngstr m exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite-retrieved aerosol optical thickness from Deep Blue are generally within 20%-30% of those measured by sunphotometers. The analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine-mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. This paper will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products.
Levy, R. C.; Remer, L. A.; Martins, J. V.; Kaufman, Y. J.; Plana-Fattori, A.; Redemann, J.; Wenny, B.
The Chesapeake Lighthouse Aircraft Measurements for Satellites (CLAMS) experiment took place from 10 July to 2 August 2001 in a combined ocean-land region that included the Chesapeake Lighthouse [Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE)] and the Wallops Flight Facility (WFF), both along coastal Virginia. This experiment was designed mainly for validating instruments and algorithms aboard the Terra satellite platform, including the Moderate Resolution Imaging Spectroradiometer (MODIS). Over the ocean, MODIS retrieved aerosol optical depths (AODs) at seven wavelengths and an estimate of the aerosol size distribution. Over the land, MODIS retrieved AOD at three wavelengths plus qualitative estimates of the aerosol size. Temporally coincident measurements of aerosol properties were made with a variety of sun photometers from ground sites and airborne sites just above the surface. The set of sun photometers provided unprecedented spectral coverage from visible (VIS) to the solar near-infrared (NIR) and infrared (IR) wavelengths. In this study, AOD and aerosol size retrieved from MODIS is compared with similar measurements from the sun photometers. Over the nearby ocean, the MODIS AOD in the VIS and NIR correlated well with sun-photometer measurements, nearly fitting a one-to-one line on a scatterplot. As one moves from ocean to land, there is a pronounced discontinuity of the MODIS AOD, where MODIS compares poorly to the sun-photometer measurements. Especially in the blue wavelength, MODIS AOD is too high in clean aerosol conditions and too low under larger aerosol loadings. Using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative code to perform atmospheric correction, the authors find inconsistency in the surface albedo assumptions used by the MODIS lookup tables. It is demonstrated how the high bias at low aerosol loadings can be corrected. By using updated urban/industrial aerosol
Chu, D. A.; Kaufman, Y. J.; Ichoku, C.; Remer, L. A.; Tanre, D.; Holben, B. N.; Einaudi, Franco (Technical Monitor)
Aerosol optical depths are derived operationally for the first time over land in the visible wavelengths by MODIS (Moderate Resolution Imaging Spectroradiometer) onboard the EOSTerra spacecraft. More than 300 Sun photometer data points from more than 30 AERONET (Aerosol Robotic Network) sites globally were used in validating the aerosol optical depths obtained during July - September 2000. Excellent agreement is found with retrieval errors within (Delta)tau=+/- 0.05 +/- 0.20 tau, as predicted, over (partially) vegetated surfaces, consistent with pre-launch theoretical analysis and aircraft field experiments. In coastal and semi-arid regions larger errors are caused predominantly by the uncertainty in evaluating the surface reflectance. The excellent fit was achieved despite the ongoing improvements in instrument characterization and calibration. This results show that MODIS-derived aerosol optical depths can be used quantitatively in many applications with cautions for residual clouds, snow/ice, and water contamination.
Xu, Feng; Dubovik, Oleg; Zhai, Peng-Wang; Diner, David J.; Kalashnikova, Olga V.; Seidel, Felix C.; Litvinov, Pavel; Bovchaliuk, Andrii; Garay, Michael J.; van Harten, Gerard; Davis, Anthony B.
An optimization approach has been developed for simultaneous retrieval of aerosol properties and normalized water-leaving radiance (nLw) from multispectral, multiangular, and polarimetric observations over ocean. The main features of the method are (1) use of a simplified bio-optical model to estimate nLw, followed by an empirical refinement within a specified range to improve its accuracy; (2) improved algorithm convergence and stability by applying constraints on the spatial smoothness of aerosol loading and Chlorophyll a (Chl a) concentration across neighboring image patches and spectral constraints on aerosol optical properties and nLw across relevant bands; and (3) enhanced Jacobian calculation by modeling and storing the radiative transfer (RT) in aerosol/Rayleigh mixed layer, pure Rayleigh-scattering layers, and ocean medium separately, then coupling them to calculate the field at the sensor. This approach avoids unnecessary and time-consuming recalculations of RT in unperturbed layers in Jacobian evaluations. The Markov chain method is used to model RT in the aerosol/Rayleigh mixed layer and the doubling method is used for the uniform layers of the atmosphere-ocean system. Our optimization approach has been tested using radiance and polarization measurements acquired by the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) over the AERONET USC_SeaPRISM ocean site (6 February 2013) and near the AERONET La Jolla site (14 January 2013), which, respectively, reported relatively high and low aerosol loadings. Validation of the results is achieved through comparisons to AERONET aerosol and ocean color products. For comparison, the USC_SeaPRISM retrieval is also performed by use of the Generalized Retrieval of Aerosol and Surface Properties algorithm (Dubovik et al., 2011). Uncertainties of aerosol and nLw retrievals due to random and systematic instrument errors are analyzed by truth-in/truth-out tests with three Chl a concentrations, five aerosol loadings
Wu, Yerong; de Graaf, Martin; Menenti, Massimo
Aerosols in the atmosphere play an important role in the climate system and human health. Retrieval from satellite data, Aerosol Optical Depth (AOD), one of most important indices of aerosol optical properties, has been extensively investigated. Benefiting from the high resolution at spatial and temporal and the maturity of the aerosol retrieval algorithm, MOderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOD product has been extensively applied in other scientific research such as climate change and air pollution. The latest product - MODIS Collection 6 Dark Target AOD (C6_DT) has been released. However, the accuracy of C6_DT AOD (global mean ±0.03) over land is still too low for the constraint on radiative forcing in the climate system, where the uncertainty should be reduced to ±0.02. The major uncertainty mainly lies on the underestimation/overestimation of the surface contribution to the Top Of Atmosphere (TOA) radiance since a lambertian surface is assumed in the C6_DT land algorithm. In the real world, it requires considering the heterogeneity of the surface reflection in the radiative transfer process. Based on this, we developed a new algorithm to retrieve AOD by considering surface Bidirectional Reflectance Distribution Function (BRDF) effects. The surface BRDF is much more complicated than isotropic reflection, described as 4 elements: directional-directional, directional-hemispherical, hemispherical-directional and hemispherical-hemispherical reflectance, and coupled into radiative transfer equation to generate an accurate top of atmosphere reflectance. The limited MODIS measurements (three channels available) allow us to retrieve only three parameters, which including AOD, the surface directional-directional reflectance and fine aerosol ratio η. The other three elements of the surface reflectance are expected to be constrained by ancillary data and assumptions or "a priori" information since there are more unknowns than MODIS
Weaver, Clark; Joiner, Joanna; Ginoux, Paul; Bhartia, P. K. (Technical Monitor)
Mineral aerosols can absorb significant radiation in the infrared spectrum. Consequently, there may be errors in TIROS Operational Vertical Sounder (TOVS) retrieved temperature and moisture profiles in regions of heavy dust loading. We first investigate the potential error in the temperature retrievals and secondly attempt to account for radiative effects of the dust in retrievals. Information on the dust concentrations and size distribution is from the Goddard Chemistry Aerosol Transport model (GOCART). Aerosol optical parameters are calculated from mie scattering theory assuming a composition of pure illite. We used the cloud-clearing DAO TOVS retrieval system of Joiner and Rokke (2000). It is incorporated into the Data Assimilation Office (DAO) Finite Volume Data Assimilation System (NDAS). The advantage of this approach is that the first guess temperature profile used in the TOVS retrieval are forecasted temperatures from the previous assimilated time period. The operational DAO fvDAS was run for 10 days during June 2001 during a period of dust outbreaks off the coast of Africa over the Atlantic. The observed minus the forecast (O-F) brightness temperature at each TOVS channel is a measure of the accuracy of the retrieval. Since there was no account of dust during this operational run, a dependence of O-F on the estimated atmospheric dust concentrations from GOCART indicates that the dust is contaminating the TOVS retrievals. Channels that measure the surface temperature, lower tropospheric temperature and moisture show this dependence. There are errors in the retrieved brightness temperature of a half a degree or more during heavy dust loading conditions. The forecasted brightness temperature is always greater than the observed value. The radiative transfer module used in the DAO TOVS retrieval system was modified to account for dust. We calculate the sensitivity of the brightness temperature of the TOVS channels to the dust concentrations in GOCART assuming
Go, S.; Kim, J.; KIM, M.; Lee, S.
Monitoring aerosols using near UV spectral region have been successfully performed over decades by Ozong Monitoring Instruments (OMI) with benefit of strong aerosol signal over continuous dark surface reflectance, both land and ocean. However, because of big foot print of OMI, the cloud contamination error was a big issue in the UV aerosol algorithm. In the present study, high resolution UV aerosol optical depth (AOD) over East Asia was derived by collaborating the Greenhouse gases Observing SATellite/Thermal And Near infrared Sensor for carbon Observation (GOSAT/TANSO)-Cloud and Aerosol Imager (CAI) and OMI together. AOD of 0.1 degree grid resolution was retrieved using CAI band 1 (380nm) by bring OMI lv.2 aerosol type, single scattering albedo, and aerosol layer peak height in 1 degree grid resolution. Collocation of the two dataset within the 0.5 degree grid with time difference of OMI and CAI less than 5 minute was selected. Selected region becomes wider as it goes to the higher latitude. Also, calculated degradation factor of 1.57 was applied to CAI band1 (380nm) by comparing normalized radiance and Lambertian Equivalent Reflectivity (LER) of both sensors. The calculated degradation factor was reasonable over dark scene, but inconsistent over cirrus cloud and bright area. Then, surface reflectance was developed by compositing CAI LER minimum data over three month period, since the infrequent sampling rate associated with the three-day recursion period of GOSAT and the narrow CAI swath of 1000 km. To retrieve AOD, look up table (LUT) was generated using radiative transfer model VLIDORT NGST. Finally, the retrieved AOD was validated with AERONET ground based measurement data during the Dragon-NE Asia campaign in 2012.
Levy, R. C.; Gupta, P.; Mattoo, S.
With amplified urbanization and industrialization during the last few decades, now more than half of the world's population lives in urban areas. With surface particle matter (PM) concentration five or ten times higher than World Health Organization guidelines in some cities, it is very critical to accurately monitor PM air quality for global cities on a daily basis. The new version (C6) of MODIS Dark Target Land Aerosol Algorithm (MDT) provides near-daily aerosol optical depth (AOD) retrievals at 10km2 and 3km2 spatial resolutions, which can be used to estimate surface PM. However, initial validation efforts showed that MDT overestimates AOD over urban areas, primarily because the bright and complex urban surface does not meet MDT assumptions. We combined the MODIS Land Classification Product (MCD12Q1) with MODIS land surface spectral reflectance product (MOD09A1) to develop new surface characterization scheme to be used within the MDT algorithm framework. We applied the new surface characterization to the MDT algorithm, and compared the retrieved AOD with AOD observed from the ground-based AERONET's DRAGON network operated during four DISCOVER-AQ field campaigns. AOD retrievals both in 10km and 3km spatial resolution show significant improvement over urban areas over the U.S. The bias in AOD reduced to -0.01 from 0.07, percentage of retrievals within uncertainty window increased to 85% from 62%. We will also present air quality assessment and implication of air quality monitoring in cities using revised MODIS aerosol retrievals.
Hernandez, Eduardo H.
Aerosols are notoriously hard to measure on a global scale since they do not have unique spectral signatures like trace green house gases. Accurate global characterization of Aerosol Optical Depth (AOD) is essential because aerosols are the most uncertain mechanism in climate forecast models, and have known impact on human health. In particular, fine mode particulates (PM2.5) can penetrate deep into the lung tissue contributing to lung damage and cardiac distress. Because of these effects on human health, the Environmental Protection Agency has strict monitoring standards for PM2.5. Aerosols measurements over urban areas are critical because extended urban centers can have significant aerosol loadings with air quality levels that are above EPA standards. For global studies, satellite measurements are the only realistic approach. Making this monitoring possible from space is the observation that column AOD is quite remarkably related to PM2.5. Dark vegetative surfaces make such correlations strongest and more accurate aerosols retrieval. However, over urban scenes, it is particularly complicated due to the confusion between the ground signal and the aerosol signal. The satellite sensors cannot distinguish if the incoming photons come from the surface or from atmosphere scattering. For global retrieval of aerosols, the MODIS sensor is perhaps the most suited for global observations, because it can cover almost the entire planet in less than 2 days. The general approach is to use the Long Wave Channel (2130nm) as a good estimate of the surface albedo, since the aerosols contribution in this channel is almost always negligible (especially urban aerosols). Then, the surface albedos in the visible channels, where aerosols are important, can be inferred from empirical relations. However, it has become more apparent that the relations used by MODIS algorithms are not optimized for urban areas and tend to overestimate the AOD. This thesis provides a more extensive study of
Kudo, R.; Nishizawa, T.; Higurashi, A.; Sugimoto, N.; Oikawa, E.
EarthCARE is an earth observation satellite and will be launched in 2016. Using its two sensors, ATLID (High spectral resolution lidar) and MSI (Multi-spectral imager), we are developing the synergy algorithm to retrieve the vertical profiles of extinction coefficients at 355 nm of four aerosol components (Water-soluble, black carbon, dust, and sea-salt particles), and the column mean of mode radii of water-soluble and dust particles. The ATLID data are extinction coefficient, backscatter coefficient, and depolarization ratio for total aerosols at 355 nm. The MSI data are radiances at 670 and 865 nm. The dry volume concentrations of four aerosol components at each altitude and the mode radii of water-soluble and dust particles in the column are simultaneously optimized to ATLID and MSI data by the gauss newton method. After the optimization, the vertical profiles of the extinction coefficient at 355 nm of four aerosol components are obtained. The size distributions of four aerosol components are assumed to be a lognormal distribution. The refractive indices of four aerosol components are given from previously observational studies. The humidity growth is considered for water-soluble and sea-salt particles. The volume concentration and the mode radius of the sea-salt particle are parameterized using the surface wind speed on the ocean. We assumed that the shape of the water-soluble, black carbon, and sea-salt particles are spherical, and the shape of the dust particle is spheroidal. We tested the algorithm using the ATLID and MSI data simulated using clean, dust-transported, and smoke-transported aerosols. The extinction coefficients of each component at 355 nm are retrieved well. The mode radius of water-soluble and dust particles were somehow overestimated.
Vountas, Marco; von Hoyningen-Huene, Wolfgang; Yoon, Jongmin; Burrows, John P.
Aside from adverse health effect urban aerosols have potential effects on the climate system. In this study Aerosol Optical Thickness (AOT) retrievals over land are performed to study the medium to long-term trends of aerosols in large agglomerations (aka megacities). This task is challenging because of the high variability of the surface reflectance. The Bremen AErosol Retrieval (BAER) algorithm has retrieved AOT successfully over land with different satellite data in other studies. Here, the annual-and long-term trend of AOT over several regions have been analyzed using BAER based on SeaWiFS (Sea-viewing Wide Field-of-view Sensor) L1b data over a period of 11 years. Among the regions analyzed were several European regions, as well as Sao Paolo, Brazil, and Perl River Delta in south China. Practically all regions investigated showed a week negative trend in AOT (validated by AERONET), except over Perl River Delta where a comparatively strong positive trend of up to 0.007/yr could be observed.
Levy, Robert C.; Remer, Lorraine A.; Kahn, Ralph A.; Chu, D. Allen; Mattoo, Shana; Holben, Brent N.; Schafer, Joel S.
The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.
Peters, Enno; Pinardi, Gaia; Bösch, Tim; Wittrock, Folkard; Richter, Andreas; Burrows, John P.; Van Roozendael, Michel; Piters, Ankie; Wagner, Thomas; Drosoglou, Theano; Bais, Alkis; Wang, Shanshan; Saiz-Lopez, Alfonso
Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements are a powerful method for monitoring of atmospheric composition in an automated way. The number of instruments and sites operated has been rapidly increasing over the last years. However, integrating the measurements from all these instruments into a consistent data set necessitates careful homogenization of measurements and data retrieval procedures. For this reason, several MAX-DOAS intercomparison campaigns have been carried out in the last years. Mostly, slant columns measured by different instruments and retrieved by different software were intercompared, i.e. observed differences were potentially caused by both, the instrument and/or the retrieval. In contrast, the approach presented here is a pure intercomparison of MAX-DOAS retrievals. In total, 16 international groups and institutes working in the field of MAX-DOAS participated. The work was performed as part of the EU-funded QA4ECV project. The intercomparison exercise is based on data recorded by the IUP-Bremen MAX-DOAS instrument during the MAD-CAT campaign (Multi-Axis DOAS comparison campaign for Aerosols and Trace gases), which was carried out at the Max-Planck-Institute of Chemistry in Mainz, Germany, in summer 2013. Each group participating in the exercise presented here performed MAX-DOAS fits using their own retrieval software but common input (IUP-Bremen spectra, same cross-sections, and same fit settings). The resulting slant columns show in general an excellent agreement (correlation coefficient > 99.9%). Surprisingly, the correlation is substantially smaller when using sequential Fraunhofer reference spectra instead of a noon reference indicating that groups calculate the sequential reference differently. Further differences were found to arise from treatment of the slit function and subsequent convolution of cross-sections as well as from wavelength calibration. The results indicate overall a high
Lee, Jaehwa; Kim, Jhoon; Lee, Yun Gon
A unified satellite algorithm is presented to simultaneously retrieve aerosol properties (aerosol optical depth; AOD and aerosol type) and clear-sky shortwave direct radiative effect (hereafter, DREA) over ocean. The algorithm is applied to Moderate Resolution Imaging spectroradiometer (MODIS) observations for a period from 2003 to 2010 to assess the DREA over the global ocean. The simultaneous retrieval utilizes lookup table (LUT) containing both spectral reflectances and solar irradiances calculated using a single radiative transfer model with the same aerosol input data. This study finds that aerosols cool the top-of-atmosphere (TOA) and bottom-of-atmosphere (BOA) by 5.2 ± 0.5 W/m2 and 8.3 W/m2, respectively, and correspondingly warm the atmosphere (hereafter, ATM) by 3.1 W/m2. These quantities, solely based on the MODIS observations, are consistent with those of previous studies incorporating chemical transport model simulations and satellite observations. However, the DREAs at BOA and ATM are expected to be less accurate compared to that of TOA due to low sensitivity in retrieving aerosol type information, which is related with the atmospheric heating by aerosols, particularly in low AOD conditions; consequently, the uncertainties could not be quantified. Despite the issue in the aerosol type information, the present method allows us to confine the DREA attributed only to fine-mode dominant aerosols, which are expected to be mostly anthropogenic origin, in the range from -1.1 W/m2 to -1.3 W/m2 at TOA. Improvements in size-resolved AOD and SSA retrievals from current and upcoming satellite instruments are suggested to better assess the DREA, particularly at BOA and ATM, where aerosol absorptivity induces substantial uncertainty.
Määttä, A.; Laine, M.; Tamminen, J.; Veefkind, J. P.
The space borne measurements provide global view of atmospheric aerosol distribution. The Ozone Monitoring Instrument (OMI) on board NASAs Earth Observing System (EOS) Aura satellite is a Dutch-Finnish nadir-viewing solar backscatter spectrometer measuring in the ultraviolet and visible wavelengths. OMI measures several trace gases and aerosols that are important in many air quality and climate studies. The OMI aerosol measurements are used, for example, for detecting volcanic ash plumes, wild fires and transportation of desert dust. We present a methodology for improving the uncertainty quantification in the aerosols retrieval algorithm. We have used the OMI measurements in this feasibility study. Our focus is on the uncertainties originating from the pre-calculated aerosol models. These models are never complete descriptions of the reality. This aerosol model uncertainty is estimated using Gaussian processes with computational tools from spatial statistics. Our approach is based on smooth systematic differences between the observed and modelled reflectances. When acknowledging this model inadequacy in the estimation of aerosol optical thickness (AOT), the uncertainty estimates are more realistic. We present here a real world example of applying the methodology.
Meissner, Thomas; Wentz, Frank J.; Lagerloef, Gary; LeVine, David
The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to a 0.2 psu accuracy. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to O2, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind. This is based on the radar backscatter measurements by the scatterometer. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water and an auxiliary field for the sea surface temperature. In the current processing (as of writing this abstract) only v-pol TB are used for this last process and NCEP winds are used for the roughness correction. Before the salinity algorithm can be operationally implemented and its accuracy assessed by comparing versus in situ measurements, an extensive calibration and validation
McHardy, T. M.; Zhang, J.; Reid, J. S.; Miller, S. D.; Hyer, E. J.; Kuehn, R. E.
Using Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) data, a method, dubbed the "variance method", is developed for retrieving nighttime aerosol optical thickness (τ) values through the examination of the dispersion of radiance values above an artificial light source. Based on the improvement of a previous algorithm, this updated method derives a semi-quantitative indicator of nighttime τ using artificial light sources. Nighttime τ retrievals from the newly developed method are inter-compared with an interpolated value from late afternoon and early morning ground observations from four AErosol RObotic NETwork (AERONET) sites as well as column-integrated τ from one High Spectral Resolution Lidar (HSRL) site at Huntsville, AL, during the NASA Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign, providing full diel coverage. Sensitivity studies are performed to examine the effects of lunar illumination on VIIRS τ retrievals made via the variance method, revealing that lunar contamination may have a smaller impact than previously thought; however, the small sample size of this study limits the conclusiveness thus far. VIIRS τ retrievals yield a coefficient of determination (r2) of 0.60 and a root-mean-squared error (RMSE) of 0.18 when compared against straddling daytime-averaged AERONET τ values. Preliminary results suggest that artificial light sources can be used for estimating regional and global nighttime aerosol distributions in the future.
Levy, Robert Carroll
Aerosols are major components of the Earth's global climate system, affecting the radiation budget and cloud processes of the atmosphere. When located near the surface, high concentrations lead to lowered visibility, increased health problems and generally reduced quality of life for the human population. Over the United States mid-Atlantic region, aerosol pollution is a problem mainly during the summer. Satellites, such as the MODerate Imaging Spectrometer (MODIS), from their vantage point above the atmosphere, provide unprecedented coverage of global and regional aerosols over land. During MODIS' eight-year operation, exhaustive data validation and analyses have shown how the algorithm should be improved. This dissertation describes the development of the 'second-generation' operational algorithm for retrieval of global tropospheric aerosol properties over dark land surfaces, from MODIS-observed spectral reflectance. New understanding about global aerosol properties, land surface reflectance characteristics, and radiative transfer properties were learned in the process. This new operational algorithm performs a simultaneous inversion of reflectance in two visible channels (0.47 and 0.66 mum) and one shortwave infrared channel (2.12 mum), thereby having increased sensitivity to coarse aerosol. Inversion of the three channels retrieves the aerosol optical depth (tau) at 0.55 mum, the percentage of non-dust (fine model) aerosol (eta) and the surface reflectance. This algorithm is applied globally, and retrieves tau that is highly correlated (y = 0.02 + 1.0x, R=0.9) with ground-based sunphotometer measurements. The new algorithm estimates the global, over-land, long-term averaged tau ˜ 0.21, a 25% reduction from previous MODIS estimates. This leads to reducing estimates of global, non-desert, over-land aerosol direct radiative effect (all aerosols) by 1.7 W·m-2 (0.5 W·m-2 over the entire globe), which significantly impacts assessment of aerosol direct radiative
Nicolae, Doina; Belegante, Livio; Talianu, Camelia; Vasilescu, Jeni
Aerosols can influence the microphysical and macrophysical properties of clouds and hence impact the energy balance, precipitation and the hydrological cycle. They have different scattering and absorption properties depending on their origin, therefore measured optical properties can be used to retrieve their physical properties, as well as to estimate their chemical composition. Due to the measurement limitations (spectral, uncertainties, range) and high variability of the aerosol properties with environmental conditions (including mixing during transport), the identification of the aerosol type from lidar data is still not solved. However, ground, airborne and space-based lidars provide more and more observations to be exploited. Since 2000, EARLINET collected more than 20,000 aerosol vertical profiles under various meteorological conditions, concerning local or long-range transport of aerosols in the free troposphere. This paper describes the basic algorithm for aerosol typing from optical data using the benefits of artificial neural networks. A relevant database was built to provide sufficient training cases for the neural network, consisting of synthetic and measured aerosol properties. Synthetic aerosols were simulated starting from the microphysical properties of basic components, internally mixed in various proportions. The algorithm combines the GADS database (Global Aerosol DataSet) to OPAC model (Optical Properties of Aerosol and Clouds) and T-Matrix code in order to compute, in an iterative way, the intensive optical properties of each aerosol type. Both pure and mixed aerosol types were considered, as well as their particular non-sphericity and hygroscopicity. Real aerosol cases were picked up from the ESA-CALIPSO database, as well as EARLINET datasets. Specific selection criteria were applied to identify cases with accurate optical data and validated sources. Cross-check of the synthetic versus measured aerosol intensive parameters was performed in
Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Wind, Gala; Yang, Ping
An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (MODIS) observations is assessed in comparison with the operational retrieval products from MODIS on the Aqua satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with Aqua. The results show that OE-IR cloud optical thickness (τ) and effective radius (reff) retrievals perform best for ice clouds having 0.5 < τ < 7 and reff < 50 µm. For global ice clouds, the averaged retrieval uncertainties of τ and reff are 19% and 33%, respectively. For optically thick ice clouds with τ larger than 10, however, the τ and reff retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48 km. Relatively large h uncertainty (e.g., > 1 km) occurs for τ < 0.5. Analysis of 1 month of the OE-IR retrievals shows large τ and reff uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent τ and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 reff are found.
Lee, Kwon Ho
The paper presents currently developing algorithm for aerosol detection and retrieval over ocean for the next generation geostationary satellite, HIMAWARI-8. Enhanced geostationary remote sensing observations are now enables for aerosol retrieval of dust, smoke, and ash, which began a new era of geostationary aerosol observations. Sixteen channels of the Advanced HIMAWARI Imager (AHI) onboard HIMAWARI-8 offer capabilities for aerosol remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS). Aerosols were estimated in detection processing from visible and infrared channel radiances, and in retrieval processing using the inversion-optimization of satellite-observed radiances with those calculated from radiative transfer model. The retrievals are performed operationally every ten minutes for pixel sizes of ~8 km. The algorithm currently under development uses a multichannel approach to estimate the effective radius, aerosol optical depth (AOD) simultaneously. The instantaneous retrieved AOD is evaluated by the MODIS level 2 operational aerosol products (C006), and the daily retrieved AOD was compared with ground-based measurements from the AERONET databases. The results show that the detection of aerosol and estimated AOD are in good agreement with the MODIS data and ground measurements with a correlation coefficient of ˜0.90 and a bias of 4%. These results suggest that the proposed method applied to the HIMAWARI-8 satellite data can accurately estimate continuous AOD. Acknowledgments This work was supported by "Development of Geostationary Meteorological Satellite Ground Segment(NMSC-2014-01)" program funded by National Meteorological Satellite Centre(NMSC) of Korea Meteorological Administration(KMA).
Ding, Y.; Yang, P.
Three physical and radiative cloud properties, namely, optical thickness (tau), effective diameter (De), and cloud top height(h) can be simultaneously inferred from IR radiances for multi-layer cloud cases. The retrieval algorithm implementation is based on a computationally efficient radiative transfer model and spaceborne measurements of narrowband infrared (IR) radiances at the top of the atmosphere. This study focuses on the evaluation of the retrieval results derived from two different algorithms, optimal estimation (OE) algorithm and Bayesian retrieval algorithm. Both of the two methods are able to offer comprehensive error analysis and quality flags. The evaluation results can potentially useful for retrieving the multi-layer clouds properties, a research subject that receives little attention. This presentation will discuss the pros and cons of retrieving cloud properties from the aforesaid retrieval algorithms.
Horng, Jorng-Tzong; Yeh, Ching-Chang
Proposes a novel approach to automatically retrieve keywords and then uses genetic algorithms to adapt the keyword weights. Discusses Chinese text retrieval, term frequency rating formulas, vector space models, bigrams, the PAT-tree structure for information retrieval, query vectors, and relevance feedback. (Author/LRW)
Capelle, Virginie; Chédin, alain; Pondrom, Marc; Pierangelo, Clémence; Armante, Raymond; Crevoisier, Cyril; Crépeau, Laurent; Scott, Noëlle
Observations from infrared hyperspectral sounders, here IASI and AIRS, are interpreted in terms of dust aerosol properties (AOD and mean altitude). The method is based on a "Look-Up-Table" (LUT) approach, where all radiative transfer computation is performed once for all and "off-line", for a large selection of atmospheric situations, of observing conditions, of surface characteristics (in particular the surface emissivity and temperature), and different aerosol refractive index models. The inversion scheme follows two main steps: first, determination of the observed atmospheric thermodynamic situation, second, simultaneous retrieval of the 10µm coarse-mode AOD and of the mean altitude. The method is here applied over sea and over land, at daily scale daytime and nighttime, and at the satellite pixel resolution (12 km at nadir). The geographical study area studied includes the northern tropics from west Atlantic to the Arabian peninsula and Indian ocean, and the Mediterranean basin, all of them characterized by strong, regular dust events. A special focus is given to the hourly variation of aerosol properties within a day. In this context, both IASI overpasses are processed, providing two measurements at 9:30AM and 9:30PM (equator local time) each day. First results obtained from AIRS observations, made at 1:30 AM and PM, open the way to the analysis of the aerosol diurnal cycle. For the AOD, comparisons are made with AERONET ground-based data , when available, in order to 1) evaluate our results, and 2) show the importance of a better knowledge of the aerosol diurnal cycle, especially close to the sources. Mean aerosol layer altitude obtained from IASI is compared at local scale with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP/CALIPSO) aerosol altitude.
This software retrieves the surface and atmosphere parameters of multi-angle, multiband spectra. The synthetic spectra are generated by applying the modified Rahman-Pinty-Verstraete Bidirectional Reflectance Distribution Function (BRDF) model, and a single-scattering dominated atmosphere model to surface reflectance data from Multiangle Imaging SpectroRadiometer (MISR). The aerosol physical model uses a single scattering approximation using Rayleigh scattering molecules, and Henyey-Greenstein aerosols. The surface and atmosphere parameters of the models are retrieved using the Lavenberg-Marquardt algorithm. The software can retrieve the surface and atmosphere parameters with two different scales. The surface parameters are retrieved pixel-by-pixel while the atmosphere parameters are retrieved for a group of pixels where the same atmosphere model parameters are applied. This two-scale approach allows one to select the natural scale of the atmosphere properties relative to surface properties. The software also takes advantage of an intelligent initial condition given by the solution of the neighbor pixels.
Paciorek, Christopher J; Liu, Yang; Moreno-Macias, Hortensia; Kondragunta, Shobha
We analyze the strength of association between aerosol optical depth (AOD) retrievals from the GOES aerosol/smoke product (GASP) and ground-level fine particulate matter (PM2.5) to assess AOD as a proxy for PM2.5 in the United States. GASP AOD is retrieved from a geostationary platform, giving half-hourly observations every day, in contrast to once per day snapshots from polar-orbiting satellites. However, GASP AOD is based on a less-sophisticated instrument and retrieval algorithm. We find that daily correlations between GASP AOD and PM2.5 over time at fixed locations are reasonably high, except in the winter and in the western U.S. Correlations over space at fixed times are lower. Simple averaging to the month and year actually reduces correlations over space, but statistical calibration allows averaging over time that produces moderately strong correlations. These results and the data density of GASP AOD highlight its potential to help improve exposure estimates for epidemiological analyses. On average 39% of days in a month have a GASP AOD retrieval compared to 11% for MODIS and 5% for MISR. Furthermore, GASP AOD has been retrieved since November 1994, providing a long-term record that predates the availability of most PM2.5 monitoring data and other satellite instruments. PMID:18754512
Dubovik, Oleg; Litvinov, Pavel; Lapyonok, Tatyana; Ducos, Fabrice; Fuertes, David; Huang, Xin; Derimian, Yevgeny; Ovigneur, Bertrand; Descloitres, Jacques
The presentation introduces a new aerosol product derived from multi-angular polarimetric POLDER/PARASOL observations using recently developed GRASP algorithm The GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm described by Dubovik et al. (2011, 2014) derives an extended set of aerosol parameters including detailed particle size distribution, spectral refractive index, single scattering albedo and the fraction of non-spherical particles. Over land GRASP simultaneously retrieves properties of both aerosol and underlying surface. The robust performance of algorithm was illustrated in a series of numerical tests and real data case studies. However, the algorithm is significantly slower than conventional look-up-table retrievals because it performs all radiative transfer calculations on-line. This is why the application of the algorithm for processing large volumes of satellite data was considered as unacceptably challenging task. During two last years GRASP algorithm and its operational retrieval environment has been significantly optimized, improved and adapted for processing extended set of observational data. Hence, here we demonstrate the first results of GRASP aerosol products obtained from large data sets of PARASOL/POLDER observations. It should be noted that in addition the core retrieved aerosol and surface parameters GRASP output may include a variety of user-oriented products including values of daily fluxes and aerosol radiative forcing. 1. Dubovik, O., M. Herman, A. Holdak, T. Lapyonok, D. Tanré, J. L. Deuzé, F. Ducos, A. Sinyuk, and A. Lopatin, "Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations", Atmos. Meas. Tech., 4, 975-1018, 2011. 2. Dubovik, O., T. Lapyonok, P. Litvinov, M. Herman, D. Fuertes, F. Ducos, A. Lopatin, A. Chaikovsky, B. Torres, Y. Derimian, X. Huang, M. Aspetsberger, and C. Federspiel "GRASP: a versatile
Peyridieu, S.; Chédin, A.; Capelle, V.; Pierangelo, C.; Lamquin, N.; Armante, R.
Observation from space, being global and quasi-continuous, is a first importance tool for aerosol studies. Remote sensing in the visible domain has been widely used to obtain better characterization of these particles and their effect on solar radiation. On the opposite, remote sensing of aerosols in the thermal infrared domain still remains marginal. However, knowledge of the effect of aerosols on terrestrial radiation is needed for the evaluation of their total radiative forcing. Infrared remote sensing provides a way to retrieve other aerosol characteristics, including their mean altitude. Moreover, observations are possible at night and day, over ocean and over land. In this context, six years (2003-2008) of the 2nd generation vertical sounder AIRS observations have been processed over the tropical belt (30°N-30°S). Aerosol properties (10 µm infrared optical depth and mean layer altitude) are retrieved using a Look-Up Table (LUT) approach. The forward radiative transfer model 4A (Automatized Atmospheric Absorption Atlas) coupled with the DISORT algorithm accounting for atmospheric diffusion is used to feed the LUTs with simulations of the brightness temperatures of AIRS channels selected for their sensitivity to dust aerosols. LUTs degrees of freedom are : instrument viewing angle, surface pressure and surface emissivity, a parameter particularly important for dust retrieval over bright surfaces, such as deserts. AODs (resp. altitude) are sampled over the range 0.0-0.8 (resp. 0-5800 m). The retrieval algorithm follows two main steps : (i) retrieval of the atmospheric situation observed (temperature and water vapour profiles) ; (ii) retrieval of aerosol properties. Results have been compared to instruments commonly used in aerosol studies and also part of the Aqua Train : MODIS/Aqua and CALIOP/CALIPSO. The agreement obtained from these comparisons is quite satisfactory, demonstrating that our algorithm effectively allows the simultaneous retrieval of dust AOD
Bhartia, Pawan K.
In this presentation we will discuss the techniques to estimate total column ozone and aerosol absorption optical depth from the measurements of back scattered ultraviolet (buv) radiation. The total ozone algorithm has been used to create a unique record of the ozone layer, spanning more than 3 decades, from a series of instruments (BUV, SBUV, TOMS, SBUV/2) flown on NASA, NOAA, Japanese and Russian satellites. We will discuss how this algorithm can be considered a generalization of the well-known Dobson/Brewer technique that has been used to process data from ground-based instruments for many decades, and how it differs from the DOAS techniques that have been used to estimate vertical column densities of a host of trace gases from data collected by GOME and SCIAMACHY instruments. The buv aerosol algorithm is most suitable for the detection of UV absorbing aerosols (smoke, desert dust, volcanic ash) and is the only technique that can detect aerosols embedded in clouds. This algorithm has been used to create a quarter century record of aerosol absorption optical depth using the buv data collected by a series of TOMS instruments. We will also discuss how the data from the OMI instrument launched on July 15, 2004 will be combined with data from MODIS and CALIPSO lidar data to enhance the accuracy and information content of satellite-derived aerosol measurements. The OMI and MODIS instruments are currently flying on EOS Aura and EOS Aqua satellites respectively, part of a constellation of satellites called the "A-train".
Bhartia, Pawan K.
In this presentation we will discuss the techniques to estimate total column ozone and aerosol absorption optical depth from the measurements of backscattered ultraviolet (buv) radiation. The total ozone algorithm has been used to create a unique record of the ozone layer, spanning more than 3 decades, from a series of instruments (BUV, SBUV, TOMS, SBUV/2) flown on NASA, NOAA, Japanese and Russian satellites. We will discuss how this algorithm can be considered a generalization of the well-known Dobson/Brewer technique that has been used to process data from ground-based instruments for many decades, and how it differs from the DOAS techniques that have been used to estimate vertical column densities of a host of trace gases from data collected by GOME and SCIAMACHY instruments. The BUV aerosol algorithm is most suitable for the detection of UV absorbing aerosols (smoke, desert dust, volcanic ash) and is the only technique that can detect aerosols embedded in clouds. This algorithm has been used to create a quarter century record of aerosol absorption optical depth using the BUV data collected by a series of TOMS instruments. We will also discuss how the data from the OM1 instrument launched on July 15,2004 will be combined with data from MODIS and CALIPSO lidar data to enhance the accuracy and information content of satellite-derived aerosol measurements. The OM1 and MODIS instruments are currently flying on EOS Aura and EOS Aqua satellites respectively, part of a constellation of satellites called the "A-train". The CALIPSO satellite is expected to join this constellation in mid 2005.
Kim, Mijin; Kim, Jhoon; Wong, Man Sing; Yoon, Jongmin; Lee, Jaehwa; Wu, Dong L.; Chan, P.W.; Nichol, Janet E.; Chung, Chu-Yong; Ou, Mi-Lim
Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from tMI [basic algorithm] = 0
Chaubey, J. P.; O'Neill, N. T.; Hudak, D. R.; Rodriguez, P.; Ivanescu, L.; Eloranta, E.; Duck, T.
Aerosols and precipitation are among the agents responsible for the ongoing changes in the Arctic climate and the hydrological cycle. The seasonal variations of Arctic aerosols (Arctic haze for e.g.) are linked to the transport efficiency as well as precipitation (wet) scavenging. Aside from affecting aerosol concentrations, precipitation is an important hydrological variable that affects the moisture budget of the atmosphere. Aerosols, in turn, influence the vertical distribution of clouds and this induces changes in the precipitation pattern. The spatial and temporal sparsity of precipitation measurements over the Arctic region means that satellite remote sensing techniques take on an importance that considerably exceeds their role south of the Arctic circle. Radar reflectivity and snow profiles from CloudSat (in support of cloud and precipitation analyses) and backscattering measurements from CALIOP (investigations of aerosol and small cloud particle properties) can be used to study Arctic winter clouds and precipitation and the role of aerosols in their formation. In this study we attempt to validate satellite-based profiling retrievals of precipitation parameters using AHSRL (Arctic High Spectral Resolution Lidar), CRL (CANDAC Raman Lidar) and MMCR (Milli-Meter Cloud Radar) profiles acquired at the PEARL high-Arctic site in Eureka (80 °N, 86 °W), Nunavut, Canada. As part of the process of validating the profiling retrievals we aspire to learn more about the mechanisms controlling aerosol, cloud and precipitation inter-dynamics. In addition, ground-based, high-frequency observations of precipitation will be used for characterizing precipitation totals as well as the conditional probability of the type of precipitation (rain or snow) and thus to help understand and validate comparable information extracted from the satellite retrievals. We also aim to characterize different particle types using AHSRL and CRL depolarization profiles, MMCR Doppler velocity
Okamoto, Hajime; Sato, Kaori; Hagihara, Yuichiro; Ishimoto, Hiroshi; Borovoi, Anatoli; Konoshonkin, Alexander; Kustova, Natalia
We developed lidar-radar algorithms that can be applied to Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar and CloudSat data to retrieve ice microphysics. The algorithms were the extended version of previously reported algorithm  and can treat both of nadir pointing of CALIPSO lidar period and 3°-off-nadir pointing one. We used the scattering data bank produced by the physical optics methods  and created lidar look-up tables of quasi-horizontally oriented ice plates (Q2D-plate) for nadir- and off-nadir lidar pointing periods. Then LUTs were implemented in the ice retrieval algorithms. We performed several sensitivity studies to evaluate uncertainties in the retrieved ice microphysics due to ice particle orientation and shape. It was found that the implementation of orientation of horizontally oriented ice plate model in the algorithm drastically improved the retrieval results in both for nadir- and off-nadir lidar pointing periods. Differences in the retrieved microphysics between only randomly oriented ice model (3D-ice) and mixture of 3D-ice and Q2Dplate model were large especially in off-nadir period, e.g., 100% in effective radius and one order in ice water content, respectively. And differences in the retrieved ice microphysics among different mixture models were smaller than about 50% for effective radius in nadir period.
von Hoyningen-Huene, Wolfgang; Kokhanovsky, Alexander; Burrows, John P.; Hesselmans, Gerard; Gale, Leslie; Wandinger, Ulla; Bouvet, Marc; Eisinger, Michael
The future EarthCARE mission is a cloud - aerosol mission and is composed of 4 scientific instruments: a) the HSRL lidar - ATLID, providing vertical profiles of backscatter-, extinction- and depolarization profiles, b) the cloud - precipitation radar - CPR, giving vertical profiles of cloud and precipitation parameters, c) the multi-spectral imager - MSI as an imager with a swath width of 150 km and 0.5 km scene resolution, delivering the cloud and aerosol conditions in the vicinity of the lidar and radar beams and d) the broad band radiometer - BBR, measuring up-welling broad band radiation fluxes. The mission intends to use synergies between the vertical profiles from ATLID and CPR and the area and columnar information on clouds and aerosols from the MSI and the combination of all in the BBR up-welling fluxes. The use of the MSI instrument as imager for aerosol optical thickness (AOT) requires retrieval methods for AOT over ocean and land, which are in development within projects (AMARSI and IRMA), supported by ESA. The algorithm development for the AOT retrieval consists of a target discrimination, the estimation of the surface reflectance and determination of aerosol reflectance, which is used for AOT determination, applying look-up-tables. The algorithms are tested with synthetic data from radiative modelling and MODIS measurements with a selection of the subset of MSI VIS and NIR channels (0.659, 0.865, 1.61 and 2.1 µm). For the instrument performance of MODIS the algorithms developed provide quite comparable AOT with AERONET observations.
Chaikovsky, Anatoli; Dubovik, Oleg; Holben, Brent; Bril, Andrey; Goloub, Philippe; Tanré, Didier; Pappalardo, Gelsomina; Wandinger, Ulla; Chaikovskaya, Ludmila; Denisov, Sergey; Grudo, Jan; Lopatin, Anton; Karol, Yana; Lapyonok, Tatsiana; Amiridis, Vassilis; Ansmann, Albert; Apituley, Arnoud; Allados-Arboledas, Lucas; Binietoglou, Ioannis; Boselli, Antonella; D'Amico, Giuseppe; Freudenthaler, Volker; Giles, David; José Granados-Muñoz, María; Kokkalis, Panayotis; Nicolae, Doina; Oshchepkov, Sergey; Papayannis, Alex; Perrone, Maria Rita; Pietruczuk, Alexander; Rocadenbosch, Francesc; Sicard, Michaël; Slutsker, Ilya; Talianu, Camelia; De Tomasi, Ferdinando; Tsekeri, Alexandra; Wagner, Janet; Wang, Xuan
This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code) algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar/radiometric input data we use measurements from European Aerosol Research Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data. The algorithm starts with the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode.The LIRIC software package was implemented and tested at a number of EARLINET stations. Intercomparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLINET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.
Filipitsch, Florian; Preusker, Rene; Fischer, Juergen
Aerosols have a significant influence on the earth climate but are still one of the least understood variables in the earth radiation budget. On average aerosol particles scatter solar radiation back to space which leads to an offset in the global warming process to due greenhouse gases. Some types of atmospheric aerosols like black carbon or dessert dust absorb solar radiation and lead to local atmospheric warming. Even if this warming effect is overwhelmed by the cooling effect is it necessary to improve our knowledge on the global distribution of absorbing aerosols if we want to understand and predict local climate variations. Within the ESA CCI-Aerosol project we developed an innovative retrieval method to quantify aerosol absorption quantified by the Single Scattering Albedo (SSA) over the ocean in the sun glint contaminated region of a wind roughed sea surface. From satellite measurement commonly retrieved Aerosol Optical Depth (AOD), which is the vertical integrated aerosol volume extinction, gives no information on the absorbing or scattering quantities of the observed aerosol. To distinct absorption from scattering independent measurements at different viewing geometries are needed. Furthermore the reflection properties of the underlying surface has to be known and therewith distinct absorption from scattering. The dual view sensor Advanced Along-Track Scanning Radiometer (AATSR) provides such information in regions where either of the two views is sun glint effected the other is not. Hence, the sun glint is used as a lower boundary condition in the presented method an accurate determination of the ocean surface is needed. Therefore we use the 3 thermal channels from to estimate the amount of reflected sunlight to due glint in measured signal at 3.7 micrometer. The determined sun glint at the 3.7 micrometer channel is further used to derive an effective wind speed based on full radiative transfer calculations where optical properties for a wind roughed sea
Dubovik, O.; Litvinov, P.; Lapyonok, T.; Ducos, F.; Huang, X.; Lopatin, A.; Fuertes, D.; Torres, B.
GRASP (Generalized Retrieval of Aerosol and Surface Properties) is rather sophisticated algorithm was developed recently by Dubovik et al. (2011, 2014) with objective of achieving more complete and accurate aerosols and surface retrieval. Specifically, GPASP searches in continuous space of solutions and doesn't utilize look-up-tables. It based on highly elaborated statistically optimized fitting. For example, it uses multi-pixel retrieval when statistically optimized inversion is implemented simultaneously for a group of satellite pixels. This allows using additional a priori information about limited variability of aerosol of surface properties in time and/or space. As a result, GRASP doesn't use any specific information about aerosol or surface type in the each observed pixel, and the results are essentially driven by observations. However GRASP retrieval takes longer computational time compare to most conventional algorithms that is the main practical challenge of employing GRASP for massive data processing. Nonetheless, in last two years, GRASP has been significantly optimized and adapted to operational needs. As a result of this optimization, GRASP has been accelerated to the level acceptable for processing large volumes of satellite observations. Recently GRASP has been applied to multi-years archives of PARASO/POLDER and ENVISAT/MERIS. Based, on the preliminary analysis GRASP results are very promising for comprehensive characterization of aerosol even for observations over bright surfaces and for monitoring very high aerosol loading events (with AOD 2 or 3). In addition, it was made the attempts to estimate such aerosol characteristics as aerosol height, air mass, radiative forcing, aerosol type, etc. The results and illustrations will be presented.
Huang, Z.; Huang, J.
In this study, an effective algorithm was developed to retrieve aerosol optical properties and vertical profile using ground-based lidar measurements. The advantage of this algorithm is that aerosol optical depth retrieving from lidar measurements do not need so-called lidar ratio for same quality retrieved by Sun photometer of AERONET. Also, errors were apparently reduced when retrieving other optical properties using obtained-AOD as constraint. This effective algorithm was applied to retrieve the dust aerosol vertical profiles measured by three MPL-net Micro-Pulse Lidar system, which are located at one permanent site (Semi-Arid Climate & Environment Observatory of Lanzhou University (SACOL)) (located in Yuzhong, 35.95N/104.1E), one SACOL’s Mobile Facility (SMF) (deployed in Jintai, 37.57N/104.23E) and the U.S. Department of Energy Atmospheric Radiation Measurements(ARM) Ancillary Facility (AAF mobile laboratories, SMART-COMMIT) (deployed in Zhangye, 39.08N/100.27E)., during 2008 China-US joined dust field campaign (March-June 2008). A dust storm case which widely influenced Northwest China for 2 May, 2008 was studied using the three ground-based lidar and satellite-borne instruments measurements. The results show the different aerosol vertical structures at each site. Characteristics of aerosol vertical structure in spring over Northwest China were also investigated using the new method.
Liu, Dong; Luo, Jing; Yang, Yongying; Cheng, Zhongtao; Zhang, Yupeng; Zhou, Yudi; Duan, Lulin; Su, Lin
High-spectral-resolution lidars (HSRLs) are increasingly being developed for atmospheric aerosol remote sensing applications due to the straightforward and independent retrieval of aerosol optical properties without reliance on assumptions about lidar ratio. In HSRL technique, spectral discrimination between scattering from molecules and aerosol particles is one of the most critical processes, which needs to be accomplished by means of a narrowband spectroscopic filter. To ensure a high retrieval accuracy of an HSRL system, the high-quality design of its spectral discrimination filter should be made. This paper reviews the available algorithms that were proposed for HSRLs and makes a general accuracy analysis of the HSRL technique focused on the spectral discrimination, in order to provide heuristic guidelines for the reasonable design of the spectral discrimination filter. We introduce a theoretical model for retrieval error evaluation of an HSRL instrument with general three-channel configuration. Monte Carlo (MC) simulations are performed to validate the correctness of the theoretical model. Results from both the model and MC simulations agree very well, and they illustrate one important, although not well realized fact: a large molecular transmittance and a large spectral discrimination ratio (SDR, i.e., ratio of the molecular transmittance to the aerosol transmittance) are beneficial t o promote the retrieval accuracy. The application of the conclusions obtained in this paper in the designing of a new type of spectroscopic filter, that is, the field-widened Michelson interferometer, is illustrated in detail. These works are with certain universality and expected to be useful guidelines for HSRL community, especially when choosing or designing the spectral discrimination filter.
Torres, O.; Ahn, C.; Zhong, C.
The height of desert dust and carbonaceous aerosols layers and, to a lesser extent, the difficulty in assessing the predominant size mode of these absorbing aerosol types, are sources of uncertainty in the retrieval of aerosol properties from near UV satellite observations. The availability of independent, near-simultaneous measurements of aerosol layer height, and aerosol-type related parameters derived from observations by other A-train sensors, makes possible the direct use of these parameters as input to the OMI (Ozone Monitoring Instrument) near UV retrieval algorithm. A monthly climatology of aerosol layer height derived from observations by the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) sensor, and real-time AIRS (Atmospheric Infrared Sounder) CO observations are used in an upgraded version of the OMI near UV aerosol algorithm. AIRS CO measurements are used as a reliable tracer of carbonaceous aerosols, which allows the identification of smoke layers in areas and times of the year where the dust-smoke differentiation is difficult in the near-UV. The use of CO measurements also enables the identification of elevated levels of boundary layer pollution undetectable by near UV observations alone. In this paper we discuss the combined use of OMI, CALIOP and AIRS observations for the characterization of aerosol properties, and show a significant improvement in OMI aerosol retrieval capabilities.
satellites and atmospheric models. Chapter 3 presents an innovative retrieval approach to measure AOD430 and the aerosol phase function parameter, g, without the need for absolute radiance calibration; the retrieval is based on solar azimuth distributions of the Raman Scattering Probability (RSP), the near-absolute Rotational Raman Scattering (RRS) intensity, during the Department of Energy Two Column Aerosol Project (TCAP) at Cape Cod, MA. Furthermore, the TCAP field campaign provides a unique dataset to evaluate innovative retrieval algorithms and perform radiation closure studies. In Chapters 4 I describe the effect of persistent elevated aerosol layers on the apparent absorption of the collision induced absorption of oxygen (O2-O2, or O4) as seen by the ground based 2-D-MAX-DOAS. Chapter 5 discusses the effect of chemical composition of aerosols for optical closure of aerosol extinction as characterized by ground based (2-D-MAX-DOAS) and airborne remote sensing instruments (HSRL-2) and in-situ observations of aerosol optical properties calculated from size distributions measured aboard the DoE G-1 aircraft. Chapter 5 also includes a discussion on the effects of dry, moist, and size-corrections that need to be applied to the in-situ observations in order to infer extinction in the atmosphere. In the final Chapter 6, I present a comprehensive analysis of CHOCHO, HCHO, and NO2 column measurements obtained in multiple field deployments of MAX-DOAS under different NOx (NO + NO2) conditions and VOC precursors. In particular, I assess the magnitude of the ratio of CHOCHO to HCHO (RGF), which has been proposed as a metric to distinguish biogenic and/or anthropogenic VOC (BVOC/AVOC) influences, and show with box-modeling that the concentration of NO2 and dictates the value of RGF . I proposed a new metric of RGF based on box-modeling and field measurements to distinguish AVOC/BVOC influences and split in BVOCs.
Kim, W. V.; Kim, J.; Lee, H.; Jung, Y.; Boesch, H.
After the industrial revolution, atmospheric carbon dioxide concentration increased drastically over the last 250 years. It is still increasing and over than 400ppm of carbon dioxide was measured at Mauna Loa observatory for the first time which value was considered as important milestone. Therefore, understanding the source, emission, transport and sink of global carbon dioxide is unprecedentedly important. Currently, Total Carbon Column Observing Network (TCCON) is operated to observe CO2 concentration by ground base instruments. However, the number of site is very few and concentrated to Europe and North America. Remote sensing of CO2 could supplement those limitations. Greenhouse Gases Observing SATellite (GOSAT) which was launched 2009 is measuring column density of CO2 and other satellites are planned to launch in a few years. GOSAT provide valuable measurement data but its low spatial resolution and poor success rate of retrieval due to aerosol and cloud, forced the results to cover less than half of the whole globe. To improve data availability, accurate aerosol information is necessary, especially for East Asia region where the aerosol concentration is higher than other region. For the first step, we are developing CO2 retrieval algorithm based on optimal estimation method with VLIDORT the vector discrete ordinate radiative transfer model. Proto type algorithm, developed from various combinations of state vectors to find best combination of state vectors, shows appropriate result and good agreement with TCCON measurements. To reduce calculation cost low-stream interpolation is applied for model simulation and the simulation time is drastically reduced. For the further study, GOSAT CO2 retrieval algorithm will be combined with accurate GOSAT-CAI aerosol retrieval algorithm to obtain more accurate result especially for East Asia.
Diémoz, Henri; Eleftheratos, Kostas; Kazadzis, Stelios; Amiridis, Vassilis; Zerefos, Christos S.
A MkIV Brewer spectrophotometer has been operating in Athens since 2004. Direct-sun measurements originally scheduled for nitrogen dioxide retrievals were reprocessed to provide aerosol optical depths (AODs) at a wavelength of about 440 nm. A novel retrieval algorithm was specifically developed and the resulting AODs were compared to those obtained from a collocated Cimel filter radiometer belonging to the Aerosol Robotic Network (AERONET). The series are perfectly correlated, with Pearson's correlation coefficients being as large as 0.996 and with 90 % of AOD deviations between the two instruments being within the World Meteorological Organisation (WMO) traceability limits. In order to reach such a high agreement, several instrumental factors impacting the quality of the Brewer retrievals must be taken into account, including sensitivity to the internal temperature, and the state of the external optics and pointing accuracy must be carefully checked. Furthermore, the long-term radiometric stability of the Brewer was investigated and the performances of in situ Langley extrapolations as a way to track the absolute calibration of the Brewer were assessed. Other sources of error, such as slight shifts of the wavelength scale, are discussed and some recommendations to Brewer operators are drawn. Although MkIV Brewers are rarely employed to retrieve AODs in the visible range, they represent a key source of information about aerosol changes in the past three decades and a potential worldwide network for present and future coordinated AOD measurements. Moreover, a better understanding of the AOD retrieval at visible wavelengths will also contribute in improving similar techniques in the more challenging UV range.
Wagner, Sebastien; Govaerts, Yves
A new aerosol algorithm is developed at EUMETSAT to derive simultaneously the surface bidirectional reflectance factor (BRF) and the hourly variations of the tropospheric aerosol load from observations acquired by the SEVIRI radiometer on-board the Meteosat Second Generation satellites. In order to retrieve the aerosol optical thickness for each cloud-free observation, the algorithm makes the assumption that both the aerosol class and the surface radiative properties do not change during the course of the day. Hence, this algorithm infers the surface BRF from a forward radiative transfer model against daily accumulated observations in the 0.6, 0.8 and 1.6 MSG/SEVIRI bands. These daily time series provide the angular sampling used to discriminate the radiative effects that result from the surface anisotropy, from those caused by the aerosol scattering. The inversion method relies on the Optimal Estimation method which balances the information derived from the observations and the prior knowledge on the system. This approach allows the tracking of sharp daily variations of the aerosol atmospheric load, in particular in the case of quickly developing dust storm fronts. Results of comparisons with the AERONET aerosol product are presented on specific cases on pixel basis in order to assess the performance of this new algorithm.
Levy, Robert C.; Remer, Lorraine R.; Kaufman, Yoram J.
Reflectance measurements in the visible and infrared wavelengths, from the Moderate Resolution Imaging Spectroradiometer (MODIS), are used to derive aerosol optical thicknesses (AOT) and aerosol properties over land surfaces. The measured spectral reflectance is compared with lookup tables, containing theoretical reflectance calculated by radiative transfer (RT) code. Specifically, this RT code calculates top of the atmosphere (TOA) intensities based on a scalar treatment of radiation, neglecting the effects of polarization. In the red and near infrared (NIR) wavelengths the use of the scalar RT code is of sufficient accuracy to model TOA reflectance. However, in the blue, molecular and aerosol scattering dominate the TOA signal. Here, polarization effects can be large, and should be included in the lookup table derivation. Using a RT code that allows for both vector and scalar calculations, we examine the reflectance differences at the TOA, with and without polarization. We find that the differences in blue channel TOA reflectance (vector - scalar) may reach values of 0.01 or greater, depending on the sun/surface/sensor scattering geometry. Reflectance errors of this magnitude translate to AOT differences of 0.1, which is a very large error, especially when the actual AOT is low. As a result of this study, the next version of aerosol retrieval from MODIS over land will include polarization.
Lacis, Andrew A.
The direct-beam spectral extinction of solar radiation contains information on atmospheric composition in a form that is essentially free from the data analysis complexities that often arise from multiple scattering. Ground based Multi-Filter Shadowband Radiometer (MFRSR) measurements provide such information for the vertical atmospheric column path, while solar occultation measurements from a satellite platform provide horizontal slices through the atmosphere. We describe application of a Multi-Spectral Atmospheric Column Extinction (MACE) analysis technique used to analyze MFRSR data also to occultation measurements made by SAGE II. For analysis, we select the 1985 Nevado del Ruiz volcanic eruption period to retrieve atmospheric profiles of ozone and NO2, and changes in the stratospheric aerosol size and optical depth. The time evolution of volcanic aerosol serves as a passive tracer to study stratospheric dynamics, and changes in particle size put constraints on the sulfur chemistry modeling of volcanic aerosols. Paper presented at The '99 Kyoto Aerosol-Cloud Workshop, held Dec 1-3, 1999, Kyoto, Japan
Sayer, A. M.; Hsu, N. C.; Eck, T. F.; Smirnov, A.; Holben, B. N.
Smoke aerosols from biomass burning are an important component of the global aerosol system. Analysis of Aerosol Robotic Network (AERONET) retrievals of aerosol microphysical/optical parameters at 10 sites reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke observed at coastal/island AERONET sites also mostly lie within the range of variability at the near-source sites. Differences between sites tend to be larger than variability at an individual site, although optical properties for some sites in different regions can be quite similar. Across the sites, typical midvisible SSA ranges from ~ 0.95-0.97 (sites dominated by boreal forest or peat burning, typically with larger fine-mode particle radius and spread) to ~ 0.88-0.9 (sites most influenced by grass, shrub, or crop burning, typically smaller fine-mode particle radius and spread). The tropical forest site Alta Floresta (Brazil) is closer to this second category, although with intermediate SSA ~ 0.92. The strongest absorption is seen in southern African savannah at Mongu (Zambia), with average midvisible SSA ~ 0.85. Sites with stronger absorption also tend to have stronger spectral gradients in SSA, becoming more absorbing at longer wavelengths. Microphysical/optical models are presented in detail so as to facilitate their use in radiative transfer calculations, including extension to UV (ultraviolet) wavelengths, and lidar ratios. One intended application is to serve as candidate optical models for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean often have insufficient absorption (i.e. too high SSA) to represent these biomass burning aerosols. The underestimates in satellite-retrieved AOD in smoke outflow regions, which have important consequences for applications of these satellite data sets, are consistent with
Pflug, B.; Main-Knorn, M.; Makarau, A.; Richter, R.
Atmospheric correction of satellite images is necessary for many applications of remote sensing, i.e. computation of vegetation indices and biomass estimation. The first step in atmospheric correction is estimation of the actual aerosol properties. Due to the spatial and temporal variability of aerosol amount and type, this step becomes crucial for an accurate correction of satellite data. Consequently, the validation of aerosol estimation contributes to the validation of atmospheric correction algorithms. In this study we present the validation of aerosol estimation using own sun photometer measurements in Central Europe and measurements of AERONET-stations at different locations in the world. Our ground-based sun photometer measurements of vertical column aerosoloptical thickness (AOT) spectra are performed synchronously to overpasses of the satellites RapidEye, Landsat 5, Landsat 7 and Landsat 8. Selected AERONET data are collocated to Landsat 8 overflights. The validation of the aerosol retrieval is conducted by a direct comparison of ground-measured AOT with satellite derived AOT using the ATCOR tool for the selected satellite images. The mean uncertainty found in our experiments is AOT550nm ~ 0.03±0.02 for cloudless conditions with cloud+haze fraction below 1%. This AOT uncertainty approximately corresponds to an uncertainty in surface albedo of ρ ~ 0.003. Inclusion of cloudy and hazy satellite images into the analysis results in mean AOT550nm ~ 0.04±0.03 for both RapidEye and Landsat imagery. About 1/3 of samples perform with the AOT uncertainty better than 0.02 and about 2/3 perform with AOT uncertainty better than 0.05.
Granados-Muñoz, M. J.; Guerrero-Rascado, J. L.; Bravo-Aranda, J. A.; Navas-Guzmán, F.; Valenzuela, A.; Lyamani, H.; Chaikovsky, A.; Wandinger, U.; Ansmann, A.; Dubovik, O.; Grudo, J. O.; Alados-Arboledas, L.
LIRIC (Lidar-Radiometer Inversion Code) is applied to combined lidar and Sun photometer data from Granada station corresponding to different case studies. The main aim of this analysis is to evaluate the stability of LIRIC output volume concentration profiles for different aerosol types, loadings, and vertical distributions of the atmospheric aerosols. For this purpose, in a first part, three case studies corresponding to different atmospheric situations are analyzed to study the influence of the user-defined input parameters in LIRIC when varied in a reasonable range. Results evidence the capabilities of LIRIC to retrieve vertical profiles of microphysical properties during daytime by the combination of the lidar and the Sun photometer systems in an automatic and self-consistent way. However, spurious values may be obtained in the lidar incomplete overlap region depending on the structure of the aerosol layers. In a second part, the use of a second Sun photometer located in Cerro Poyos, in the same atmospheric column as Granada but at higher altitude, allowed us to obtain LIRIC retrievals from two different altitudes with independent Sun photometer measurements in order to check the self-consistency and robustness of the method. Retrievals at both levels are compared, providing a very good agreement (differences below 5 µm3/cm3) in those cases with the same aerosol type in the whole atmospheric column. However, some assumptions such as the height independency of parameters (sphericity, size distribution, or refractive index, among others) need to be carefully reviewed for those cases with the presence of aerosol layers corresponding to different types of atmospheric aerosols.
Wang, P H; McCormick, M P; McMaster, L R; Chu, W P; Swissler, T J; Osborn, M T; Russell, P B; Oberbeck, V R; Livingston, J; Rosen, J M; Hofmann, D J; Grams, G W; Fuller, W H; Yue, G K
This paper describes an investigation of the comprehensive aerosol correlative measurement experiments conducted between November 1984 and July 1986 for satellite measurement program of the Stratospheric Aerosol and Gas Experiment (SAGE II). The correlative sensors involved in the experiments consist of the NASA Ames Research Center impactor/laser probe, the University of Wyoming dustsonde, and the NASA Langley Research Center airborne 14-inch (36 cm) lidar system. The approach of the analysis is to compare the primary aerosol quantities measured by the ground-based instruments with the calculated ones based on the aerosol size distributions retrieved from the SAGE II aerosol extinction measurements. The analysis shows that the aerosol size distributions derived from the SAGE II observations agree qualitatively with the in situ measurements made by the impactor/laser probe. The SAGE II-derived vertical distributions of the ratio N0.15/N0.25 (where Nr is the cumulative aerosol concentration for particle radii greater than r, in micrometers) and the aerosol backscatter profiles at 0.532- and 0.6943-micrometer lidar wavelengths are shown to agree with the dustsonde and the 14-inch (36-cm) lidar observations, with the differences being within the respective uncertainties of the SAGE II and the other instruments. PMID:11539801
Xu, F.; Diner, D. J.; Seidel, F. C.; Dubovik, O.; Zhai, P.
A vector Markov chain radiative transfer method was developed for forward modeling of radiance and polarization fields in a coupled atmosphere-ocean system. The method was benchmarked against an independent Successive Orders of Scattering code and linearized through the use of Jacobians. Incorporated with the multi-patch optimization algorithm and look-up-table method, simultaneous aerosol and ocean color retrievals were performed using imagery acquired by the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) when it was operated in step-and-stare mode with 9 viewing angles ranging between ±67°. Data from channels near 355, 380, 445, 470*, 555, 660*, and 865* nm were used in the retrievals, where the asterisk denotes the polarimetric bands. Retrievals were run for AirMSPI overflights over Southern California and Monterey Bay, CA. For the relatively high aerosol optical depth (AOD) case (~0.28 at 550 nm), the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentration were compared to those reported by the USC SeaPRISM AERONET-OC site off the coast of Southern California on 6 February 2013. For the relatively low AOD case (~0.08 at 550 nm), the retrieved aerosol concentration and size distribution were compared to those reported by the Monterey Bay AERONET site on 28 April 2014. Further, we evaluate the benefits of multi-angle and polarimetric observations by performing the retrievals using (a) all view angles and channels; (b) all view angles but radiances only (no polarization); (c) the nadir view angle only with both radiance and polarization; and (d) the nadir view angle without polarization. Optimized retrievals using different initial guesses were performed to provide a measure of retrieval uncertainty. Removal of multi-angular or polarimetric information resulted in increases in both parameter uncertainty and systematic bias. Potential accuracy improvements afforded by applying constraints on the surface
Xie, Ya'nan; Liu, Zhikun; An, Dawei
This paper presents a new type of rainfall retrieval algorithm, called the model-oriented statistical and Volterra integration. It is a combination of the model-oriented statistical (MOS) and Volterra integral equation (VIE) approaches. The steps involved in this new algorithm can be briefly illustrated as follows. Firstly, information such as the start point and width of the rain is obtained through pre-analysis of the data received by synthetic aperture radar (SAR). Secondly, the VIE retrieval algorithm is employed over a short distance to obtain information on the shape of the rain. Finally, the rain rate can be calculated by using the MOS retrieval algorithm. Simulation results show that the proposed algorithm is effective and simple, and can lead to time savings of nearly 50% compared with MOS. An example of application of SAR data is also discussed, involving the retrieval of precipitation information over the South China Sea.
Chou, Mong-Dah; Chan, Pui-King; Wang, Menghua; Einaudi, Franco (Technical Monitor)
To understand climatic implications of aerosols over global oceans, the aerosol optical properties retrieved from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) are analyzed, and the effects of the aerosols on the Earth's radiation budgets (aerosol radiative forcing, ARF) are computed using a radiative transfer model. It is found that the distribution of the SeaWiFS-retrieved aerosol optical thickness is distinctively zonal. The maximum in the equatorial region coincides with the Intertropical Convergence Zone, and the maximum in the Southern Hemispheric high latitudes coincides with the region of prevailing westerlies. The minimum aerosol optical thickness is found in the subtropical high pressure regions, especially in the Southern Hemisphere. These zonal patterns clearly demonstrate the influence of atmospheric circulation on the oceanic aerosol distribution. Over global oceans, aerosols reduce the annual mean net downward solar flux by 5.4 W m-2 at the top of the atmosphere and by 6.1 W m-2 at the surface. The largest ARF is found in the tropical Atlantic, Arabian Sea, Bay of Bengal, the coastal regions of Southeast and East Asia, and the Southern Hemispheric high latitudes. During the period of the Indonesian big fires (September-December 1997), the cooling due to aerosols is greater than 15 W m-2 at the top of the atmosphere and greater than 30 W m(exp -1) at the surface in the vicinity of the maritime continents. The atmosphere receives extra solar radiation by greater than 15 W m(exp -1) over a large area. These large changes in radiative fluxes are expected to have enhanced the atmospheric stability, weakened the atmospheric circulation, and augmented the drought condition during that period. It would be very instructive to simulate the regional climatic. The model-calculated clear sky solar flux at the top of the atmosphere is compared with that derived from the Clouds and the Earth's Radiant Energy System (CERES). The net downward solar flux of
Peyridieu, Sophie; Chédin, Alain; Tanré, Didier; Capelle, Virginie; Pierangelo, Clémence; Lamquin, Nicolas; Armante, Raymond
Remote sensing of aerosol properties in the visible domain has been widely used for a better characterization of these particles and of their effect on solar radiation. On the opposite, remote sensing of aerosols in the thermal infrared domain still remains marginal. However, knowledge of the effect of aerosols on terrestrial radiation is needed for the evaluation of their total radiative forcing. A key point of infrared remote sensing is its ability to retrieve aerosol optical depth as well as mean dust layer altitude, a variable required for measuring their impact on climate. Moreover, observations are possible night and day, over ocean and over land. Our algorithm is specifically designed to retrieve simultaneously coarse mode dust aerosol 10 µm optical depth (AOD) and mean layer altitude from high spectral resolution infrared sounders observations. Thanks to IASI higher spectral resolution, the selection of finer channels for aerosol detection allows an even more accurate determination of aerosol properties. In this context, results obtained from 7 years (2003-2010) of AIRS/Aqua and more than 2 years (2007-2010) of IASI/Metop observations have been compared to other aerosol sensors. Compared to MODIS/Aqua optical depth product, 10 µm dust optical depth shows a very good agreement, particularly for tropical Atlantic regions downwind of the Sahara during the dust season. Comparisons with PARASOL non-spherical coarse mode product allows explaining small differences observed far from the sources. Time series of the mean aerosol layer altitude are compared to the CALIOP Level-2 products starting June 2006. For regions located downwind of the Sahara, the comparison again shows a good agreement with a mean standard deviation between the two products of about 400 m over the period processed, demonstrating that our algorithm effectively allows retrieving accurate mean dust layer altitude. A 7-year global climatology of the aerosol 10 µm dust optical depth and of the
The MODIS aerosol products today are widely used by the climate and air quality communities, operationally in data assimilation systems, by air quality forecasters, and throughout the research world. The product is the result of algorithms that were conceptualized 20 years ago by Yoram Kaufman and Didier Tanre, developed through the entire 1990's by a team spanning two continents, and maintained and evaluated since Terra launch in 1999. I will use this opportunity to point out the highlights of the past 20 years, and preview plans for a future that is beginning even now.
Levy, Robert C.; Remer, Lorraine A.; Tanré, Didier; Kaufman, Yoram J.; Ichoku, Charles; Holben, Brent N.; Livingston, John M.; Russell, Philip B.; Maring, Hal
The Puerto Rico Dust Experiment (PRIDE) took place in Roosevelt Roads, Puerto Rico from 26 June to 24 July 2000 to study the radiative and physical properties of African dust aerosol transported into the region. PRIDE had the unique distinction of being the first major field experiment to allow direct comparison of aerosol retrievals from the Moderate Imaging Spectroradiometer (MODIS) with Sun photometer and in situ aerosol measurements. Over the ocean the MODIS algorithm retrieves aerosol optical depth (AOD) as well as information about the aerosols' size distribution. During PRIDE, AODs derived by MODIS in the red wavelengths (0.66 μm) compare closely with Sun photometers. However, MODIS-derived AODs are too large in the blue and green wavelengths (0.47 and 0.55 μm) and too small in the near infrared (0.87 μm). This error in AOD spectral dependence results in retrieved particle size distributions that are small compared to in situ measurements and smaller still when compared to Sun photometer sky radiance inversions. The differences in size distributions may be, in part, associated with MODIS' simplification of dust as spherical particles. Analysis of this PRIDE data set is a first step toward derivation of realistic models for future MODIS retrievals.
Damman, Alix; Zunz, Violette; Govaerts, Yves; Kaminski, Thomas; Voßbeck, Michael
The Meteosat satellites play an important role for the generation of consistent long time series of aerosol properties. This importance relies on (i) the long duration of past (Meteosat First Generation, MFG), present (Meteosat Second Generation, MSG) and future (Meteosat Third Generation, MTG) missions and (ii) their frequent cycle of acquisition that can be used to document the anisotropy of the surface and therefore the lower boundary condition for aerosol retrieval over land surfaces. The Package for the joint Inversion of Surface and Aerosol (PISA) is a new algorithm developed by Rayference and The Inversion Lab for the joint retrieval of surface reflectance and aerosol properties. It relies on the inversion of a physically-based radiative transfer model accounting for the surface reflectance anisotropy and its coupling with aerosol scattering. The inversion scheme accounts for prior knowledge on the surface properties and smoothness constraints on the temporal variation of aerosols. PISA also provides the posterior uncertainty covariance matrix for the retrieved variables in every processed pixel. The package has been applied on Top Of Atmosphere (TOA) Bidirectional Reflectance Factor (BRF) acquired by SEVIRI onboard Meteosat Second Generation (MSG) in the VIS0.6, VIS0.8 and NIR1.6 spectral bands. Observations are accumulated during a certain period of time to sufficiently document the surface anisotropy and minimize the impact of clouds. The surface radiative properties are retrieved for this entire accumulation period during which they are supposed to be constant. Aerosol properties however are derived on an hourly basis. Based on PISA, a processing chain has been developed and applied on 2008 MSG/SEVIRI observations for some specific sub-domains of the Earth disk. For these processed sub-domains, the information content of each MSG/SEVIRI band will be analysed based on the prior and posterior uncertainty covariance matrices. This constitutes a first step
Lang-Yona, N; Rudich, Y; Segre, E; Dinar, E; Abo-Riziq, A
The major uncertainties associated with the direct impact of aerosols on climate call for fast and accurate characterization of their optical properties. Cavity ring down (CRD) spectroscopy provides highly sensitive measurement of aerosols' extinction coefficients from which the complex refractive index (RI) of the aerosol may be retrieved accurately for spherical particles of known size and number density, thus it is possible to calculate the single scattering albedo and other atmospherically relevant optical parameters. We present a CRD system employing continuous wave (CW) single mode laser. The single mode laser and the high repetition rate obtained significantly improve the sensitivity and reliability of the system, compared to a pulsed laser CRD setup. The detection limit of the CW-CRD system is between 6.67 x 10(-10) cm(-1) for an empty cavity and 3.63 x 10(-9) cm(-1) for 1000 particles per cm(3) inside the cavity, at a 400 Hz sampling and averaging of 2000 shots for one sample measurement taken in 5 s. For typical pulsed-CRD, the detection limit for an empty cavity is less than 3.8 x 10(-9) cm(-1) for 1000 shots averaged over 100 s at 10 Hz. The system was tested for stability, accuracy, and RI retrievals for scattering and absorbing laboratory-generated aerosols. Specifically, the retrieved extinction remains very stable for long measurement times (1 h) with an order of magnitude change in aerosol number concentration. In addition, the optical cross section (sigma(ext)) of a 400 nm polystyrene latex sphere (PSL) was determined within 2% error compared to the calculated value based on Mie theory. The complex RI of PSL, nigrosin, and ammonium sulfate (AS) aerosols were determined by measuring the extinction efficiency (Q(ext)) as a function of the size parameter ((piD)/lambda) and found to be in very good agreement with literature values. A mismatch in the retrieved RI of Suwannee River fulvic acid (SRFA) compared to a previous study was observed and is
Yorks, J. E.; McGill, M. J.; Hlavka, D. L.
The Airborne Cloud-Aerosol Transport System (ACATS) is a Doppler lidar system and high spectral resolution lidar (HSRL) recently developed at NASA Goddard Space Flight Center (GSFC). ACATS passes the returned atmospheric backscatter through a single etalon and divides the transmitted signal into several channels (wavelength intervals), which are measured simultaneously and independently (Figure 1). Both the particulate and molecular scattered signal can be directly and unambiguously measured, allowing for direct retrievals of particle extinction. The broad Rayleigh-scattered spectrum is imaged as a nearly flat background, illustrated in Figure 1c. The integral of the particulate backscattered spectrum is analogous to the aerosol measurement from the typical absorption filter HSRL technique in that the molecular and particulate backscatter components can be separated (Figure 1c and 1d). The main difference between HSRL systems that use the iodine filter technique and the multichannel etalon technique used in the ACATS instrument is that the latter directly measures the spectral broadening of the particulate backscatter using the etalon to filter out all backscattered light with the exception of a narrow wavelength interval (1.5 picometers for ACATS) that contains the particulate spectrum (grey, Figure 1a). This study outlines the method and retrieval algorithms for ACATS data products, focusing on the HSRL derived cloud and aerosol properties. While previous ground-based multi-channel etalon systems have been built and operated for wind retrievals, there has been no airborne demonstration of the technique and the method has not been used to derive HSRL cloud and aerosol properties. ACATS has flown on the NASA ER-2 during flights over Alaska in July 2014 and as part of the Wallops Airborne Vegetation Experiment (WAVE) in September 2012. This study will focus on the HSRL aspect of the ACATS instrument, since the method and retrieval algorithms have direct application
Petry, Frederick E.; And Others
Describes an approach that combines concepts from information retrieval, fuzzy set theory, and genetic programing to improve weighted Boolean query formulation via relevance feedback. Highlights include background on information retrieval systems; genetic algorithms; subproblem formulation; and preliminary results based on a testbed. (Contains 12…
Hart, William D.; Palm, Stephen P.; Spinhirne, James D.
The Geoscience Laser Altimeter System (GLAS) is scheduled for launch in July of 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESAT). In addition to being a precision altimeter for mapping the height of the Earth's icesheets, GLAS will be an atmospheric lidar, sensitive enough to detect gaseous, aerosol, and cloud backscatter signals, at horizontal and vertical resolutions of 175 and 75m, respectively. GLAS will be the first lidar to produce temporally continuous atmospheric backscatter profiles with nearly global coverage (94-degree orbital inclination). With a projected operational lifetime of five years, GLAS will collect approximately six billion lidar return profiles. The large volume of data dictates that operational analysis algorithms, which need to keep pace with the data yield of the instrument, must be efficient. So, we need to evaluate the ability of operational algorithms to detect atmospheric constituents that affect global climate. We have to quantify, in a statistical manner, the accuracy and precision of GLAS cloud and aerosol observations. Our poster presentation will show the results of modeling studies that are designed to reveal the effectiveness and sensitivity of GLAS in detecting various atmospheric cloud and aerosol features. The studies consist of analyzing simulated lidar returns. Simulation cases are constructed either from idealized renditions of atmospheric cloud and aerosol layers or from data obtained by the NASA ER-2 Cloud Lidar System (CLS). The fabricated renditions permit quantitative evaluations of operational algorithms to retrieve cloud and aerosol parameters. The use of observational data permits the evaluations of performance for actual atmospheric conditions. The intended outcome of the presentation is that climatology community will be able to use the results of these studies to evaluate and quantify the impact of GLAS data upon atmospheric modeling efforts.
Tripathi, Ashish; Leyffer, Sven; Munson, Todd; Wild, Stefan M.
Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.
Levy, R. C.; Remer, L. A.; Mattoo, S.; Kleidman, R. G.; Leptoukh, G. G.; Kahn, R. A.; Tanré, D.
As we celebrate the ten-year anniversary of Terra launch, we can step back and assess Yoram Kaufman’s vision of the global aerosol system. From Terra’s space vantage, the MODerate-resolution Imaging Spectroradiometer (MODIS) has observed global production and transport of aerosols, including plumes of desert dust, billows of smoke, and streams of pollution. From MODIS, we now have a ten-year climatology that can be used to quantify not only the mean, but also interannual variability, anomalies and possibly trends. However, before we are able to interpret the results with confidence, we must ensure we have performed solid validation analyses. An identical twin MODIS, launched aboard Aqua two years after, has given us complementary characterization of the global aerosol system. We have applied consistent retrieval algorithms and processing procedures to both sensors for the entire mission, deriving the Collection 5 (C005) dark-target aerosol products. By comparing to measurements from over 300 globally distributed, ground-based AERONET sunphotometers, we have ‘validated’ along-orbit, aerosol optical depth (AOD or τ) over both ocean (66% within ±(0.04+0.05τ)) and land (66% within ±(0.05+0.15τ)). At the same time, we are learning why there are systematic biases in certain regions and seasons, and how we might correct for them. Yet there are differences between the two MODIS instruments that are puzzling. They seem to give us inconsistent pictures of global means and trends. Some possible reasons include tiny calibration drifts, differences in sampling due to orbital geometry and clouds, as well as methods of aggregating the along-orbit (Level 2) data for deriving gridded daily and monthly statistics (Level 3). MODIS has been observing aerosol for ten years, and we are working towards characterizing regional and global aerosol climatology with confidence.
Kacenelenbogen, M. S.; Vaughan, M.; Redemann, J.; Hoff, R. M.; Rogers, R.; Ferrare, R. A.; Russell, P. B.; Hostetler, C. A.; Hair, J. W.; Holben, B.
The Cloud Aerosol LIdar with Orthogonal Polarization (CALIOP), on board the CALIPSO platform, has measured profiles of total attenuated backscatter coefficient (level 1 products) since June 2006. CALIOP’s level 2 products, such as the aerosol backscatter and extinction coefficient profiles, are retrieved using a complex succession of automated algorithms. One of our goals was to help identify potential shortcomings in the CALIOP version 2 level 2 aerosol extinction product and to illustrate some of the motivation for the changes that were introduced in the next version of CALIOP data (version 3, currently being processed). As a first step, we compared CALIOP version 2-derived AOD with collocated MODerate-resolution Imaging Spectroradiometer (MODIS) AOD retrievals over the Continental United States. The best statistical agreement between those two quantities was found over the Eastern part of the United States with, nonetheless, a weak correlation (R~0.4) and an apparent CALIOP version 2 underestimation (by ~66 %) of MODIS AOD. To help quantify the potential factors contributing to the uncertainty of the CALIOP aerosol extinction retrieval, we then focused on a one-day, multi-instrument, multiplatform comparison study during the CALIPSO and Twilight Zone (CATZ) validation campaign on August 04, 2007. This case study illustrates the following potential reasons for a bias in the version 2 CALIOP AOD: (i) CALIOP’s low signal-to-noise ratio (SNR) leading to the misclassification and/or lack of aerosol layer identification, especially close to the Earth’s surface; (ii) the cloud contamination of CALIOP version 2 aerosol backscatter and extinction profiles; (iii) potentially erroneous assumptions of the backscatter-to-extinction ratio (Sa) used in CALIOP’s extinction retrievals; and (iv) calibration coefficient biases in the CALIOP daytime attenuated backscatter coefficient profiles. We then show the use of the CALIPSO aerosol vertical distribution information in
Kim, M.; Kim, J.; Jeong, U.; Kim, W.; Holben, B.; Eck, T. F.; Lim, J. H.; Song, C. K.; Lee, S.
An aerosol model optimized for East Asia is improved by applying inversion data from both long-term monitoring of the Aerosol Robotic Network (AERONET) sun photometer and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia campaign from 2012. This model plays an important role in retrieving accurate aerosol optical depth (AOD) from satellite-based measurements. In particular, the performance of a single visible channel algorithm, limited to a specific aerosol type, from real-time measurements is strongly affected by the assumed aerosol optical properties (AOPs) for the measured scene. In sensitivity tests, a 4% difference in single scattering albedo (SSA) between modeled and measured values can cause a retrieval error in AOD of over 20%, and the overestimation of SSA leads to an underestimation of AOD. Based on the AERONET inversion datasets obtained over East Asia before 2011, seasonally analyzed AOPs can be summarized by SSAs (measured at 675 nm) of 0.92, 0.94, 0.92, and 0.91 for spring (March, April, and May), summer (June, July, and August), autumn (September, October, and November), and winter (December, January, and February), respectively. After DRAGON-Asia 2012, the SSA during spring shows a slight increase to 0.93. The large volume of data and spatially concentrated measurements from this campaign can be used to improve the representative aerosol model for East Asia. Accordingly, the AOD datasets retrieved from a single channel algorithm, which uses a pre-calculated look-up table (LUT) with the new aerosol model, show an improved correlation with the measured AOD during the DRAGON-Asia campaign (March to May 2012). Compared with the correlation of the AOD retrieved using the original aerosol model, the regression slope between the new AOD and the AERONET values is reduced from 1.08 to 1.00, while the change of the y-offset of -0.08 is significant. The correlation coefficients for the comparisons are 0.87 and 0.85, respectively. The
Grzegorski, Michael; Munro, Rosemary; Poli, Gabriele; Holdak, Andriy; Lang, Ruediger
The retrieval of aerosol optical properties is an important task to provide data for industry and climate forecasting. An ideal instrument should include observations with moderate spectral and high spatial resolution for a wide range of wavelengths (from the UV to the TIR), measurements of the polarization state at different wavelengths and measurements of the same scene for different observation geometries. As such an ideal instrument is currently unavailable the usage of different instruments on one satellite platform is an alternative choice. Since February 2014, the Polar Multi sensor Aerosol product (PMAp) has been delivered as an operational GOME product to our customers. The algorithm retrieves aerosol optical properties over ocean (AOD, volcanic ash, aerosol type) using a multi-sensor approach (GOME, AVHRR, IASI). The product is now extended to pixels over land using a new release of the operational PMAp processor (PMAp v2). The pre-operational data dissemination of the new PMAp v2 data to our users is scheduled for March 2016. This presentation gives an overview on the new operational product PMAp v2 with a focus on the validation of the PMAp aerosol optical depth over land. The impact of different error sources on the results (e.g. surface contribution to the TOA reflectance) is discussed. We also show first results of upcoming extensions of our PMAp processor, in particular the improvement of the cloud/aerosol discrimination of thick aerosol events (e.g. volcanic ash plumes, desert dust outbreaks).
Kassianov, Evgueni I.; Ovchinnikov, Mikhail; Berg, Larry K.; McFarlane, Sally A.; Flynn, Connor J.; Ferrare, Richard; Hostetler, Chris A.; Alexandrov, Mikhail
A recently developed reflectance ratio (RR) method for the retrieval of aerosol optical depth (AOD) is evaluated using extensive airborne and ground-based data sets collected during the Cloud and Land Surface Interaction Campaign (CLASIC) and the Cumulus Humilis Aerosol Processing Study (CHAPS), which took place in June 2007 over the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site. A detailed case study is performed for a field of single-layer shallow cumuli observed on June 12, 2007. The RR method is applied to retrieve the spectral values of AOD from the reflectance ratios measured by the MODIS Airborne Simulator (MAS) for two pairs of wavelengths (660 and 470 nm and 870 and 470 nm) collected at a spatial resolution of 0.05 km. The retrieval is compared with an independent AOD estimate from three ground-based Multi-filter Rotating Shadowband Radiometers (MFRSRs). The interpolation algorithm that is used to project MFRSR point measurements onto the aircraft flight tracks is tested using AOD derived from NASA Langley High Spectral Resolution Lidar (HSRL). The RR AOD estimates are in a good agreement (within 5%) with the MFRSR-derived AOD values for the 660-nm wavelength. The AODs obtained from MAS reflectance ratios overestimate those derived from MFRSR measurements by 15-30% for the 470-nm wavelength and underestimate the 870-nm AOD by the same amount.
Chemyakin, Eduard; Burton, Sharon; Kolgotin, Alexei; Müller, Detlef; Hostetler, Chris; Ferrare, Richard
We present an investigation of some important mathematical and numerical features related to the retrieval of microphysical parameters [complex refractive index, single-scattering albedo, effective radius, total number, surface area, and volume concentrations] of ambient aerosol particles using multiwavelength Raman or high-spectral-resolution lidar. Using simple examples, we prove the non-uniqueness of an inverse solution to be the major source of the retrieval difficulties. Some theoretically possible ways of partially compensating for these difficulties are offered. For instance, an increase in the variety of input data via combination of lidar and certain passive remote sensing instruments will be helpful to reduce the error of estimation of the complex refractive index. We also demonstrate a significant interference between Aitken and accumulation aerosol modes in our inversion algorithm, and confirm that the solutions can be better constrained by limiting the particle radii. Applying a combination of an analytical approach and numerical simulations, we explain the statistical behavior of the microphysical size parameters. We reveal and clarify why the total surface area concentration is consistent even in the presence of non-unique solution sets and is on average the most stable parameter to be estimated, as long as at least one extinction optical coefficient is employed. We find that for selected particle size distributions, the total surface area and volume concentrations can be quickly retrieved with fair precision using only single extinction coefficients in a simple arithmetical relationship. PMID:27140552
Mielonen, T.; Levy, R. C.; Aaltonen, V.; Komppula, M.; de Leeuw, G.; Huttunen, J.; Lihavainen, H.; Kolmonen, P.; Lehtinen, K. E. J.; Arola, A.
Aerosol Optical Depth (AOD) and Angstrom exponent (AE) values derived with the MODIS retrieval algorithm over land (Collection 5) are compared with ground based sun photometer measurements at eleven sites spanning the globe. Although, in general, total AOD compares well at these sites (R2 values generally over 0.8), there are cases (from 2 to 67% of the measurements depending on the site) where MODIS clearly retrieves the wrong spectral dependence, and hence, an unrealistic AE value. Some of these poor AE retrievals are due to the aerosol signal being too small (total AOD<0.3) but in other cases the AOD should have been high enough to derive accurate AE. However, in these cases, MODIS indicates AE values close to 0.6 and zero fine model weighting (FMW), i.e. dust model provides the best fitting to the MODIS observed reflectance. Yet, according to evidence from the collocated sun photometer measurements and back-trajectory analyses, there should be no dust present. This indicates that the assumptions about aerosol model and surface properties made by the MODIS algorithm may have been incorrect. Here we focus on problems related to parameterization of the land-surface optical properties in the algorithm, in particular the relationship between the surface reflectance at 660 and 2130 nm.
Chemyakin, Eduard; Müller, Detlef; Burton, Sharon; Hostetler, Chris; Ferrare, Richard
We present the results of a comparison study in which a simple, automated, and unsupervised algorithm, which we call the arrange and average algorithm, was used to infer microphysical parameters (complex refractive index (CRI), effective radius, total number, surface area, and volume concentrations) of atmospheric aerosol particles. The algorithm normally uses backscatter coefficients (β) at 355, 532, and 1064 nm and extinction coefficients (α) at 355 and 532 nm as input information. We compared the performance of the algorithm for the existing "3β+α" and potential "3β+3α" configurations of a multiwavelength aerosol Raman lidar or highspectral-resolution lidar (HSRL). The "3β+3α" configuration uses an extra extinction coefficient at 1064 nm. Testing of the algorithm is based on synthetic optical data that are computed from prescribed CRIs and monomodal logarithmically normal particle size distributions that represent spherical, primarily fine mode aerosols. We investigated the degree to which the microphysical results retrieved by this algorithm benefits from the increased number of input extinction coefficients.
Talianu, Camelia; Labzovskii, Lev; Toanca, Florica
This paper presents a new method to retrieve the aerosol complex refractive index and effective radius from multiwavelength lidar data, using an integrated model-measurement approach. In the model, aerosols are assumed to be a non-spherical ensemble of internally mixed components, with variable proportions. OPAC classification schemes and basic components are used to calculate the microphysical properties, which are then fed into the T-matrix calculation code to generate the corresponding optical parameters. Aerosol intensive parameters (lidar ratios, extinction and backscatter Angstrom coefficients, and linear particle depolarization ratios) are computed at the altitude of the aerosol layers determined from lidar measurements, and iteratively compared to the values obtained by simulation for a certain aerosol type, for which the critical component's proportion in the overall mixture is varied. Microphysical inversion based on the Truncated Singular Value Decomposition (TSVD) algorithm is performed for selected cases of spherical aerosols, and comparative results of the two methods are shown. Keywords: Lidar, aerosols, Data inversion, Optical parameters, Complex Refractive Index Acknowledgments: This work has been supported by grants of the Romanian National Authority for Scientific Research, Programme for Research- Space Technology and Advanced Research - STAR, project numbers 38/2012 - CAPESA and 55/2013 - CARESSE, and by the European Community's FP7-INFRASTRUCTURES-2010-1 under grant no. 262254 - ACTRIS and by the European Community's FP7-PEOPLE-2011-ITN under grant no. 289923 - ITARS
Remer, L. A.; Kaufman, Y. J.; Tanre, D.
The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, complementing field and modeling efforts to produce a comprehensive picture of aerosol characteristics. The three years of Terra-MODIS data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the MODIS aerosol optical thickness retrievals are accurate to within the pre-launch expectations. MODIS-derived size parameters are also compared with AERONET retrievals and found to agree well for fine-mode dominated aerosol regimes. Aerosol regimes dominated by dust aerosol are less accurate, attributed to what is thought to be nonsphericity. Errors due to nonsphericity will be reduced by introducing a new set of empirical phase functions, derived without any assumptions of particle shape. The major innovation that MODIS bring to the field of remote sensing of aerosol is the measure of particle size and the separation of finemode and coarsemode dominated aerosol regimes. Particle size can separate finemode man-made aerosols created during combustion, from larger natural aerosols originating from salt spray or wind erosion. This separation allows for the calculation of aerosol radiative effect and the estimation of the man-made aerosol radiative forcing. MODIS can also be used in regional studies of aerosol-cloud interaction that affect the global radiative and hydrological cycles.
Loria-Salazar, S. Marcela
The aim of the present work is to carry out a detailed analysis of ground and columnar aerosol properties obtained by in-situ Photoacoustic and Integrated Nephelometer (PIN), Cimel CE-318 sunphotometer and MODIS instrument onboard Aqua and Terra satellites, for semi-arid Reno, Nevada, USA in the local summer months of 2012. Satellite determination of local aerosol pollution is desirable because of the potential for broad spatial and temporal coverage. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging because of the underlying surface albedo being heterogeneous in space and time. Therefore, comparisons of satellite retrievals with measurements from ground-based sun photometers are crucial for validation, testing, and further development of instruments and retrieval algorithms. Ground-based sunphotometry and in-situ ground observations show that seasonal weather changes and fire plumes have great influence on the atmosphere aerosol optics. The Apparent Optical Height (AOH) follows the shape of the development of the Convective Boundary Layer (CBL) when fire conditions were not present. However, significant fine particle optical depth was inferred beyond the CBL thereby complicating the use of remote sensing measurements for near-ground aerosol pollution measurements. A meteorological analysis was performed to help diagnose the nature of the aerosols above Reno. The calculation of a Zephyr index and back trajectory analysis demonstrated that a local circulation often induces aerosol transport from Northern CA over the Sierra Nevada Mountains that doubles the Aerosol Optical Depth (AOD) at 500 nm. Sunphotometer measurements were used as a `ground truth' for satellite retrievals to evaluate the current state of the science retrievals in this challenging location. Satellite retrieved for AOD showed the presence of wild fires in Northern CA during August. AOD retrieved using the
Yang, Chao; Qian, Jianliang; Schirotzek, Andre; Maia, Filipe; Marchesini, Stefano
Ptychography promises diffraction limited resolution without the need for high resolution lenses. To achieve high resolution one has to solve the phase problem for many partially overlapping frames. Here we review some of the existing methods for solving ptychographic phase retrieval problem from a numerical analysis point of view, and propose alternative methods based on numerical optimization.
For ten years the MODIS aerosol algorithm has been applied to measured MODIS radiances to produce a continuous set of aerosol products, over land and ocean. The MODIS aerosol products are widely used by the scientific and applied science communities for variety of purposes that span operational air quality forecasting in estimates o[ clear-sky direct radiative effects over ocean and aerosol-cloud interactions. The products undergo continual evaluation, including self-consistency checks and comparisons with highly accurate ground-based instruments. The result of these evaluation exercises is a quantitative understanding of the strengths and weaknesses of the retrieval, where and when the products are accurate and the situations where and when accuracy degrades. We intend 10 present results of the most recent critical evaluations including the first comparison of the over ocean products against the shipboard aerosol optical depth measurements of the Marine Aerosol Network (MAN), the demonstration of the lack of sensitivity to size parameter in the over land products and identification of residual problems and regional issues. While the current data set is undergoing evaluation, we are preparing for the next data processing, labeled Collection 6. Collection 6 will include transparent Quality Flags, a 3 km aerosol product and the 500m resolution cloud mask used within the aerosol n:bicvu|. These new products and adjustments to algorithm assumptions should provide users with more options and greater control, as they adapt the product for their own purposes.
Several algorithms have been used to retrieve surface soil moisture from brightness temperature observations provided by low frequency microwave satellite sensors such as the Advanced Microwave Scanning Radiometer on NASA EOS satellite Aqua (AMSR-E). Most of these algorithms have originated from the...
Hsu, Nai-Yung; Tsay, Si-Chee; King, M. D.; Herman, J. R.
Mineral aerosols (dust) play an important role in both climate forcing and oceanic productivity throughout the entire year. Due to the relatively short lifetime (a few hours to about a week), the distributions of these airborne dust particles vary extensively in both space and time. Consequently, satellite observations are needed over both source and sink regions for continuous temporal and spatial sampling of dust properties. However, despite their importance, the high spatial resolution satellite measurements of dust near its source have been lacking. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, sinre the stirfare reflectance nver land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments.
Thorsen, Tyler J.; Fu, Qiang; Newsom, Rob K.; Turner, David D.; Comstock, Jennifer M.
A Feature detection and EXtinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement (ARM) program’s Raman lidar (RL) has been developed. Presented here is part 1 of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitro-gen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio— to identify features using range-dependent detection thresholds. FEX is designed to be context-sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities pro-vides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically-thin features containing non-spherical particles such as cirrus clouds. Improve-ments over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia site. While we focus on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.
She, Lu; Xue, Yong; Guang, Jie; Di, Aojie
In the present study we proposed an algorithm to estimate hourly Aerosol Optical Depth (AOD) using multi-temporal data from SEVIRI aboard Meteosat Second Generation (MSG). The algorithm coupled a Radiative Transfer Model with Ross-Li-sparse bidirectional reflectance factor (BRF) to calculate the AOD and bidirectional reflectance simultaneously using the visible and near-infrared (NIR) channel of SEVIRI data. We assume the surface albedo doesn't vary over a short time (e.g. 1 day), and a κ-ratio approach was used which assumes the ratio of surface reflectance in the visible and NIR channel for two observations is the same. In the inversion, the MODIS product (MCD43) was used as the prior information of the surface reflectance and the single scattering albedo (SSA) and asymmetry factor (g) were derived from six pre-defined aerosol types. The retrieved AOD and AngstrÖm exponent α were compared with Aerosol Robotic Network (AERONET) measurements, which shows good consistency.
Bruegge, Carol J.; Halthore, Rangasayi N.; Markham, Brian; Spanner, Michael; Wrigley, Robert
The aerosol optical depth over the Konza Prairie, near Manhattan, Kansas, was recorded at various locations by five separate teams. These measurements were made in support of the First ISLSCP Field Experiment (FIFE) and used to correct imagery from a variety of satellite and aircraft sensors for the effects of atmospheric scattering and absorption. The results from one instrument are reported here for 26 days in 1987 and for 7 in 1989. Daily averages span a range of 0.05 to 0.28 in the midvisible wavelengths. In addition, diurnal variations are noted in which the afternoon optical depths are greater than those of the morning by as much as 0.07. A comparison between instruments and processing techniques used to determine these aerosol optical depths is provided. The first comparisons are made using summer 1987 data. Differences of as much as 0.05 (midvisible) are observed. Although these data allow reasonable surface reflectance retrievals, they do not agree to within the performance limits typically associated with these types of instruments. With an accuracy goal of 0.02 a preseason calibration/comparison experiment was conducted at a mountain site prior to the final field campaign in 1989. Good calibration data were obtained, and good agreement (0.01, midvisible) was observed in the retrieved optical depth acquired over the Konza. By comparing data from the surface instruments at different locations, spatial inhomogeneities are determined. Then, data from the airborne tracking sunphotometer allow one to determine variations as a function of altitude. Finally, a technique is proposed for using the in situ data to establish an instrument calibration.
Tanelli, Simone; Sacco, Gian Franco; Durden, Stephen L.; Haddad, Ziad S.
In this presentation we will discuss the performance of classification and retrieval algorithms for spaceborne cloud and precipitation radars such as the Global Precipitation Measurement mission Dual-frequency Precipitation Radar (GPM/DPR), and notional radar for the Aerosol/Clouds/Ecosystem (ACE) mission and related concepts. Spaceborne radar measurements are simulated either from Airborne Precipitation Radar 2nd Generation observations, or from atmospheric model outputs via instrument simulators contained in the NASA Earth Observing Systems Simulators Suite (NEOS(sup 3)). Both methods account for the three dimensional nature of the scattering field at resolutions smaller than that of the spaceborne radar under consideration. We will focus on the impact of non-homogeneities of the field of hydrometeors within the beam. We will discuss also the performance of methods to identify and mitigate such conditions, and the resulting improvements in retrieval accuracy. The classification and retrieval algorithms analyzed in this study are those derived from APR-2's Suite of Processing and Retrieval Algorithms (ASPRA); here generalized to operate on an arbitrary set of radar configuration parameters to study the expected performance of spaceborne cloud and precipitation radars. The presentation will highlight which findings extend to other algorithm families and which ones do not.
Witek, M. L.; Diner, D. J.; Garay, M. J.; Xu, F.
Satellite remote sensing of aerosols is taking bold steps towards higher spatial resolutions, as evidenced by the newly released MODIS 3 km product and the soon to be released MISR 4.4 km product. Finer horizontal resolution allows for a better aerosol characterization in proximity to clouds—which is important for studying indirect aerosol effects—but also poses additional challenges due to various cloud artifact effects. It is therefore imperative to refine satellite algorithms to correctly interpret aerosol behavior in the proximity of clouds. For instance, MISR aerosol optical depth (AOD) retrievals frequently overestimate AODs in pristine oceanic areas, in particular close to Antarctica, as evidenced by comparison with Maritime Aerosol Network (MAN) observations. We trace the origin of this overestimation to stray light, or veiling light, being scattered more or less uniformly over the camera's field of view and reducing the contrast of the primary image. We found that the MISR-MODIS radiance difference in dark areas correlates with average scene brightness within the whole MISR camera field of view. A simple, single parameter model is proposed to effect the corrections. Collocated MISR/MODIS pixels are used to fit the parameter in the MISR nadir camera. For the off-nadir cameras two alternative approaches are employed that are based on MISR radiances and radiative transfer model calculations. These two methods are prone to higher uncertainties, but suggest somewhat increasing correction values for the longer focal length cameras. Finally, the empirical corrections applied in the operational MISR retrieval algorithm substantially decrease AODs in analyzed cases, and lead to closer agreement with MAN and MODIS, proving the efficacy of the developed procedure.
Bulgin, C. E.; Palmer, P. I.; Merchant, C. J.; Siddans, R.; Poulsen, C.; Grainger, R. G.; Thomas, G.; Carboni, E.; McConnell, C.; Highwood, E.
Radiative forcing contributions from aerosol direct and indirect effects remain one of the most uncertain components of the climate system. Satellite observations of aerosol optical properties offer important constraints on atmospheric aerosols but their sensitivity to prior assumptions must be better characterized before they are used effectively to reduce uncertainty in aerosol radiative forcing. We assess the sensitivity of the Oxford-RAL Aerosol and Cloud (ORAC) optimal estimation retrieval of aerosol optical depth (AOD) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) to a priori aerosol data. SEVIRI is a geostationary satellite instrument centred over Africa and the neighbouring Atlantic Ocean, routinely sampling desert dust and biomass burning outflow from Africa. We quantify the uncertainty in SEVIRI AOD retrievals in the presence of desert dust by comparing retrievals that use prior information from the Optical Properties of Aerosol and Cloud (OPAC) database, with those that use measured aerosol properties during the Dust Outflow and Deposition to the Ocean (DODO) aircraft campaign (August, 2006). We also assess the sensitivity of retrieved AODs to changes in solar zenith angle, and the vertical profile of aerosol effective radius and extinction coefficient input into the retrieval forward model. Currently the ORAC retrieval scheme retrieves AODs for five aerosol types (desert dust, biomass burning, maritime, urban and continental) and chooses the most appropriate AOD based on the cost functions. We generate an improved prior aerosol speciation database for SEVIRI based on a statistical analysis of a Saharan Dust Index (SDI) determined using variances of different brightness temperatures, and organic and black carbon tracers from the GEOS-Chem chemistry transport model. This database is described as a function of season and time of day. We quantify the difference in AODs between those chosen based on prior information from the SDI and GEOS
Smirnov, A.; Holben, B. N.; Sakerin, S.; Kabanov, D.; Slutsker, I.; Remer, L. A.; Kahn, R.; Ignatov, A.; Chin, M.; Diehl, T. L.; Mishchenko, M.; Liu, L.; Kucsera, T. L.; Giles, D.; Eck, T. F.; Torres, O.; Kopelevich, O.
Aerosol optical depth measurements were made in October -December 2004 aboard of R/V Akademik Sergey Vavilov. The cruise area included the Atlantic transect from North Sea to Cape Town and then a crossing in the South Atlantic to Ushuaia, Argentina. The hand-held Microtops II sunphotometer was used to acquire 314 series of measurements spanning 38 days. The sunphotometer was pre-calibrated at the NASA Goddard Space Flight Center against a master sun/sky radiometer instrument of the Aerosol Robotic Network (AERONET). The direct sun measurements were acquired in five spectral channels: 340, 440, 675, 870 and 940 nm. To retrieve aerosol optical depths we applied AERONET processing algorithm (Version 2) to the raw data. Aerosol optical depth values were close to background oceanic conditions (0.04-0.08) in the open oceanic areas not influenced by continental sources. Spectral dependence can be described as almost neutral (Angstrom parameter was less than 0.6), especially in the Southern Atlantic. A notable latitudinal variability of optical depth was observed between 15N and 21S, which was associated with the aerosol transport from Africa. Correlations between optical depth and meteorological parameters were considered and comparison between ship-based measurements and AERONET sites along the cruise track was made. Aerosol optical depths were compared to the global transport model (GOCART) simulations and satellite retrievals from MODIS, MISR, and AVHRR.
Wu, L.; Hasekamp, O.; Van Diedenhoven, B.; Cairns, B.
We investigated the importance of spectral range and angular resolution for aerosol retrieval from multiangle photopolarimetric measurements over land. For this purpose, we use an extensive set of simulated measurements for different spectral ranges and angular resolutions and subsets of real measurements of the airborne Research Scanning Polarimeter (RSP) carried out during the PODEX and SEAC4RS campaigns over the continental USA. Aerosol retrievals performed from RSP measurements show good agreement with ground-based AERONET measurements for aerosol optical depth (AOD), single scattering albedo (SSA) and refractive index. Furthermore, we found that inclusion of shortwave infrared bands (1590 and/or 2250 nm) significantly improves the retrieval of AOD, SSA and coarse mode microphysical properties. However, accuracies of the retrieved aerosol properties do not improve significantly when more than five viewing angles are used in the retrieval.
Kuo, K. S.; Weger, R. C.; Welch, R. M.
Atmospheric aerosol particles, both natural and anthropogenic, are important to the earth's radiative balance through their direct and indirect effects. They scatter the incoming solar radiation (direct effect) and modify the shortwave reflective properties of clouds by acting as cloud condensation nuclei (indirect effect). Although it has been suggested that aerosols exert a net cooling influence on climate, this effect has received less attention than the radiative forcing due to clouds and greenhouse gases. In order to understand the role that aerosols play in a changing climate, detailed and accurate observations are a prerequisite. The retrieval of aerosol optical properties by satellite remote sensing has proven to be a difficult task. The difficulty results mainly from the tenuous nature and variable composition of aerosols. To date, with single-angle satellite observations, we can only retrieve reliably against dark backgrounds, such as over oceans and dense vegetation. Even then, assumptions must be made concerning the chemical composition of aerosols. The best hope we have for aerosol retrievals over bright backgrounds are observations from multiple angles, such as those provided by the MISR and POLDER instruments. In this investigation we examine the feasibility of simultaneous retrieval of multiple aerosol optical parameters using reflectances from a typical set of twelve angles observed by the French POLDER instrument. The retrieved aerosol optical parameters consist of asymmetry factor, single scattering albedo, surface albedo, and optical thickness.
Guo, Changliang; Liu, Shi; Sheridan, John T
The modified iterative phase retrieval algorithms developed in Part I [Guo et al., Appl. Opt.54, 4698 (2015)] are applied to perform known plaintext and ciphertext attacks on amplitude encoding and phase encoding Fourier-transform-based double random phase encryption (DRPE) systems. It is shown that the new algorithms can retrieve the two random phase keys (RPKs) perfectly. The performances of the algorithms are tested by using the retrieved RPKs to decrypt a set of different ciphertexts encrypted using the same RPKs. Significantly, it is also shown that the DRPE system is, under certain conditions, vulnerable to ciphertext-only attack, i.e., in some cases an attacker can decrypt DRPE data successfully when only the ciphertext is intercepted. PMID:26192505
J. THEILER; ET AL
The retrieval of scene properties (surface temperature, material type, vegetation health, etc.) from remotely sensed data is the ultimate goal of many earth observing satellites. The algorithms that have been developed for these retrievals are informed by physical models of how the raw data were generated. This includes models of radiation as emitted and/or rejected by the scene, propagated through the atmosphere, collected by the optics, detected by the sensor, and digitized by the electronics. To some extent, the retrieval is the inverse of this ''forward'' modeling problem. But in contrast to this forward modeling, the practical task of making inferences about the original scene usually requires some ad hoc assumptions, good physical intuition, and a healthy dose of trial and error. The standard MTI data processing pipeline will employ algorithms developed with this traditional approach. But we will discuss some preliminary research on the use of a genetic programming scheme to ''evolve'' retrieval algorithms. Such a scheme cannot compete with the physical intuition of a remote sensing scientist, but it may be able to automate some of the trial and error. In this scenario, a training set is used, which consists of multispectral image data and the associated ''ground truth;'' that is, a registered map of the desired retrieval quantity. The genetic programming scheme attempts to combine a core set of image processing primitives to produce an IDL (Interactive Data Language) program which estimates this retrieval quantity from the raw data.
Theiler, James P.; Harvey, Neal R.; Brumby, Steven P.; Szymanski, John J.; Alferink, Steve; Perkins, Simon J.; Porter, Reid B.; Bloch, Jeffrey J.
The retrieval of scene properties (surface temperature, material type, vegetation health, etc.) from remotely sensed data is the ultimate goal of many earth observing satellites. The algorithms that have been developed for these retrievals are informed by physical models of how the raw data were generated. This includes models of radiation as emitted and/or reflected by the scene, propagated through the atmosphere, collected by the optics, detected by the sensor, and digitized by the electronics. To some extent, the retrieval is the inverse of this 'forward' modeling problem. But in contrast to this forward modeling, the practical task of making inferences about the original scene usually requires some ad hoc assumptions, good physical intuition, and a healthy dose of trial and error. The standard MTI data processing pipeline will employ algorithms developed with this traditional approach. But we will discuss some preliminary research on the use of a genetic programming scheme to 'evolve' retrieval algorithms. Such a scheme cannot compete with the physical intuition of a remote sensing scientist, but it may be able to automate some of the trial and error. In this scenario, a training set is used, which consists of multispectral image data and the associated 'ground truth;' that is, a registered map of the desired retrieval quantity. The genetic programming scheme attempts to combine a core set of image processing primitives to produce an IDL (Interactive Data Language) program which estimates this retrieval quantity from the raw data.
Omar, Ali H.; Winker, David M.; Won, Jae-Gwang
We use measurements and models to develop aerosol models for use in the inversion algorithms for the Cloud Aerosol Lidar and Imager Pathfinder Spaceborne Observations (CALIPSO). Radiance measurements and inversions of the AErosol RObotic NETwork (AERONET1, 2) are used to group global atmospheric aerosols using optical and microphysical parameters. This study uses more than 105 records of radiance measurements, aerosol size distributions, and complex refractive indices to generate the optical properties of the aerosol at more 200 sites worldwide. These properties together with the radiance measurements are then classified using classical clustering methods to group the sites according to the type of aerosol with the greatest frequency of occurrence at each site. Six significant clusters are identified: desert dust, biomass burning, urban industrial pollution, rural background, marine, and dirty pollution. Three of these are used in the CALIPSO aerosol models to characterize desert dust, biomass burning, and polluted continental aerosols. The CALIPSO aerosol model also uses the coarse mode of desert dust and the fine mode of biomass burning to build a polluted dust model. For marine aerosol, the CALIPSO aerosol model uses measurements from the SEAS experiment 3. In addition to categorizing the aerosol types, the cluster analysis provides all the column optical and microphysical properties for each cluster.