Classification of Aerosol Retrievals from Spaceborne Polarimetry Using a Multiparameter Algorithm

NASA Technical Reports Server (NTRS)

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.;

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.

2013-01-01

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.

Use of Multiangle Satellite Observations to Retrieve Aerosol Properties and Ocean Color

NASA Technical Reports Server (NTRS)

Martonchik, John V.; Diner, David; Khan, Ralph

2005-01-01

A new technique is described for retrieving aerosol over ocean water and the associated ocean color using multiangle satellite observations. Unlike current satellite aerosol retrieval algorithms which only utilize observations at red wavelengths and longer, with the assumption that these wavelengths have a negligible ocean (water-leaving radiance), this new algorithm uses all available spectral bands and simultaneously retrieves both aerosol properties and the spectral ocean color. We show some results of case studies using MISR data, performed over different water conditions (coastal water, blooms, and open water).

SEOM's Sentinel-3/OLCI' project CAWA: advanced GRASP aerosol retrieval

NASA Astrophysics Data System (ADS)

Dubovik, Oleg; litvinov, Pavel; Huang, Xin; Aspetsberger, Michael; Fuertes, David; Brockmann, Carsten; Fischer, Jürgen; Bojkov, Bojan

2016-04-01

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.

Investigating the Use of a Simplified Aerosol Parameterization in Space-Based XCO2 Retrievals from OCO-2

NASA Astrophysics Data System (ADS)

Nelson, R. R.; O'Dell, C.

2017-12-01

The primary goal of OCO-2 is to use hyperspectral measurements of reflected near-infrared sunlight to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with high accuracy. This is only possible for measurements of scenes nearly free of optically thick clouds and aerosols. As some cloud or aerosol contamination will always be present, the OCO-2 retrieval algorithm includes clouds and aerosols as retrieved properties in its state vector. Information content analyses demonstrate that there are only 2-6 pieces of information about aerosols in the OCO-2 radiances. However, the upcoming OCO-2 algorithm (B8) attempts to retrieve 9 aerosol parameters; this over-fitting can hinder convergence and produce multiple solutions. In this work, we develop a simplified cloud and aerosol parameterization that intelligently reduces the number of retrieved parameters to 5 by only retrieving information about two aerosol layers: a lower tropospheric layer and an upper tropospheric / stratospheric layer. We retrieve the optical depth of each layer and the height of the lower tropospheric layer. Each of these layers contains a mixture of fine and coarse mode aerosol. In comparisons between OCO-2 XCO2 estimates and validation sources including TCCON, this scheme performs about as well as the more complicated OCO-2 retrieval algorithm, but has the potential benefits of more interpretable aerosol results, faster convergence, less nonlinearity, and greater throughput. We also investigate the dependence of our results on the optical properties of the fine and coarse mode aerosol types, such as their effective radii and the environmental relative humidity.

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of VIIRS, OMPS, and CALIOP Observations

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae

2015-01-01

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.

Characterizing the Vertical Distribution of Aerosols using Ground-based Multiwavelength Lidar Data

NASA Astrophysics Data System (ADS)

Ferrare, R. A.; Thorsen, T. J.; Clayton, M.; Mueller, D.; Chemyakin, E.; Burton, S. P.; Goldsmith, J.; Holz, R.; Kuehn, R.; Eloranta, E. W.; Marais, W.; Newsom, R. K.; Liu, X.; Sawamura, P.; Holben, B. N.; Hostetler, C. A.

2016-12-01

Observations of aerosol optical and microphysical properties are critical for developing and evaluating aerosol transport model parameterizations and assessing global aerosol-radiation impacts on climate. During the Combined HSRL And Raman lidar Measurement Study (CHARMS), we investigated the synergistic use of ground-based Raman lidar and High Spectral Resolution Lidar (HSRL) measurements to retrieve aerosol properties aloft. Continuous (24/7) operation of these co-located lidars during the ten-week CHARMS mission (mid-July through September 2015) allowed the acquisition of a unique, multiwavelength ground-based lidar dataset for studying aerosol properties above the Southern Great Plains (SGP) site. The ARM Raman lidar measured profiles of aerosol backscatter, extinction and depolarization at 355 nm as well as profiles of water vapor mixing ratio and temperature. The University of Wisconsin HSRL simultaneously measured profiles of aerosol backscatter, extinction and depolarization at 532 nm and aerosol backscatter at 1064 nm. Recent advances in both lidar retrieval theory and algorithm development demonstrate that vertically-resolved retrievals using such multiwavelength lidar measurements of aerosol backscatter and extinction can help constrain both the aerosol optical (e.g. complex refractive index, scattering, etc.) and microphysical properties (e.g. effective radius, concentrations) as well as provide qualitative aerosol classification. Based on this work, the NASA Langley Research Center (LaRC) HSRL group developed automated algorithms for classifying and retrieving aerosol optical and microphysical properties, demonstrated these retrievals using data from the unique NASA/LaRC airborne multiwavelength HSRL-2 system, and validated the results using coincident airborne in situ data. We apply these algorithms to the CHARMS multiwavelength (Raman+HSRL) lidar dataset to retrieve aerosol properties above the SGP site. We present some profiles of aerosol effective radius and concentration retrieved from the CHARMS data and compare column-average aerosol properties derived from the multiwavelength lidar aerosol retrievals to corresponding values retrieved from AERONET measurements.

V2.1.4 L2AS Detailed Release Description September 27, 2001

Atmospheric Science Data Center

2013-03-14

... 27, 2001 Algorithm Changes Change method of selecting radiance pixels to use in aerosol retrieval over ... het. surface retrieval algorithm over areas of 100% dark water. Modify algorithm for selecting a default aerosol model to use in ...

The performance of Yonsei CArbon Retrieval (YCAR) algorithm with improved aerosol information using GOSAT measurements over East Asia

NASA Astrophysics Data System (ADS)

Jung, Y.; Kim, J.; Kim, W.; Boesch, H.; Yoshida, Y.; Cho, C.; Lee, H.; Goo, T. Y.

2016-12-01

The Greenhouse Gases Observing SATellite (GOSAT) is the first satellite dedicated to measure atmospheric CO2 concentrations from space that can able to improve our knowledge about carbon cycle. Several studies have performed to develop the CO2 retrieval algorithms using GOSAT measurements, but limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. In this study, we develop the Yonsei CArbon Retrieval (YCAR) algorithm based on optimal estimation method to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) and the aerosol top height used to cause significant errors in retrieved XCO2 up to 2.5 ppm. Since this bias comes from a rough assumption of aerosol information in the forward model used in CO2 retrieval process, the YCAR algorithm improves the process to take into account AOPs as well as aerosol vertical distribution; total AOD and the fine mode fraction (FMF) are obtained from the ground-based measurements closely located, and other parameters are obtained from a priori information. Comparing to ground-based XCO2 measurements, the YCAR XCO2 product has a bias of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, showing lower biases and higher correlations rather than the GOSAT standard products. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties.

Vertical profiles of aerosol optical properties and the solar heating rate estimated by combining sky radiometer and lidar measurements

NASA Astrophysics Data System (ADS)

Kudo, Rei; Nishizawa, Tomoaki; Aoyagi, Toshinori

2016-07-01

The SKYLIDAR algorithm was developed to estimate vertical profiles of aerosol optical properties from sky radiometer (SKYNET) and lidar (AD-Net) measurements. The solar heating rate was also estimated from the SKYLIDAR retrievals. The algorithm consists of two retrieval steps: (1) columnar properties are retrieved from the sky radiometer measurements and the vertically mean depolarization ratio obtained from the lidar measurements and (2) vertical profiles are retrieved from the lidar measurements and the results of the first step. The derived parameters are the vertical profiles of the size distribution, refractive index (real and imaginary parts), extinction coefficient, single-scattering albedo, and asymmetry factor. Sensitivity tests were conducted by applying the SKYLIDAR algorithm to the simulated sky radiometer and lidar data for vertical profiles of three different aerosols, continental average, transported dust, and pollution aerosols. The vertical profiles of the size distribution, extinction coefficient, and asymmetry factor were well estimated in all cases. The vertical profiles of the refractive index and single-scattering albedo of transported dust, but not those of transported pollution aerosol, were well estimated. To demonstrate the performance and validity of the SKYLIDAR algorithm, we applied the SKYLIDAR algorithm to the actual measurements at Tsukuba, Japan. The detailed vertical structures of the aerosol optical properties and solar heating rate of transported dust and smoke were investigated. Examination of the relationship between the solar heating rate and the aerosol optical properties showed that the vertical profile of the asymmetry factor played an important role in creating vertical variation in the solar heating rate. We then compared the columnar optical properties retrieved with the SKYLIDAR algorithm to those produced with the more established scheme SKYRAD.PACK, and the surface solar irradiance calculated from the SKYLIDAR retrievals was compared with pyranometer measurement. The results showed good agreements: the columnar values of the SKYLIDAR retrievals agreed with reliable SKYRAD.PACK retrievals, and the SKYLIDAR retrievals were sufficiently accurate to evaluate the surface solar irradiance.

The Role of Cloud Contamination, Aerosol Layer Height and Aerosol Model in the Assessment of the OMI Near-UV Retrievals Over the Ocean

NASA Technical Reports Server (NTRS)

Gasso, Santiago; Torres, Omar

2016-01-01

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 less than 0.3, 30% for AOD greater than 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 approximately less than 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 (less than 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 retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

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

NASA Astrophysics Data System (ADS)

Wurl, D.; Grainger, R. G.; McDonald, A. J.; Deshler, T.

2010-05-01

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

Comparative Analysis of Aerosol Retrievals from MODIS, OMI and MISR Over Sahara Region

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Hsu, C.; Terres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, S.

2011-01-01

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.

Development of a generalized algorithm of satellite remote sensing using multi-wavelength and multi-pixel information (MWP method) for aerosol properties by satellite-borne imager

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Morimoto, S.; Takenaka, H.

2014-12-01

We have developed a new satellite remote sensing algorithm to retrieve the aerosol optical characteristics using multi-wavelength and multi-pixel information of satellite imagers (MWP method). In this algorithm, the inversion method is a combination of maximum a posteriori (MAP) method (Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, with the progress of computing technique, this method has being combined with the direct radiation transfer calculation numerically solved by each iteration step of the non-linear inverse problem, without using LUT (Look Up Table) with several constraints.Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area.We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. The result of the experiment showed that AOTs of fine mode and coarse mode, soot fraction and ground surface albedo are successfully retrieved within expected accuracy. We discuss the accuracy of the algorithm for various land surface types. Then, we applied this algorithm to GOSAT/CAI imager data, and we compared retrieved and surface-observed AOTs at the CAI pixel closest to an AERONET (Aerosol Robotic Network) or SKYNET site in each region. Comparison at several sites in urban area indicated that AOTs retrieved by our method are in agreement with surface-observed AOT within ±0.066.Our future work is to extend the algorithm for analysis of AGEOS-II/GLI and GCOM/C-SGLI data.

Evaluation of Long-term Aerosol Data Records from SeaWiFS over Land and Ocean

NASA Astrophysics Data System (ADS)

Bettenhausen, C.; Hsu, C.; Jeong, M.; Huang, J.

2010-12-01

Deserts around the globe produce mineral dust aerosols that may then be transported over cities, across continents, or even oceans. These aerosols affect the Earth’s energy balance through direct and indirect interactions with incoming solar radiation. They also have a biogeochemical effect as they deliver scarce nutrients to remote ecosystems. Large dust storms regularly disrupt air traffic and are a general nuisance to those living in transport regions. In the past, measuring dust aerosols has been incomplete at best. Satellite retrieval algorithms were limited to oceans or vegetated surfaces and typically neglected desert regions due to their high surface reflectivity in the mid-visible and near-infrared wavelengths, which have been typically used for aerosol retrievals. The Deep Blue aerosol retrieval algorithm was developed to resolve these shortcomings by utilizing the blue channels from instruments such as the Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) to infer aerosol properties over these highly reflective surfaces. The surface reflectivity of desert regions is much lower in the blue channels and thus it is easier to separate the aerosol and surface signals than at the longer wavelengths used in other algorithms. More recently, the Deep Blue algorithm has been expanded to retrieve over vegetated surfaces and oceans as well. A single algorithm can now follow dust from source to sink. In this work, we introduce the SeaWiFS instrument and the Deep Blue aerosol retrieval algorithm. We have produced global aerosol data records over land and ocean from 1997 through 2009 using the Deep Blue algorithm and SeaWiFS data. We describe these data records and validate them with data from the Aerosol Robotic Network (AERONET). We also show the relative performance compared to the current MODIS Deep Blue operational aerosol data in desert regions. The current results are encouraging and this dataset will be useful to future studies in understanding the effects of dust aerosols on global processes, long-term aerosol trends, quantifying dust emissions, transport, and inter-annual variability.

An operational retrieval algorithm for determining aerosol optical properties in the ultraviolet

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; L'Ecuyer, Tristan S.; Slusser, James R.; Stephens, Graeme L.; Goering, Christian D.

2008-02-01

This paper describes a number of practical considerations concerning the optimization and operational implementation of an algorithm used to characterize the optical properties of aerosols across part of the ultraviolet (UV) spectrum. The algorithm estimates values of aerosol optical depth (AOD) and aerosol single scattering albedo (SSA) at seven wavelengths in the UV, as well as total column ozone (TOC) and wavelength-independent asymmetry factor (g) using direct and diffuse irradiances measured with a UV multifilter rotating shadowband radiometer (UV-MFRSR). A novel method for cloud screening the irradiance data set is introduced, as well as several improvements and optimizations to the retrieval scheme which yield a more realistic physical model for the inversion and increase the efficiency of the algorithm. Introduction of a wavelength-dependent retrieval error budget generated from rigorous forward model analysis as well as broadened covariances on the a priori values of AOD, SSA and g and tightened covariances of TOC allows sufficient retrieval sensitivity and resolution to obtain unique solutions of aerosol optical properties as demonstrated by synthetic retrievals. Analysis of a cloud screened data set (May 2003) from Panther Junction, Texas, demonstrates that the algorithm produces realistic values of the optical properties that compare favorably with pseudo-independent methods for AOD, TOC and calculated Ångstrom exponents. Retrieval errors of all parameters (except TOC) are shown to be negatively correlated to AOD, while the Shannon information content is positively correlated, indicating that retrieval skill improves with increasing atmospheric turbidity. When implemented operationally on more than thirty instruments in the Ultraviolet Monitoring and Research Program's (UVMRP) network, this retrieval algorithm will provide a comprehensive and internally consistent climatology of ground-based aerosol properties in the UV spectral range that can be used for both validation of satellite measurements as well as regional aerosol and ultraviolet transmission studies.

The Time Series Technique for Aerosol Retrievals over Land from MODIS: Algorithm MAIAC

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Wang, Yujie

2008-01-01

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 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.

An Alternative Retrieval Algorithm for the Ozone Mapping and Profiler Suite Limb Profiler

DTIC Science & Technology

2012-05-01

behavior of aerosol extinction from the upper troposphere through the stratosphere is critical for retrieving ozone in this region. Aerosol scattering is......include area code) b. ABSTRACT c. THIS PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT An Alternative Retrieval Algorithm for the Ozone Mapping and

New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water

NASA Astrophysics Data System (ADS)

Witek, Marcin L.; Garay, Michael J.; Diner, David J.; Bull, Michael A.; Seidel, Felix C.

2018-01-01

A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, best estimate AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥ 0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

New Approach to the Retrieval of AOD and its Uncertainty from MISR Observations Over Dark Water

NASA Astrophysics Data System (ADS)

Witek, M. L.; Garay, M. J.; Diner, D. J.; Bull, M. A.; Seidel, F.

2017-12-01

A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous Version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture, then used a combination of these values to compute the final, "best estimate" AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of a) the absolute values of the cost functions for each aerosol mixture, b) the widths of the cost function distributions as a function of AOD, and c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on arbitrary thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new Aerosol Retrieval Confidence Index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

a New Algorithm for the Aod Inversion from Noaa/avhrr Data

NASA Astrophysics Data System (ADS)

Sun, L.; Li, R.; Yu, H.

2018-04-01

The advanced very high resolution radiometer (AVHRR) data from the National Oceanic and Atmospheric Administration satellite is one of the earliest data applied in aerosol research. The dense dark vegetation (DDV) algorithm is a popular method for the present land aerosol retrieval. One of the most crucial steps in the DDV algorithm with AVHRR data is estimating the land surface reflectance (LSR). However, LSR cannot be easily estimated because of the lack of a 2.13 μm band. In this article, the moderate resolution imaging spectroradiometer (MODIS) vegetation index product (MYD13) is introduced to support the estimation of AVHRR LSR. The relationship between MODIS NDVI and the AVHRR LSR of the visible band is analysed to retrieve aerosol optical depth (AOD) from AVHRR data. Retrieval experiments are carried out in mid-eastern America. The AOD data from AErosol RObotic NETwork (AERONET) measurements are used to evaluate the aerosol retrieval from AVHRR data, the results indicate that about 74 % of the retrieved AOD are within the expected error range of ±(0.05 + 0.2), and a cross comparison of the AOD retrieval results with the MODIS aerosol product (MYD04) shows that the AOD datasets have a similar spatial distribution.

Aerosol Airmass Type Mapping Over the Urban Mexico City Region From Space-based Multi-angle Imaging

NASA Technical Reports Server (NTRS)

Patadia, F.; Kahn, R. A.; Limbacher, J. A.; Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.

2013-01-01

Using Multi-angle Imaging SpectroRadiometer (MISR) and sub-orbital measurements from the 2006 INTEX-B/MILAGRO field campaign, in this study we explore MISR's ability to map different aerosol air mass types over the Mexico City metropolitan area. The aerosol air mass distinctions are based on shape, size and single scattering albedo retrievals from the MISR Research Aerosol Retrieval algorithm. In this region, the research algorithm identifies dust-dominated aerosol mixtures based on non-spherical particle shape, whereas spherical biomass burning and urban pollution particles are distinguished by particle size. Two distinct aerosol air mass types based on retrieved particle microphysical properties, and four spatially distributed aerosol air masses, are identified in the MISR data on 6 March 2006. The aerosol air mass type identification results are supported by coincident, airborne high-spectral-resolution lidar (HSRL) measurements. Aerosol optical depth (AOD) gradients are also consistent between the MISR and sub-orbital measurements, but particles having single-scattering albedo of approx. 0.7 at 558 nm must be included in the retrieval algorithm to produce good absolute AOD comparisons over pollution-dominated aerosol air masses. The MISR standard V22 AOD product, at 17.6 km resolution, captures the observed AOD gradients qualitatively, but retrievals at this coarse spatial scale and with limited spherical absorbing particle options underestimate AOD and do not retrieve particle properties adequately over this complex urban region. However, we demonstrate how AOD and aerosol type mapping can be accomplished with MISR data over complex urban regions, provided the retrieval is performed at sufficiently high spatial resolution, and with a rich enough set of aerosol components and mixtures.

Atmospheric correction over case 2 waters with an iterative fitting algorithm: relative humidity effects.

PubMed

Land, P E; Haigh, J D

1997-12-20

In algorithms for the atmospheric correction of visible and near-IR satellite observations of the Earth's surface, it is generally assumed that the spectral variation of aerosol optical depth is characterized by an Angström power law or similar dependence. In an iterative fitting algorithm for atmospheric correction of ocean color imagery over case 2 waters, this assumption leads to an inability to retrieve the aerosol type and to the attribution to aerosol spectral variations of spectral effects actually caused by the water contents. An improvement to this algorithm is described in which the spectral variation of optical depth is calculated as a function of aerosol type and relative humidity, and an attempt is made to retrieve the relative humidity in addition to aerosol type. The aerosol is treated as a mixture of aerosol components (e.g., soot), rather than of aerosol types (e.g., urban). We demonstrate the improvement over the previous method by using simulated case 1 and case 2 sea-viewing wide field-of-view sensor data, although the retrieval of relative humidity was not successful.

Validation and Comparison of AATRS AOD L2 Products over China

NASA Astrophysics Data System (ADS)

Che, Yahui; Xue, Yong; Guang, Jie; Guo, Jianping; Li, Ying

2016-04-01

The Advanced Along-Track Scanning Radiometer (AATSR) aboard on ENVISAT has been used to observe the Earth for more than 10 years since than 2002. One of main applications of AATSR instrument is to observe atmospheric aerosol, especially in retrieval of aerosol optical depth (AOD), taking advantage of its dual-view that helps to separate the contribution of aerosol from top of atmosphere reflectance (A. A. Kokhanovsky and de Leeuw, 2009). The project of Aerosol_CCI, as part of European Space Agency's Climate Change Initiative (CCI), has released new AATSR aerosol AOD products by the of 2015, including the SU v4.21 product from Swansea algorithm, ADV v2.3 product from the ATSR-2/AATSR dual view aerosol retrieval algorithm (ADV) and ORAC v03.04 product from the Oxford-RAL Retrieval of Aerosol and Cloud algorithm. The previous versions of these three AOD level 2 (L2) products in 2008 have been validated over mainland China (Che and Xue, 2015). In this paper, we validated these AATSR AOD products with latest versions in mainland China in 2007, 2008 and 2010 by the means of comparison with the AErosol RObotic NETwork (AERONET) and the China Aerosol Remote Sensing Network (CARSNET). The combination of AERONET and CARSNET helps to make up for the disadvantages of small number and uneven distribution of AEROENT cites. The validation results show different performance of these AOD products over China. The performances of SU and ADV products seem to be the same with close correlation coefficient (CC) about 08~0.9 and root mean square (RMS) within 0.15 in all three years, and sensitive to high AOD values (AOD >1): more AODs and more underestimated. However, these two products do exist difference, which is that the SU algorithm retrieves more high AODs, leading to more space-time validation matches with ground-based data. The ORAC algorithm is different from the others, it can be not only used to retrieve low AODs but also high AODs over different landcover types. Even though ORAC algorithm has ability in retrieving AODs in different values, it shows largest uncertainty in retrieving different AODs.

A Simple and Universal Aerosol Retrieval Algorithm for Landsat Series Images Over Complex Surfaces

NASA Astrophysics Data System (ADS)

Wei, Jing; Huang, Bo; Sun, Lin; Zhang, Zhaoyang; Wang, Lunche; Bilal, Muhammad

2017-12-01

Operational aerosol optical depth (AOD) products are available at coarse spatial resolutions from several to tens of kilometers. These resolutions limit the application of these products for monitoring atmospheric pollutants at the city level. Therefore, a simple, universal, and high-resolution (30 m) Landsat aerosol retrieval algorithm over complex urban surfaces is developed. The surface reflectance is estimated from a combination of top of atmosphere reflectance at short-wave infrared (2.22 μm) and Landsat 4-7 surface reflectance climate data records over densely vegetated areas and bright areas. The aerosol type is determined using the historical aerosol optical properties derived from the local urban Aerosol Robotic Network (AERONET) site (Beijing). AERONET ground-based sun photometer AOD measurements from five sites located in urban and rural areas are obtained to validate the AOD retrievals. Terra MODerate resolution Imaging Spectrometer Collection (C) 6 AOD products (MOD04) including the dark target (DT), the deep blue (DB), and the combined DT and DB (DT&DB) retrievals at 10 km spatial resolution are obtained for comparison purposes. Validation results show that the Landsat AOD retrievals at a 30 m resolution are well correlated with the AERONET AOD measurements (R2 = 0.932) and that approximately 77.46% of the retrievals fall within the expected error with a low mean absolute error of 0.090 and a root-mean-square error of 0.126. Comparison results show that Landsat AOD retrievals are overall better and less biased than MOD04 AOD products, indicating that the new algorithm is robust and performs well in AOD retrieval over complex surfaces. The new algorithm can provide continuous and detailed spatial distributions of AOD during both low and high aerosol loadings.

Multiangle Imaging Spectroradiometer (MISR) Global Aerosol Optical Depth Validation Based on 2 Years of Coincident Aerosol Robotic Network (AERONET) Observations

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Gaitley, Barbara J.; Martonchik, John V.; Diner, David J.; Crean, Kathleen A.; Holben, Brent

2005-01-01

Performance of the Multiangle Imaging Spectroradiometer (MISR) early postlaunch aerosol optical thickness (AOT) retrieval algorithm is assessed quantitatively over land and ocean by comparison with a 2-year measurement record of globally distributed AERONET Sun photometers. There are sufficient coincident observations to stratify the data set by season and expected aerosol type. In addition to reporting uncertainty envelopes, we identify trends and outliers, and investigate their likely causes, with the aim of refining algorithm performance. Overall, about 2/3 of the MISR-retrieved AOT values fall within [0.05 or 20% x AOT] of Aerosol Robotic Network (AERONET). More than a third are within [0.03 or 10% x AOT]. Correlation coefficients are highest for maritime stations (approx.0.9), and lowest for dusty sites (more than approx.0.7). Retrieved spectral slopes closely match Sun photometer values for Biomass burning and continental aerosol types. Detailed comparisons suggest that adding to the algorithm climatology more absorbing spherical particles, more realistic dust analogs, and a richer selection of multimodal aerosol mixtures would reduce the remaining discrepancies for MISR retrievals over land; in addition, refining instrument low-light-level calibration could reduce or eliminate a small but systematic offset in maritime AOT values. On the basis of cases for which current particle models are representative, a second-generation MISR aerosol retrieval algorithm incorporating these improvements could provide AOT accuracy unprecedented for a spaceborne technique.

Sensitivity of Multiangle Imaging to the Optical and Microphysical Properties of Biomass Burning Aerosols

NASA Technical Reports Server (NTRS)

Chen, Wei-Ting; Kahn, Ralph A.; Nelson, David; Yau, Kevin; Seinfeld, John H.

2008-01-01

The treatment of biomass burning (BB) carbonaceous particles in the Multiangle Imaging SpectroRadiometer (MISR) Standard Aerosol Retrieval Algorithm is assessed, and algorithm refinements are suggested, based on a theoretical sensitivity analysis and comparisons with near-coincident AERONET measurements at representative BB sites. Over the natural ranges of BB aerosol microphysical and optical properties observed in past field campaigns, patterns of retrieved Aerosol Optical Depth (AOD), particle size, and single scattering albedo (SSA) are evaluated. On the basis of the theoretical analysis, assuming total column AOD of 0.2, over a dark, uniform surface, MISR can distinguish two to three groups in each of size and SSA, except when the assumed atmospheric particles are significantly absorbing (mid-visible SSA approx.0.84), or of medium sizes (mean radius approx.0.13 pin); sensitivity to absorbing, medium-large size particles increases considerably when the assumed column AOD is raised to 0.5. MISR Research Aerosol Retrievals confirm the theoretical results, based on coincident AERONET inversions under BB-dominated conditions. When BB is externally mixed with dust in the atmosphere, dust optical model and surface reflection uncertainties, along with spatial variability, contribute to differences between the Research Retrievals and AERONET. These results suggest specific refinements to the MISR Standard Aerosol Algorithm complement of component particles and mixtures. They also highlight the importance for satellite aerosol retrievals of surface reflectance characterization, with accuracies that can be difficult to achieve with coupled surface-aerosol algorithms in some higher AOD situations.

The potential of LIRIC to validate the vertical profiles of the aerosol mass concentration estimated by an air quality model

NASA Astrophysics Data System (ADS)

Siomos, Nikolaos; Filoglou, Maria; Poupkou, Anastasia; Liora, Natalia; Dimopoulos, Spyros; Melas, Dimitris; Chaikovsky, Anatoli; Balis, Dimitris

2015-04-01

Vertical profiles of the aerosol mass concentration derived by a retrieval algorithm that uses combined sunphotometer and LIDAR data (LIRIC) were used in order to validate the mass concentration profiles estimated by the air quality model CAMx. LIDAR and CIMEL measurements of the Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki were used for this validation.The aerosol mass concentration profiles of the fine and coarse mode derived by CAMx were compared with the respective profiles derived by the retrieval algorithm. For the coarse mode particles, forecasts of the Saharan dust transportation model BSC-DREAM8bV2 were also taken into account. Each of the retrieval algorithm's profiles were matched to the models' profile with the best agreement within a time window of four hours before and after the central measurement. OPAC, a software than can provide optical properties of aerosol mixtures, was also employed in order to calculate the angstrom exponent and the lidar ratio values for 355nm and 532nm for each of the model's profiles aiming in a comparison with the angstrom exponent and the lidar ratio values derived by the retrieval algorithm for each measurement. The comparisons between the fine mode aerosol concentration profiles resulted in a good agreement between CAMx and the retrieval algorithm, with the vertical mean bias error never exceeding 7 μgr/m3. Concerning the aerosol coarse mode concentration profiles both CAMx and BSC-DREAM8bV2 values are severely underestimated, although, in cases of Saharan dust transportation events there is an agreement between the profiles of BSC-DREAM8bV2 model and the retrieval algorithm.

MAX-DOAS retrieval of aerosol extinction properties in Madrid, Spain

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Cuevas, Carlos A.; Frieß, Udo; Saiz-Lopez, Alfonso

2017-04-01

We present Multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements performed in the urban environment of Madrid, Spain, from March to September 2015. The O4 absorption in the ultraviolet (UV) spectral region was used to retrieve the aerosol extinction profile using an inversion algorithm. The results show a good agreement between the hourly retrieved aerosol optical depth (AOD) and the correlative Aerosol Robotic Network (AERONET) product. Higher AODs are found in the summer season due to the more frequent occurrence of Saharan dust intrusions. The surface aerosol extinction coefficient as retrieved by the MAX-DOAS measurements was also compared to in situ PM2:5 concentrations. The level of agreement between both measurements indicates that the MAX-DOAS retrieval has the ability to characterize the extinction of aerosol particles near the surface. The retrieval algorithm was also used to study a case of severe dust intrusion on 12 May 2015. The capability of the MAX-DOAS retrieval to recognize the dust event including an elevated particle layer is investigated along with air mass back-trajectory analysis.

[A review of atmospheric aerosol research by using polarization remote sensing].

PubMed

Guo, Hong; Gu, Xing-Fa; Xie, Dong-Hai; Yu, Tao; Meng, Qing-Yan

2014-07-01

In the present paper, aerosol research by using polarization remote sensing in last two decades (1993-2013) was reviewed, including aerosol researches based on POLDER/PARASOL, APS(Aerosol Polarimetry Sensor), Polarized Airborne camera and Ground-based measurements. We emphasize the following three aspects: (1) The retrieval algorithms developed for land and marine aerosol by using POLDER/PARASOL; The validation and application of POLDER/PARASOL AOD, and cross-comparison with AOD of other satellites, such as MODIS AOD. (2) The retrieval algorithms developed for land and marine aerosol by using MICROPOL and RSP/APS. We also introduce the new progress in aerosol research based on The Directional Polarimetric Camera (DPC), which was produced by Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (CAS). (3) The aerosol retrieval algorithms by using measurements from ground-based instruments, such as CE318-2 and CE318-DP. The retrieval results from spaceborne sensors, airborne camera and ground-based measurements include total AOD, fine-mode AOD, coarse-mode AOD, size distribution, particle shape, complex refractive indices, single scattering albedo, scattering phase function, polarization phase function and AOD above cloud. Finally, based on the research, the authors present the problems and prospects of atmospheric aerosol research by using polarization remote sensing, and provide a valuable reference for the future studies of atmospheric aerosol.

Evaluation of Aerosol Pollution Determination From MODIS Satellite Retrievals for Semi-Arid Reno, NV, USA with In-Situ Measurements

NASA Astrophysics Data System (ADS)

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 "dark-target algorithm" may be unrealistically high over the Great Basin. Low correlation was found between AERONET AOD and dark-target algorithm AOD retrievals from Aqua and Terra during June and July. During fire conditions the dark-target algorithm AOD values correlated better with AERONET measurements in August. Use of the Deep-blue algorithm for MODIS data to retrieve AOD did not provide enough points to compare with AERONET in June and July. In August, AOD from deep-blue and AERONET retrievals exhibited low correlation. AEE from MODIS products and AERONET exhibited low correlation during every month. Apparently satellite AOD retrievals need much improvement for areas like semi-arid Reno.

Cloud, Aerosol, and Volcanic Ash Retrievals Using ASTR and SLSTR with ORAC

NASA Astrophysics Data System (ADS)

McGarragh, Gregory; Poulsen, Caroline; Povey, Adam; Thomas, Gareth; Christensen, Matt; Sus, Oliver; Schlundt, Cornelia; Stapelberg, Stefan; Stengel, Martin; Grainger, Don

2015-12-01

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.

Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A

NASA Astrophysics Data System (ADS)

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.

2015-06-01

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.e., layer high in the atmosphere) to the extent that retrieved values are not realistically representing actual extinction profiles anymore. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). In case one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large such that the retrieved height of the single layer is above the two-layer profile. Furthermore, we find that the retrieval solution, once retrieval converges, hardly depends on the starting values for the fit. Sensitivity experiments with GOME-2A spectra also show that aerosol layer height is indeed relatively robust against inaccuracies in the assumed aerosol model, even when the surface albedo is not fitted. We show spectral fit residuals, which can be used for further investigations. Fit residuals may be partly explained by spectroscopic uncertainties, which is suggested by an experiment showing the improvement of convergence when the absorption cross section is scaled in agreement with Butz et al. (2012) and Crisp et al. (2012) and a temperature offset to the a priori ECMWF temperature profile is fitted. Retrieved temperature offsets are always negative and quite large (ranging between -4 and -8 K), which is not expected if temperature offsets absorb remaining inaccuracies in meteorological data. Other sensitivity experiments investigate fitting of stray light and fluorescence emissions. We find negative radiance offsets and negative fluorescence emissions, also for non-vegetated areas, but from the results it is not clear whether fitting these parameters improves the retrieval. Based on the present results, the operational baseline for the Aerosol Layer Height product currently will not fit the surface albedo. The product will be particularly suited for elevated, optically thick aerosol layers. In addition to its scientific value in climate research, anticipated applications of the product for TROPOMI are providing aerosol height information for aviation safety and improving interpretation of the Absorbing Aerosol Index.

Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A

NASA Astrophysics Data System (ADS)

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.

2015-11-01

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.e., layer high in the atmosphere) to the extent that retrieved values no longer realistically represent actual extinction profiles. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). If one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large, in such a way that the retrieved height of the single layer is above the two-layer profile. Furthermore, we find that the retrieval solution, once retrieval converges, hardly depends on the starting values for the fit. Sensitivity experiments with GOME-2A spectra also show that aerosol layer height is indeed relatively robust against inaccuracies in the assumed aerosol model, even when the surface albedo is not fitted. We show spectral fit residuals, which can be used for further investigations. Fit residuals may be partly explained by spectroscopic uncertainties, which is suggested by an experiment showing the improvement of convergence when the absorption cross section is scaled in agreement with Butz et al. (2013) and Crisp et al. (2012), and a temperature offset to the a priori ECMWF temperature profile is fitted. Retrieved temperature offsets are always negative and quite large (ranging between -4 and -8 K), which is not expected if temperature offsets absorb remaining inaccuracies in meteorological data. Other sensitivity experiments investigate fitting of stray light and fluorescence emissions. We find negative radiance offsets and negative fluorescence emissions, also for non-vegetated areas, but from the results it is not clear whether fitting these parameters improves the retrieval. Based on the present results, the operational baseline for the Aerosol Layer Height product currently will not fit the surface albedo. The product will be particularly suited for elevated, optically thick aerosol layers. In addition to its scientific value in climate research, anticipated applications of the product for TROPOMI are providing aerosol height information for aviation safety and improving interpretation of the Absorbing Aerosol Index.

Atmospheric correction of SeaWiFS ocean color imagery in the presence of absorbing aerosols off the Indian coast using a neuro-variational method

NASA Astrophysics Data System (ADS)

Brajard, J.; Moulin, C.; Thiria, S.

2008-10-01

This paper presents a comparison of the atmospheric correction accuracy between the standard sea-viewing wide field-of-view sensor (SeaWiFS) algorithm and the NeuroVaria algorithm for the ocean off the Indian coast in March 1999. NeuroVaria is a general method developed to retrieve aerosol optical properties and water-leaving reflectances for all types of aerosols, including absorbing ones. It has been applied to SeaWiFS images of March 1999, during an episode of transport of absorbing aerosols coming from pollutant sources in India. Water-leaving reflectances and aerosol optical thickness estimated by the two methods were extracted along a transect across the aerosol plume for three days. The comparison showed that NeuroVaria allows the retrieval of oceanic properties in the presence of absorbing aerosols with a better spatial and temporal stability than the standard SeaWiFS algorithm. NeuroVaria was then applied to the available SeaWiFS images over a two-week period. NeuroVaria algorithm retrieves ocean products for a larger number of pixels than the standard one and eliminates most of the discontinuities and artifacts associated with the standard algorithm in presence of absorbing aerosols.

Development and Testing of the New Surface LER Climatology for OMI UV Aerosol Retrievals

NASA Technical Reports Server (NTRS)

Gupta, Pawan; Torres, Omar; Jethva, Hiren; Ahn, Changwoo

2014-01-01

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.

The Retrieval of Aerosol Optical Thickness Using the MERIS Instrument

NASA Astrophysics Data System (ADS)

Mei, L.; Rozanov, V. V.; Vountas, M.; Burrows, J. P.; Levy, R. C.; Lotz, W.

2015-12-01

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.

Algorithms for radiative transfer simulations for aerosol retrieval

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Sano, Itaru; Nakata, Makiko

2012-11-01

Aerosol retrieval work from satellite data, i.e. aerosol remote sensing, is divided into three parts as: satellite data analysis, aerosol modeling and multiple light scattering calculation in the atmosphere model which is called radiative transfer simulation. The aerosol model is compiled from the accumulated measurements during more than ten years provided with the world wide aerosol monitoring network (AERONET). The radiative transfer simulations take Rayleigh scattering by molecules and Mie scattering by aerosols in the atmosphere, and reflection by the Earth surface into account. Thus the aerosol properties are estimated by comparing satellite measurements with the numerical values of radiation simulations in the Earth-atmosphere-surface model. It is reasonable to consider that the precise simulation of multiple light-scattering processes is necessary, and needs a long computational time especially in an optically thick atmosphere model. Therefore efficient algorithms for radiative transfer problems are indispensable to retrieve aerosols from space.

Error analysis of the greenhouse-gases monitor instrument short wave infrared XCO2 retrieval algorithm

NASA Astrophysics Data System (ADS)

Wu, Hao; Wang, Xianhua; Ye, Hanhan; Jiang, Yun; Duan, Fenghua

2018-01-01

We developed an algorithm (named GMI_XCO2) to retrieve the global column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) for greenhouse-gases monitor instrument (GMI) and directional polarized camera (DPC) on the GF-5 satellite. This algorithm is designed to work in cloudless atmospheric conditions with aerosol optical thickness (AOT)<0.3. To quantify the uncertainty level of the retrieved XCO2 when the aerosols and cirrus clouds occurred in retrieving XCO2 with the GMI short wave infrared (SWIR) data, we analyzed the errors rate caused by the six types of aerosols and cirrus clouds. The results indicated that in AOT range of 0.05 to 0.3 (550 nm), the uncertainties of aerosols could lead to errors of -0.27% to 0.59%, -0.32% to 1.43%, -0.10% to 0.49%, -0.12% to 1.17%, -0.35% to 0.49%, and -0.02% to -0.24% for rural, dust, clean continental, maritime, urban, and soot aerosols, respectively. The retrieval results presented a large error due to cirrus clouds. In the cirrus optical thickness range of 0.05 to 0.8 (500 nm), the most underestimation is up to 26.25% when the surface albedo is 0.05. The most overestimation is 8.1% when the surface albedo is 0.65. The retrieval results of GMI simulation data demonstrated that the accuracy of our algorithm is within 4 ppm (˜1%) using the simultaneous measurement of aerosols and clouds from DPC. Moreover, the speed of our algorithm is faster than full-physics (FP) methods. We verified our algorithm with Greenhouse-gases Observing Satellite (GOSAT) data in Beijing area during 2016. The retrieval errors of most observations are within 4 ppm except for summer. Compared with the results of GOSAT, the correlation coefficient is 0.55 for the whole year data, increasing to 0.62 after excluding the summer data.

An algorithm for estimating aerosol optical depth from HIMAWARI-8 data over Ocean

NASA Astrophysics Data System (ADS)

Lee, Kwon Ho

2016-04-01

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).

What is the "Clim-Likely" aerosol product?

Atmospheric Science Data Center

2014-12-08

... identifying a range of components and mixtures for the MISR Standard Aerosol Retrieval Algorithm climatology, and as one standard against ... retrieval results. Six component aerosols included in the model were medium and coarse mode mineral dust, sulfate, sea salt, black ...

Validation of YCAR algorithm over East Asia TCCON sites

NASA Astrophysics Data System (ADS)

Kim, W.; Kim, J.; Jung, Y.; Lee, H.; Goo, T. Y.; Cho, C. H.; Lee, S.

2016-12-01

In order to reduce the retrieval error of TANSO-FTS column averaged CO2 concentration (XCO2) induced by aerosol, we develop the Yonsei university CArbon Retrieval (YCAR) algorithm using aerosol information from TANSO-Cloud and Aerosol Imager (TANSO-CAI), providing simultaneous aerosol optical depth properties for the same geometry and optical path along with the FTS. Also we validate the retrieved results using ground-based TCCON measurement. Particularly this study first utilized the measurements at Anmyeondo, the only TCCON site located in South Korea, which can improve the quality of validation in East Asia. After the post screening process, YCAR algorithms have higher data availability by 33 - 85 % than other operational algorithms (NIES, ACOS, UoL). Although the YCAR algorithm has higher data availability, regression analysis with TCCON measurements are better or similar to other algorithms; Regression line of YCAR algorithm is close to linear identity function with RMSE of 2.05, bias of - 0.86 ppm. According to error analysis, retrieval error of YCAR algorithm is 1.394 - 1.478 ppm at East Asia. In addition, spatio-temporal sampling error of 0.324 - 0.358 ppm for each single sounding retrieval is also analyzed with Carbon Tracker - Asia data. These results of error analysis reveal the reliability and accuracy of latest version of our YCAR algorithm. Both XCO2 values retrieved using YCAR algorithm on TANSO-FTS and TCCON measurements show the consistent increasing trend about 2.3 - 2.6 ppm per year. Comparing to the increasing rate of global background CO2 amount measured in Mauna Loa, Hawaii (2 ppm per year), the increasing trend in East Asia shows about 30% higher trend due to the rapid increase of CO2 emission from the source region.

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae

2016-01-01

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.

Using OMI Observations to Measure Aerosol Absorption of Biomass Burning Aerosols Above Clouds

NASA Technical Reports Server (NTRS)

Torres, Omar; Bhartia, P. K.; Jethva, Hiren

2011-01-01

The presence of absorbing aerosol layers above clouds is unambiguously detected by the TOMS/OMI UV Aerosol Index (AI) that uses satellite observations at two near-UV channels. A sensitivity study using radiative transfer calculations shows that the AI signal of resulting from the presence of aerosols above clouds is mainly driven by the aerosol absorption optical depth and the optical depth of the underlying cloud. Based on these results, an inversion algorithm has been developed to retrieve the aerosol optical depth (AOD) of aerosol layers above clouds. In this presentation we will discuss the sensitivity analysis, describe the retrieval approach, and present results of applications of the retrieval method to OMI observations over the South Atlantic Ocean. Preliminary error analyses, to be discussed, indicate that the AOD can be underestimated (up to -30%) or overestimated (up to 60%) depending on algorithmic assumptions.

Explicit and Observation-based Aerosol Treatment in Tropospheric NO2 Retrieval over China from the Ozone Monitoring Instrument

NASA Astrophysics Data System (ADS)

Liu, M.; Lin, J.; Boersma, F.; Pinardi, G.; Wang, Y.; Chimot, J.; Wagner, T.; Xie, P.; Eskes, H.; Van Roozendael, M.; Hendrick, F.

2017-12-01

Satellite retrieval of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) is influenced by aerosols substantially. Aerosols affect the retrieval of "effective cloud fraction (CF)" and "effective cloud top pressure (CP)" that are used in the subsequent NO2 retrieval to account for the presentence of clouds. And aerosol properties and vertical distributions directly affect the NO2 air mass factor (AMF) calculations. Our published POMINO algorithm uses a parallelized LIDORT-driven AMFv6 code to derive CF, CP and NO2 VCD. Daily information on aerosol optical properties are taken from GEOS-Chem simulations, with aerosol optical depth (AOD) further constrained by monthly MODIS AOD. However, the published algorithm does not include an observation-based constraint of aerosol vertical distribution. Here we construct a monthly climatological observation dataset of aerosol extinction profiles, based on Level-2 CALIOP data over 2007-2015, to further constrain aerosol vertical distributions. GEOS-Chem captures the temporal variations of CALIOP aerosol layer heights (ALH) but has an overall underestimate by about 0.3 km. It tends to overestimate the aerosol extinction by 10% below 2 km but with an underestimate by 30% above 2 km, leading to a low bias by 10-30% in the retrieved tropospheric NO2 VCD. After adjusting GEOS-Chem aerosol extinction profiles by the CALIOP monthly ALH climatology, the retrieved NO2 VCDs increase by 4-16% over China on a monthly basis in 2012. The improved NO2 VCDs are better correlated to independent MAX-DOAS observations at three sites than POMINO and DOMINO are - especially for the polluted cases, R2 reaches 0.76 for the adjusted POMINO, much higher than that for the published POMINO (0.68) and DOMINO (0.38). The newly retrieved CP increases by 60 hPa on average, because of a stronger aerosol screening effect. Compared to the CF used in DOMINO, which implicitly includes aerosol information, our improved CF is much lower and can reach a value of zero on actual cloud-free days. Overall, constraining aerosol vertical profiles greatly improves the retrievals of clouds and NO2 VCDs from satellite remote sensing. Our algorithm can be applied, with minimum modifications, to formaldehyde, sulfur dioxide and other species with similar retrieval methodologies.

Next Generation of Air Quality Measurements from Geo Orbits: Breaking The Temporal Barrier

NASA Astrophysics Data System (ADS)

Gupta, P.; Levy, R. C.; Mattoo, S.; Remer, L.; Heidinger, A.

2017-12-01

NASA's dark target (DT) aerosol algorithm provides operational retrieval of atmospheric aerosols from multiple polar orbiting satellites. The DT algorithm, initially developed for MODIS observations, has been continuously improved since the first MODIS launch in early 2000. Now, we are adapting the DT algorithm to retrieve on new-generation geostationary (GEO) sensors, including the Advanced Himawari Imager (AHI) on Japan's Himawari-8 (H8) satellite and Advanced Baseline Imager (ABI) on NOAA's GOES-16 (or GOES-R). H8 is a weather geostationary satellite operating since July 2015, and AHI observes earth-atmosphere system over the Asia-Pacific region at spatial resolutions of 1km or less. GOES-R is launched in Nov 2016 and provides high temporal resolution observations over Americas. With 16 spectral channels, including 7 bands that observe similar wavelengths as the MODIS bands used for DT aerosol retrieval. Most exciting, however, is that both ABI and AHI provides full disk observations every 10-15 minutes and zoom mode observations every 30 second to 2.5 minutes. Therefore, spectral, spatial and temporal resolution observations from these GEO satellites provide opportunity to monitor atmospheric aerosols in the region, plus a new capability to monitor aerosol transport and aerosol/cloud diurnal cycles. In this paper, we will introduce retrieval results from AHI using the DT algorithm during the KORUS-AQ field campaign during summer 2016. These results are evaluated against surface measurements (e.g. AERONET). . We will also discuss, its potential applications in monitoring diurnal cycles of urban pollution, smoke and dust in the region. The same DT algorithm will also be adapted to retrieve aerosol properties using GOES-16 over Americas.

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

NASA Astrophysics Data System (ADS)

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

2016-04-01

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 agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

GOCI Yonsei Aerosol Retrieval (YAER) Algorithm and Validation During the DRAGON-NE Asia 2012 Campaign

NASA Technical Reports Server (NTRS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.;

Adaptation of an aerosol retrieval algorithm using multi-wavelength and multi-pixel information of satellites (MWPM) to GOSAT/TANSO-CAI

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Takenaka, H.; Higurashi, A.; Nakajima, T.

2017-12-01

Aerosol in the atmosphere is an important constituent for determining the earth's radiation budget, so the accurate aerosol retrievals from satellite is useful. We have developed a satellite remote sensing algorithm to retrieve the aerosol optical properties using multi-wavelength and multi-pixel information of satellite imagers (MWPM). The method simultaneously derives aerosol optical properties, such as aerosol optical thickness (AOT), single scattering albedo (SSA) and aerosol size information, by using spatial difference of wavelegths (multi-wavelength) and surface reflectances (multi-pixel). The method is useful for aerosol retrieval over spatially heterogeneous surface like an urban region. In this algorithm, the inversion method is a combination of an optimal method and smoothing constraint for the state vector. Furthermore, this method has been combined with the direct radiation transfer calculation (RTM) numerically solved by each iteration step of the non-linear inverse problem, without using look up table (LUT) with several constraints. However, it takes too much computation time. To accelerate the calculation time, we replaced the RTM with an accelerated RTM solver learned by neural network-based method, EXAM (Takenaka et al., 2011), using Rster code. And then, the calculation time was shorternd to about one thouthandth. We applyed MWPM combined with EXAM to GOSAT/TANSO-CAI (Cloud and Aerosol Imager). CAI is a supplement sensor of TANSO-FTS, dedicated to measure cloud and aerosol properties. CAI has four bands, 380, 674, 870 and 1600 nm, and observes in 500 meters resolution for band1, band2 and band3, and 1.5 km for band4. Retrieved parameters are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles at a wavelenth of 500nm, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength by combining a minimum reflectance method and Fukuda et al. (2013). We will show the results and discuss the accuracy of the algorithm for various surface types. Our future work is to extend the algorithm for analysis of GOSAT-2/TANSO-CAI-2 and GCOM/C-SGLI data.

Characterization and error analysis of an operational retrieval algorithm for estimating column ozone and aerosol properties from ground-based ultra-violet irradiance measurements

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; L'Ecuyer, Tristan; Slusser, James; Stephens, Graeme; Krotkov, Nick; Davis, John; Goering, Christian

2005-08-01

Extensive sensitivity and error characteristics of a recently developed optimal estimation retrieval algorithm which simultaneously determines aerosol optical depth (AOD), aerosol single scatter albedo (SSA) and total ozone column (TOC) from ultra-violet irradiances are described. The algorithm inverts measured diffuse and direct irradiances at 7 channels in the UV spectral range obtained from the United States Department of Agriculture's (USDA) UV-B Monitoring and Research Program's (UVMRP) network of 33 ground-based UV-MFRSR instruments to produce aerosol optical properties and TOC at all seven wavelengths. Sensitivity studies of the Tropospheric Ultra-violet/Visible (TUV) radiative transfer model performed for various operating modes (Delta-Eddington versus n-stream Discrete Ordinate) over domains of AOD, SSA, TOC, asymmetry parameter and surface albedo show that the solutions are well constrained. Realistic input error budgets and diagnostic and error outputs from the retrieval are analyzed to demonstrate the atmospheric conditions under which the retrieval provides useful and significant results. After optimizing the algorithm for the USDA site in Panther Junction, Texas the retrieval algorithm was run on a cloud screened set of irradiance measurements for the month of May 2003. Comparisons to independently derived AOD's are favorable with root mean square (RMS) differences of about 3% to 7% at 300nm and less than 1% at 368nm, on May 12 and 22, 2003. This retrieval method will be used to build an aerosol climatology and provide ground-truthing of satellite measurements by running it operationally on the USDA UV network database.

Lidar-Radiometer Inversion Code (LIRIC) for the Retrieval of Vertical Aerosol Properties from Combined Lidar Radiometer Data: Development and Distribution in EARLINET

NASA Technical Reports Server (NTRS)

Chaikovsky, A.; Dubovik, O.; Holben, Brent N.; Bril, A.; Goloub, P.; Tanre, D.; Pappalardo, G.; Wandinger, U.; Chaikovskaya, L.; Denisov, S.;

Aerosol retrieval experiments in the ESA Aerosol_cci project

NASA Astrophysics Data System (ADS)

Holzer-Popp, T.; de Leeuw, G.; Martynenko, D.; Klüser, L.; Bevan, S.; Davies, W.; Ducos, F.; Deuzé, J. L.; Graigner, R. G.; Heckel, A.; von Hoyningen-Hüne, W.; Kolmonen, P.; Litvinov, P.; North, P.; Poulsen, C. A.; Ramon, D.; Siddans, R.; Sogacheva, L.; Tanre, D.; Thomas, G. E.; Vountas, M.; Descloitres, J.; Griesfeller, J.; Kinne, S.; Schulz, M.; Pinnock, S.

2013-03-01

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

Two-Channel Satellite Retrievals of Aerosol Properties: An Overview

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.

1999-01-01

In order to reduce current uncertainties in the evaluation of the direct and indirect effects of tropospheric aerosols on climate on the global scale, it has been suggested to apply multi-channel retrieval algorithms to the full period of existing satellite data. This talk will outline the methodology of interpreting two-channel satellite radiance data over the ocean and describe a detailed analysis of the sensitivity of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. We will specifically address the calibration and cloud screening issues, consider the suitability of existing satellite data sets to detecting short- and long-term regional and global changes, compare preliminary results obtained by several research groups, and discuss the prospects of creating an advanced retroactive climatology of aerosol optical thickness and size over the oceans.

Satellite aerosol retrieval using dark target algorithm by coupling BRDF effect over AERONET site

NASA Astrophysics Data System (ADS)

Yang, Leiku; Xue, Yong; Guang, Jie; Li, Chi

2012-11-01

For most satellite aerosol retrieval algorithms even for multi-angle instrument, the simple forward model (FM) based on Lambertian surface assumption is employed to simulate top of the atmosphere (TOA) spectral reflectance, which does not fully consider the surface bi-directional reflectance functions (BRDF) effect. The approximating forward model largely simplifies the radiative transfer model, reduces the size of the look-up tables, and creates faster algorithm. At the same time, it creates systematic biases in the aerosol optical depth (AOD) retrieval. AOD product from the Moderate Resolution Imaging Spectro-radiometer (MODIS) data based on the dark target algorithm is considered as one of accurate satellite aerosol products at present. Though it performs well at a global scale, uncertainties are still found on regional in a lot of studies. The Lambertian surface assumpiton employed in the retrieving algorithm may be one of the uncertain factors. In this study, we first use radiative transfer simulations over dark target to assess the uncertainty to what extent is introduced from the Lambertian surface assumption. The result shows that the uncertainties of AOD retrieval could reach up to ±0.3. Then the Lambertian FM (L_FM) and the BRDF FM (BRDF_FM) are respectively employed in AOD retrieval using dark target algorithm from MODARNSS (MODIS/Terra and MODIS/Aqua Atmosphere Aeronet Subsetting Product) data over Beijing AERONET site. The validation shows that accuracy in AOD retrieval has been improved by employing the BRDF_FM accounting for the surface BRDF effect, the regression slope of scatter plots with retrieved AOD against AEROENET AOD increases from 0.7163 (for L_FM) to 0.7776 (for BRDF_FM) and the intercept decreases from 0.0778 (for L_FM) to 0.0627 (for BRDF_FM).

MISR Aerosol Product Attributes and Statistical Comparisons with MODIS

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Nelson, David L.; Garay, Michael J.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Paradise, Susan R.; Hansen, Earl G.; Remer, Lorraine A.

2009-01-01

In this paper, Multi-angle Imaging SpectroRadiometer (MISR) aerosol product attributes are described, including geometry and algorithm performance flags. Actual retrieval coverage is mapped and explained in detail using representative global monthly data. Statistical comparisons are made with coincident aerosol optical depth (AOD) and Angstrom exponent (ANG) retrieval results from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The relationship between these results and the ones previously obtained for MISR and MODIS individually, based on comparisons with coincident ground-truth observations, is established. For the data examined, MISR and MODIS each obtain successful aerosol retrievals about 15% of the time, and coincident MISR-MODIS aerosol retrievals are obtained for about 6%-7% of the total overlap region. Cloud avoidance, glint and oblique-Sun exclusions, and other algorithm physical limitations account for these results. For both MISR and MODIS, successful retrievals are obtained for over 75% of locations where attempts are made. Where coincident AOD retrievals are obtained over ocean, the MISR-MODIS correlation coefficient is about 0.9; over land, the correlation coefficient is about 0.7. Differences are traced to specific known algorithm issues or conditions. Over-ocean ANG comparisons yield a correlation of 0.67, showing consistency in distinguishing aerosol air masses dominated by coarse-mode versus fine-mode particles. Sampling considerations imply that care must be taken when assessing monthly global aerosol direct radiative forcing and AOD trends with these products, but they can be used directly for many other applications, such as regional AOD gradient and aerosol air mass type mapping and aerosol transport model validation. Users are urged to take seriously the published product data-quality statements.

Assessment of diverse algorithms applied on MODIS Aqua and Terra data over land surfaces in Europe

NASA Astrophysics Data System (ADS)

Glantz, P.; Tesche, M.

2012-04-01

Beside an increase of greenhouse gases (e.g., carbon dioxide, methane and nitrous oxide) human activities (for instance fossil fuel and biomass burning) have lead to perturbation of the atmospheric content of aerosol particles. Aerosols exhibits high spatial and temporal variability in the atmosphere. Therefore, aerosol investigation for climate research and environmental control require the identification of source regions, their strength and aerosol type, which can be retrieved based on space-borne observations. The aim of the present study is to validate and evaluate AOT (aerosol optical thickness) and Ångström exponent, obtained with the SAER (Satellite AErosol Retrieval) algorithm for MODIS (MODerate resolution Imaging Spectroradiometer) Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground), against AERONET (AErosol RObotic NETwork) observations and MODIS Collection 5 (c005) standard product retrievals (10 km), respectively, over land surfaces in Europe for the seasons; early spring (period 1), mid spring (period 2) and summer (period 3). For several of the cases analyzed here the Aqua and Terra satellites passed the investigation area twice during a day. Thus, beside a variation in the sun elevation the satellite aerosol retrievals have also on a daily basis been performed with a significant variation in the satellite-viewing geometry. An inter-comparison of the two algorithms has also been performed. The validation with AERONET shows that the MODIS c005 retrieved AOT is, for the wavelengths 0.469 and 0.500 nm, on the whole within the expected uncertainty for one standard deviation of the MODIS retrievals over Europe (Δτ = ±0.05 ± 0.15τ). The SAER estimated AOT for the wavelength 0.443 nm also agree reasonable well with AERONET. Thus, the majority of the SAER AOT values are within the MODIS expected uncertainty range, although somewhat larger RMSD (root mean square deviation) occurs compared to the results obtained with the MODIS c005 algorithm. The discrepancy between SAERand AERONET AOT is, however, substantially larger for the wavelength 488 nm, which means that several of the AOT values are without the MODIS expected uncertainty range. Both algorithms are unable to estimate Ångström exponent accurately, although the MODIS c005 algorithm performs a better job. Based on the inter-comparison of the SAER and MODIS c005 algorithms it was found here that the former estimation of AOT is for values up to 1on the whole within the expected uncertainties for one standard deviation of the MODIS retrievals, considering both Aqua and Terra and periods 1 and 3. The latter also occurs for Aqua and period 2, while then for AOT values lower than 0.5. The present algorithms were, beside aerosols emitted from clean sources and continental sources in Europe, also applied with favor on aerosol particles transported from agricultural fires in Russia and Ukraine. The latter events were associated with high aerosol loadings, although probably with similar single scattering albedo as the days classified as clean. We also present observations performed with space borne and ground-based lidars in the area investigated. From the latter platforms the vertical distribution of aerosol extinction in the atmosphere can be measured. This study suggests that the present satellite retrievals of AOT, particularly obtained with the MODIS c005 algorithm, will, in combination with the lidar measurements, be very useful in validation of regional and climate models over Europe.

Passive remote sensing of altitude and optical depth of dust plumes using the oxygen A and B bands: First results from EPIC/DSCOVR at Lagrange-1 point

NASA Astrophysics Data System (ADS)

Xu, Xiaoguang; Wang, Jun; Wang, Yi; Zeng, Jing; Torres, Omar; Yang, Yuekui; Marshak, Alexander; Reid, Jeffrey; Miller, Steve

2017-07-01

We presented an algorithm for inferring aerosol layer height (ALH) and optical depth (AOD) over ocean surface from radiances in oxygen A and B bands measured by the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) orbiting at Lagrangian-1 point. The algorithm was applied to EPIC imagery of a 2 day dust outbreak over the North Atlantic Ocean. Retrieved ALHs and AODs were evaluated against counterparts observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer, and Aerosol Robotic Network. The comparisons showed 71.5% of EPIC-retrieved ALHs were within ±0.5 km of those determined from CALIOP and 74.4% of EPIC AOD retrievals fell within a ± (0.1 + 10%) envelope of MODIS retrievals. This study demonstrates the potential of EPIC measurements for retrieving global aerosol height multiple times daily, which are essential for evaluating aerosol profile simulated in climate models and for better estimating aerosol radiative effects.

XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation

NASA Astrophysics Data System (ADS)

Mei, Linlu; Rozanov, Vladimir; Vountas, Marco; Burrows, John P.; Richter, Andreas

2018-02-01

A cloud identification algorithm used for cloud masking, which is based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths, has been developed for the retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance, as observed from space, is very different from that of aerosols. Clouds show a high spatial variability in the scale of a hundred metres to a few kilometres, whereas aerosols in general are homogeneous. The concept of spatial variability of reflectances at the top of the atmosphere is mainly applicable over the ocean, where the surface background is sufficiently homogeneous for the separation between aerosols and clouds. Aerosol retrievals require a sufficiently accurate cloud identification to be able to mask these ground scenes. However, a conservative mask will exclude strong aerosol episodes and a less conservative mask could introduce cloud contamination that biases the retrieved aerosol optical properties (e.g. aerosol optical depth and effective radii). A detailed study on the effect of cloud contamination on aerosol retrievals has been performed and parameters are established determining the threshold value for the MODIS aerosol cloud mask (3×3-STD) over the ocean. The 3×3-STD algorithm discussed in this paper is the operational cloud mask used for MODIS aerosol retrievals over the ocean.A prolonged pollution haze event occurred in the northeast part of China during the period 16-21 December 2016. To assess the impact of such events, the amounts and distribution of aerosol particles, formed in such events, need to be quantified. The newly launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3 is the successor of the MEdium Resolution Imaging Spectrometer (MERIS). It provides measurements of the radiance and reflectance at the top of the atmosphere, which can be used to retrieve the aerosol optical thickness (AOT) from synoptic to global scales. In this study, the recently developed AOT retrieval algorithm eXtensible Bremen AErosol Retrieval (XBAER) has been applied to data from the OLCI instrument for the first time to illustrate the feasibility of applying XBAER to the data from this new instrument. The first global retrieval results show similar patterns of aerosol optical thickness, AOT, to those from MODIS and MISR aerosol products. The AOT retrieved from OLCI is validated by comparison with AERONET observations and a correlation coefficient of 0.819 and bias (root mean square) of 0.115 is obtained. The haze episode is well captured by the OLCI-derived AOT product. XBAER is shown to retrieve AOT well from the observations of MERIS and OLCI.

New approaches to removing cloud shadows and evaluating the 380 nm surface reflectance for improved aerosol optical thickness retrievals from the GOSAT/TANSO-Cloud and Aerosol Imager

NASA Astrophysics Data System (ADS)

Fukuda, Satoru; Nakajima, Teruyuki; Takenaka, Hideaki; Higurashi, Akiko; Kikuchi, Nobuyuki; Nakajima, Takashi Y.; Ishida, Haruma

2013-12-01

satellite aerosol retrieval algorithm was developed to utilize a near-ultraviolet band of the Greenhouse gases Observing SATellite/Thermal And Near infrared Sensor for carbon Observation (GOSAT/TANSO)-Cloud and Aerosol Imager (CAI). At near-ultraviolet wavelengths, the surface reflectance over land is smaller than that at visible wavelengths. Therefore, it is thought possible to reduce retrieval error by using the near-ultraviolet spectral region. In the present study, we first developed a cloud shadow detection algorithm that uses first and second minimum reflectances of 380 nm and 680 nm based on the difference in Rayleigh scattering contribution for these two bands. Then, we developed a new surface reflectance correction algorithm, the modified Kaufman method, which uses minimum reflectance data at 680 nm and the NDVI to estimate the surface reflectance at 380 nm. This algorithm was found to be particularly effective at reducing the aerosol effect remaining in the 380 nm minimum reflectance; this effect has previously proven difficult to remove owing to the infrequent sampling rate associated with the three-day recursion period of GOSAT and the narrow CAI swath of 1000 km. Finally, we applied these two algorithms to retrieve aerosol optical thicknesses over a land area. Our results exhibited better agreement with sun-sky radiometer observations than results obtained using a simple surface reflectance correction technique using minimum radiances.

Retrieval of aerosol optical properties using MERIS observations: Algorithm and some first results.

PubMed

Mei, Linlu; Rozanov, Vladimir; Vountas, Marco; Burrows, John P; Levy, Robert C; Lotz, Wolfhardt

2017-08-01

The MEdium Resolution Imaging Spectrometer (MERIS) instrument on board ESA Envisat made measurements from 2002 to 2012. Although MERIS was limited in spectral coverage, accurate Aerosol Optical Thickness (AOT) from MERIS data are retrieved by using appropriate additional information. We introduce a new AOT retrieval algorithm for MERIS over land surfaces, referred to as eXtensible Bremen AErosol Retrieval (XBAER). XBAER is similar to the "dark-target" (DT) retrieval algorithm used for Moderate-resolution Imaging Spectroradiometer (MODIS), in that it uses a lookup table (LUT) to match to satellite-observed reflectance and derive the AOT. Instead of a global parameterization of surface spectral reflectance, XBAER uses a set of spectral coefficients to prescribe surface properties. In this manner, XBAER is not limited to dark surfaces (vegetation) and retrieves AOT over bright surface (desert, semiarid, and urban areas). Preliminary validation of the MERIS-derived AOT and the ground-based Aerosol Robotic Network (AERONET) measurements yield good agreement, the resulting regression equation is y = (0.92 × ± 0.07) + (0.05 ± 0.01) and Pearson correlation coefficient of R = 0.78. Global monthly means of AOT have been compared from XBAER, MODIS and other satellite-derived datasets.

Retrieval of tropospheric aerosol properties over land from visible and near-infrared spectral reflectance: Application over Maryland

NASA Astrophysics Data System (ADS)

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 forcing (contribution from anthropogenic aerosols only). Over the U.S. mid-Atlantic region, validated retrievals of tau (an integrated column property) can help to estimate surface PM2.5 concentration, a monitored criteria air quality property. The 3-dimensional aerosol loading in the region is characterized using aircraft measurements and the Community Multi-scale Air Quality Model (CMAQ) model, leading to some convergence of observed quantities and modeled processes.

An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database

NASA Astrophysics Data System (ADS)

Zhang, Hai; Kondragunta, Shobha; Laszlo, Istvan; Liu, Hongqing; Remer, Lorraine A.; Huang, Jingfeng; Superczynski, Stephen; Ciren, Pubu

2016-09-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been retrieving aerosol optical thickness (AOT), operationally and globally, over ocean and land since shortly after S-NPP launch in 2011. However, the current operational VIIRS AOT retrieval algorithm over land has two limitations in its assumptions for land surfaces: (1) it only retrieves AOT over the dark surfaces and (2) it assumes that the global surface reflectance ratios between VIIRS bands are constants. In this work, we develop a surface reflectance ratio database over land with a spatial resolution 0.1° × 0.1° using 2 years of VIIRS top of atmosphere reflectances. We enhance the current operational VIIRS AOT retrieval algorithm by applying the surface reflectance ratio database in the algorithm. The enhanced algorithm is able to retrieve AOT over both dark and bright surfaces. Over bright surfaces, the VIIRS AOT retrievals from the enhanced algorithm have a correlation of 0.79, mean bias of -0.008, and standard deviation (STD) of error of 0.139 when compared against the ground-based observations at the global AERONET (Aerosol Robotic Network) sites. Over dark surfaces, the VIIRS AOT retrievals using the surface reflectance ratio database improve the root-mean-square error from 0.150 to 0.123. The use of the surface reflectance ratio database also increases the data coverage of more than 20% over dark surfaces. The AOT retrievals over bright surfaces are comparable to MODIS Deep Blue AOT retrievals.

Aerosol retrieval experiments in the ESA Aerosol_cci project

NASA Astrophysics Data System (ADS)

Holzer-Popp, T.; de Leeuw, G.; Griesfeller, J.; Martynenko, D.; Klüser, L.; Bevan, S.; Davies, W.; Ducos, F.; Deuzé, J. L.; Graigner, R. G.; Heckel, A.; von Hoyningen-Hüne, W.; Kolmonen, P.; Litvinov, P.; North, P.; Poulsen, C. A.; Ramon, D.; Siddans, R.; Sogacheva, L.; Tanre, D.; Thomas, G. E.; Vountas, M.; Descloitres, J.; Griesfeller, J.; Kinne, S.; Schulz, M.; Pinnock, S.

2013-08-01

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

Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S-NPP VIIRS as Part of the "Deep Blue" Aerosol Project

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Lee, J.; Bettenhausen, C.; Kim, W. V.; Smirnov, A.

2018-01-01

The Suomi National Polar-Orbiting Partnership (S-NPP) satellite, launched in late 2011, carries the Visible Infrared Imaging Radiometer Suite (VIIRS) and several other instruments. VIIRS has similar characteristics to prior satellite sensors used for aerosol optical depth (AOD) retrieval, allowing the continuation of space-based aerosol data records. The Deep Blue algorithm has previously been applied to retrieve AOD from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements over land. The SeaWiFS Deep Blue data set also included a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm to cover water surfaces. As part of NASA's VIIRS data processing, Deep Blue is being applied to VIIRS data over land, and SOAR has been adapted from SeaWiFS to VIIRS for use over water surfaces. This study describes SOAR as applied in version 1 of NASA's S-NPP VIIRS Deep Blue data product suite. Several advances have been made since the SeaWiFS application, as well as changes to make use of the broader spectral range of VIIRS. A preliminary validation against Maritime Aerosol Network (MAN) measurements suggests a typical uncertainty on retrieved 550 nm AOD of order ±(0.03+10%), comparable to existing SeaWiFS/MODIS aerosol data products. Retrieved Ångström exponent and fine-mode AOD fraction are also well correlated with MAN data, with small biases and uncertainty similar to or better than SeaWiFS/MODIS products.

Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China

NASA Astrophysics Data System (ADS)

Che, Yahui; Xue, Yong; Mei, Linlu; Guang, Jie; She, Lu; Guo, Jianping; Hu, Yincui; Xu, Hui; He, Xingwei; Di, Aojie; Fan, Cheng

2016-08-01

One of four main focus areas of the PEEX initiative is to establish and sustain long-term, continuous, and comprehensive ground-based, airborne, and seaborne observation infrastructure together with satellite data. The Advanced Along-Track Scanning Radiometer (AATSR) aboard ENVISAT is used to observe the Earth in dual view. The AATSR data can be used to retrieve aerosol optical depth (AOD) over both land and ocean, which is an important parameter in the characterization of aerosol properties. In recent years, aerosol retrieval algorithms have been developed both over land and ocean, taking advantage of the features of dual view, which can help eliminate the contribution of Earth's surface to top-of-atmosphere (TOA) reflectance. The Aerosol_cci project, as a part of the Climate Change Initiative (CCI), provides users with three AOD retrieval algorithms for AATSR data, including the Swansea algorithm (SU), the ATSR-2ATSR dual-view aerosol retrieval algorithm (ADV), and the Oxford-RAL Retrieval of Aerosol and Cloud algorithm (ORAC). The validation team of the Aerosol-CCI project has validated AOD (both Level 2 and Level 3 products) and AE (Ångström Exponent) (Level 2 product only) against the AERONET data in a round-robin evaluation using the validation tool of the AeroCOM (Aerosol Comparison between Observations and Models) project. For the purpose of evaluating different performances of these three algorithms in calculating AODs over mainland China, we introduce ground-based data from CARSNET (China Aerosol Remote Sensing Network), which was designed for aerosol observations in China. Because China is vast in territory and has great differences in terms of land surfaces, the combination of the AERONET and CARSNET data can validate the L2 AOD products more comprehensively. The validation results show different performances of these products in 2007, 2008, and 2010. The SU algorithm performs very well over sites with different surface conditions in mainland China from March to October, but it slightly underestimates AOD over barren or sparsely vegetated surfaces in western China, with mean bias error (MBE) ranging from 0.05 to 0.10. The ADV product has the same precision with a low root mean square error (RMSE) smaller than 0.2 over most sites and the same error distribution as the SU product. The main limits of the ADV algorithm are underestimation and applicability; underestimation is particularly obvious over the sites of Datong, Lanzhou, and Urumchi, where the dominant land cover is grassland, with an MBE larger than 0.2, and the main aerosol sources are coal combustion and dust. The ORAC algorithm has the ability to retrieve AOD at different ranges, including high AOD (larger than 1.0); however, the stability deceases significantly with increasing AOD, especially when AOD > 1.0. In addition, the ORAC product is consistent with the CARSNET product in winter (December, January, and February), whereas other validation results lack matches during winter.

Aerosol Retrievals from Proposed Satellite Bistatic Lidar Observations: Algorithm and Information Content

NASA Astrophysics Data System (ADS)

Alexandrov, M. D.; Mishchenko, M. I.

2017-12-01

Accurate aerosol retrievals from space remain quite challenging and typically involve solving a severely ill-posed inverse scattering problem. We suggested to address this ill-posedness by flying a bistatic lidar system. Such a system would consist of formation flying constellation of a primary satellite equipped with a conventional monostatic (backscattering) lidar and an additional platform hosting a receiver of the scattered laser light. If successfully implemented, this concept would combine the measurement capabilities of a passive multi-angle multi-spectral polarimeter with the vertical profiling capability of a lidar. Thus, bistatic lidar observations will be free of deficiencies affecting both monostatic lidar measurements (caused by the highly limited information content) and passive photopolarimetric measurements (caused by vertical integration and surface reflection).We present a preliminary aerosol retrieval algorithm for a bistatic lidar system consisting of a high spectral resolution lidar (HSRL) and an additional receiver flown in formation with it at a scattering angle of 165 degrees. This algorithm was applied to synthetic data generated using Mie-theory computations. The model/retrieval parameters in our tests were the effective radius and variance of the aerosol size distribution, complex refractive index of the particles, and their number concentration. Both mono- and bimodal aerosol mixtures were considered. Our algorithm allowed for definitive evaluation of error propagation from measurements to retrievals using a Monte Carlo technique, which involves random distortion of the observations and statistical characterization of the resulting retrieval errors. Our tests demonstrated that supplementing a conventional monostatic HSRL with an additional receiver dramatically increases the information content of the measurements and allows for a sufficiently accurate characterization of tropospheric aerosols.

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during DRAGON-NE Asia 2012 campaign

NASA Astrophysics Data System (ADS)

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.

2015-09-01

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 over ocean than land. Over land, especially, GOCI AOD shows better agreement with MODIS DB than MODIS DT because of the choice of surface reflectance assumptions. Other GOCI YAER products show lower correlation with AERONET than AOD, but are still qualitatively useful.

Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements

NASA Astrophysics Data System (ADS)

Veselovskii, I.; Dubovik, O.; Kolgotin, A.; Lapyonok, T.; di Girolamo, P.; Summa, D.; Whiteman, D. N.; Mishchenko, M.; Tanré, D.

2010-11-01

Multiwavelength (MW) Raman lidars have demonstrated their potential to profile particle parameters; however, until now, the physical models used in retrieval algorithms for processing MW lidar data have been predominantly based on the Mie theory. This approach is applicable to the modeling of light scattering by spherically symmetric particles only and does not adequately reproduce the scattering by generally nonspherical desert dust particles. Here we present an algorithm based on a model of randomly oriented spheroids for the inversion of multiwavelength lidar data. The aerosols are modeled as a mixture of two aerosol components: one composed only of spherical and the second composed of nonspherical particles. The nonspherical component is an ensemble of randomly oriented spheroids with size-independent shape distribution. This approach has been integrated into an algorithm retrieving aerosol properties from the observations with a Raman lidar based on a tripled Nd:YAG laser. Such a lidar provides three backscattering coefficients, two extinction coefficients, and the particle depolarization ratio at a single or multiple wavelengths. Simulations were performed for a bimodal particle size distribution typical of desert dust particles. The uncertainty of the retrieved particle surface, volume concentration, and effective radius for 10% measurement errors is estimated to be below 30%. We show that if the effect of particle nonsphericity is not accounted for, the errors in the retrieved aerosol parameters increase notably. The algorithm was tested with experimental data from a Saharan dust outbreak episode, measured with the BASIL multiwavelength Raman lidar in August 2007. The vertical profiles of particle parameters as well as the particle size distributions at different heights were retrieved. It was shown that the algorithm developed provided substantially reasonable results consistent with the available independent information about the observed aerosol event.

Satellite remote sensing of aerosol and cloud properties over Eurasia

NASA Astrophysics Data System (ADS)

Sogacheva, Larisa; Kolmonen, Pekka; Saponaro, Giulia; Virtanen, Timo; Rodriguez, Edith; Sundström, Anu-Maija; Atlaskina, Ksenia; de Leeuw, Gerrit

2015-04-01

Satellite remote sensing provides the spatial distribution of aerosol and cloud properties over a wide area. In our studies large data sets are used for statistical studies on aerosol and cloud interaction in an area over Fennoscandia, the Baltic Sea and adjacent regions over the European mainland. This area spans several regimes with different influences on aerosol cloud interaction such as a the transition from relative clean air over Fennoscandia to more anthropogenically polluted air further south, and the influence maritime air over the Baltic and oceanic air advected from the North Atlantic. Anthropogenic pollution occurs in several parts of the study area, and in particular near densely populated areas and megacities, but also in industrialized areas and areas with dense traffic. The aerosol in such areas is quite different from that produced over the boreal forest and has different effects on air quality and climate. Studies have been made on the effects of aerosols on air quality and on the radiation balance in China. The aim of the study is to study the effect of these different regimes on aerosol-cloud interaction using a large aerosol and cloud data set retrieved with the (Advanced) Along Track Scanning Radiometer (A)ATSR Dual View algorithm (ADV) further developed at Finnish Meteorological Institute and aerosol and cloud data provided by MODIS. Retrieval algorithms for aerosol and clouds have been developed for the (A)ATSR, consisting of a series of instruments of which we use the second and third one: ATSR-2 which flew on the ERS-2 satellite (1995-2003) and AATSR which flew on the ENVISAT satellite (2002-2012) (both from the European Space Agency, ESA). The ADV algorithm provides aerosol data on a global scale with a default resolution of 10x10km2 (L2) and an aggregate product on 1x1 degree (L3). Optional, a 1x1 km2 retrieval products is available over smaller areas for specific studies. Since for the retrieval of AOD no prior knowledge is needed on surface properties, the surface reflectance can be independently retrieved using the AOD for atmospheric correction. For the retrieval of cloud properties, the SACURA algorithm has been implemented in the ADV/ASV aerosol retrieval suite. Cloud properties retrieved from AATSR data are cloud fraction, cloud optical thickness, cloud top height, cloud droplet effective radius, liquid water path. Aerosol and cloud properties are applied for different studies over the Eurasia area. Using the simultaneous retrieval of aerosol and cloud properties allows for study of the transition from the aerosol regime to the cloud regime, such as changes in effective radius or AOD (aerosol optical depth) to COT (cloud optical thickness). The column- integrated aerosol extinction, aerosol optical depth or AOD, which is primarily reported from satellite observations, can be used as a proxy for cloud condensation nuclei (CCN) and hence contains information on the ability of aerosol particles to form clouds. Hence, connecting this information with direct observations of cloud properties provides information on aerosol-cloud interactions.

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

NASA Astrophysics Data System (ADS)

Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.

2015-10-01

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 cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

NASA Astrophysics Data System (ADS)

Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.

2015-07-01

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 cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ∼ 0.025), while reducing the differences between AE. We characterize algorithm retrievibility through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

NASA Astrophysics Data System (ADS)

Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-07-01

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 operational remote-sensing algorithms.Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (M{O/Y}D04). The M{O/Y}D04 product is of course normally produced from M{O/Y}D021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a M{O/Y}D021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source.We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

NASA Technical Reports Server (NTRS)

Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-01-01

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 sub grid 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 operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain

NASA Technical Reports Server (NTRS)

Zhu, Jun; Xia, Xiangao; Wang, Jun; Che, Huizheng; Chen, Hongbin; Zhang, Jinqiang; Xu, Xiaoguang; Levy, Robert; Oo, Min; Holz, Robert;

Evaluation of aerosol optical depth and aerosol models from VIIRS retrieval algorithms over North China Plain.

PubMed

Zhu, Jun; Xia, Xiangao; Wang, Jun; Che, Huizheng; Chen, Hongbin; Zhang, Jinqiang; Xu, Xiaoguang; Levy, Robert; Oo, Min; Holz, Robert; Ayoub, Mohammed

2017-01-01

The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on Suomi National Polar-orbiting Partnership (S-NPP) satellite in late 2011. Similar to the Moderate resolution Imaging Spectroradiometer (MODIS), VIIRS observes top-of-atmosphere spectral reflectance and is potentially suitable for retrieval of the aerosol optical depth (AOD). The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. The "MODIS-like" VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the "dark-target" algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012 - 31 March 2014 at three sites. These sites represent three different surface types: urban (Beijing), suburban (XiangHe) and rural (Xinglong). Firstly, we evaluate the retrieved spectral AOD. For the three sites, VIIRS_EDR AOD at 550 nm shows a positive mean bias (MB) of 0.04-0.06 and the correlation of 0.83-0.86, with the largest MB (0.10-0.15) observed in Beijing. In contrast, VIIRS_ML AOD at 550 nm has overall higher positive MB of 0.13-0.14 and a higher correlation (0.93-0.94) with CE318 AOD. Secondly, we evaluate the aerosol model types assumed by each algorithm, as well as the aerosol optical properties used in the AOD retrievals. The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. The overall accuracy rate of the aerosol model used in VIIRS_ML over NCP three sites (0.48) is higher than that of VIIRS_EDR (0.27). The differences in Single Scattering Albedo (SSA) at 670 nm between VIIRS_ML and CE318 are mostly less than 0.015, but high seasonal differences are found especially over the Xinglong site. The values of SSA from VIIRS_EDR are higher than that observed by CE318 over all sites and all assumed aerosol modes, with a positive bias of 0.02-0.04 for fine mode, 0.06-0.12 for coarse mode and 0.03-0.05 for bi-mode at 440nm. The overestimation of SSA but positive AOD MB of VIIRS_EDR indicate that other factors (e.g. surface reflectance characterization or cloud contamination) are important sources of error in the VIIRS_EDR algorithm, and their effects on aerosol retrievals may override the effects from non-ideality in these aerosol models.

An operational MODIS aerosol retrieval algorithm at high spatial resolution, and its application over a complex urban region

NASA Astrophysics Data System (ADS)

Wong, Man Sing; Nichol, Janet E.; Lee, Kwon Ho

2011-03-01

Aerosol retrieval algorithms for the MODerate Resolution Imaging Spectroradiometer (MODIS) have been developed to estimate aerosol and microphysical properties of the atmosphere, which help to address aerosol climatic issues at global scale. However, higher spatial resolution aerosol products for urban areas have not been well-researched mainly due to the difficulty of differentiating aerosols from bright surfaces in urban areas. Here, an aerosol retrieval algorithm using the MODIS 500-m resolution bands is described, to retrieve aerosol properties over Hong Kong and the Pearl River Delta region. The rationale of our technique is to first estimate the aerosol reflectances by decomposing the top-of-atmosphere reflectances from surface reflectances and Rayleigh path reflectances. For the determination of surface reflectances, a Minimum Reflectance Technique (MRT) is used, and MRT images are computed for different seasons. For conversion of aerosol reflectance to aerosol optical thickness (AOT), comprehensive Look Up Tables specific to the local region are constructed, which consider aerosol properties and sun-viewing geometry in the radiative transfer calculations. Four local aerosol types, namely coastal urban, polluted urban, dust, and heavy pollution, were derived using cluster analysis on 3 years of AERONET measurements in Hong Kong. The resulting 500 m AOT images were found to be highly correlated with ground measurements from the AERONET (r2 = 0.767) and Microtops II sunphotometers (r2 = 0.760) in Hong Kong. This study further demonstrates the application of the fine resolution AOT images for monitoring inter-urban and intra-urban aerosol distributions and the influence of trans-boundary flows. These applications include characterization of spatial patterns of AOT within the city, and detection of regional biomass burning sources.

Improvements to the OMI Near-uv Aerosol Algorithm Using A-train CALIOP and AIRS Observations

NASA Technical Reports Server (NTRS)

Torres, O.; Ahn, C.; Zhong, C.

2014-01-01

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.

Columnar aerosol properties over oceans by combining surface and aircraft measurements: sensitivity analysis.

PubMed

Zhang, T; Gordon, H R

1997-04-20

We report a sensitivity analysis for the algorithm presented by Gordon and Zhang [Appl. Opt. 34, 5552 (1995)] for inverting the radiance exiting the top and bottom of the atmosphere to yield the aerosol-scattering phase function [P(?)] and single-scattering albedo (omega(0)). The study of the algorithm's sensitivity to radiometric calibration errors, mean-zero instrument noise, sea-surface roughness, the curvature of the Earth's atmosphere, the polarization of the light field, and incorrect assumptions regarding the vertical structure of the atmosphere, indicates that the retrieved omega(0) has excellent stability even for very large values (~2) of the aerosol optical thickness; however, the error in the retrieved P(?) strongly depends on the measurement error and on the assumptions made in the retrieval algorithm. The retrieved phase functions in the blue are usually poor compared with those in the near infrared.

Evaluation of MODIS columnar aerosol retrievals using AERONET in semi-arid Nevada and California, U.S.A., during the summer of 2012

NASA Astrophysics Data System (ADS)

Loría-Salazar, S. Marcela; Holmes, Heather A.; Patrick Arnott, W.; Barnard, James C.; Moosmüller, Hans

2016-11-01

Satellite characterization of local aerosol pollution is desirable because of the potential for broad spatial coverage, enabling transport studies of pollution from major sources, such as biomass burning events. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging over land because the underlying surface albedo may be heterogeneous in space and time. Ground-based sunphotometer measurements of AOD are unaffected by surface albedo and are crucial in enabling evaluation, testing, and further development of satellite instruments and retrieval algorithms. Columnar aerosol optical properties from ground-based sunphotometers (Cimel CE-318) as part of AERONET and MODIS aerosol retrievals from Aqua and Terra satellites were compared over semi-arid California and Nevada during the summer season of 2012. Sunphotometer measurements were used as a 'ground truth' to evaluate the current state of satellite retrievals in this spatiotemporal domain. Satellite retrieved (MODIS Collection 6) AOD showed the presence of wildfires in northern California during August. During the study period, the dark-target (DT) retrieval algorithm appears to overestimate AERONET AOD by an average factor of 3.85 in the entire study domain. AOD from the deep-blue (DB) algorithm overestimates AERONET AOD by an average factor of 1.64. Low AOD correlation was also found between AERONET, DT, and DB retrievals. Smoke from fires strengthened the aerosol signal, but MODIS versus AERONET AOD correlation hardly increased during fire events (r2∼0.1-0.2 during non-fire periods and r2∼0-0.31 during fire periods). Furthermore, aerosol from fires increased the normalized mean bias (NMB) of MODIS retrievals of AOD (NMB∼23%-154% for non-fire periods and NMB∼77%-196% for fire periods). Ångström Extinction Exponent (AEE) from DB for both Terra and Aqua did not correlate with AERONET observations. High surface reflectance and incorrect aerosol physical parametrizations may still be affecting the DT and DB MODIS AOD retrievals in the semi-arid western U.S.

Validation of MODIS Aerosol Retrieval Over Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Mattoo, Shana; Levy, Robert; Chu, D. Allen; Holben, Brent N.; Dubovik, Oleg; Ahmad, Ziauddin;

Validating and improving long-term aerosol data records from SeaWiFS

NASA Astrophysics Data System (ADS)

Bettenhausen, C.; Hsu, N. C.; Sayer, A. M.; Huang, J.; Gautam, R.

2011-12-01

Natural and anthropogenic aerosols influence the radiative balance of the Earth through direct and indirect interactions with incoming solar radiation. However, the quantification of these interactions and their ultimate effect on the Earth's climate still have large uncertainties. This is partly due to the limitations of current satellite data records which include short satellite lifetimes, retrieval algorithm uncertainty, or insufficient calibration accuracy. We have taken the first steps in overcoming this hurdle with the production and public release of an aerosol data record using the radiances from the Sea-viewing Wide Field-of-View Sensor (SeaWiFS). SeaWiFS was launched in late 1997 and provided exceptionally well-calibrated top-of-atmosphere radiance data until December 2010, more than 13 years. We have partnered this data with an expanded Deep Blue aerosol retrieval algorithm. In accordance with Deep Blue's original focus, the latest algorithm retrieves aerosol properties not only over bright desert surfaces, but also over oceans and vegetated surfaces. With this combination of a long time series and global algorithm, we can finally identify the changing patterns of regional aerosol loading and provide insight into long-term variability and trends of aerosols on regional and global scales. In this work, we provide an introduction to SeaWiFS, the current algorithms, and our aerosol data records. We have validated the data over land and ocean with ground measurements from the Aerosol Robotic Network (AERONET) and compared them with other satellites such as MODIS and MISR. Looking ahead to the next data release, we will also provide details on the implemented and planned algorithm improvements, and subsequent validation results.

Validating and Improving Long-Term Aerosol Data Records from SeaWiFS

NASA Technical Reports Server (NTRS)

Bettenhausen, Corey; Hsu, N. Christina; Sayer, Andrew; Huang, Jinhfeng; Gautam, Ritesh

2011-01-01

Natural and anthropogenic aerosols influence the radiative balance of the Earth through direct and indirect interactions with incoming solar radiation. However, the quantification of these interactions and their ultimate effect on the Earth's climate still have large uncertainties. This is partly due to the limitations of current satellite data records which include short satellite lifetimes, retrieval algorithm uncertainty, or insufficient calibration accuracy. We have taken the first steps in overcoming this hurdle with the production and public release of an aerosol data record using the radiances from the Sea-viewing Wide Field-of-View Sensor (Sea WiFS). Sea WiFS was launched in late 1997 and provided exceptionally well-calibrated top-of-atmosphere radiance data until December 2010, more than 13 years. We have partnered this data with an expanded Deep Blue aerosol retrieval algorithm. In accordance with Deep Blue's original focus, the latest algorithm retrieves aerosol properties not only over bright desert surfaces, but also over oceans and vegetated surfaces. With this combination of a long time series and global algorithm, we can finally identify the changing patterns of regional aerosol loading and provide insight into longterm variability and trends of aerosols on regional and global scales. In this work, we provide an introduction to Sea WiFS, the current algorithms, and our aerosol data records. We have validated the data over land and ocean with ground measurements from the Aerosol Robotic Network (AERONET) and compared them with other satellites such as MODIS and MISR. Looking ahead to the next data release, we will also provide details on the implemented and planned algorithm improvements, and subsequent validation results.

Retrieval and Validation of aerosol optical properties from AHI measurements: impact of surface reflectance assumption

NASA Astrophysics Data System (ADS)

Lim, H.; Choi, M.; Kim, J.; Go, S.; Chan, P.; Kasai, Y.

2017-12-01

This study attempts to retrieve the aerosol optical properties (AOPs) based on the spectral matching method, with using three visible and one near infrared channels (470, 510, 640, 860nm). This method requires the preparation of look-up table (LUT) approach based on the radiative transfer modeling. Cloud detection is one of the most important processes for guaranteed quality of AOPs. Since the AHI has several infrared channels, which are very advantageous for cloud detection, clouds can be removed by using brightness temperature difference (BTD) and spatial variability test. The Yonsei Aerosol Retrieval (YAER) algorithm is basically utilized on a dark surface, therefore a bright surface (e.g., desert, snow) should be removed first. Then we consider the characteristics of the reflectance of land and ocean surface using three visible channels. The known surface reflectivity problem in high latitude area can be solved in this algorithm by selecting appropriate channels through improving tests. On the other hand, we retrieved the AOPs by obtaining the visible surface reflectance using NIR to normalized difference vegetation index short wave infrared (NDVIswir) relationship. ESR tends to underestimate urban and cropland area, we improved the visible surface reflectance considering urban effect. In this version, ocean surface reflectance is using the new cox and munk method which considers ocean bidirectional reflectance distribution function (BRDF). Input of this method has wind speed, chlorophyll, salinity and so on. Based on validation results with the sun-photometer measurement in AErosol Robotic NETwork (AERONET), we confirm that the quality of Aerosol Optical Depth (AOD) from the YAER algorithm is comparable to the product from the Japan Aerospace Exploration Agency (JAXA) retrieval algorithm. Our future update includes a consideration of improvement land surface reflectance by hybrid approach, and non-spherical aerosols. This will improve the quality of YAER algorithm more, particularly retrieval for the dust particle over the bright surface in East Asia.

Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

NASA Technical Reports Server (NTRS)

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

2014-01-01

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] = 0.41tAERONET + 0.16 to tMI [new algorithm] = 0.70tAERONET + 0.01.

An effective inversion algorithm for retrieving bimodal aerosol particle size distribution from spectral extinction data

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Yao, Yuchen; Ruan, Liming

2014-12-01

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.

Retrieval of Aerosol Optical Properties from Ground-Based Remote Sensing Measurements: Aerosol Asymmetry Factor and Single Scattering Albedo

NASA Astrophysics Data System (ADS)

Qie, L.; Li, Z.; Li, L.; Li, K.; Li, D.; Xu, H.

2018-04-01

The Devaux-Vermeulen-Li method (DVL method) is a simple approach to retrieve aerosol optical parameters from the Sun-sky radiance measurements. This study inherited the previous works of retrieving aerosol single scattering albedo (SSA) and scattering phase function, the DVL method was modified to derive aerosol asymmetric factor (g). To assess the algorithm performance at various atmospheric aerosol conditions, retrievals from AERONET observations were implemented, and the results are compared with AERONET official products. The comparison shows that both the DVL SSA and g were well correlated with those of AERONET. The RMSD and the absolute value of MBD deviations between the SSAs are 0.025 and 0.015 respectively, well below the AERONET declared SSA uncertainty of 0.03 for all wavelengths. For asymmetry factor g, the RMSD deviations are smaller than 0.02 and the absolute values of MBDs smaller than 0.01 at 675, 870 and 1020 nm bands. Then, considering several factors probably affecting retrieval quality (i.e. the aerosol optical depth (AOD), the solar zenith angle, and the sky residual error, sphericity proportion and Ångström exponent), the deviations for SSA and g of these two algorithms were calculated at varying value intervals. Both the SSA and g deviations were found decrease with the AOD and the solar zenith angle, and increase with sky residual error. However, the deviations do not show clear sensitivity to the sphericity proportion and Ångström exponent. This indicated that the DVL algorithm is available for both large, non-spherical particles and spherical particles. The DVL results are suitable for the evaluation of aerosol direct radiative effects of different aerosol types.

Aerosol optical properties retrieved from the future space lidar mission ADM-aeolus

NASA Astrophysics Data System (ADS)

Martinet, Pauline; Flament, Thomas; Dabas, Alain

2018-04-01

The ADM-Aeolus mission, to be launched by end of 2017, will enable the retrieval of aerosol optical properties (extinction and backscatter coefficients essentially) for different atmospheric conditions. A newly developed feature finder (FF) algorithm enabling the detection of aerosol and cloud targets in the atmospheric scene has been implemented. Retrievals of aerosol properties at a better horizontal resolution based on the feature finder groups have shown an improvement mainly on the backscatter coefficient compared to the common 90 km product.

Developments in the Aerosol Layer Height Retrieval Algorithm for the Copernicus Sentinel-4/UVN Instrument

NASA Astrophysics Data System (ADS)

Nanda, Swadhin; Sanders, Abram; Veefkind, Pepijn

2016-04-01

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 thickness. We will present the development work around the ALH retrieval algorithm in the framework of the Sentinel-4/UVN instrument. The main challenges are highlighted and retrieval simulation results are provided. Also, an outlook towards application of the S4 bread board algorithm to Sentinel-5 Precursor data later this year will be discussed.

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

NASA Technical Reports Server (NTRS)

Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

2011-01-01

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.

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

NASA Technical Reports Server (NTRS)

Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.

2012-01-01

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

An optimal-estimation-based aerosol retrieval algorithm using OMI near-UV observations

NASA Astrophysics Data System (ADS)

Jeong, U.; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

2016-01-01

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.

An Optimal-Estimation-Based Aerosol Retrieval Algorithm Using OMI Near-UV Observations

NASA Technical Reports Server (NTRS)

Jeong, U; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

2016-01-01

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.

Long-term analysis of aerosol optical depth over Northeast Asia using a satellite-based measurement: MI Yonsei Aerosol Retrieval Algorithm (YAER)

NASA Astrophysics Data System (ADS)

Kim, Mijin; Kim, Jhoon; Yoon, Jongmin; Chung, Chu-Yong; Chung, Sung-Rae

2017-04-01

In 2010, the Korean geostationary earth orbit (GEO) satellite, the Communication, Ocean, and Meteorological Satellite (COMS), was launched including the Meteorological Imager (MI). The MI measures atmospheric condition over Northeast Asia (NEA) using a single visible channel centered at 0.675 μm and four IR channels at 3.75, 6.75, 10.8, 12.0 μm. The visible measurement can also be utilized for the retrieval of aerosol optical properties (AOPs). Since the GEO satellite measurement has an advantage for continuous monitoring of AOPs, we can analyze the spatiotemporal variation of the aerosol using the MI observations over NEA. Therefore, we developed an algorithm to retrieve aerosol optical depth (AOD) using the visible observation of MI, and named as MI Yonsei Aerosol Retrieval Algorithm (YAER). In this study, we investigated the accuracy of MI YAER AOD by comparing the values with the long-term products of AERONET sun-photometer. The result showed that the MI AODs were significantly overestimated than the AERONET values over bright surface in low AOD case. Because the MI visible channel centered at red color range, contribution of aerosol signal to the measured reflectance is relatively lower than the surface contribution. Therefore, the AOD error in low AOD case over bright surface can be a fundamental limitation of the algorithm. Meanwhile, an assumption of background aerosol optical depth (BAOD) could result in the retrieval uncertainty, also. To estimate the surface reflectance by considering polluted air condition over the NEA, we estimated the BAOD from the MODIS dark target (DT) aerosol products by pixel. The satellite-based AOD retrieval, however, largely depends on the accuracy of the surface reflectance estimation especially in low AOD case, and thus, the BAOD could include the uncertainty in surface reflectance estimation of the satellite-based retrieval. Therefore, we re-estimated the BAOD using the ground-based sun-photometer measurement, and investigated the effects of the BAOD assumption. The satellite-based BAOD was significantly higher than the ground-based value over urban area, and thus, resulted in the underestimation of surface reflectance and the overestimation of AOD. The error analysis of the MI AOD also showed sensitivity to cloud contamination, clearly. Therefore, improvements of cloud masking process in the developed single channel MI algorithm as well as the modification of the surface reflectance estimation will be required for the future study.

The Influence of Aerosol Hygroscopicity on Retrieving the Aerosol Extincting Coefficient from MPL Data

NASA Astrophysics Data System (ADS)

Zhao, G.; Zhao, C.

2016-12-01

Micro-pulse Lidar (MPL) measurements have been widely used to profile the ambient aerosol extincting coefficient(). Lidar Ratio (LR) ,which highly depends on the particle number size distribution (PNSD) and aerosol hygroscopicity, is the most important factor to retrieve the profile. A constant AOD constrained LR is usually used in current algorithms, which would lead to large bias when the relative humidity (RH) in the mixed layer is high. In this research, the influences of PNSD, aerosol hygroscopicity and RH profiles on the vertical variation of LR were investigated based on the datasets from field measurements in the North China Plain (NCP). Results show that LR can have an enhancement factor of more than 120% when the RH reaches to 92%. A new algorithm of retrieving the profile is proposed based on the variation of LR due to aerosol hygroscopicity. The magnitude and vertical structures of retrieved using this method can be significantly different to that of the fiexed LR method. The relative difference can reach up to 40% when the RH in the mixed layer is higher than 90% . Sensitivity studies show that RH profile and PNSD affect most on the retrieved by fiexed LR method. In view of this, a scheme of LR enhancement factor by RH is proposed in the NCP. The relative differnce of the calculated between using this scheme and the new algorithm with the variable LR can be less than 10%.

Direct Retrieval of Sulfur Dioxide Amount and Altitude from Spaceborne Hyperspectral UV Measurements: Theory and Application

NASA Technical Reports Server (NTRS)

Yang, Kau; Liu, Xiong; Bhartia, Pawan K.; Krotkov, Nickolay A.; Carn, Simon A.; Hughes, Eric J.; Krueger, Arlin J.; Spurr, Robert D.; Trahan, Samuel G.

2010-01-01

We describe the physical processes by which a vertically localized absorber perturbs the top-of-atmosphere solar backscattered ultraviolet (UV) radiance. The distinct spectral responses to perturbations of an absorber in its column amount and layer altitude provide the basis for a practical satellite retrieval technique, the Extended Iterative Spectral Fitting (EISF) algorithm, for the simultaneous retrieval of these quantities of a SO2 plume. In addition, the EISF retrieval provides an improved UV aerosol index for quantifying the spectral contrast of apparent scene reflectance at the bottom of atmosphere bounded by the surface and/or cloud; hence it can be used for detection of the presence or absence of UV absorbing aerosols. We study the performance and characterize the uncertainties of the EISF algorithm using synthetic backscattered UV radiances, retrievals from which can be compared with those used in the simulation. Our findings indicate that the presence of aerosols (both absorbing and nonabsorbing) does not cause large errors in EISF retrievals under most observing conditions when they are located below the SO2 plume. The EISF retrievals assuming a homogeneous field of view can provide accurate column amounts for inhomogeneous scenes, but they always underestimate the plume altitudes. The EISF algorithm reduces systematic errors present in existing linear retrieval algorithms that use prescribed SO2 plume heights. Applying the EISF algorithm to Ozone Monitoring Instrument satellite observations of the recent Kasatochi volcanic eruption, we demonstrate the successful retrieval of effective plume altitude of volcanic SO2, and we also show the improvement in accuracy in the corresponding SO2 columns.

Retrieval of aerosol properties and water leaving radiance from multi-angle spectro-polarimetric measurement over coastal waters

NASA Astrophysics Data System (ADS)

Gao, M.; Zhai, P.; Franz, B. A.; Hu, Y.; Knobelspiesse, K. D.; Xu, F.; Ibrahim, A.

2017-12-01

Ocean color remote sensing in coastal waters remains a challenging task due to the complex optical properties of aerosols and ocean water properties. It is highly desirable to develop an advanced ocean color and aerosol retrieval algorithm for coastal waters, to advance our capabilities in monitoring water quality, improve our understanding of coastal carbon cycle dynamics, and allow for the development of more accurate circulation models. However, distinguishing the dissolved and suspended material from absorbing aerosols over coastal waters is challenging as they share similar absorption spectrum within the deep blue to UV range. In this paper we report a research algorithm on aerosol and ocean color retrieval with emphasis on coastal waters. The main features of our algorithm include: 1) combining co-located measurements from a hyperspectral ocean color instrument (OCI) and a multi-angle polarimeter (MAP); 2) using the radiative transfer model for coupled atmosphere and ocean system (CAOS), which is based on the highly accurate and efficient successive order of scattering method; and 3) incorporating a generalized bio-optical model with direct accounting of the total absorption of phytoplankton, CDOM and non-algal particles(NAP), and the total scattering of phytoplankton and NAP for improved description of ocean light scattering. The non-linear least square fitting algorithm is used to optimize the bio-optical model parameters and the aerosol optical and microphysical properties including refractive indices and size distributions for both fine and coarse modes. The retrieved aerosol information is used to calculate the atmospheric path radiance, which is then subtracted from the OCI observations to obtain the water leaving radiance contribution. Our work aims to maximize the use of available information from the co-located dataset and conduct the atmospheric correction with minimal assumptions. The algorithm will contribute to the success of current MAP instruments, such as the Research Scanning Polarimeter (RSP), and future ocean color missions, such as the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission, by enabling retrieval of ocean biogeochemical properties under optically-complex atmospheric and oceanic conditions.

Development, Validation, and Potential Enhancements to the Second-Generation Operational Aerosol Product at the National Environmental Satellite, Data, and Information Service of the National Oceanic and Atmospheric Administration

NASA Technical Reports Server (NTRS)

Stowe, Larry L.; Ignatov, Alexander M.; Singh, Ramdas R.

1997-01-01

A revised (phase 2) single-channel algorithm for aerosol optical thickness, tau(sup A)(sub SAT), retrieval over oceans from radiances in channel 1 (0.63 microns) of the Advanced Very High Resolution Radiometer (AVHRR) has been implemented at the National Oceanic and Atmospheric Administration's National Environmental Satellite Data and Information Service for the NOAA 14 satellite launched December 30, 1994. It is based on careful validation of its operational predecessor (phase 1 algorithm), implemented for NOAA 14 in 1989. Both algorithms scale the upward satellite radiances in cloud-free conditions to aerosol optical thickness using an updated radiative transfer model of the ocean and atmosphere. Application of the phase 2 algorithm to three matchup Sun-photometer and satellite data sets, one with NOAA 9 in 1988 and two with NOAA 11 in 1989 and 1991, respectively, show systematic error is less than 10%, with a random error of sigma(sub tau) approx. equal 0.04. First results of tau(sup A)(sub SAT) retrievals from NOAA 14 using the phase 2 algorithm, and from checking its internal consistency, are presented. The potential two-channel (phase 3) algorithm for the retrieval of an aerosol size parameter, such as the Junge size distribution exponent, by adding either channel 2 (0.83 microns) from the current AVHRR instrument, or a 1.6-microns channel to be available on the Tropical Rainfall Measurement Mission and the NOAA-KLM satellites by 1997 is under investigation. The possibility of using this additional information in the retrieval of a more accurate estimate of aerosol optical thickness is being explored.

Extending "Deep Blue" aerosol retrieval coverage to cases of absorbing aerosols above clouds: Sensitivity analysis and first case studies

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-05-01

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.

How Do A-train Sensors Intercompare in the Retrieval of Above-cloud Aerosol Optical Depth? A Case Study-based Assessment

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Waquet, Fabien; Chand, Duli; Hu, Yongxiang

2014-01-01

We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

Aerosol Retrievals Over Land and Water using Deep Blue Algorithm from SeaWiFS and MODIS during UAE2 Field Campaign

NASA Astrophysics Data System (ADS)

Hsu, N.

2005-12-01

The environment in Southwest Asia exhibits one of the most complex situations for aerosol remote sensing from space. Several air masses with different aerosol characteristics commonly converge in this region. In particular, there are often fine mode pollution particles generated from oil industry activities in the Persian Gulf colliding with coarse mode dust particles lifted from desert sources in the surrounding areas. During the course of the UAE field campaign (August-October, 2004), we provided near-real time information, calculated using the Deep Blue algorithm, of satellite aerosol optical thickness and Angstrom exponent over the Southwest Asia region, including the Arabian Peninsula, Iran, Afghanistan, Pakistan, and part of north Africa. In this paper, we will present results of aerosol characteristics retrieved from SeaWiFS and MODIS over the Arabian Peninsula, Persian Gulf, and the Arabian Sea during the UAE experiment. The spectral surface reflectance data base constructed using satellite reflectance from MODIS and SeaWiFS employed in our algorithm will be discussed. We will also compare the resulting satellite retrieved aerosol optical thickness and Angstrom exponent with those obtained from the ground based sun photometers from AERONET in the region. Finally, we will discuss the changes in shortwave and longwave fluxes at the top of atmosphere in response to changes in aerosol optical thickness (i.e. aerosol forcing).

Improvement of Aerosol Optical Depth Retrieval from MODIS Spectral Reflectance over the Global Ocean Using New Aerosol Models Archived from AERONET Inversion Data and Tri-axial Ellipsoidal Dust Database

NASA Technical Reports Server (NTRS)

Lee, J.; Kim, J.; Yang, P.; Hsu, N. C.

2012-01-01

New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the case of high AOD (AOD greater than 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the singlescattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and MODIS for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the MODIS Collection 5 data. Moreover, the percentage of data within an expected error of +/-(0.03 + 0.05xAOD) is increased from 62 percent to 64 percent for overall data and from 39 percent to 51 percent for AOD greater than 0.3. Errors in the retrieved AOD are further characterized with respect to the Angstrom exponent (AE), scattering angle, SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.

Extending 'Deep Blue' aerosol retrieval coverage to cases of absorbing aerosols above clouds: sensitivity analysis and first case studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sayer, Andrew M.; Hsu, C.; Bettenhausen, Corey

Cases of absorbing aerosols above clouds (AAC), 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

Development of an Aerosol Opacity Retrieval Algorithm for Use with Multi-Angle Land Surface Images

NASA Technical Reports Server (NTRS)

Diner, D.; Paradise, S.; Martonchik, J.

1994-01-01

In 1998, the Multi-angle Imaging SpectroRadiometer (MISR) will fly aboard the EOS-AM1 spacecraft. MISR will enable unique methods for retrieving the properties of atmospheric aerosols, by providing global imagery of the Earth at nine viewing angles in four visible and near-IR spectral bands. As part of the MISR algorithm development, theoretical methods of analyzing multi-angle, multi-spectral data are being tested using images acquired by the airborne Advanced Solid-State Array Spectroradiometer (ASAS). In this paper we derive a method to be used over land surfaces for retrieving the change in opacity between spectral bands, which can then be used in conjunction with an aerosol model to derive a bound on absolute opacity.

Retrieval of Aerosol Optical Depth Under Thin Cirrus from MODIS: Application to an Ocean Algorithm

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, Nai-Yung Christina; Sayer, Andrew Mark; Bettenhausen, Corey

2013-01-01

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.

Aeronet-based Microphysical and Optical Properties of Smoke-dominated Aerosol near Source Regions and Transported over Oceans, and Implications for Satellite Retrievals of Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Eck, T. F.; Smirnov, A.; Holben, B. N.

2013-01-01

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.

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)

NASA Technical Reports Server (NTRS)

Kim, M.; Kim, J.; Jeong, U.; Kim, W.; Hong, H.; Holben, B.; Eck, T. F.; Lim, J.; Song, C.; Lee, S.;

The Collection 6 'dark-target' MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Mattoo, Shana; Munchak, Leigh A.; Kleidman, Richard G.; Patadia, Falguni; Gupta, Pawan; Remer, Lorraine

2013-01-01

Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie

Neural Network (NN) retrievals of Stratocumulus cloud properties using multi-angle polarimetric observations during ORACLES

NASA Astrophysics Data System (ADS)

Segal-Rosenhaimer, M.; Knobelspiesse, K. D.; Redemann, J.; Cairns, B.; Alexandrov, M. D.

2016-12-01

The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign is taking place in the South-East Atlantic during the Austral Spring for three consecutive years from 2016-2018. The study area encompasses one of the Earth's three semi-permanent subtropical Stratocumulus (Sc) cloud decks, and experiences very large aerosol optical depths, mainly biomass burning, originating from Africa. Over time, cloud optical depth (COD), lifetime and cloud microphysics (number concentration, effective radii Reff and precipitation) are expected to be influenced by indirect aerosol effects. These changes play a key role in the energetic balance of the region, and are part of the core investigation objectives of the ORACLES campaign, which acquires measurements of clean and polluted scenes of above cloud aerosols (ACA). Simultaneous retrievals of aerosol and cloud optical properties are being developed (e.g. MODIS, OMI), but still challenging, especially for passive, single viewing angle instruments. By comparison, multiangle polarimetric instruments like RSP (Research Scanning Polarimeter) show promise for detection and quantification of ACA, however, there are no operational retrieval algorithms available yet. Here we describe a new algorithm to retrieve cloud and aerosol optical properties from observations by RSP flown on the ER-2 and P-3 during the 2016 ORACLES campaign. The algorithm is based on training a NN, and is intended to retrieve aerosol and cloud properties simultaneously. However, the first step was to establish the retrieval scheme for low level Sc cloud optical properties. The NN training was based on simulated RSP total and polarized radiances for a range of COD, Reff, and effective variances, spanning 7 wavelength bands and 152 viewing zenith angles. Random and correlated noise were added to the simulations to achieve a more realistic representation of the signals. Before introducing the input variables to the network, the signals are projected on a principle component plane that retains the maximal signal information but minimizes the noise contribution. We will discuss parameter choices for the network and present preliminary results of cloud retrievals from ORACLES, compared with standard RSP low-level cloud retrieval method that has been validated against in situ observations.

Aerosol algorithm evaluation within aerosol-CCI

NASA Astrophysics Data System (ADS)

Kinne, Stefan; Schulz, Michael; Griesfeller, Jan

Properties of aerosol retrievals from space are difficult. Even data from dedicated satellite sensors face contaminations which limit the accuracy of aerosol retrieval products. Issues are the identification of complete cloud-free scenes, the need to assume aerosol compositional features in an underdetermined solution space and the requirement to characterize the background at high accuracy. Usually the development of aerosol is a slow process, requiring continuous feedback from evaluations. To demonstrate maturity, these evaluations need to cover different regions and seasons and many different aerosol properties, because aerosol composition is quite diverse and highly variable in space and time, as atmospheric aerosol lifetimes are only a few days. Three years ago the ESA Climate Change Initiative started to support aerosol retrieval efforts in order to develop aerosol retrieval products for the climate community from underutilized ESA satellite sensors. The initial focus was on retrievals of AOD (a measure for the atmospheric column amount) and of Angstrom (a proxy for aerosol size) from the ATSR and MERIS sensors on ENVISAT. The goal was to offer retrieval products that are comparable or better in accuracy than commonly used NASA products of MODIS or MISR. Fortunately, accurate reference data of ground based sun-/sky-photometry networks exist. Thus, retrieval assessments could and were conducted independently by different evaluation groups. Here, results of these evaluations for the year 2008 are summarized. The capability of these newly developed retrievals is analyzed and quantified in scores. These scores allowed a ranking of competing efforts and also allow skill comparisons of these new retrievals against existing and commonly used retrievals.

Preliminary results of the aerosol optical depth retrieval in Johor, Malaysia

NASA Astrophysics Data System (ADS)

Lim, H. Q.; Kanniah, K. D.; Lau, A. M. S.

2014-02-01

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.

Simultaneous aerosol/ocean products retrieved during the 2014 SABOR campaign using the NASA Research Scanning Polarimeter (RSP)

NASA Astrophysics Data System (ADS)

Stamnes, S.; Hostetler, C. A.; Ferrare, R. A.; Hair, J. W.; Burton, S. P.; Liu, X.; Hu, Y.; Stamnes, K. H.; Chowdhary, J.; Brian, C.

2017-12-01

The SABOR (Ship-Aircraft Bio-Optical Research) campaign was conducted during the summer of 2014, in the Atlantic Ocean, over the Chesapeake Bay and the eastern coastal region of the United States. The NASA GISS Research Scanning Polarimeter, a multi-angle, multi-spectral polarimeter measured the upwelling polarized radiances from a B200 aircraft. We present results from the new "MAPP" algorithm for RSP that is based on optimal estimation and that can retrieve simultaneous aerosol microphysical properties (including effective radius, single-scattering albedo, and real refractive index) and ocean color products using accurate radiative transfer and Mie calculations. The algorithm was applied to data collected during SABOR to retrieve aerosol microphysics and ocean products for all Aerosols-Above-Ocean (AAO) scenes. The RSP MAPP products are compared against collocated aerosol extinction and backscatter profiles collected by the NASA LaRC airborne High Spectral Resolution Lidar (HSRL-1), including lidar depth profiles of the ocean diffuse attenuation coefficient and the hemispherical backscatter coefficient.

Improved MODIS aerosol retrieval in urban areas using a land classification approach and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Levitan, Nathaniel; Gross, Barry

2016-10-01

New, high-resolution aerosol products are required in urban areas to improve the spatial coverage of the products, in terms of both resolution and retrieval frequency. These new products will improve our understanding of the spatial variability of aerosols in urban areas and will be useful in the detection of localized aerosol emissions. Urban aerosol retrieval is challenging for existing algorithms because of the high spatial variability of the surface reflectance, indicating the need for improved urban surface reflectance models. This problem can be stated in the language of novelty detection as the problem of selecting aerosol parameters whose effective surface reflectance spectrum is not an outlier in some space. In this paper, empirical orthogonal functions, a reconstruction-based novelty detection technique, is used to perform single-pixel aerosol retrieval using the single angular and temporal sample provided by the MODIS sensor. The empirical orthogonal basis functions are trained for different land classes using the MODIS BRDF MCD43 product. Existing land classification products are used in training and aerosol retrieval. The retrieval is compared against the existing operational MODIS 3 KM Dark Target (DT) aerosol product and co-located AERONET data. Based on the comparison, our method allows for a significant increase in retrieval frequency and a moderate decrease in the known biases of MODIS urban aerosol retrievals.

Aerosol layer height from synergistic use of VIIRS and OMPS

NASA Astrophysics Data System (ADS)

Lee, J.; Hsu, N. Y. C.; Sayer, A. M.; Kim, W.; Seftor, C. J.

2017-12-01

This study presents an Aerosol Single-scattering albedo and Height Estimation (ASHE) algorithm, which retrieves the height of UV-absorbing aerosols by synergistically using the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Ozone Mapping and Profiler Suite (OMPS). ASHE provides height information over a much broader area than ground-based or spaceborne lidar measurements by benefitting from the wide swaths of the two instruments used. As determination of single-scattering albedo (SSA) of the aerosol layer is the most critical part for the performance and coverage of ASHE, here we demonstrate three different strategies to constrain the SSA. First, ASHE is able to retrieve the SSA of UV-absorbing aerosols when Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) provides vertical profiles of the aerosol layer of interest. Second, Aerosol Robotic Network (AERONET) inversions can directly constrain the SSA of the aerosol layer when collocated with VIIRS or OMPS. Last, a SSA climatology from ASHE, AERONET, or other data sources can be used for large-scale, aged aerosol events, for which climatological SSA is well-known, at the cost of a slight decrease in retrieval accuracy. The same algorithm can be applied to measurements of similar type, such as those made by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI), for a long-term, consistent data record.

Evaluating the Assumptions of Surface Reflectance and Aerosol Type Selection Within the MODIS Aerosol Retrieval Over Land: The Problem of Dust Type Selection

NASA Technical Reports Server (NTRS)

Mielonen, T.; Levy, R. C.; Aaltonen, V.; Komppula, M.; de Leeuw, G.; Huttunen, J.; Lihavainen, H.; Kolmonen, P.; Lehtinen, K. E. J.; Arola, A.

2011-01-01

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.

Creating Aerosol Types from CHemistry (CATCH): A New Algorithm to Extend the Link Between Remote Sensing and Models

NASA Astrophysics Data System (ADS)

Dawson, K. W.; Meskhidze, N.; Burton, S. P.; Johnson, M. S.; Kacenelenbogen, M. S.; Hostetler, C. A.; Hu, Y.

2017-11-01

Current remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH-derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first-generation airborne High Spectral Resolution Lidar (HSRL-1) retrievals during the Ship-Aircraft Bio-Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH-derived aerosol types are determined by multivariate clustering of model-calculated variables that have been trained using retrievals of aerosol types from HSRL-1. CATCH-derived aerosol types (with the exception of smoke) compare well with HSRL-1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System- with Chemistry (GEOS-Chem) model. Spatial distributions of CATCH-derived aerosol types for the North American model domain during July/August 2014 show that aerosol type-specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model-generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL-1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

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

PubMed

Stamnes, S; Hostetler, C; Ferrare, R; Burton, S; Liu, X; Hair, J; Hu, Y; Wasilewski, A; Martin, W; van Diedenhoven, B; Chowdhary, J; Cetinić, I; Berg, L K; Stamnes, K; Cairns, B

2018-04-01

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stamnes, S.; Hostetler, C.; Ferrare, R.

We present an optimal estimation based retrieval framework, the Microphysical Aerosol Properties from Polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High Spectral Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355, 532, and 1064 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ã…ngstrømmore » exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio- Optical Research (SABOR) campaign. For the SABOR campaign, 71% RSP MAPP retrievals fall within 0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.925 and root-mean-square deviation of 0.04. For the TCAP campaign, 55% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.925 and root-mean-square deviation of 0.07. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.96 and a root-mean-square deviation of also 0.07. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar+polarimeter retrieval using both HSRL and RSP measurements.« less

An Observing System Simulation Experiment (OSSE) Investigating the OMI Aerosol Products Using Simulated Aerosol and Atmospheric Fields from the NASA GEOS-5 Model

NASA Astrophysics Data System (ADS)

Colarco, P. R.; Gasso, S.; Jethva, H. T.; Buchard, V.; Ahn, C.; Torres, O.; daSilva, A.

2016-12-01

Output from the NASA Goddard Earth Observing System, version 5 (GEOS-5) Earth system model is used to simulate the top-of-atmosphere 354 and 388 nm radiances observed by the Ozone Monitoring Instrument (OMI) onboard the Aura spacecraft. The principle purpose of developing this simulator tool is to compute from the modeled fields the so-called OMI Aerosol Index (AI), which is a more fundamental retrieval product than higher level products such as the aerosol optical depth (AOD) or absorbing aerosol optical depth (AAOD). This lays the groundwork for eventually developing a capability to assimilate either the OMI AI or its radiances, which would provide further constraint on aerosol loading and absorption properties for global models. We extend the use of the simulator capability to understand the nature of the OMI aerosol retrieval algorithms themselves in an Observing System Simulation Experiment (OSSE). The simulated radiances are used to calculate the AI from the modeled fields. These radiances are also provided to the OMI aerosol algorithms, which return their own retrievals of the AI, AOD, and AAOD. Our assessment reveals that the OMI-retrieved AI can be mostly harmonized with the model-derived AI given the same radiances provided a common surface pressure field is assumed. This is important because the operational OMI algorithms presently assume a fixed pressure field, while the contribution of molecular scattering to the actual OMI signal in fact responds to the actual atmospheric pressure profile, which is accounted for in our OSSE by using GEOS-5 produced atmospheric reanalyses. Other differences between the model and OMI AI are discussed, and we present a preliminary assessment of the OMI AOD and AAOD products with respect to the known inputs from the GEOS-5 simulation.

A New Satellite Aerosol Retrieval Using High Spectral Resolution Oxygen A-Band Measurements

NASA Astrophysics Data System (ADS)

Winker, D. M.; Zhai, P.

2014-12-01

Efforts to advance current satellite aerosol retrieval capabilities have mostly focused on polarimetric techniques. While there has been much interest in recent decades in the use of the oxygen A-band for retrievals of cloud height or surface pressure, these techniques are mostly based on A-band measurements with relatively low spectral resolution. We report here on a new aerosol retrieval technique based on high-resolution A-band spectra. Our goal is the development of a technique to retrieve aerosol absorption, one of the critical parameters affecting the global radiation budget and one which is currently poorly constrained by satellite measurements. Our approach relies on two key factors: 1) the use of high spectral resolution measurements which resolve the A-band line structure, and 2) the use of co-located lidar profile measurements to constrain the vertical distribution of scatterers. The OCO-2 satellite, launched in July this year and now flying in formation with the CALIPSO satellite, carries an oxygen A-band spectrometer with a spectral resolution of 21,000:1. This is sufficient to resolve the A-band line structure, which contains information on atmospheric photon path lengths. Combining channels with oxygen absorption ranging from weak to strong allows the separation of atmospheric and surface scattering. An optimal estimation algorithm for simultaneous retrieval of aerosol optical depth, aerosol absorption, and surface albedo has been developed. Lidar profile data is used for scene identification and to provide constraints on the vertical distribution of scatterers. As calibrated OCO-2 data is not expected until the end of this year, the algorithm has been developed and tested using simulated OCO-2 spectra. The simulations show that AOD and surface albedo can be retrieved with high accuracy. Retrievals of aerosol single scatter albedo are encouraging, showing good performance when AOD is larger than about 0.15. Retrieval performance improves as the albedo of the underlying surface increases. Thus, the technique shows great promise for retrieving the absorption optical depth of aerosols located above clouds. This presentation will discuss the basis of the approach and results of the A-band/lidar retrievals based on simulated data.

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-01-01

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.

The influence of aerosols and land-use type on NO2 satellite retrieval over China

NASA Astrophysics Data System (ADS)

Liu, Mengyao; Lin, Jintai; Boersma, Folkert; Eskes, Henk; Chimot, Julien

2017-04-01

Both aerosols and surface reflectance have a strong influence on the retrieval of NO2 tropospheric vertical column densities (VCDs), especially over China with its heavy aerosol loading and rapid changes in land-use type. However, satellite retrievals of NO2 VCDs usually do not explicitly account for aerosol optical effects and surface reflectance anisotropy (BRDF) that varies in space and time. We develop an improved algorithm to derive tropospheric AMFs and VCDs over China from the OMI instrument - POMINO and DOMINO. This method can also be applied to TropOMI NO2 retrievals in the future. With small pixels of TropOMI and higher probability of encountering clear-sky scenes, the influence of BRDF and aerosol interference becomes more important than for OMI. Daily aerosol information is taken from the GEOS-Chem chemistry transport model and the aerosol optical depth (AOD) is adjusted via MODIS AOD climatology. We take the MODIS MCD43C2 C5 product to account for BRDF effects. The relative altitude of NO2 and aerosols is critical factor influencing the NO2 retrieval. In order to evaluate the aerosol extinction profiles (AEP) of GEOS-Chem improve our algorithm, we compare the GEOS-Chem simulation with CALIOP and develop a CALIOP AEP climatology to regulate the model's AEP. This provides a new way to include aerosol information into the tracer gas retrieval for OMI and TropOMI. Preliminary results indicate that the model performs reasonably well in reproducing the AEP shape. However, it seems to overestimate aerosols under 2km and underestimate above. We find that relative humidity (RH) is an important factor influencing the AEP shape when comparing the model with observations. If we adjust the GEOS-Chem RH to CALIOP's RH, the correlations of their AEPs also improve. Besides, take advantage of our retrieval method, we executed sensitivity tests to analyze their influences on NO2 trend and spatiotemporal variations in retrieval. It' the first time to investigate influence from aerosols and surface reflectance in 10-year period (2005-2015) in the real retrieval. We find their influences are largely time and space dependent, but their effects on trend are small, leading relative 7% differences in different areas.

Development of a generalized multi-pixel and multi-parameter satellite remote sensing algorithm for aerosol properties

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Takenaka, H.; Higurashi, A.

2013-12-01

We develop a new satellite remote sensing algorithm to retrieve the properties of aerosol particles in the atmosphere. In late years, high resolution and multi-wavelength, and multiple-angle observation data have been obtained by grand-based spectral radiometers and imaging sensors on board the satellite. With this development, optimized multi-parameter remote sensing methods based on the Bayesian theory have become popularly used (Turchin and Nozik, 1969; Rodgers, 2000; Dubovik et al., 2000). Additionally, a direct use of radiation transfer calculation has been employed for non-linear remote sensing problems taking place of look up table methods supported by the progress of computing technology (Dubovik et al., 2011; Yoshida et al., 2011). We are developing a flexible multi-pixel and multi-parameter remote sensing algorithm for aerosol optical properties. In this algorithm, the inversion method is a combination of the MAP method (Maximum a posteriori method, Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, we include a radiation transfer calculation code, Rstar (Nakajima and Tanaka, 1986, 1988), numerically solved each time in iteration for solution search. The Rstar-code has been directly used in the AERONET operational processing system (Dubovik and King, 2000). Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine mode, sea salt, and dust particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area. We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. In this test, we simulated satellite-observed radiances for a sub-domain consisting of 5 by 5 pixels by the Rstar code assuming wavelengths of 380, 674, 870 and 1600 [nm], atmospheric condition of the US standard atmosphere, and the several aerosol and ground surface conditions. The result of the experiment showed that AOTs of fine mode and dust particles, soot fraction and ground surface albedo at the wavelength of 674 [nm] are retrieved within absolute value differences of 0.04, 0.01, 0.06 and 0.006 from the true value, respectively, for the case of dark surface, and also, for the case of blight surface, 0.06, 0.03, 0.04 and 0.10 from the true value, respectively. We will conduct more tests to study the information contents of parameters needed for aerosol and land surface remote sensing with different boundary conditions among sub-domains.

A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

2010-07-01

A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 μm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sun-glint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.

A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

2010-03-01

A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 μm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sun-glint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.

Beyond MODIS: Developing an aerosol climate data record

NASA Astrophysics Data System (ADS)

Levy, R. C.; Mattoo, S.; Munchak, L. A.; Patadia, F.; Laszlo, I.; Holz, R.

2013-12-01

As defined by the National Research Council, a climate data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. As one of our most pressing research questions concerns changes in global direct aerosol radiative forcing (DARF), creating an aerosol CDR is of high importance. To reduce our uncertainties in DARF, we need uncertainty in global aerosol optical depth (AOD) reduced to ×0.02 or better, or about 10% of global mean AOD (~0.15-0.20). To quantify aerosol trends with significance, we also need a stable time series at least 20-30 years. By this Fall-2013 AGU meeting, the Moderate Resolution Imaging Spectrometer (MODIS) has been flying on NASA's Terra and Aqua satellites for 14 years and 11.5 years, respectively. During this time, we have fine-tuned the aerosol retrieval algorithms and data processing protocols, resulting in a well characterized product of aerosol optical depth (AOD). MODIS AOD has been extensively compared to ground-based sunphotometer data, showing per-retrieval expected error (EE) of ×(0.03 + 5%) over ocean, and has been generally adopted as a robust and stable environmental data record (EDR). With the 2011 launch of the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, we have begun a new aerosol time series. The VIIRS AOD product has stabilized to the point where, compared to ground-based AERONET sunphotometer, the VIIRS AOD is within similar EE envelope as MODIS. Thus, if VIIRS continues to perform as expected, it too can provide a robust and stable aerosol EDR. What will it take to stitch MODIS and VIIRS into a robust aerosol CDR? Based on the recent experience of MODIS 'Collection 6' development, there are many details of aerosol retrieval that each lead to ×0.01 uncertainties in global AOD. These include 'radiative transfer' assumptions such as calculations for gas absorption and sea-level Rayleigh optical depth, 'decision making' assumptions such as cloud masking and pixel selection, as well as 'retrieval' assumptions such as aerosol type, and surface reflectance model. Also there are instrument issues such as calibration and geo-location, which even on the level of 1-2%, will lead to 10% error in retrieved AOD. At this point, however, many of these issues have been solved, or are being quantified for MODIS and VIIRS. In the past year, we created a generic dark-target aerosol retrieval algorithm, which can be applied to MODIS, VIIRS, or any other sensor with a similar set of wavelength bands. We applied the same radiative transfer codes for creating lookup tables, the same protocols for deriving non-aerosol assumptions, and the same criteria for cloud masking. Although there are still inconsistencies to work out, this generic algorithm is being applied to selected months having VIIRS/MODIS overlap. Comparing to AERONET, and with each other, we quantify the statistical agreement between MODIS and VIIRS, both for the official algorithms run on each sensor, as well as for our generic algorithm run on both.

Earlinet single calculus chain: new products overview

NASA Astrophysics Data System (ADS)

D'Amico, Giuseppe; Mattis, Ina; Binietoglou, Ioannis; Baars, Holger; Mona, Lucia; Amato, Francesco; Kokkalis, Panos; Rodríguez-Gómez, Alejandro; Soupiona, Ourania; Kalliopi-Artemis, Voudouri

2018-04-01

The Single Calculus Chain (SCC) is an automatic and flexible tool to analyze raw lidar data using EARLINET quality assured retrieval algorithms. It has been already demonstrated the SCC can retrieve reliable aerosol backscatter and extinction coefficient profiles for different lidar systems. In this paper we provide an overview of new SCC products like particle linear depolarization ratio, cloud masking, aerosol layering allowing relevant improvements in the atmospheric aerosol characterization.

Aerosol Remote Sensing

NASA Technical Reports Server (NTRS)

Lenoble, Jacqueline (Editor); Remer, Lorraine (Editor); Tanre, Didier (Editor)

2012-01-01

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

Regional variation of carbonaceous aerosols from space and simulations

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Sano, Itaru; Nakata, Makiko; Kokhanovsky, Alexander

2017-04-01

Satellite remote sensing provides us with a systematic monitoring in a global scale. As such, aerosol observation via satellites is known to be useful and effective. However, before attempting to retrieve aerosol properties from satellite data, the efficient algorithms for aerosol retrieval need to be considered. The characteristics and distributions of atmospheric aerosols are known to be complicated, owing to both natural factors and human activities. It is known that the biomass burning aerosols generated by the large-scale forest fires and burn agriculture have influenced the severity of air pollution. Nevertheless the biomass burning episodes increase due to global warming and climate change and vice versa. It is worth noting that the near ultra violet (NUV) measurements are helpful for the detection of carbonaceous particles, which are the main component of aerosols from biomass burning. In this work, improved retrieval algorithms for biomass burning aerosols are shown by using the measurements observed by GLI and POLDER-2 on Japanese short term mission ADEOS-2 in 2003. The GLI sensor has 380nm channel. For detection of biomass burning episodes, the aerosol optical thickness of carbonaceous aerosols simulated with the numerical model simulations (SPRINTARS) is available as well as fire products from satellite imagery. Moreover the algorithm using shorter wavelength data is available for detection of absorbing aerosols. An algorithm based on the combined use of near-UV and violet data has been introduced in our previous work with ADEOS (Advanced Earth Observing Satellite) -2 /GLI measurements [1]. It is well known that biomass burning plume is a seasonal phenomenon peculiar to a particular region. Hence, the mass concentrations of aerosols are frequently governed with spatial and/or temporal variations of biomass burning plumes. Accordingly the satellite data sets for our present study are adopted from the view points of investigation of regional and seasonal effect on carbonaceous aerosols. And then the selected data observed by ADEOS-2/GLI and POLDER in 2003 are treated by using Vector form Method of Successive Order of Scattering (VMSOS) for radiative transfer simulations in the semi-infinite atmosphere [2]. Finally the obtained optical properties of the carbonaceous aerosols are investigated in comparison with the numerical model simulations of SPRINTARS. In spite of the limited case studies, it has been pointed out that NUV-channel data are effective for retrieval of the carbonaceous aerosol properties. Therefore we have to treat with this issue for not only detection of biomass burning plume but also retrieval itself. If that happens, synthetic analysis based on multi-channel and/or polarization measurements become practical, and the proposed procedure and results are available for a feasibility study of coming space missions. [1] Sano, I., Y. Okada, M. Mukai and S. Mukai, "Retrieval algorithm based on combined use of POLDER and GLI data for biomass aerosols," J. RSSJ, vol. 29, no. 1, pp. 54-59, doi:10.11440/rssj.29.54, 2009. [2] Mukai, S., M. Nakata, M. Yasumoto, I. Sano and A. Kokhanovsky, "A study of aerosol pollution episode due to agriculture biomass burning in the east-central China using satellite data," Front. Environ. Sci., vol. 3:57, doi:　10.3389/fenvs.2015.00057, 2015.

Verification, improvement and application of aerosol optical depths in China Part 1: Inter-comparison of NPP-VIIRS and Aqua-MODIS

NASA Astrophysics Data System (ADS)

Wei, Jing; Sun, Lin; Huang, Bo; Bilal, Muhammad; Zhang, Zhaoyang; Wang, Lunche

2018-02-01

The objective of this study is to evaluate typical aerosol optical depth (AOD) products in China, which experienced seriously increasing atmospheric particulate pollution. For this, the Aqua-MODerate resolution Imaging Spectroradiometer (MODIS) AOD products (MYD04) at 10 km spatial resolution and Visible Infrared Imaging Radiometer Suite (VIIRS) Environmental Data Record (EDR) AOD product at 6 km resolution for different Quality Flags (QF) are obtained for validation against AErosol RObotic NETwork (AERONET) AOD measurements during 2013-2016. Results show that VIIRS EDR similarly Dark Target (DT) and MODIS DT algorithms perform worse with only 45.36% and 45.59% of the retrievals (QF = 3) falling within the Expected Error (EE, ±(0.05 + 15%)) compared to the Deep Blue (DB) algorithm (69.25%, QF ≥ 2). The DT retrievals perform poorly over the Beijing-Tianjin-Hebei (BTH) and Yangtze-River-Delta (YRD) regions, which significantly overestimate the AOD observations, but the performance is better over the Pearl-River-Delta (PRD) region than DB retrievals, which seriously under-estimate the AOD loadings. It is not surprising that the DT algorithm performs better over vegetated areas, while the DB algorithm performs better over bright areas mainly depends on the accuracy of surface reflectance estimation over different land use types. In general, the sensitivity of aerosol to apparent reflectance reduces by about 34% with an increasing surface reflectance by 0.01. Moreover, VIIRS EDR and MODIS DT algorithms perform overall better in the winter as 64.53% and 72.22% of the retrievals are within the EE but with less retrievals. However, the DB algorithm performs worst (57.17%) in summer mainly affected by the vegetation growth but there are overall high accuracies with more than 62% of the collections falling within the EE in other three seasons. Results suggest that the quality assurance process can help improve the overall data quality for MYD04 DB retrievals, but it is not always true for VIIRS EDR and MYD04 DT AOD retrievals.

A-Train Aerosol Observations Preliminary Comparisons with AeroCom Models and Pathways to Observationally Based All-Sky Estimates

NASA Technical Reports Server (NTRS)

Redemann, J.; Livingston, J.; Shinozuka, Y.; Kacenelenbogen, M.; Russell, P.; LeBlanc, S.; Vaughan, M.; Ferrare, R.; Hostetler, C.; Rogers, R.;

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Petrenko, Maksym; Ichoku, Charles

2012-01-01

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.

Hyperspectral retrieval of surface reflectances: A new scheme

NASA Astrophysics Data System (ADS)

Thelen, Jean-Claude; Havemann, Stephan

2013-05-01

Here, we present a new prototype algorithm for the simultaneous retrieval of the atmospheric profiles (temperature, humidity, ozone and aerosol) and the surface reflectance from hyperspectral radiance measurements obtained from air/space borne, hyperspectral imagers. The new scheme, proposed here, consists of a fast radiative transfer code, based on empirical orthogonal functions (EOFs), in conjunction with a 1D-Var retrieval scheme. The inclusion of an 'exact' scattering code based on spherical harmonics, allows for an accurate treatment of Rayleigh scattering and scattering by aerosols, water droplets and ice-crystals, thus making it possible to also retrieve cloud and aerosol optical properties, although here we will concentrate on non-cloudy scenes.

Lessons learned and way forward from 6 years of Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, Thomas; de Leeuw, Gerrit; Pinnock, Simon

2017-04-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve and qualify algorithms for the retrieval of aerosol information from European sensors. Meanwhile, several validated (multi-) decadal time series of different aerosol parameters from complementary sensors are available: Aerosol Optical Depth (AOD), stratospheric extinction profiles, a qualitative Absorbing Aerosol Index (AAI), fine mode AOD, mineral dust AOD; absorption information and aerosol layer height are in an evaluation phase and the multi-pixel GRASP algorithm for the POLDER instrument is used for selected regions. Validation (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account in an iterative evolution cycle. The datasets contain pixel level uncertainty estimates which were also validated and improved in the reprocessing. The use of an ensemble method was tested, where several algorithms are applied to the same sensor. The presentation will summarize and discuss the lessons learned from the 6 years of intensive collaboration and highlight major achievements (significantly improved AOD quality, fine mode AOD, dust AOD, pixel level uncertainties, ensemble approach); also limitations and remaining deficits shall be discussed. An outlook will discuss the way forward for the continuous algorithm improvement and re-processing together with opportunities for time series extension with successor instruments of the Sentinel family and the complementarity of the different satellite aerosol products.

17 years of aerosol and clouds from the ATSR Series of Instruments

NASA Astrophysics Data System (ADS)

Poulsen, C. A.

2015-12-01

Aerosols play a significant role in Earth's climate by scattering and absorbing incoming sunlight and affecting the formation and radiative properties of clouds. The extent to which aerosols affect cloud remains one of the largest sources of uncertainty amongst all influences on climate change. Now, a new comprehensive datasets has been developed under the ESA Climate Change Initiative (CCI) programme to quantify how changes in aerosol levels affect these clouds. The unique dataset is constructed from the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm used in (A)ATSR (Along Track Scanning Radiometer) retrievals of aerosols generated in the Aerosol CCI and the CC4CL ( Community Code for CLimate) for cloud retrieval in the Cloud CCI. The ATSR instrument is a dual viewing instrument with on board visible and infra red calibration systems making it an ideal instrument to study trends of Aerosol and Clouds and their interactions. The data set begins in 1995 and ends in 2012. A new instrument in the series SLSTR(Sea and Land Surface Temperature Radiometer) will be launch in 2015. The Aerosol and Clouds are retreived using similar algorithms to maximise the consistency of the results These state-of-the-art retrievals have been merged together to quantify the susceptibility of cloud properties to changes in aerosol concentration. Aerosol-cloud susceptibilities are calculated from several thousand samples in each 1x1 degree globally gridded region. Two-D histograms of the aerosol and cloud properties are also included to facilitate seamless comparisons between other satellite and modelling data sets. The analysis of these two long term records will be discussed individually and the initial comparisons between these new joint products and models will be presented.

Aerosol Correction for Improving OMPS/LP Ozone Retrieval

NASA Technical Reports Server (NTRS)

Chen, Zhong; Bhartia, Pawan K.; Loughman, Robert

2015-01-01

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.

Joint retrieval of aerosol and water-leaving radiance from multispectral, multiangular and polarimetric measurements over ocean

NASA Astrophysics Data System (ADS)

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.

2016-07-01

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, three different types of aerosols, and nine combinations of solar incidence and viewing geometries.

10 Years of Asian Dust Storm Observations from SeaWiFS: Source, Pathway, and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, S.-C.; King, M.D.; Jeong, M.-J.

2008-01-01

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, 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 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. The multiyear satellite measurements (1998 - 2007) from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Eyjafjallajokull Volcano Plume Particle-Type Characterization from Space-Based Multi-angle Imaging

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Limbacher, James

2012-01-01

The Multi-angle Imaging SpectroRadiometer (MISR) Research Aerosol algorithm makes it possible to study individual aerosol plumes in considerable detail. From the MISR data for two optically thick, near-source plumes from the spring 2010 eruption of the Eyjafjallaj kull volcano, we map aerosol optical depth (AOD) gradients and changing aerosol particle types with this algorithm; several days downwind, we identify the occurrence of volcanic ash particles and retrieve AOD, demonstrating the extent and the limits of ash detection and mapping capability with the multi-angle, multi-spectral imaging data. Retrieved volcanic plume AOD and particle microphysical properties are distinct from background values near-source, as well as for overwater cases several days downwind. The results also provide some indication that as they evolve, plume particles brighten, and average particle size decreases. Such detailed mapping offers context for suborbital plume observations having much more limited sampling. The MISR Standard aerosol product identified similar trends in plume properties as the Research algorithm, though with much smaller differences compared to background, and it does not resolve plume structure. Better optical analogs of non-spherical volcanic ash, and coincident suborbital data to validate the satellite retrieval results, are the factors most important for further advancing the remote sensing of volcanic ash plumes from space.

MODIS 3km Aerosol Product: Algorithm and Global Perspective

NASA Technical Reports Server (NTRS)

Remer, L. A.; Mattoo, S.; Levy, R. C.; Munchak, L.

2013-01-01

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.

Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

2012-01-01

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.

Measurement of phase function of aerosol at different altitudes by CCD Lidar

NASA Astrophysics Data System (ADS)

Sun, Peiyu; Yuan, Ke'e.; Yang, Jie; Hu, Shunxing

2018-02-01

The aerosols near the ground are closely related to human health and climate change, the study on which has important significance. As we all know, the aerosol is inhomogeneous at different altitudes, of which the phase function is also different. In order to simplify the retrieval algorithm, it is usually assumed that the aerosol is uniform at different altitudes, which will bring measurement error. In this work, an experimental approach is demonstrated to measure the scattering phase function of atmospheric aerosol particles at different heights by CCD lidar system, which could solve the problem of the traditional CCD lidar system in assumption of phase function. The phase functions obtained by the new experimental approach are used to retrieve the aerosol extinction coefficient profiles. By comparison of the aerosol extinction coefficient retrieved by Mie-scattering aerosol lidar and CCD lidar at night, the reliability of new experimental approach is verified.

Assessment and application of AirMSPI high-resolution multiangle imaging photo-polarimetric observations for atmospheric correction

NASA Astrophysics Data System (ADS)

Kalashnikova, O. V.; Xu, F.; Garay, M. J.; Seidel, F. C.; Diner, D. J.

2016-02-01

Water-leaving radiance comprises less than 10% of the signal measured from space, making correction for absorption and scattering by the intervening atmosphere imperative. Modern improvements have been developed in ocean color retrieval algorithms to handle absorbing aerosols such as urban particulates in coastal areas and transported desert dust over the open ocean. In addition, imperfect knowledge of the absorbing aerosol optical properties or their height distribution results in well-documented sources of error in the retrieved water leaving radiance. Multi-angle spectro-polarimetric measurements have been advocated as an additional tool to better understand and retrieve the aerosol properties needed for atmospheric correction for ocean color retrievals. The Airborne Multiangle SpectroPolarimetric Imager-1 (AirMSPI-1) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI typically acquires observations of a target area at 9 view angles between ±67° at 10 m resolution. AirMSPI spectral channels are centered at 355, 380, 445, 470, 555, 660, and 865 nm, with 470, 660, and 865 reporting linear polarization. We have developed a retrieval code that employs a coupled Markov Chain (MC) and adding/doubling radiative transfer method for joint retrieval of aerosol properties and water leaving radiance from AirMSPI polarimetric observations. We tested prototype retrievals by comparing the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentrations to values reported by the USC SeaPRISM AERONET-OC site off the coast of California. The retrieval then was applied to a variety of costal regions in California to evaluate variability in the water-leaving radiance under different atmospheric conditions. We will present results, and will discuss algorithm sensitivity and potential applications for future space-borne coastal monitoring.

MODIS Aerosol Optical Depth retrieval over land considering surface BRDF effects

NASA Astrophysics Data System (ADS)

Wu, Yerong; de Graaf, Martin; Menenti, Massimo

2016-04-01

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 measurements in our algorithm. We validated three case studies with AErosol Robotic NETwork (AERONET) AOD, and the results show that the AOD retrieval was improved compared to C6_DT AOD, with the increase of within expected accuracy ±(0.05 + 15%) by ranging from 2.7% to 7.5% for the best quality only (Quality Assurance =3), and from 5.8% to 9.5% for the marginal and better quality (Quality Assurance ≥ 1).

A High-Resolution Aerosol Retrieval Method for Urban Areas Using MISR Data

NASA Astrophysics Data System (ADS)

Moon, T.; Wang, Y.; Liu, Y.; Yu, B.

2012-12-01

Satellite-retrieved Aerosol Optical Depth (AOD) can provide a cost-effective way to monitor particulate air pollution without using expensive ground measurement sensors. One of the current state-of-the-art AOD retrieval method is NASA's Multi-angle Imaging SpectroRadiometer (MISR) operational algorithm, which has the spatial resolution of 17.6 km x 17.6 km. While the MISR baseline scheme already leads to exciting research opportunities to study particle compositions at regional scale, its spatial resolution is too coarse for analyzing urban areas where the AOD level has stronger spatial variations. We develop a novel high-resolution AOD retrieval algorithm that still uses MISR's radiance observations but has the resolution of 4.4km x 4.4km. We achieve the high resolution AOD retrieval by implementing a hierarchical Bayesian model and Monte-Carlo Markov Chain (MCMC) inference method. Our algorithm not only improves the spatial resolution, but also extends the coverage of AOD retrieval and provides with additional composition information of aerosol components that contribute to the AOD. We validate our method using the recent NASA's DISCOVER-AQ mission data, which contains the ground measured AOD values for Washington DC and Baltimore area. The validation result shows that, compared to the operational MISR retrievals, our scheme has 41.1% more AOD retrieval coverage for the DISCOVER-AQ data points and 24.2% improvement in mean-squared error (MSE) with respect to the AERONET ground measurements.

A New Algorithm for Retrieving Aerosol Properties Over Land from MODIS Spectral Reflectance

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Mattoo, Shana; Vermote, Eric F.; Kaufman, Yoram J.

2006-01-01

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.

The Sensitivity of SeaWiFS Ocean Color Retrievals to Aerosol Amount and Type

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Sayer, Andrew M.; Ahmad, Ziauddin; Franz, Bryan A.

2016-01-01

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.

Aerosol correction for remotely sensed sea surface temperatures from the National Oceanic and Atmospheric Administration advanced very high resolution radiometer

NASA Astrophysics Data System (ADS)

Nalli, Nicholas R.; Stowe, Larry L.

2002-10-01

This research presents the first-phase derivation and implementation of daytime aerosol correction algorithms for remotely sensed sea surface temperature (SST) from the advanced very high resolution radiometer (AVHRR) instrument flown onboard NOAA polar orbiting satellites. To accomplish this, a long-term (1990-1998), global AVHRR-buoy match-up database was created by merging the NOAA/NASA Pathfinder Atmospheres and Pathfinder Oceans data sets. The merged data set is unique in that it includes daytime estimates of aerosol optical depth (AOD) derived from AVHRR channel 1 (0.63 μm) under global conditions of significant aerosol loading. Histograms of retrieved AOD reveal monomodal, lognormal distributions for both tropospheric and stratospheric aerosol modes. It is then shown empirically that the SST depression caused under each aerosol mode can be expressed as a linear function in two predictors, these being the slant path AOD retrieved from AVHRR channel 1 along with the ratio of channels 1 and 2 normalized reflectances. On the basis of these relationships, parametric equations are derived to provide an aerosol correction for retrievals from the daytime NOAA operational multichannel and nonlinear SST algorithms. Separate sets of coefficients are utilized for two aerosol modes: tropospheric (i.e., dust, smoke, haze) and stratospheric/tropospheric (i.e., following a major volcanic eruption). The equations are shown to significantly reduce retrieved SST bias using an independent set of match-ups. Eliminating aerosol-induced bias in both real-time and retrospective processing will enhance the utility of the AVHRR SST for the general user community and in climate research.

A Comparison of Aerosol Measurements from OCO-2 and MODIS

NASA Astrophysics Data System (ADS)

Nelson, R. R.; O'Dell, C.

2016-12-01

The goal of OCO-2 is to use hyperspectral measurements of reflected near-infrared sunlight to retrieve carbon dioxide with high accuracy and precision. This is only possible, however, if the light-path modification effects caused by clouds and aerosols are properly quantified. Even tiny amounts of clouds or aerosols can induce sufficient light-path modifications to lead to large errors in the estimated CO2 column-mean (XCO2). Therefore, it is imperative to evaluate the accuracy of the OCO-2 retrieved aerosol parameters. In this study, we compare OCO-2 retrieved aerosol parameters to Aqua-MODIS observations co-located in time and space. We find that there are significant disagreements between the aerosol information derived from MODIS and the retrieved aerosol parameters from OCO-2. These results are unsurprising, as previous comparisons to AERONET have also been poor. However, the tight co-location between Aqua and OCO-2 in the Afternoon Constellation allows us to examine the potential synergistic use of OCO-2 and MODIS measurements to more accurately constrain aerosol properties, potentially leading to a more accurate CO2 measurement. Specifically, we used select MODIS aerosol properties as the a priori for the OCO-2 retrievals and present the results here. Future studies include investigating the possibility of ingesting the MODIS radiances directly into the OCO-2 retrieval algorithm to further improve OCO-2's aerosol scheme and the resulting measurements.

Quantification of model uncertainty in aerosol optical thickness retrieval from Ozone Monitoring Instrument (OMI) measurements

NASA Astrophysics Data System (ADS)

Määttä, A.; Laine, M.; Tamminen, J.; Veefkind, J. P.

2013-09-01

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.

Calculations of Aerosol Radiative Forcing in the SAFARI Region from MODIS Data

NASA Technical Reports Server (NTRS)

Remer, L. A.; Ichoku, C.; Kaufman, Y. J.; Chu, D. A.

2003-01-01

SAFARI 2000 provided the opportunity to validate MODIS aerosol retrievals and to correct any assumptions in the retrieval process. By comparing MODIS retrievals with ground-based sunphotometer data, we quantified the degree to which the MODIS algorithm underestimated the aerosol optical thickness. This discrepancy was attributed to underestimating the degree of light absorption by the southern African smoke aerosol. Correcting for this underestimation of absorption, produces more realistic aerosol retrievals that allow various applications of the MODIS aerosol products. One such application is the calculation of the aerosol radiative forcing at the top and bottom of the atmosphere. The combination of MODIS accuracy, coverage, resolution and the ability to separate fine and coarse mode make this calculation substantially advanced over previous attempts with other satellites. We focus on the oceans adjacent to southern Africa and use a solar radiative transfer model to perform the flux calculations. The forcing at the top of atmosphere is calculated to be 10 W/sq m, while the forcing at the surface is -26 W/sq m. These results resemble those calculated from INDOEX data, and are most sensitive to assumptions of aerosol absorption, the same parameter that initially interfered with our retrievals.

Retrieving Aerosol in a Cloudy Environment: Aerosol Availability as a Function of Spatial and Temporal Resolution

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Mattoo, Shana; Levy, Robert C.; Heidinger, Andrew; Pierce, R. Bradley; Chin, Mian

2011-01-01

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 applied to an independent aerosol retrieval will likely fail.

Retrieval of atmospheric backscatter and extinction profiles with the aladin airborne demonstrator (A2D)

NASA Astrophysics Data System (ADS)

Geiss, Alexander; Marksteiner, Uwe; Lux, Oliver; Lemmerz, Christian; Reitebuch, Oliver; Kanitz, Thomas; Straume-Lindner, Anne Grete

2018-04-01

By the end of 2017, the European Space Agency (ESA) will launch the Atmospheric laser Doppler instrument (ALADIN), a direct detection Doppler wind lidar operating at 355 nm. An important tool for the validation and optimization of ALADIN's hardware and data processors for wind retrievals with real atmospheric signals is the ALADIN airborne demonstrator A2D. In order to be able to validate and test aerosol retrieval algorithms from ALADIN, an algorithm for the retrieval of atmospheric backscatter and extinction profiles from A2D is necessary. The A2D is utilizing a direct detection scheme by using a dual Fabry-Pérot interferometer to measure molecular Rayleigh signals and a Fizeau interferometer to measure aerosol Mie returns. Signals are captured by accumulation charge coupled devices (ACCD). These specifications make different steps in the signal preprocessing necessary. In this paper, the required steps to retrieve aerosol optical products, i. e. particle backscatter coefficient βp, particle extinction coefficient αp and lidar ratio Sp from A2D raw signals are described.

Updated MISR Dark Water Research Aerosol Retrieval Algorithm - Part 1: Coupled 1.1 km Ocean Surface Chlorophyll a Retrievals with Empirical Calibration Corrections

NASA Technical Reports Server (NTRS)

Limbacher, James A.; Kahn, Ralph A.

2017-01-01

As aerosol amount and type are key factors in the 'atmospheric correction' required for remote-sensing chlorophyll alpha concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chl(sub in situ) less than 1.5 mg m(exp -3), the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov- Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p greater than 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl less than 1.5 mg m(exp -3), MISR and MODIS show very good agreement: r = 0.96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Updated MISR dark water research aerosol retrieval algorithm - Part 1: Coupled 1.1 km ocean surface chlorophyll a retrievals with empirical calibration corrections

NASA Astrophysics Data System (ADS)

Limbacher, James A.; Kahn, Ralph A.

2017-04-01

As aerosol amount and type are key factors in the atmospheric correction required for remote-sensing chlorophyll a concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chlin situ < 1.5 mg m-3, the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov-Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p > 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl < 1.5 mg m-3, MISR and MODIS show very good agreement: r = 0. 96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Validation of MODIS Aerosol Retrievals during PRIDE

NASA Technical Reports Server (NTRS)

Levy, R.; Remier, L.; Kaufman, Y.; Kleidman, R.; Holben, B.; Russell, P.; Livingston, J.; Einaudi, Franco (Technical Monitor)

2000-01-01

The Puerto Rico Dust Experiment (PRIDE) was held in Roosevelt Roads, Puerto Rico from June 26 to July 24, 2000. It was intended to study the radiative and microphysical properties of Saharan dust transported into Puerto Rico. PRIDE had the unique distinction of being the first major field experiment to allow direct comparison of aerosol retrievals from MODIS (MODerate Imaging Spectro-radiometer - aboard the Terra satellite) with data from a variety of ground, shipboard and air-based instruments. Over the ocean the MODIS algorithm retrieves optical depth as well as information about the aerosol's size. During PRIDE, MODIS passed over Roosevelt Roads approximately once per day during daylight hours. Due to sunglint and clouds over Puerto Rico, aerosol retrievals can be made from only about half the MODIS scenes. In this study we try to "validate" our aerosol retrievals by comparing to measurements taken by sun-photometers from multiple platforms, including: Cimel (AERONET) from the ground, Microtops (handheld) from ground and ship, and the NASA-Ames sunphotometer from the air.

Validation and Uncertainty Estimates for MODIS Collection 6 "Deep Blue" Aerosol Data

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.

2013-01-01

The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (MODIS) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of MODIS products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from MODIS Aqua against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56Tau(sub M))/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20Tau(sub M), comparable in quality to other satellite AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.

Aerosol Climate Time Series in ESA Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, Thomas; de Leeuw, Gerrit; Pinnock, Simon

2016-04-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve algorithms for the retrieval of aerosol information from European sensors. Meanwhile, full mission time series of 2 GCOS-required aerosol parameters are completely validated and released: Aerosol Optical Depth (AOD) from dual view ATSR-2 / AATSR radiometers (3 algorithms, 1995 - 2012), and stratospheric extinction profiles from star occultation GOMOS spectrometer (2002 - 2012). Additionally, a 35-year multi-sensor time series of the qualitative Absorbing Aerosol Index (AAI) together with sensitivity information and an AAI model simulator is available. Complementary aerosol properties requested by GCOS are in a "round robin" phase, where various algorithms are inter-compared: fine mode AOD, mineral dust AOD (from the thermal IASI spectrometer, but also from ATSR instruments and the POLDER sensor), absorption information and aerosol layer height. As a quasi-reference for validation in few selected regions with sparse ground-based observations the multi-pixel GRASP algorithm for the POLDER instrument is used. Validation of first dataset versions (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account for a reprocessing. The datasets contain pixel level uncertainty estimates which were also validated and improved in the reprocessing. For the three ATSR algorithms the use of an ensemble method was tested. The paper will summarize and discuss the status of dataset reprocessing and validation. The focus will be on the ATSR, GOMOS and IASI datasets. Pixel level uncertainties validation will be summarized and discussed including unknown components and their potential usefulness and limitations. Opportunities for time series extension with successor instruments of the Sentinel family will be described and the complementarity of the different satellite aerosol products (e.g. dust vs. total AOD, ensembles from different algorithms for the same sensor) will be discussed.

The Airborne Cloud-Aerosol Transport System. Part I; Overview and Description of the Instrument and Retrival Algorithms

NASA Technical Reports Server (NTRS)

Yorks, John E.; Mcgill, Matthew J.; Scott, V. Stanley; Kupchock, Andrew; Wake, Shane; Hlavka, Dennis; Hart, William; Selmer, Patrick

2014-01-01

The Airborne Cloud-Aerosol Transport System (ACATS) is a multi-channel Doppler lidar system recently developed at NASA Goddard Space Flight Center (GSFC). A unique aspect of the multi-channel Doppler lidar concept such as ACATS is that it is also, by its very nature, a high spectral resolution lidar (HSRL). Both the particulate and molecular scattered signal can be directly and unambiguously measured, allowing for direct retrievals of particulate extinction. ACATS is therefore capable of simultaneously resolving the backscatterextinction properties and motion of a particle from a high altitude aircraft. ACATS has flown on the NASA ER-2 during test flights over California in June 2012 and science flights during the Wallops Airborne Vegetation Experiment (WAVE) in September 2012. This paper provides an overview of the ACATS method and instrument design, describes the ACATS retrieval algorithms for cloud and aerosol properties, and demonstrates the data products that will be derived from the ACATS data using initial results from the WAVE project. The HSRL retrieval algorithms developed for ACATS have direct application to future spaceborne missions such as the Cloud-Aerosol Transport System (CATS) to be installed on the International Space Station (ISS). Furthermore, the direct extinction and particle wind velocity retrieved from the ACATS data can be used for science applications such 27 as dust or smoke transport and convective outflow in anvil cirrus clouds.

Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land

PubMed Central

Bassani, Cristiana; Cavalli, Rosa Maria; Pignatti, Stefano

2010-01-01

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

Desert Dust Satellite Retrieval Intercomparison

NASA Technical Reports Server (NTRS)

Carboni, E.; Thomas, G. E.; Sayer, A. M.; Siddans, R.; Poulsen, C. A.; Grainger, R. G.; Ahn, C.; Antoine, D.; Bevan, S.; Braak, R.;

New capabilities for characterizing smoke and dust aerosol over land using MODIS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.

2006-12-01

Smoke and dust aerosol have different chemical, optical and physical properties and both types affect many processes within the climate system. As earth's surface and atmosphere are continuously altered by natural and anthropogenic processes, the emission and presumably the effects of these aerosols are also changing. Thus it is necessary to observe and characterize aerosols on a global and climatic scale. While MODIS has been reporting characteristics of smoke and dust aerosol over land and ocean since shortly after Terra launch, the uncertainties in the over-land retrieval have been larger than expected. To better characterize different aerosol types closer to their source regions with greater accuracy, we have developed a new operational algorithm for retrieving aerosol properties over dark land surfaces from MODIS-observed visible (VIS) and infrared (IR) reflectance. Like earlier versions, this algorithm estimates the total loading (aerosol optical depth-τ) and relative weighting of fine (non-dust) and coarse (dust) -dominated aerosol to the total τ (fine weighting-η) over dark land surfaces. However, the fundamental mathematics and major assumptions have been overhauled. The new algorithm performs simultaneous multi-channel inversion that includes information about coarse aerosol in the IR channels, while assuming a fine-tuned relationship between VIS and IR surface reflectances, that is itself a function of scattering angle and vegetation condition. Finally, the suite of expected aerosol optical models described by the lookup table have been revised to closer resemble the AERONET climatology, including for smoke and dust aerosol. Beginning in April 2006, this algorithm has been used for forward processing and backward re- processing of the entire MODIS dataset observed from both Terra and Aqua. "Collection 5" products were completed for Aqua reprocessing by July 2006 and should be complete for Terra by December 2006. In this study, we used the complete Aqua dataset (July 2002-Aug 2006) and two years of Terra (2005-Aug 2006) data to evaluate the products in regions known to be dominated by smoke and/or dust. We compared with sunphotometer data at selected AERONET sites and found improved τ retrievals,within prescribed accuracy.

Aerosol Correction for Remotely Sensed Sea Surface Temperatures From the NOAA AVHRR: Phase II

NASA Astrophysics Data System (ADS)

Nalli, N. R.; Ignatov, A.

2002-05-01

For over two decades, the National Oceanic and Atmospheric Administration (NOAA) has produced global retrievals of sea surface temperature (SST) using infrared (IR) data from the Advanced Very High Resolution Radiometer (AVHRR). The standard multichannel retrieval algorithms are derived from regression analyses of AVHRR window channel brightness temperatures against in situ buoy measurements under non-cloudy conditions thus providing a correction for IR attenuation due to molecular water vapor absorption. However, for atmospheric conditions with elevated aerosol levels (e.g., arising from dust, biomass burning and volcanic eruptions), such algorithms lead to significant negative biases in SST because of IR attenuation arising from aerosol absorption and scattering. This research presents the development of a 2nd-phase aerosol correction algorithm for daytime AVHRR SST. To accomplish this, a long-term (1990-1998), global AVHRR-buoy matchup database was created by merging the Pathfinder Atmospheres (PATMOS) and Oceans (PFMDB) data sets. The merged data are unique in that they include multi-year, global daytime estimates of aerosol optical depth (AOD) derived from AVHRR channels 1 and 2 (0.63 and 0.83 μ m, respectively), along with an effective Angstrom exponent derived from the AOD retrievals (Ignatov and Nalli, 2002). Recent enhancements in the aerosol data constitute an improvement over the Phase I algorithm (Nalli and Stowe, 2002) which relied only on channel 1 AOD and the ratio of normalized reflectance from channels 1 and 2. The Angstrom exponent and channel 2 AOD provide important statistical information about the particle size distribution of the aerosol. The SST bias can be parametrically expressed as a function of observed AVHRR channels 1 and 2 slant-path AOD, normalized reflectance ratio and the Angstrom exponent. Based upon these empirical relationships, aerosol correction equations are then derived for the daytime multichannel and nonlinear SST (MCSST and NLSST) algorithms. Separate sets of coefficients are utilized for two aerosol modes, these being stratospheric/tropospheric (e.g., volcanic aerosol) and tropospheric (e.g., dust, smoke). The algorithms are subsequently applied to retrospective PATMOS data to demonstrate the potential for climate applications. The minimization of cold biases in the AVHRR SST, as demonstrated in this work, should improve its overall utility for the general user community.

Simultaneously inferring above-cloud absorbing aerosol optical thickness and underlying liquid phase cloud optical and microphysical properties using MODIS

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Platnick, Steven; Zhang, Zhibo

2015-06-01

The regional haze over the southeast (SE) Atlantic Ocean induced by biomass burning in southern Africa can be problematic for passive imager-based retrievals of the underlying quasi-permanent marine boundary layer (MBL) clouds and for estimates of top-of-atmosphere (TOA) aerosol direct radiative effect (DRE). Here an algorithm is introduced to simultaneously retrieve above-cloud aerosol optical thickness (AOT), the cloud optical thickness (COT), and cloud effective particle radius (CER) of the underlying MBL clouds while also providing pixel-level estimates of retrieval uncertainty. This approach utilizes reflectance measurements at six Moderate Resolution Imaging Spectroradiometer (MODIS) channels from the visible to the shortwave infrared. Retrievals are run under two aerosol model assumptions on 8 years (2006-2013) of June-October Aqua MODIS data over the SE Atlantic, from which a regional cloud and above-cloud aerosol climatology is produced. The cloud retrieval methodology is shown to yield COT and CER consistent with those from the MODIS operational cloud product (MOD06) when forcing AOT to zero, while the full COT-CER-AOT retrievals that account for the above-cloud aerosol attenuation increase regional monthly mean COT and CER by up to 9% and 2%, respectively. Retrieved AOT is roughly 3 to 5 times larger than the collocated 532 nm Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals, though closer agreement is observed with the CALIOP 1064 nm retrievals, a result consistent with previous case study analyses. Regional cloudy-sky above-cloud aerosol DRE calculations are also performed that illustrate the importance of the aerosol model assumption and underlying cloud retrievals.

Quantifying the response of the ORAC aerosol optical depth retrieval for MSG SEVIRI to aerosol model assumptions

NASA Astrophysics Data System (ADS)

Bulgin, Claire E.; Palmer, Paul I.; Merchant, Christopher J.; Siddans, Richard; Gonzi, Siegfried; Poulsen, Caroline A.; Thomas, Gareth E.; Sayer, Andrew M.; Carboni, Elisa; Grainger, Roy G.; Highwood, Eleanor J.; Ryder, Claire L.

2011-03-01

We test the response of the Oxford-RAL Aerosol and Cloud (ORAC) retrieval algorithm for Meteosat Second Generation Spinning Enhanced Visible and InfraRed Imager (MSG SEVIRI) to changes in the aerosol properties used in the dust aerosol model, using data from the Dust Outflow and Deposition to the Ocean (DODO) flight campaign in August 2006. We find that using the observed DODO free tropospheric aerosol size distribution and refractive index increases simulated top of the atmosphere radiance at 0.55 μm assuming a fixed aerosol optical depth of 0.5 by 10-15%, reaching a maximum difference at low solar zenith angles. We test the sensitivity of the retrieval to the vertical distribution of the aerosol and find that this is unimportant in determining simulated radiance at 0.55 μm. We also test the ability of the ORAC retrieval when used to produce the GlobAerosol data set to correctly identify continental aerosol outflow from the African continent, and we find that it poorly constrains aerosol speciation. We develop spatially and temporally resolved prior distributions of aerosols to inform the retrieval which incorporates five aerosol models: desert dust, maritime, biomass burning, urban, and continental. We use a Saharan Dust Index and the GEOS-Chem chemistry transport model to describe dust and biomass burning aerosol outflow and compare AOD using our speciation against the GlobAerosol retrieval during January and July 2006. We find AOD discrepancies of 0.2-1 over regions of intense biomass burning outflow, where AOD from our aerosol speciation and GlobAerosol speciation can differ by as much as 50-70%.

Advantages of measuring the Q Stokes parameter in addition to the total radiance I in the detection of absorbing aerosols

NASA Astrophysics Data System (ADS)

Stamnes, Snorre; Fan, Yongzhen; Chen, Nan; Li, Wei; Tanikawa, Tomonori; Lin, Zhenyi; Liu, Xu; Burton, Sharon; Omar, Ali; Stamnes, Jakob J.; Cairns, Brian; Stamnes, Knut

2018-05-01

A simple but novel study was conducted to investigate whether an imager-type spectroradiometer instrument like MODIS, currently flying on board the Aqua and Terra satellites, or MERIS, which flew on board Envisat, could detect absorbing aerosols if they could measure the Q Stokes parameter in addition to the total radiance I, that is if they could also measure the linear polarization of the light. Accurate radiative transfer calculations were used to train a fast neural network forward model, which together with a simple statistical optimal estimation scheme was used to retrieve three aerosol parameters: aerosol optical depth at 869 nm, optical depth fraction of fine mode (absorbing) aerosols at 869 nm, and aerosol vertical location. The aerosols were assumed to be bimodal, each with a lognormal size distribution, located either between 0 and 2 km or between 2 and 4 km in the Earth's atmosphere. From simulated data with 3% random Gaussian measurement noise added for each Stokes parameter, it was found that by itself the total radiance I at the nine MODIS VIS channels was generally insufficient to accurately retrieve all three aerosol parameters (˜ 15% to 37% successful), but that together with the Q Stokes component it was possible to retrieve values of aerosol optical depth at 869 nm to ± 0.03, single-scattering albedo at 869 nm to ± 0.04, and vertical location in ˜ 65% of the cases. This proof-of-concept retrieval algorithm uses neural networks to overcome the computational burdens of using vector radiative transfer to accurately simulate top-of-atmosphere (TOA) total and polarized radiances, enabling optimal estimation techniques to exploit information from multiple channels. Therefore such an algorithm could, in concept, be readily implemented for operational retrieval of aerosol and ocean products from moderate or hyperspectral spectroradiometers.

DSCOVR EPIC AERUV Parameters

Atmospheric Science Data Center

2018-06-27

... AerosolType      The aerosol type associated with the ground pixel.        1 - Smoke ... algorithm flag associated with the ground pixel:     Aerosol extinction Optical Depth (AOD), Single Scattering Albedo (SSA), and     Aerosol Absorption Optical Depth (AAOD) Retrievals:        0 - Most ...

Adaptation of a Hyperspectral Atmospheric Correction Algorithm for Multi-spectral Ocean Color Data in Coastal Waters. Chapter 3

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Montes, Marcos J.; Davis, Curtiss O.

2003-01-01

This SIMBIOS contract supports several activities over its three-year time-span. These include certain computational aspects of atmospheric correction, including the modification of our hyperspectral atmospheric correction algorithm Tafkaa for various multi-spectral instruments, such as SeaWiFS, MODIS, and GLI. Additionally, since absorbing aerosols are becoming common in many coastal areas, we are making the model calculations to incorporate various absorbing aerosol models into tables used by our Tafkaa atmospheric correction algorithm. Finally, we have developed the algorithms to use MODIS data to characterize thin cirrus effects on aerosol retrieval.

Using High-Resolution Airborne Remote Sensing to Study Aerosol Near Clouds

NASA Technical Reports Server (NTRS)

Levy, Robert; Munchak, Leigh; Mattoo, Shana; Marshak, Alexander; Wilcox, Eric; Gao, Lan; Yorks, John; Platnick, Steven

2016-01-01

The horizontal space in between clear and cloudy air is very complex. This so-called twilight zone includes activated aerosols that are not quite clouds, thin cloud fragments that are not easily observable, and dying clouds that have not quite disappeared. This is a huge challenge for satellite remote sensing, specifically for retrieval of aerosol properties. Identifying what is cloud versus what is not cloud is critically important for attributing radiative effects and forcings to aerosols. At the same time, the radiative interactions between clouds and the surrounding media (molecules, surface and aerosols themselves) will contaminate retrieval of aerosol properties, even in clear skies. Most studies on aerosol cloud interactions are relevant to moderate resolution imagery (e.g. 500 m) from sensors such as MODIS. Since standard aerosol retrieval algorithms tend to keep a distance (e.g. 1 km) from the nearest detected cloud, it is impossible to evaluate what happens closer to the cloud. During Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), the NASA ER-2 flew with the enhanced MODIS Airborne Simulator (eMAS), providing MODIS-like spectral observations at high (50 m) spatial resolution. We have applied MODIS-like aerosol retrieval for the eMAS data, providing new detail to characterization of aerosol near clouds. Interpretation and evaluation of these eMAS aerosol retrievals is aided by independent MODIS-like cloud retrievals, as well as profiles from the co-flying Cloud Physics Lidar (CPL). Understanding aerosolcloud retrieval at high resolution will lead to better characterization and interpretation of long-term, global products from lower resolution (e.g.MODIS) satellite retrievals.

AERONET-Based Nonspherical Dust Optical Models and Effects on the VIIRS Deep Blue/SOAR Over Water Aerosol Product

NASA Astrophysics Data System (ADS)

Lee, Jaehwa; Hsu, N. Christina; Sayer, Andrew M.; Bettenhausen, Corey; Yang, Ping

2017-10-01

Aerosol Robotic Network (AERONET)-based nonspherical dust optical models are developed and applied to the Satellite Ocean Aerosol Retrieval (SOAR) algorithm as part of the Version 1 Visible Infrared Imaging Radiometer Suite (VIIRS) NASA "Deep Blue" aerosol data product suite. The optical models are created using Version 2 AERONET inversion data at six distinct sites influenced frequently by dust aerosols from different source regions. The same spheroid shape distribution as used in the AERONET inversion algorithm is assumed to account for the nonspherical characteristics of mineral dust, which ensures the consistency between the bulk scattering properties of the developed optical models and the AERONET-retrieved microphysical and optical properties. For the Version 1 SOAR aerosol product, the dust optical model representative for Capo Verde site is used, considering the strong influence of Saharan dust over the global ocean in terms of amount and spatial coverage. Comparisons of the VIIRS-retrieved aerosol optical properties against AERONET direct-Sun observations at five island/coastal sites suggest that the use of nonspherical dust optical models significantly improves the retrievals of aerosol optical depth (AOD) and Ångström exponent by mitigating the well-known artifact of scattering angle dependence of the variables, which is observed when incorrectly assuming spherical dust. The resulting removal of these artifacts results in a more natural spatial pattern of AOD along the transport path of Saharan dust to the Atlantic Ocean; that is, AOD decreases with increasing distance transported, whereas the spherical assumption leads to a strong wave pattern due to the spurious scattering angle dependence of AOD.

Assessment of 10-Year Global Record of Aerosol Products from the OMI Near-UV Algorithm

NASA Astrophysics Data System (ADS)

Ahn, C.; Torres, O.; Jethva, H. T.

2014-12-01

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).

Feasibility study for GCOM-C/SGLI: Retrieval algorithms for carbonaceous aerosols

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Sano, Itaru; Yasumoto, Masayoshi; Fujito, Toshiyuki; Nakata, Makiko; Kokhanovsky, Alexander

2016-04-01

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 possibility of GCOM-C1 / SGLI related to remote sensing for aerosols and/or clouds can be examined. [1] Mukai, S., M. Yasumoto and M. Nakata, 2014: Estimation of biomass burning influence on air pollution around Beijing from an aerosol retrieval model. The Scientific World Journal, Article ID 649648. [2] Mukai, S., M. Nakata, M. Yasumoto, I. Sano and A. Kokhanovsky, 2015:A study of aerosol pollution episode due to agriculture biomass burning in the east-central China using satellite data, Front. Environ. Sci., 3:57, doi: 10.3389/fenvs.2015.00057.

Rehearsal for Assessment of atmospheric optical Properties during biomass burning Events and Long-range transportation episodes at Metropolitan Area of São Paulo-Brazil (RAPEL)

NASA Astrophysics Data System (ADS)

Lopes, Fábio J. S.; Luis Guerrero-Rascado, Juan; Benavent-Oltra, Jose A.; Román, Roberto; Moreira, Gregori A.; Marques, Marcia T. A.; da Silva, Jonatan J.; Alados-Arboledas, Lucas; Artaxo, Paulo; Landulfo, Eduardo

2018-04-01

During the period of August-September 2016 an intensive campaign was carried out to assess aerosol properties in São Paulo-Brazil aiming to detect long-range aerosol transport events and to characterize the instrument regarding data quality. Aerosol optical properties retrieved by the GALION - LALINET SPU lidar station and collocated AERONET sunphotometer system are presented as extinction/ backscatter vertical profiles with microphysical products retrieved with GRASP inversion algorithm.

Cloud cover detection combining high dynamic range sky images and ceilometer measurements

NASA Astrophysics Data System (ADS)

Román, R.; Cazorla, A.; Toledano, C.; Olmo, F. J.; Cachorro, V. E.; de Frutos, A.; Alados-Arboledas, L.

2017-11-01

This paper presents a new algorithm for cloud detection based on high dynamic range images from a sky camera and ceilometer measurements. The algorithm is also able to detect the obstruction of the sun. This algorithm, called CPC (Camera Plus Ceilometer), is based on the assumption that under cloud-free conditions the sky field must show symmetry. The symmetry criteria are applied depending on ceilometer measurements of the cloud base height. CPC algorithm is applied in two Spanish locations (Granada and Valladolid). The performance of CPC retrieving the sun conditions (obstructed or unobstructed) is analyzed in detail using as reference pyranometer measurements at Granada. CPC retrievals are in agreement with those derived from the reference pyranometer in 85% of the cases (it seems that this agreement does not depend on aerosol size or optical depth). The agreement percentage goes down to only 48% when another algorithm, based on Red-Blue Ratio (RBR), is applied to the sky camera images. The retrieved cloud cover at Granada and Valladolid is compared with that registered by trained meteorological observers. CPC cloud cover is in agreement with the reference showing a slight overestimation and a mean absolute error around 1 okta. A major advantage of the CPC algorithm with respect to the RBR method is that the determined cloud cover is independent of aerosol properties. The RBR algorithm overestimates cloud cover for coarse aerosols and high loads. Cloud cover obtained only from ceilometer shows similar results than CPC algorithm; but the horizontal distribution cannot be obtained. In addition, it has been observed that under quick and strong changes on cloud cover ceilometers retrieve a cloud cover fitting worse with the real cloud cover.

The Continuous Monitoring of Desert Dust using an Infrared-based Dust Detection and Retrieval Method

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick; Trepte, Qing; Sun-Mack, Sunny

2006-01-01

Airborne dust and sand are significant aerosol sources that can impact the atmospheric and surface radiation budgets. Because airborne dust affects visibility and air quality, it is desirable to monitor the location and concentrations of this aerosol for transportation and public health. Although aerosol retrievals have been derived for many years using visible and near-infrared reflectance measurements from satellites, the detection and quantification of dust from these channels is problematic over bright surfaces, or when dust concentrations are large. In addition, aerosol retrievals from polar orbiting satellites lack the ability to monitor the progression and sources of dust storms. As a complement to current aerosol dust retrieval algorithms, multi-spectral thermal infrared (8-12 micron) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat-8 Spinning Enhanced Visible and Infrared Imager (SEVIRI) are used in the development of a prototype dust detection method and dust property retrieval that can monitor the progress of Saharan dust fields continuously, both night and day. The dust detection method is incorporated into the processing of CERES (Clouds and the Earth s Radiant Energy System) aerosol retrievals to produce dust property retrievals. Both MODIS (from Terra and Aqua) and SEVERI data are used to develop the method.

Analysis of DIAL/HSRL aerosol backscatter and extinction profiles during the SEAC4RS campaign with an aerosol assimilation system

NASA Astrophysics Data System (ADS)

Weaver, C. J.; da Silva, A. M., Jr.; Colarco, P. R.; Randles, C. A.

2015-12-01

We retrieve aerosol concentrations and optical information from vertical profiles of airborne 532 nm extinction and 532 and 1064 nm backscatter measurements made during the SEAC4RS summer 2013 campaign. The observations are from the High Spectral Resolution Lidar (HSRL) Airborne Differential Absorption Lidar (DIAL) on board the NASA DC-8. Instead of retrieving information about aerosol microphysical properties such as indexes of refraction, we seek information more directly applicable to an aerosol transport model - in our case the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module used in the GEOS-5 Earth modeling system. A joint atmosphere/aerosol mini-reanalysis was performed for the SEAC4RS period using GEOS-5. The meteorological reanalysis followed the MERRA-2 atmospheric reanalysis protocol, and aerosol information from MODIS, MISR, and AERONET provided a constraint on the simulated aerosol optical depth (i.e., total column loading of aerosols). We focus on the simulated concentrations of 10 relevant aerosol species simulated by the GOCART module: dust, sulfate, and organic and black carbon. Our first retrieval algorithm starts with the SEAC4RS mini-reanalysis and adjusts the concentration of each GOCART aerosol species so that differences between the observed and simulated backscatter and extinction measurements are minimized. In this case, too often we are unable to simulate the observations by simple adjustment of the aerosol concentrations. A second retrieval approach adjusts both the aerosol concentrations and the optical parameters (i.e., assigned mass extinction efficiency) associated with each GOCART species. We present results from DC-8 flights over smoke from forest fires over the western US using both retrieval approaches. Finally, we compare our retrieved quantities with in-situ observations of aerosol absorption, scattering, and mass concentrations at flight altitude.

Evaluating the Height of Biomass Burning Smoke Aerosols Retrieved from Synergistic Use of Multiple Satellite Sensors Over Southeast Asia

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae; Tsay, Si-Chee; Welton, Ellsworth J.; Wang, Sheng-Hsiang; Chen, Wei-Nai

2016-01-01

This study evaluates the height of biomass burning smoke aerosols retrieved from a combined use of Visible Infrared Imaging Radiometer Suite (VIIRS), Ozone Mapping and Profiler Suite (OMPS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. The retrieved heights are compared against space borne and ground-based lidar measurements during the peak biomass burning season (March and April) over Southeast Asia from 2013 to 2015. Based on the comparison against CALIOP, a quality assurance (QA) procedure is developed. It is found that 74 (8184) of the retrieved heights fall within 1 km of CALIOP observations for unfiltered (QA-filtered) data, with root-mean-square error (RMSE) of 1.1 km (0.81.0 km). Eliminating the requirement of CALIOP observations from the retrieval process significantly increases the temporal coverage with only a slight decrease in the retrieval accuracy; for best QA data, 64 of data fall within 1 km of CALIOP observations with RMSE of 1.1 km. When compared with Micro-Pulse Lidar Network (MPLNET) measurements deployed at Doi Ang Khang, Thailand, the retrieved heights show RMSE of 1.7 km (1.1 km) for unfiltered (QA-filtered) data for the complete algorithm, and 0.9 km (0.8 km) for the simplified algorithm.

Application of the LSQR algorithm in non-parametric estimation of aerosol size distribution

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Lew, Zhongyuan; Ruan, Liming; Tan, Heping; Luo, Kun

2016-05-01

Based on the Least Squares QR decomposition (LSQR) algorithm, the aerosol size distribution (ASD) is retrieved in non-parametric approach. The direct problem is solved by the Anomalous Diffraction Approximation (ADA) and the Lambert-Beer Law. An optimal wavelength selection method is developed to improve the retrieval accuracy of the ASD. The proposed optimal wavelength set is selected by the method which can make the measurement signals sensitive to wavelength and decrease the degree of the ill-condition of coefficient matrix of linear systems effectively to enhance the anti-interference ability of retrieval results. Two common kinds of monomodal and bimodal ASDs, log-normal (L-N) and Gamma distributions, are estimated, respectively. Numerical tests show that the LSQR algorithm can be successfully applied to retrieve the ASD with high stability in the presence of random noise and low susceptibility to the shape of distributions. Finally, the experimental measurement ASD over Harbin in China is recovered reasonably. All the results confirm that the LSQR algorithm combined with the optimal wavelength selection method is an effective and reliable technique in non-parametric estimation of ASD.

What We are Learning about Airborne Particles from MISR Multi-angle Imaging

NASA Astrophysics Data System (ADS)

Kahn, Ralph

The NASA Earth Observing System’s Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global observations in 36 angular-spectral channels about once per week for over 14 years. Regarding airborne particles, MISR is contributing in three broad areas: (1) aerosol optical depth (AOD), especially over land surface, including bright desert, (2) wildfire smoke, desert dust, and volcanic ash injection and near-source plume height, and (3) aerosol type, the aggregate of qualitative constraints on particle size, shape, and single-scattering albedo (SSA). Early advances in the retrieval of these quantities focused on AOD, for which surface-based sun photometers provided a global network of ground truth, and plume height, for which ground-based and airborne lidar offered near-coincident validation data. MSIR monthly, global AOD products contributed directly to the advances in modeling aerosol impacts on climate made between the Inter-governmental Panel on Climate Change (IPCC) third and fourth assessment reports. MISR stereo-derived plume heights are now being used to constrain source inventories for the AeroCom aerosol-climate modeling effort. The remaining challenge for the MISR aerosol effort is to refine and validate our global aerosol type product. Unlike AOD and plume height, aerosol type as retrieved by MISR is a qualitative classification derived from multi-dimensional constraints, so evaluation must be done on a categorical basis. Coincident aerosol type validation data are far less common than for AOD, and, except for rare Golden Days during aircraft field campaigns, amount to remote sensing retrievals from suborbital instruments having uncertainties comparable to those from the MISR product itself. And satellite remote sensing retrievals of aerosol type are much more sensitive to scene conditions such as surface variability and AOD than either AOD or plume height. MISR aerosol type retrieval capability and information content have been demonstrated in case studies using the MISR Operational as especially the MISR Research aerosol retrieval algorithms. Refinements to the Operational algorithm, as indicated by these studies, are required to generate a high-quality next-generation aerosol type product from the MISR data. This presentation will briefly review the MISR AOD and plume height product attributes, and will then focus on the MISR aerosol type product: validation, data quality, and refinements.

Multispectral information for gas and aerosol retrieval from TANSO-FTS instrument

NASA Astrophysics Data System (ADS)

Herbin, H.; Labonnote, L. C.; Dubuisson, P.

2012-11-01

The Greenhouse gases Observing SATellite (GOSAT) mission and in particular TANSO-FTS instrument has the advantage to measure simultaneously the same field of view in different spectral ranges with a high spectral resolution. These features are promising to improve, not only, gaseous retrieval in clear sky or scattering atmosphere, but also to retrieve aerosol parameters. Therefore, this paper is dedicated to an Information Content (IC) analysis of potential synergy between thermal infrared, shortwave infrared and visible, in order to obtain a more accurate retrieval of gas and aerosol. The latter is based on Shannon theory and used a sophisticated radiative transfer algorithm developed at "Laboratoire d'Optique Atmosphérique", dealing with multiple scattering. This forward model can be relied to an optimal estimation method, which allows simultaneously retrieving gases profiles and aerosol granulometry and concentration. The analysis of the information provided by the spectral synergy is based on climatology of dust, volcanic ash and biomass burning aerosols. This work was conducted in order to develop a powerful tool that allows retrieving simultaneously not only the gas concentrations but also the aerosol characteristics by selecting the so called "best channels", i.e. the channels that bring most of the information concerning gas and aerosol. The methodology developed in this paper could also be used to define the specifications of future high spectral resolution mission to reach a given accuracy on retrieved parameters.

Improvement of retrieval algorithms for severe air pollution

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Sano, Itaru; Nakata, Makiko

2016-10-01

Increased emissions of anthropogenic aerosols associated with economic growth can lead to increased concentrations of hazardous air pollutants. Furthermore, dust storms or biomass burning plumes can cause serious environmental hazards, yet their aerosol properties are poorly understood. Our research group has worked on the development of an efficient algorithm for aerosol retrieval during hazy episodes (dense concentrations of atmospheric aerosols). It is noted that near UV measurements are available for detection of carbonaceous aerosols. The biomass burning aerosols (BBA) due to large-scale forest fires and/or burn agriculture exacerbated the severe air pollution. It is known that global warming and climate change have caused increasing instances of forest fires, which have in turn accelerated climate change. It is well known that this negative cycle decreases the quality of the global environment and human health. The Japan Aerospace Exploration Agency (JAXA) has been developing a new Earth observing system, the GCOM (Global Change Observation Mission) project, which consists of two satellite series: GCOM-W1 and GCOM-C1. The first GCOM-C satellite will board the SGLI (second generation GLI [global imager]) to be launched in early 2017. The SGLI is capable of multi-channel (19) observation, including a near UV channel (0.380 μm) and two polarization channels at red and near-infrared wavelengths of 0.67 and 0.87 μm. Thus, global aerosol retrieval will be achieved with simultaneous polarization and total radiance. In this study, algorithm improvement for aerosol remote sensing, especially of BBA episodes, is examined using Terra/MODIS measurements from 2003, when the GLI and POLDER-2 sensors were working onboard the Japanese satellite ADEOS-2.

Retrieving Smoke Aerosol Height from DSCOVR/EPIC

NASA Astrophysics Data System (ADS)

Xu, X.; Wang, J.; Wang, Y.

2017-12-01

Unlike industrial pollutant particles that are often confined within the planetary boundary layer, smoke from forest and agriculture fires can inject massive carbonaceous aerosols into the upper troposphere due to the intense pyro-convection. Sensitivity of weather and climate to absorbing carbonaceous aerosols is regulated by the altitude of those aerosol layers. However, aerosol height information remains limited from passive satellite sensors. Here we present an algorithm to estimate smoke aerosol height from radiances in the oxygen A and B bands measured by the Earth Polychromatic Imaging Camera (EPIC) from the Deep Space Climate Observatory (DSCOVR). With a suit of case studies and validation efforts, we demonstrate that smoke aerosol height can be well retrieved over both ocean and land surfaces multiple times daily.

Lidar Ratios for Dust Aerosols Derived From Retrievals of CALIPSO Visible Extinction Profiles Constrained by Optical Depths from MODIS-Aqua and CALIPSO/CloudSat Ocean Surface Reflectance Measurements

NASA Technical Reports Server (NTRS)

Young, Stuart A.; Josset, Damien B.; Vaughan, Mark A.

2010-01-01

CALIPSO's (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) analysis algorithms generally require the use of tabulated values of the lidar ratio in order to retrieve aerosol extinction and optical depth from measured profiles of attenuated backscatter. However, for any given time or location, the lidar ratio for a given aerosol type can differ from the tabulated value. To gain some insight as to the extent of the variability, we here calculate the lidar ratio for dust aerosols using aerosol optical depth constraints from two sources. Daytime measurements are constrained using Level 2, Collection 5, 550-nm aerosol optical depth measurements made over the ocean by the MODIS (Moderate Resolution Imaging Spectroradiometer) on board the Aqua satellite, which flies in formation with CALIPSO. We also retrieve lidar ratios from night-time profiles constrained by aerosol column optical depths obtained by analysis of CALIPSO and CloudSat backscatter signals from the ocean surface.

Aerosol Climate Time Series Evaluation In ESA Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, T.; de Leeuw, G.; Pinnock, S.

2015-12-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve algorithms for the retrieval of aerosol information from European sensors. By the end of 2015 full mission time series of 2 GCOS-required aerosol parameters are completely validated and released: Aerosol Optical Depth (AOD) from dual view ATSR-2 / AATSR radiometers (3 algorithms, 1995 - 2012), and stratospheric extinction profiles from star occultation GOMOS spectrometer (2002 - 2012). Additionally, a 35-year multi-sensor time series of the qualitative Absorbing Aerosol Index (AAI) together with sensitivity information and an AAI model simulator is available. Complementary aerosol properties requested by GCOS are in a "round robin" phase, where various algorithms are inter-compared: fine mode AOD, mineral dust AOD (from the thermal IASI spectrometer), absorption information and aerosol layer height. As a quasi-reference for validation in few selected regions with sparse ground-based observations the multi-pixel GRASP algorithm for the POLDER instrument is used. Validation of first dataset versions (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account for a reprocessing. The datasets contain pixel level uncertainty estimates which are also validated. The paper will summarize and discuss the results of major reprocessing and validation conducted in 2015. The focus will be on the ATSR, GOMOS and IASI datasets. Pixel level uncertainties validation will be summarized and discussed including unknown components and their potential usefulness and limitations. Opportunities for time series extension with successor instruments of the Sentinel family will be described and the complementarity of the different satellite aerosol products (e.g. dust vs. total AOD, ensembles from different algorithms for the same sensor) will be discussed.

Aerosols correction of the OMI tropospheric NO2 retrievals over cloud-free scenes: Different methodologies based on the O2-O2 477 nm band

NASA Astrophysics Data System (ADS)

Chimot, Julien; Vlemmix, Tim; Veefkind, Pepijn; Levelt, Pieternel

2016-04-01

Numerous studies have drawn attention to the complexities related to the retrievals of tropospheric NO2 columns derived from satellite UltraViolet-Visible (UV-Vis) measurements in the presence of aerosols. Correction for aerosol effects will remain a challenge for the next generation of air quality satellite instruments such as TROPOMI on Sentinel-5 Precursor, Sentinel-4 and Sentinel-5. The Ozone Monitoring Instrument (OMI) instrument has provided daily global measurements of tropospheric NO2 for more than a decade. However, aerosols are not explicitly taken into account in the current operational OMI tropospheric NO2 retrieval chain (DOMINO v2 [Boersma et al., 2011]). Our study analyses 2 approaches for an operational aerosol correction, based on the use of the O2-O2 477 nm band. The 1st approach is the cloud-model based aerosol correction, also named "implicit aerosol correction", and already used in the operational chain. The OMI O2-O2 cloud retrieval algorithm, based on the Differential Optical Absorption Spectroscopy (DOAS) approach, is applied both to cloudy and to cloud-free scenes with aerosols present. Perturbation of the OMI cloud retrievals over scenes dominated by aerosols has been observed in recent studies led by [Castellanos et al., 2015; Lin et al., 2015; Lin et al., 2014]. We investigated the causes of these perturbations by: (1) confronting the OMI tropospheric NO2, clouds and MODIS AQUA aerosol products; (2) characterizing the key drivers of the aerosol net effects, compared to a signal from clouds, in the UV-Vis spectra. This study has focused on large industrialised areas like East-China, over cloud-free scenes. One of the key findings is the limitation due to the coarse sampling of the employed cloud Look-Up Table (LUT) to convert the results of the applied DOAS fit into effective cloud fraction and pressure. This leads to an underestimation of tropospheric NO2 amount in cases of particles located at elevated altitude. A higher sampling of the variation of O2-O2 SCD and continuum reflectance as a function of effective cloud parameters in case of low effective cloud fraction values is requested for applying an aerosol correction. The updates of the OMI O2-O2 cloud algorithm, based on the scheduled new OMI cloud LUT, will be presented in terms of impacts of the effective cloud retrievals and reduced biases of tropospheric NO2 columns over cloud-free scenes dominated by aerosols in China. A 2nd approach is investigated, assuming a more explicit aerosol correction. Previous analyses pointed out that the O2-O2 spectra contain information about aerosols: the continuum reflectance is primarily constrained by the Aerosol Optical thickness (AOT) while the O2-O2 Slant Column Density (SCD) mostly results from the combination of AOT and aerosols altitude. We have developed a first prototype algorithm allowing to retrieve information about AOT and aerosol altitude from the O2-O2 DOAS fit. We will discuss preliminary sensitivities and the potential accuracy of the associated explicit aerosol correction, without the use of effective cloud parameters.

GOCI Yonsei aerosol retrieval version 2 aerosol products: improved algorithm description and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, M.; Kim, J.; Lee, J.; KIM, M.; Park, Y. J.; Holben, B. N.; Eck, T. F.; Li, Z.; Song, C. H.

2017-12-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed for retrieving hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD showed comparable accuracy compared to ground-based and other satellite-based observations, but still had errors due to uncertainties in surface reflectance and simple cloud masking. Also, it was not capable of near-real-time (NRT) processing because it required a monthly database of each year encompassing the day of retrieval for the determination of surface reflectance. This study describes the improvement of GOCI YAER algorithm to the version 2 (V2) for NRT processing with improved accuracy from the modification of cloud masking, surface reflectance determination using multi-year Rayleigh corrected reflectance and wind speed database, and inversion channels per surface conditions. Therefore, the improved GOCI AOD ( ) is similar with those of Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD compared to V1 of the YAER algorithm. The shows reduced median bias and increased ratio within range (i.e. absolute expected error range of MODIS AOD) compared to V1 in the validation results using Aerosol Robotic Network (AERONET) AOD ( ) from 2011 to 2016. The validation using the Sun-Sky Radiometer Observation Network (SONET) over China also shows similar results. The bias of error ( is within -0.1 and 0.1 range as a function of AERONET AOD and AE, scattering angle, NDVI, cloud fraction and homogeneity of retrieved AOD, observation time, month, and year. Also, the diagnostic and prognostic expected error (DEE and PEE, respectively) of are estimated. The estimated multiple PEE of GOCI V2 AOD is well matched with actual error over East Asia, and the GOCI V2 AOD over Korea shows higher ratio within PEE compared to over China and Japan. Hourly AOD products based on the improved GOCI YAER AOD could contribute to better understandings of aerosols in terms of long-term climate changes and short-term air quality monitoring and forecasting perspectives over East Asia, especially rapid diurnal variation and transboundary transport.

Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets.

NASA Astrophysics Data System (ADS)

Ignatov, Alexander; Minnis, Patrick; Loeb, Norman; Wielicki, Bruce; Miller, Walter; Sun-Mack, Sunny; Tanré, Didier; Remer, Lorraine; Laszlo, Istvan; Geier, Erika

2005-04-01

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

Assessment of 10 Year Record of Aerosol Optical Depth from OMI UV Observations

NASA Technical Reports Server (NTRS)

Ahn, Changwoo; Torres, Omar; Jethva, Hiren

2014-01-01

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 in the near-ultraviolet (UV) spectral region. Another important advantage of using near UV observations for aerosol characterization is the low surface albedo of all terrestrial surfaces in this spectral region that reduces retrieval errors associated with land surface reflectance characterization. In spite of the 13 × 24 square kilometers coarse sensor footprint, the OMI near UV aerosol algorithm (OMAERUV) retrieves aerosol optical depth (AOD) and single-scattering albedo under cloud-free conditions from radiance measurements at 354 and 388 nanometers. We present validation results of OMI AOD against space and time collocated Aerosol Robotic Network measured AOD values over multiple stations representing major aerosol episodes and regimes. OMAERUV's performance is also evaluated with respect to those of the Aqua-MODIS Deep Blue and Terra-MISR AOD algorithms over arid and semi-arid regions in Northern Africa. 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.

Quantification of uncertainty in aerosol optical thickness retrieval arising from aerosol microphysical model and other sources, applied to Ozone Monitoring Instrument (OMI) measurements

NASA Astrophysics Data System (ADS)

Määttä, A.; Laine, M.; Tamminen, J.; Veefkind, J. P.

2014-05-01

Satellite instruments are nowadays successfully utilised for measuring atmospheric aerosol in many applications as well as in research. Therefore, there is a growing need for rigorous error characterisation of the measurements. Here, we introduce a methodology for quantifying the uncertainty in the retrieval of aerosol optical thickness (AOT). In particular, we concentrate on two aspects: uncertainty due to aerosol microphysical model selection and uncertainty due to imperfect forward modelling. We apply the introduced methodology for aerosol optical thickness retrieval of the Ozone Monitoring Instrument (OMI) on board NASA's Earth Observing System (EOS) Aura satellite, launched in 2004. We apply statistical methodologies that improve the uncertainty estimates of the aerosol optical thickness retrieval by propagating aerosol microphysical model selection and forward model error more realistically. For the microphysical model selection problem, we utilise Bayesian model selection and model averaging methods. Gaussian processes are utilised to characterise the smooth systematic discrepancies between the measured and modelled reflectances (i.e. residuals). The spectral correlation is composed empirically by exploring a set of residuals. 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 introduced here. The method and improved uncertainty characterisation is demonstrated by several examples with different aerosol properties: weakly absorbing aerosols, forest fires over Greece and Russia, and Sahara desert dust. The statistical methodology presented is general; it is not restricted to this particular satellite retrieval application.

Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors

NASA Technical Reports Server (NTRS)

Petrenko, Maksym; Ichoku, Charles; Leptoukh, Gregory

2011-01-01

Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.

Global Assessment of OMI Aerosol Single-scattering Albedo Using Ground-based AERONET and SKYNET Inversions

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Ahn, Changwoo

2014-01-01

We compare the aerosol single-scattering albedo (SSA) retrieved by the near-UV two-channel algorithm (OMAERUV) applied to the Aura-Ozone Monitoring Instrument (OMI) measurements with an equivalent inversion made by the ground-based Aerosol Robotic Network (AERONET). This work is the first comprehensive effort to globally compare the OMI-retrieved SSA with that of AERONET using all available sites spanning the regions of biomass burning, dust, and urban pollution. An analysis of the co-located retrievals over 269 sites reveals that about 46 percent (69 percent) of OMI-AERONET matchups agree within the absolute difference of plus or minus 0.03 (plus or minus 0.05) for all aerosol types. The comparison improves to 52 percent (77 percent) when only 'smoke' and 'dust' aerosol types were identified by the OMAERUV algorithm. Regionally, the agreement between the two inversions was robust over the biomass burning sites of South America, Sahel, Indian subcontinent, and oceanic-coastal sites followed by a reasonable agreement over north-east Asia. Over the desert regions, OMI tends to retrieve higher SSA, particularly over the Arabian Peninsula. Globally, the OMI-AERONET matchups agree mostly within plus or minus 0.03 for the aerosol optical depth (440 nanometers) and UV-aerosol index larger than 0.4 and 1.0, respectively. We also compare the OMAERUV SSA against the inversion made by an independent network of ground-based radiometer called SKYNET with its operating sites in Japan, China, South-East Asia, India, and Europe. The advantage of the SKYNET database over AERONET is that it performs retrieval at near-UV wavelengths which facilitate the direct comparison of OMI retrievals with the equivalent ground-based inversion. Comparison of OMI and SKYNET over currently available sites reveals a good agreement between the two where more than 70 percent of matchups agree within the absolute difference of 0.05.

What is the Uncertainty in MODIS Aerosol Optical Depth in the Vicinity of Clouds?

NASA Technical Reports Server (NTRS)

Patadia, Falguni; Levy, Rob; Mattoo, Shana

2017-01-01

MODIS dark-target (DT) algorithm retrieves aerosol optical depth (AOD) using a Look Up Table (LUT) approach. Global comparison of AOD (Collection 6 ) with ground-based sun photometer gives an Estimated Error (EE) of +/-(0.04 + 10%) over ocean. However, EE does not represent per-retrieval uncertainty. For retrievals that are biased high compared to AERONET, here we aim to closely examine the contribution of biases due to presence of clouds and per-pixel retrieval uncertainty. We have characterized AOD uncertainty at 550 nm, due to standard deviation of reflectance in 10 km retrieval region, uncertainty related to gas (H2O, O3) absorption, surface albedo, and aerosol models. The uncertainty in retrieved AOD seems to lie within the estimated over ocean error envelope of +/-(0.03+10%). Regions between broken clouds tend to have higher uncertainty. Compared to C6 AOD, a retrieval omitting observations in the vicinity of clouds (< or = 1 km) is biased by about +/- 0.05. For homogeneous aerosol distribution, clear sky retrievals show near zero bias. Close look at per-pixel reflectance histograms suggests retrieval possibility using median reflectance values.

Characterization of Properties of Earth Atmosphere from Multi-Angular Polarimetric Observations of Polder/Parasol Using GRASP Algorithm

NASA Astrophysics Data System (ADS)

Dubovik, O.; Litvinov, P.; Lapyonok, T.; Ducos, F.; Fuertes, D.; Huang, X.; Torres, B.; Aspetsberger, M.; Federspiel, C.

2014-12-01

The POLDER imager on board of the PARASOL micro-satellite is the only satellite polarimeter provided ~ 9 years extensive record of detailed polarmertic observations of Earth atmosphere from space. POLDER / PARASOL registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. Such observations have very high sensitivity to the variability of the properties of atmosphere and underlying surface and can not be adequately interpreted using look-up-table retrieval algorithms developed for analyzing mono-viewing intensity only observations traditionally used in atmospheric remote sensing. Therefore, a new enhanced retrieval algorithm GRASP (Generalized Retrieval of Aerosol and Surface Properties) has been developed and applied for processing of PARASOL data. GRASP relies on highly optimized statistical fitting of observations and derives large number of unknowns for each observed pixel. The algorithm uses elaborated model of the atmosphere and fully accounts for all multiple interactions of scattered solar light with aerosol, gases and the underlying surface. All calculations are implemented during inversion and no look-up tables are used. The algorithm is very flexible in utilization of various types of a priori constraints on the retrieved characteristics and in parameterization of surface - atmosphere system. It is also optimized for high performance calculations. The results of the PARASOL data processing will be presented with the emphasis on the discussion of transferability and adaptability of the developed retrieval concept for processing polarimetric observations of other planets. For example, flexibility and possible alternative in modeling properties of aerosol polydisperse mixtures, particle composition and shape, reflectance of surface, etc. will be discussed.

Steps Toward an EOS-Era Aerosol Type Climatology

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2012-01-01

We still have a way to go to develop a global climatology of aerosol type from the EOS-era satellite data record that currently spans more than 12 years of observations. We have demonstrated the ability to retrieve aerosol type regionally, providing a classification based on the combined constraints on particle size, shape, and single-scattering albedo (SSA) from the MISR instrument. Under good but not necessarily ideal conditions, the MISR data can distinguish three-to-five size bins, two-to-four bins in SSA, and spherical vs. non-spherical particles. However, retrieval sensitivity varies enormously with scene conditions. So, for example, there is less information about aerosol type when the mid-visible aerosol optical depth (AOD) is less that about 0.15 or 0.2, or when the range of scattering angles observed is reduced by solar geometry, even though the quality of the AOD retrieval itself is much less sensitive to these factors. This presentation will review a series of studies aimed at assessing the capabilities, as well as the limitations, of MISR aerosol type retrievals involving wildfire smoke, desert dust, volcanic ash, and urban pollution, in specific cases where suborbital validation data are available. A synthesis of results, planned upgrades to the MISR Standard aerosol algorithm to improve aerosol type retrievals, and steps toward the development of an aerosol type quality flag for the Standard product, will also be covered.

Evaluation of the MODIS Retrievals of Dust Aerosol over the Ocean during PRIDE

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Holben, Brent N.; Livingston, John M.; Russell, Philip B.; Maring, Hal

2002-01-01

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.

Retrieval and Validation of Aerosol Optical Depth by using the GF-1 Remote Sensing Data

NASA Astrophysics Data System (ADS)

Zhang, L.; Xu, S.; Wang, L.; Cai, K.; Ge, Q.

2017-05-01

Based on the characteristics of GF-1 remote sensing data, the method and data processing procedure to retrieve the Aerosol Optical Depth (AOD) are developed in this study. The surface contribution over dense vegetation and urban bright target areas are respectively removed by using the dark target and deep blue algorithms. Our method is applied for the three serious polluted Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions. The retrieved AOD are validated by ground-based AERONET data from Beijing, Hangzhou, Hong Kong sites. Our results show that, 1) the heavy aerosol loadings are usually distributed in high industrial emission and dense populated cities, with the AOD value near 1. 2) There is a good agreement between satellite-retrievals and in-site observations, with the coefficient factors of 0.71 (BTH), 0.55 (YRD) and 0.54(PRD). 3) The GF-1 retrieval uncertainties are mainly from the impact of cloud contamination, high surface reflectance and assumed aerosol model.

Dust altitude and infrared optical depth retrieved from 6 years of AIRS observations : a focus on Saharan dust using A-Train synergy (MODIS, CALIOP)

NASA Astrophysics Data System (ADS)

Peyridieu, S.; Chédin, A.; Capelle, V.; Pierangelo, C.; Lamquin, N.; Armante, R.

2009-04-01

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). Our results of the dust optical depth at 10 µm have been compared to the 0.55 µm Aqua/MODIS optical depth product for this period. The detailed study of Atlantic regions shows a very good agreement between the two products, with a VIS/IR ratio around 0.3-0.5 during the Saharan dust season. Comparing these two AOD products should allow separating different aerosols signals, given that our retrieval algorithm is specifically designed for dust coarse mode whereas MODIS retrieves both accumulation and fine aerosol modes. Mean aerosol layer altitude has also been retrieved from AIRS data and we show global maps and time series of altitude retrieved from space. Altitude retrievals are compared to the CALIOP/Calipso Level-2 product starting June 2006. This comparison, for a region located downwind from the Sahara, again shows a good agreement demonstrating that our algorithm effectively allows retrieving reliable mean dust layer altitude. A global climatology of the dust optical depth at 10 µm and of the aerosol layer mean altitude has also been established. An interesting conclusion is the fact that if the AOD decreases from Africa to the Caribbean as a result of transport and dilution, altitude decreases less rapidly. This is in agreement with in situ measurements made during the Puerto Rico Dust Experiment (PRIDE) campaign and modelled forward trajectories.

Validation of new satellite aerosol optical depth retrieval algorithm using Raman lidar observations at radiative transfer laboratory in Warsaw

NASA Astrophysics Data System (ADS)

Zawadzka, Olga; Stachlewska, Iwona S.; Markowicz, Krzysztof M.; Nemuc, Anca; Stebel, Kerstin

2018-04-01

During an exceptionally warm September of 2016, the unique, stable weather conditions over Poland allowed for an extensive testing of the new algorithm developed to improve the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) aerosol optical depth (AOD) retrieval. The development was conducted in the frame of the ESA-ESRIN SAMIRA project. The new AOD algorithm aims at providing the aerosol optical depth maps over the territory of Poland with a high temporal resolution of 15 minutes. It was tested on the data set obtained between 11-16 September 2016, during which a day of relatively clean atmospheric background related to an Arctic airmass inflow was surrounded by a few days with well increased aerosol load of different origin. On the clean reference day, for estimating surface reflectance the AOD forecast available on-line via the Copernicus Atmosphere Monitoring Service (CAMS) was used. The obtained AOD maps were validated against AODs available within the Poland-AOD and AERONET networks, and with AOD values obtained from the PollyXT-UW lidar. of the University of Warsaw (UW).

Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip T.; Cronk, Heather Q.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert Y.; Fisher, Brenden; Osterman, Gregory B.; Pollock, Randy H.; Crisp, David; Eldering, Annmarie; Gunson, Michael R.

2016-03-01

The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O2 A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 µm (weak CO2 band) and 2.06 µm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set.To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of ≃ 20-25 % of all OCO-2 soundings, agreement between the OCO-2 and MODIS cloud screening methods is found to be ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April-May) for OCO-2 nadir-land, glint-land and glint-water observations.No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Holben, Brent; Eck, Thomas F.; Li, Zhengqiang; Song, Chul H.

2018-01-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed to retrieve hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD had accuracy comparable to ground-based and other satellite-based observations but still had errors because of uncertainties in surface reflectance and simple cloud masking. In addition, near-real-time (NRT) processing was not possible because a monthly database for each year encompassing the day of retrieval was required for the determination of surface reflectance. This study describes the improved GOCI YAER algorithm version 2 (V2) for NRT processing with improved accuracy based on updates to the cloud-masking and surface-reflectance calculations using a multi-year Rayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD τG is closer to that of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2 τG has a lower median bias and higher ratio within the MODIS expected error range (0.60 for land and 0.71 for ocean) compared with V1 (0.49 for land and 0.62 for ocean) in a validation test against Aerosol Robotic Network (AERONET) AOD τA from 2011 to 2016. A validation using the Sun-Sky Radiometer Observation Network (SONET) over China shows similar results. The bias of error (τG - τA) is within -0.1 and 0.1, and it is a function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction and homogeneity of retrieved AOD, and observation time, month, and year. In addition, the diagnostic and prognostic expected error (PEE) of τG are estimated. The estimated PEE of GOCI V2 AOD is well correlated with the actual error over East Asia, and the GOCI V2 AOD over South Korea has a higher ratio within PEE than that over China and Japan.

Remote Sensing of Spectral Aerosol Properties: A Classroom Experience

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Pinker, Rachel T.

2006-01-01

Bridging the gap between current research and the classroom is a major challenge to today s instructor, especially in the sciences where progress happens quickly. NASA Goddard Space Flight Center and the University of Maryland teamed up in designing a graduate class project intended to provide a hands-on introduction to the physical basis for the retrieval of aerosol properties from state-of-the-art MODIS observations. Students learned to recognize spectral signatures of atmospheric aerosols and to perform spectral inversions. They became acquainted with the operational MODIS aerosol retrieval algorithm over oceans, and methods for its evaluation, including comparisons with groundbased AERONET sun-photometer data.

The MODIS Aerosol Algorithm, Products and Validation

NASA Technical Reports Server (NTRS)

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.

2003-01-01

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.

Vertical Profiles of Aerosol Optical Properties Over Central Illinois and Comparison with Surface and Satellite Measurements

NASA Technical Reports Server (NTRS)

Sheridan P. J.; Andrews, E.; Ogren, J A.; Tackett, J. L.; Winker, D. M.

2012-01-01

Between June 2006 and September 2009, an instrumented light aircraft measured over 400 vertical profiles of aerosol and trace gas properties over eastern and central Illinois. The primary objectives of this program were to (1) measure the in situ aerosol properties and determine their vertical and temporal variability and (2) relate these aircraft measurements to concurrent surface and satellite measurements. Underflights of the CALIPSO satellite show reasonable agreement in a majority of retrieved profiles between aircraft-measured extinction at 532 nm (adjusted to ambient relative humidity) and CALIPSO-retrieved extinction, and suggest that routine aircraft profiling programs can be used to better understand and validate satellite retrieval algorithms. CALIPSO tended to overestimate the aerosol extinction at this location in some boundary layer flight segments when scattered or broken clouds were present, which could be related to problems with CALIPSO cloud screening methods. The in situ aircraft-collected aerosol data suggest extinction thresholds for the likelihood of aerosol layers being detected by the CALIOP lidar. These statistical data offer guidance as to the likelihood of CALIPSO's ability to retrieve aerosol extinction at various locations around the globe.

Evaluation and Windspeed Dependence of MODIS Aerosol Retrievals Over Open Ocean

NASA Technical Reports Server (NTRS)

Kleidman, Richard G.; Smirnov, Alexander; Levy, Robert C.; Mattoo, Shana; Tanre, Didier

2011-01-01

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.

Unveiling aerosol-cloud interactions - Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate

NASA Astrophysics Data System (ADS)

Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.

2017-11-01

Increased concentrations of aerosol can enhance the albedo of warm low-level cloud. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near clouds. Aerosol retrievals near clouds can be influenced by stray cloud particles in areas assumed to be cloud-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) clouds. To screen for this contamination we have developed a new cloud-aerosol pairing algorithm (CAPA) to link cloud observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest cloud is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the clouds (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest cloud (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to cloud artificially enhance the relationship between aerosol-loading, cloud albedo, and cloud fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near clouds.

Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager

NASA Astrophysics Data System (ADS)

Xu, Feng; van Harten, Gerard; Diner, David J.; Kalashnikova, Olga V.; Seidel, Felix C.; Bruegge, Carol J.; Dubovik, Oleg

2017-07-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high-altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 11 km and is typically observed from nine viewing angles between ±66° off nadir. For a simultaneous retrieval of aerosol properties and surface reflection using AirMSPI, an efficient and flexible retrieval algorithm has been developed. It imposes multiple types of physical constraints on spectral and spatial variations of aerosol properties as well as spectral and temporal variations of surface reflection. Retrieval uncertainty is formulated by accounting for both instrumental errors and physical constraints. A hybrid Markov-chain/adding-doubling radiative transfer (RT) model is developed to combine the computational strengths of these two methods in modeling polarized RT in vertically inhomogeneous and homogeneous media, respectively. Our retrieval approach is tested using 27 AirMSPI data sets with low to moderately high aerosol loadings, acquired during four NASA field campaigns plus one AirMSPI preengineering test flight. The retrieval results including aerosol optical depth, single-scattering albedo, aerosol size and refractive index are compared with Aerosol Robotic Network reference data. We identify the best angular combinations for 2, 3, 5, and 7 angle observations from the retrieval quality assessment of various angular combinations. We also explore the benefits of polarimetric and multiangular measurements and target revisits in constraining aerosol property and surface reflection retrieval.

Determination of the single scattering albedo and direct radiative forcing of biomass burning aerosol with data from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite instrument

NASA Astrophysics Data System (ADS)

Zhu, Li

Biomass burning aerosols absorb and scatter solar radiation and therefore affect the energy balance of the Earth-atmosphere system. The single scattering albedo (SSA), the ratio of the scattering coefficient to the extinction coefficient, is an important parameter to describe the optical properties of aerosols and to determine the effect of aerosols on the energy balance of the planet and climate. Aerosol effects on radiation also depend strongly on surface albedo. Large uncertainties remain in current estimates of radiative impacts of biomass burning aerosols, due largely to the lack of reliable measurements of aerosol and surface properties. In this work we investigate how satellite measurements can be used to estimate the direct radiative forcing of biomass burning aerosols. We developed a method using the critical reflectance technique to retrieve SSA from the Moderate Resolution Imaging Spectroradiometer (MODIS) observed reflectance at the top of the atmosphere (TOA). We evaluated MODIS retrieved SSAs with AErosol RObotic NETwork (AERONET) retrievals and found good agreements within the published uncertainty of the AERONET retrievals. We then developed an algorithm, the MODIS Enhanced Vegetation Albedo (MEVA), to improve the representations of spectral variations of vegetation surface albedo based on MODIS observations at the discrete 0.67, 0.86, 0.47, 0.55, 1.24, 1.64, and 2.12 mu-m channels. This algorithm is validated using laboratory measurements of the different vegetation types from the Amazon region, data from the Johns Hopkins University (JHU) spectral library, and data from the U.S. Geological Survey (USGS) digital spectral library. We show that the MEVA method can improve the accuracy of flux and aerosol forcing calculations at the TOA compared to more traditional interpolated approaches. Lastly, we combine the MODIS retrieved biomass burning aerosol SSA and the surface albedo spectrum determined from the MEVA technique to calculate TOA flux and aerosol direct radiative forcing over the Amazon region and compare it with Clouds and the Earth's Radiant Energy System (CERES) satellite results. The results show that MODIS based forcing calculations present similar averaged results compared to CERES, but MODIS shows greater spatial variation of aerosol forcing than CERES. Possible reasons for these differences are explored and discussed in this work. Potential future research based on these results is discussed as well.

Surface retrievals from Hyperion EO1 using a new, fast, 1D-Var based retrieval code

NASA Astrophysics Data System (ADS)

Thelen, Jean-Claude; Havemann, Stephan; Wong, Gerald

2015-05-01

We have developed a new algorithm for the simultaneous retrieval of the atmospheric profiles (temperature, humidity, ozone and aerosol) and the surface reflectance from hyperspectral radiance measurements obtained from air/space-borne, hyperspectral imagers such as Hyperion EO-1. The new scheme, proposed here, consists of a fast radiative transfer code, based on empirical orthogonal functions (EOFs), in conjunction with a 1D-Var retrieval scheme. The inclusion of an 'exact' scattering code based on spherical harmonics, allows for an accurate treatment of Rayleigh scattering and scattering by aerosols, water droplets and ice-crystals, thus making it possible to also retrieve cloud and aerosol optical properties, although here we will concentrate on non-cloudy scenes. We successfully tested this new approach using hyperspectral images taken by Hyperion EO-1, an experimental pushbroom imaging spectrometer operated by NASA.

Validation of MODIS Dust Aerosol Retrieval and Development Ambient Dust Phase Function using PRIDE Data

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Lau, William (Technical Monitor)

2002-01-01

The PRIDE data set of MODIS aerosol retrievals co-located with sunphotometer measurements provides the basis of MODIS validation in a dust environment. The sunphotometer measurements include AERONET automatic instruments, land-based Microtops instruments, ship-board Microtops instruments and the AATS-6 aboard the Navajo aircraft. Analysis of these data indicate that the MODIS retrieval is within pre-launch estimates of uncertainty within the spectral range of 600-900 nm. However, the MODIS algorithm consistently retrieves smaller particles than reality thus leading to incorrect spectral response outside of the 600-900 nm range and improper size information. Further analysis of MODIS retrievals in other dust environments shows the inconsistencies are due to nonspherical effects in the phase function. These data are used to develop an ambient phase function for dust aerosol to be used for remote sensing purposes.

Direct Radiative Forcing from Saharan Mineral Dust Layers from In-situ Measurements and Satellite Retrievals

NASA Astrophysics Data System (ADS)

Sauer, D. N.; Vázquez-Navarro, M.; Gasteiger, J.; Chouza, F.; Weinzierl, B.

2016-12-01

Mineral dust is the major species of airborne particulate matter by mass in the atmosphere. Each year an estimated 200-3000 Tg of dust are emitted from the North African desert and arid regions alone. A large fraction of the dust is lifted into the free troposphere and gets transported in extended dust layers westward over the Atlantic Ocean into the Caribbean Sea. Especially over the dark surface of the ocean, those dust layers exert a significant effect on the atmospheric radiative balance though aerosol-radiation interactions. During the Saharan Aerosol Long-range Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE) in summer 2013 airborne in-situ aerosol measurements on both sides of the Atlantic Ocean, near the African coast and the Caribbean were performed. In this study we use data about aerosol microphysical properties acquired between Cabo Verde and Senegal to derive the aerosol optical properties and the resulting radiative forcing using the radiative transfer package libRadtran. We compare the results to values retrieved from MSG/SEVIRI data using the RRUMS algorithm. The RRUMS algorithm can derive shortwave and longwave top-of-atmosphere outgoing fluxes using only information issued from the narrow-band MSG/SEVIRI channels. A specific calibration based on collocated Terra/CERES measurements ensures a correct retrieval of the upwelling flux from the dust covered pixels. The comparison of radiative forcings based on in-situ data to satellite-retrieved values enables us to extend the radiative forcing estimates from small-scale in-situ measurements to large scale satellite coverage over the Atlantic Ocean.

Air Quality Monitoring and Forecasting Applications of Suomi NPP VIIRS Aerosol Products

NASA Astrophysics Data System (ADS)

Kondragunta, Shobha

The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched on October 28, 2011. It provides Aerosol Optical Thickness (AOT) at two different spatial resolutions: a pixel level (~750 m at nadir) product called the Intermediate Product (IP) and an aggregated (~6 km at nadir) product called the Environmental Data Record (EDR), and a Suspended Matter (SM) EDR that provides aerosol type (dust, smoke, sea salt, and volcanic ash) information. An extensive validation of VIIRS best quality aerosol products with ground based L1.5 Aerosol Robotic NETwork (AERONET) data shows that the AOT EDR product has an accuracy/precision of -0.01/0.11 and 0.01/0.08 over land and ocean respectively. Globally, VIIRS mean AOT EDR (0.20) is similar to Aqua MODIS (0.16) with some important regional and seasonal differences. The accuracy of the SM product, however, is found to be very low (20 percent) when compared to Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) and AERONET. Several algorithm updates which include a better approach to retrieve surface reflectance have been developed for AOT retrieval. For dust aerosol type retrieval, a new approach that takes advantage of spectral dependence of Rayleigh scattering, surface reflectance, dust absorption in the deep blue (412 nm), blue (440 nm), and mid-IR (2.2 um) has been developed that detects dust with an accuracy of ~80 percent. For smoke plume identification, a source apportionment algorithm that combines fire hot spots with AOT imagery has been developed that provides smoke plume extent with an accuracy of ~70 percent. The VIIRS aerosol products will provide continuity to the current operational use of aerosol products from Aqua and Terra MODIS. These include aerosol data assimilation in Naval Research Laboratory (NRL) global aerosol model, verification of National Weather Service (NWS) dust and smoke forecasts, exceptional events monitoring by different states, air quality warnings by Environmental Protection Agency (EPA). This talk will provide an overview of VIIRS algorithms, aerosol product validation, and examples of various applications with a discussion on the relevance of product accuracy.

Deep Blue Retrievals of Asian Aerosol Properties During ACE-Asia

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, Si-Cee; King, Michael D.; Herman, Jay R.

2006-01-01

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.

Validation of TOMS Aerosol Products using AERONET Observations

NASA Technical Reports Server (NTRS)

Bhartia, P. K.; Torres, O.; Sinyuk, A.; Holben, B.

2002-01-01

The Total Ozone Mapping Spectrometer (TOMS) aerosol algorithm uses measurements of radiances at two near UV channels in the range 331-380 nm to derive aerosol optical depth and single scattering albedo. Because of the low near UV surface albedo of all terrestrial surfaces (between 0.02 and 0.08), the TOMS algorithm has the capability of retrieving aerosol properties over the oceans and the continents. The Aerosol Robotic Network (AERONET) routinely derives spectral aerosol optical depth and single scattering albedo at a large number of sites around the globe. We have performed comparisons of both aerosol optical depth and single scattering albedo derived from TOMS and AERONET. In general, the TOMS aerosol products agree well with the ground-based observations, Results of this validation will be discussed.

Description and Sensitivity Analysis of the SOLSE/LORE-2 and SAGE III Limb Scattering Ozone Retrieval Algorithms

NASA Technical Reports Server (NTRS)

Loughman, R.; Flittner, D.; Herman, B.; Bhartia, P.; Hilsenrath, E.; McPeters, R.; Rault, D.

2002-01-01

The SOLSE (Shuttle Ozone Limb Sounding Experiment) and LORE (Limb Ozone Retrieval Experiment) instruments are scheduled for reflight on Space Shuttle flight STS-107 in July 2002. In addition, the SAGE III (Stratospheric Aerosol and Gas Experiment) instrument will begin to make limb scattering measurements during Spring 2002. The optimal estimation technique is used to analyze visible and ultraviolet limb scattered radiances and produce a retrieved ozone profile. The algorithm used to analyze data from the initial flight of the SOLSE/LORE instruments (on Space Shuttle flight STS-87 in November 1997) forms the basis of the current algorithms, with expansion to take advantage of the increased multispectral information provided by SOLSE/LORE-2 and SAGE III. We also present detailed sensitivity analysis for these ozone retrieval algorithms. The primary source of ozone retrieval error is tangent height misregistration (i.e., instrument pointing error), which is relevant throughout the altitude range of interest, and can produce retrieval errors on the order of 10-20 percent due to a tangent height registration error of 0.5 km at the tangent point. Other significant sources of error are sensitivity to stratospheric aerosol and sensitivity to error in the a priori ozone estimate (given assumed instrument signal-to-noise = 200). These can produce errors up to 10 percent for the ozone retrieval at altitudes less than 20 km, but produce little error above that level.

Extending MODIS Deep Blue Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: First Results

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Shinozuka, Y.; Schmid, B.

2015-01-01

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.

Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms; validation against collocated MODIS and CALIOP data

NASA Astrophysics Data System (ADS)

Taylor, T. E.; O'Dell, C. W.; Frankenberg, C.; Partain, P.; Cronk, H. Q.; Savtchenko, A.; Nelson, R. R.; Rosenthal, E. J.; Chang, A. Y.; Fisher, B.; Osterman, G.; Pollock, R. H.; Crisp, D.; Eldering, A.; Gunson, M. R.

2015-12-01

The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols within the instrument's field of view (FOV). Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 μm O2 A-band, neglecting scattering by clouds and aerosols, which introduce photon path-length (PPL) differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 μm (weak CO2 band) and 2.06 μm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which key off of different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning to allow throughputs of ≃ 30 %, agreement between the OCO-2 and MODIS cloud screening methods is found to be ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April-May) for OCO-2 nadir-land, glint-land and glint-water observations. No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

Direct Aerosol Radiative Forcing from Combined A-Train Observations - Preliminary Comparisons with AeroCom Models and Pathways to Observationally Based All-sky Estimates

NASA Astrophysics Data System (ADS)

Redemann, J.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Russell, P. B.; LeBlanc, S. E.; Vaughan, M.; Ferrare, R. A.; Hostetler, C. A.; Rogers, R. R.; Burton, S. P.; Torres, O.; Remer, L. A.; Stier, P.; Schutgens, N.

2014-12-01

We describe a technique for combining CALIOP aerosol backscatter, MODIS spectral AOD (aerosol optical depth), and OMI AAOD (absorption aerosol optical depth) retrievals for the purpose of estimating full spectral sets of aerosol radiative properties, and ultimately for calculating the 3-D distribution of direct aerosol radiative forcing. We present results using one year of data collected in 2007 and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the recently released MODIS Collection 6 data for aerosol optical depths derived with the dark target and deep blue algorithms has extended the coverage of the multi-sensor estimates towards higher latitudes. Initial calculations of seasonal clear-sky aerosol radiative forcing based on our multi-sensor aerosol retrievals compare well with over-ocean and top of the atmosphere IPCC-2007 model-based results, and with more recent assessments in the "Climate Change Science Program Report: Atmospheric Aerosol Properties and Climate Impacts" (2009). For the first time, we present comparisons of our multi-sensor aerosol direct radiative forcing estimates to values derived from a subset of models that participated in the latest AeroCom initiative. We discuss the major challenges that exist in extending our clear-sky results to all-sky conditions. On the basis of comparisons to suborbital measurements, we present some of the limitations of the MODIS and CALIOP retrievals in the presence of adjacent or underlying clouds. Strategies for meeting these challenges are discussed.

1984-1995 Evolution of Stratospheric Aerosol Size, Surface Area, and Volume Derived by Combining SAGE II and CLAES Extinction Measurements

NASA Technical Reports Server (NTRS)

Russell, Philip B.; Bauman, Jill J.

2000-01-01

This SAGE II Science Team task focuses on the development of a multi-wavelength, multi- sensor Look-Up-Table (LUT) algorithm for retrieving information about stratospheric aerosols from global satellite-based observations of particulate extinction. The LUT algorithm combines the 4-wavelength SAGE II extinction measurements (0.385 <= lambda <= 1.02 microns) with the 7.96 micron and 12.82 micron extinction measurements from the Cryogenic Limb Array Etalon Spectrometer (CLAES) instrument, thus increasing the information content available from either sensor alone. The algorithm uses the SAGE II/CLAES composite spectra in month-latitude-altitude bins to retrieve values and uncertainties of particle effective radius R(sub eff), surface area S, volume V and size distribution width sigma(sub g).

Intercomparison of Eight Forward 1D Vector Radiative Transfer Models, with the Performance of Satellite Aerosol Remote Sensing Algorithms in Mind

NASA Astrophysics Data System (ADS)

Davis, Anthony B.; Kalashnikova, Olga V.; Diner, David J.; Garay, Michael J.; Lyapustin, Alexei I.; Korkin, Sergey V.; Martonchik, John V.; Natraj, Vijay; Sanghavi, Suniti V.; Xu, Feng; Zhai, Pengwang; Rozanov, Vladimir V.; Kokhanovsky, Alexander A.

2014-05-01

Quantification and characterization of the omnipresent atmospheric aerosol by remote sensing methods is key to answering many challenging questions in atmospheric science, in climate modeling and in air quality monitoring foremost. In recent years, accurate measurement of the state of polarization of photon fluxes at optical sensors in the visible and near-IR spectrum has been hailed as a very promising approach to aerosol remote sensing. Consequently, there has been a flurry of activity in polarized or 'vector' radiative transfer (vRT) model development. This covers the multiple scattering and ground reflection aspects of sensor signal prediction that complement single-particle scattering computation, and lies at the core of all physics-based retrieval algorithms. One can legitimately ask: What level of model fidelity (representativeness of natural scenes) and what computational accuracy should be achieved for this task in view of the practical constraints that apply? These constraints are, at a minimum: (i) the desired accuracy of the retrieved aerosol properties, (ii) observational uncertainties, and (iii) operational efficiency requirements as determined by throughput. We offer a rational and balanced approach to address these questions and illustrate it with a systematic inter-comparison of the performance of a diverse set of 1D vRT models using a small but representative set of test cases. This 'JPL' benchmarking suite of cases is naturally divided into two parts. First the emphasis is on stratified atmospheres with a continuous mixture of molecular and aerosol scattering and absorption over a black surface, with the corresponding pure cases treated for diagnostic purposes. Then the emphasis shifts to the variety of surfaces, both polarizing and not, that can be encountered in real observations and may confuse the aerosol retrieval algorithm if not properly treated.

Development and assessment of a higher-spatial-resolution (4.4 km) MISR aerosol optical depth product using AERONET-DRAGON data

NASA Astrophysics Data System (ADS)

Garay, Michael J.; Kalashnikova, Olga V.; Bull, Michael A.

2017-04-01

Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been acquiring data that have been used to produce aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution. Capitalizing on the capabilities provided by multi-angle viewing, the current operational (Version 22) MISR algorithm performs well, with about 75 % of MISR AOD retrievals globally falling within 0.05 or 20 % × AOD of paired validation data from the ground-based Aerosol Robotic Network (AERONET). This paper describes the development and assessment of a prototype version of a higher-spatial-resolution 4.4 km MISR aerosol optical depth product compared against multiple AERONET Distributed Regional Aerosol Gridded Observations Network (DRAGON) deployments around the globe. In comparisons with AERONET-DRAGON AODs, the 4.4 km resolution retrievals show improved correlation (r = 0. 9595), smaller RMSE (0.0768), reduced bias (-0.0208), and a larger fraction within the expected error envelope (80.92 %) relative to the Version 22 MISR retrievals.

MODIS Retrieval of Dust Aerosol

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kaufman, Yoram J.; Tanre, Didier

2003-01-01

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.

Use of A-Train Aerosol Observations to Constrain Direct Aerosol Radiative Effects (DARE) Comparisons with Aerocom Models and Uncertainty Assessments

NASA Technical Reports Server (NTRS)

Redemann, J.; Shinozuka, Y.; Kacenelenbogen, M.; Segal-Rozenhaimer, M.; LeBlanc, S.; Vaughan, M.; Stier, P.; Schutgens, N.

2017-01-01

We describe a technique for combining multiple A-Train aerosol data sets, namely MODIS spectral AOD (aerosol optical depth), OMI AAOD (absorption aerosol optical depth) and CALIOP aerosol backscatter retrievals (hereafter referred to as MOC retrievals) to estimate full spectral sets of aerosol radiative properties, and ultimately to calculate the 3-D distribution of direct aerosol radiative effects (DARE). We present MOC results using almost two years of data collected in 2007 and 2008, and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the MODIS Collection 6 AOD data derived with the dark target and deep blue algorithms has extended the coverage of the MOC retrievals towards higher latitudes. The MOC aerosol retrievals agree better with AERONET in terms of the single scattering albedo (ssa) at 441 nm than ssa calculated from OMI and MODIS data alone, indicating that CALIOP aerosol backscatter data contains information on aerosol absorption. We compare the spatio-temporal distribution of the MOC retrievals and MOC-based calculations of seasonal clear-sky DARE to values derived from four models that participated in the Phase II AeroCom model intercomparison initiative. Overall, the MOC-based calculations of clear-sky DARE at TOA over land are smaller (less negative) than previous model or observational estimates due to the inclusion of more absorbing aerosol retrievals over brighter surfaces, not previously available for observationally-based estimates of DARE. MOC-based DARE estimates at the surface over land and total (land and ocean) DARE estimates at TOA are in between previous model and observational results. Comparisons of seasonal aerosol property to AeroCom Phase II results show generally good agreement best agreement with forcing results at TOA is found with GMI-MerraV3. We discuss sampling issues that affect the comparisons and the major challenges in extending our clear-sky DARE results to all-sky conditions. We present estimates of clear-sky and all-sky DARE and show uncertainties that stem from the assumptions in the spatial extrapolation and accuracy of aerosol and cloud properties, in the diurnal evolution of these properties, and in the radiative transfer calculations.

Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer

NASA Technical Reports Server (NTRS)

Broderick, Daniel

2012-01-01

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.

Evaluations of Thin Cirrus Contamination and Screening in Ground Aerosol Observations Using Collocated Lidar Systems

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Holben, Brent N.; Welton, Ellsworth J.; Smirnov, Alexander; Jeong, Myeong-Jae; Hansell, Richard A.; Berkoff, Timothy A.

2012-01-01

Cirrus clouds, particularly sub visual high thin cirrus with low optical thickness, are difficult to be screened in operational aerosol retrieval algorithms. Collocated aerosol and cirrus observations from ground measurements, such as the Aerosol Robotic Network (AERONET) and the Micro-Pulse Lidar Network (MPLNET), provide us with an unprecedented opportunity to examine the susceptibility of operational aerosol products to thin cirrus contamination. Quality assured aerosol optical thickness (AOT) measurements were also tested against the CALIPSO vertical feature mask (VFM) and the MODIS-derived thin cirrus screening parameters for the purpose of evaluating thin cirrus contamination. Key results of this study include: (1) Quantitative evaluations of data uncertainties in AERONET AOT retrievals are conducted. Although AERONET cirrus screening schemes are successful in removing most cirrus contamination, strong residuals displaying strong spatial and seasonal variability still exist, particularly over thin cirrus prevalent regions during cirrus peak seasons, (2) Challenges in matching up different data for analysis are highlighted and corresponding solutions proposed, and (3) Estimation of the relative contributions from cirrus contamination to aerosol retrievals are discussed. The results are valuable for better understanding and further improving ground aerosol measurements that are critical for aerosol-related climate research.

Aerosol particle size distribution in the stratosphere retrieved from SCIAMACHY limb measurements

NASA Astrophysics Data System (ADS)

Malinina, Elizaveta; Rozanov, Alexei; Rozanov, Vladimir; Liebing, Patricia; Bovensmann, Heinrich; Burrows, John P.

2018-04-01

V2.2 L2AS Detailed Release Description April 15, 2002

Atmospheric Science Data Center

2013-03-14

... 'optically thick atmosphere' algorithm. Implement new experimental aerosol retrieval algorithm over homogeneous surface types. ... Change values: cloud_mask_decision_matrix(1,1): .true. -> .false. cloud_mask_decision_matrix(2,1): .true. -> .false. ...

Aerosol retrieval for APEX airborne imaging spectrometer: a preliminary analysis

NASA Astrophysics Data System (ADS)

Seidel, Felix; Nieke, Jens; Schläpfer, Daniel; Höller, Robert; von Hoyningen-Huene, Wolfgang; Itten, Klaus

2005-10-01

In order to achieve quantitative measurements of the Earth's surface radiance and reflectance, it is important to determine the aerosol optical thickness (AOT) to correct for the optical influence of atmospheric particles. An advanced method for aerosol detection and quantification is required, which is not strongly dependant on disturbing effects due to surface reflectance, gas absorption and Rayleigh scattering features. A short review of existing applicable methods to the APEX airborne imaging spectrometer (380nm to 2500nm), leads to the suggested aerosol retrieval method here in this paper. It will measure the distinct radiance change between two near-UV spectral bands (385nm & 412nm) due to aerosol induced scattering and absorption features. Atmospheric radiation transfer model calculations have been used to analyze the AOT retrieval capability and accuracy of APEX. The noise-equivalent differential AOT is presented along with the retrieval sensitivity to various input variables. It is shown, that the suggested method will be able to identify different aerosol model types and measure AOT and columnar size distribution. The proposed accurate AOT determination will lead to a unique opportunity of two-dimensional pixel-wise mapping of aerosol properties at a high spatial resolution. This will be helpful especially for regional climate studies, atmospheric pollution monitoring and for the improvement of aerosol dispersion models and the validation of aerosol algorithms on spaceborne sensors.

Influence of the micro-physical properties of the aerosol on the atmospheric correction of OLI data acquired over desert area

NASA Astrophysics Data System (ADS)

Manzo, Ciro; Bassani, Cristiana

2016-04-01

This paper focuses on the evaluation of surface reflectance obtained by different atmospheric correction algorithms of the Landsat 8 OLI data considering or not the micro-physical properties of the aerosol when images are acquired in desert area located in South-West of Nile delta. The atmospheric correction of remote sensing data was shown to be sensitive to the aerosol micro-physical properties, as reported in Bassani et al., 2012. In particular, the role of the aerosol micro-physical properties on the accuracy of the atmospheric correction of remote sensing data was investigated [Bassani et al., 2015; Tirelli et al., 2015]. In this work, the OLI surface reflectance was retrieved by the developed OLI@CRI (OLI ATmospherically Corrected Reflectance Imagery) physically-based atmospheric correction which considers the aerosol micro-physical properties available from the two AERONET stations [Holben et al., 1998] close to the study area (El_Farafra and Cairo_EMA_2). The OLI@CRI algorithm is based on 6SV radiative transfer model, last generation of the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer code [Kotchenova et al., 2007; Vermote et al., 1997], specifically developed for Landsat 8 OLI data. The OLI reflectance obtained by the OLI@CRI was compared with reflectance obtained by other atmospheric correction algorithms which do not consider micro-physical properties of aerosol (DOS) or take on aerosol standard models (FLAASH, implemented in ENVI software). The accuracy of the surface reflectance retrieved by different algorithms were calculated by comparing the spatially resampled OLI images with the MODIS surface reflectance products. Finally, specific image processing was applied to the OLI reflectance images in order to compare remote sensing products obtained for same scene. The results highlight the influence of the physical characterization of aerosol on the OLI data improving the retrieved atmospherically corrected reflectance. One of the most important outreach of this research is the retrieval of the highest possible accuracy of the OLI reflectance for land surface variables by spectral indices. Consequently if OLI@CRI algorithm is applied to time series data, the uncertainty into the time curve can be reduced. Kotchenova and Vermote, 2007. Appl. Opt. doi:10.1364/AO.46.004455. Vermote et al., 1997. IEEE Trans. Geosci. Remote Sens. doi:10.1109/36.581987. Bassani et al., 2015. Atmos. Meas. Tech. doi:10.5194/amt-8-1593-2015. Bassani et al., 2012. Atmos. Meas. Tech. doi:10.5194/amt-5-1193-2012. Tirelli et al., 2015. Remote Sens. doi:10.3390/rs70708391. Holben et al., 1998. Rem. Sens. Environ. doi:10.1016/S0034-4257(98)00031-5.

Extending the Deep Blue aerosol record from SeaWiFS and MODIS to NPP-VIIRS

NASA Technical Reports Server (NTRS)

Sayer, Andrew M.; Hsu, Nai-Yung Christina; Bettenhausen, Corey; Lee, Jaehwa

2015-01-01

Deep Blue expands AOD coverage to deserts and other bright surfaces. Using multiple similar satellite sensors enables us to obtain a long data record. The Deep Blue family consists of three separate aerosol optical depth (AOD) retrieval algorithms: 1. Bright Land: Surface reflectance database, BRDF correction. AOD retrieved separately at each of 412, 470/490, (650) nm. SSA retrieved for heavy dust events. 2. Dark Land: Spectral/directional surface reflectance relationship. AOD retrieved separately at 470/490 and 650 nm. 3. Water: Surface BRDF including glint, foam, underlight. Multispectral inversion (Not present in MODISdataset) All report the AOD at 550 nm, and Ångström exponent (AE).

Analysis of MAIAC Dust Aerosol Retrievals from MODIS Over North Africa

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Hsu, C.; Torres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, S.

2011-01-01

An initial comparison of aerosol optical thickness over North Africa for year 2007 was performed between the Deep Blue and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms complimented with MISR and OMI data. The new MAIAC algorithm has a better sensitivity to the small dust storms than the DB algorithm, but it also has biases in the brightest desert regions indicating the need for improvement. The quarterly averaged AOT values in the Bodele depression and western downwind transport region show a good agreement among MAIAC, MISR and OMI data, while the DB algorithm shows a somewhat different seasonality.

Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites

NASA Astrophysics Data System (ADS)

Naeger, Aaron R.; Gupta, Pawan; Zavodsky, Bradley T.; McGrath, Kevin M.

2016-06-01

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 as the frequent geostationary observations lead to a greater coverage of cloud-free AOD retrievals equatorward of about 35° N, while the polar-orbiting satellites provide a greater coverage of AOD poleward of 35° N. However, we note several areas across the domain of interest from Asia to North America where the GOES-15 and MTSAT-2 retrieval algorithms can introduce significant uncertainties into the new product.

Remote sensing measurements of biomass burning aerosol optical properties during the 2015 Indonesian burning season from AERONET and MODIS satellite data

NASA Astrophysics Data System (ADS)

2016-04-01

The strong El Nino event in 2015 resulted in below normal rainfall leading to very dry conditions throughout Indonesia from August though October 2015. These conditions in turn allowed for exceptionally large numbers of biomass burning fires with very high emissions of aerosols. Over the island of Borneo, three AERONET sites (Palangkaraya, Pontianak, and Kuching) measured monthly mean fine mode aerosol optical depth (AOD) at 500 nm from the spectral deconvolution algorithm in September and October ranging from 1.6 to 3.7, with daily average AOD as high as 6.1. In fact, the AOD was sometimes too high to obtain any significant signal in the mid-visible wavelengths, therefore a previously developed new algorithm in the AERONET Version 3 database was invoked to retain the measurements in as many of the red and near-infrared wavelengths (675, 870, 1020, and 1640 nm) as possible to analyze the AOD in those wavelengths. These AOD at longer wavelengths are then utilized to provide some estimate the AOD in the mid-visible. Additionally, satellite retrievals of AOD at 550 nm from MODIS sensor data and the Dark Target, Beep Blue, and MAIAC algorithms were also analyzed and compared to AERONET measured AOD. Not surprisingly, the AOD was often too high for the satellite algorithms to also measure accurate AOD on many days in the densest smoke regions. The AERONET sky radiance inversion algorithm was utilized to analyze retrievals of the aerosol optical properties of complex refractive indices and size distributions. Since the AOD was often extremely high there was sometimes insufficient direct sun signal for the larger solar zenith angles (> 50 degrees) required for almucantar retrievals. However, the new hybrid sky radiance scan can attain sufficient scattering angle range even at small solar zenith angles when 440 nm direct beam irradiance can be accurately measured, thereby allowing for many more retrievals and also at higher AOD levels during this event. Due to extreme dryness occurring in the region, significant biomass burning of peat soils occurred in some areas. The retrieved volume median radius of the fine mode increased from ~0.18 micron to ~0.25 micron as AOD increased from 1 to 3 at 440 nm. These are very large size particles for biomass burning aerosol and are similar in size to smoke particles measured in Alaska during the very dry years of 2004 and 2005 when peat soil burning also contributed to the fuel burned. The average single scattering albedo over the wavelength range of 440 to 1020 nm was very high ranging from ~0.96 to 0.98, indicative of dominant smoldering phase combustion. These very high values of single scattering albedo for biomass burning aerosols are similar to those retrieved by AERONET for the Alaska smoke in 2004 and 2005.

Effect of black carbon on dust property retrievals from satellite observations

NASA Astrophysics Data System (ADS)

Lin, Tang-Huang; Yang, Ping; Yi, Bingqi

2013-01-01

The effect of black carbon on the optical properties of polluted mineral dust is studied from a satellite remote-sensing perspective. By including the auxiliary data of surface reflectivity and aerosol mixing weight, the optical properties of mineral dust, or more specifically, the aerosol optical depth (AOD) and single-scattering albedo (SSA), can be retrieved with improved accuracy. Precomputed look-up tables based on the principle of the Deep Blue algorithm are utilized in the retrieval. The mean differences between the retrieved results and the corresponding ground-based measurements are smaller than 1% for both AOD and SSA in the case of pure dust. However, the retrievals can be underestimated by as much as 11.9% for AOD and overestimated by up to 4.1% for SSA in the case of polluted dust with an estimated 10% (in terms of the number-density mixing ratio) of soot aggregates if the black carbon effect on dust aerosols is neglected.

Day and Night Dust Retrievals from MODIS IR Band Measurements using Artificial Neural Network (ANN) model

NASA Astrophysics Data System (ADS)

Lee, S.; Sohn, B.

2008-12-01

Artificial Neural Network (ANN) on the East Asia domain (20°N-55°N, 90°E-145°E) during the springs of 2006 and 2007 was investigated for retrieving aerosol optical thickness (AOT) of dust aerosol at both daytime and nighttime. The input data for ANN include brightness temperature, BTD (11 μm - 12 μm), spectral emissivity, surface temperature (Land: Price [1984] Equation, Ocean: The IMAPP MODIS Algorithm), relative airmass of satellite, and topography (SRTM30). The D*-parameter is adopted as dust detection algorithm which was developed by Hansell et al [2007]. The target data of the ANN is corresponding AOT at 550nm obtained from MODIS aerosol product (MYD04). After optimization and training, ANN AOT is retrieved. Among the many dust episodes during the spring of 2006, only the 8 April 2006 case was selected for the detailed analysis. Because it is one of the strongest episodes and shows a well-developed root penetrating the Korean peninsula and reaching the Japanese area. It is shown that ANN AOT coincide well with MODIS AOT having correlation coefficient of 0.8502 when the training and applying periods are the same (spring of 2006). Even a different period with training ANN AOT has a good relationship with MODIS AOT with the correlation coefficient of 0.7766 (spring 2007). This yearly difference is resulted from vegetation change and fixed IGBP land cover map. Also notable is that ANN AOT is underestimated in most IGBP types having low slope and negative mean bias. This study showed that ANN model has a good potential to retrieve AOT. More examinations and trials are needed, however, to improve this ANN algorithm using IR bands. Also this model should be extended to specify the dust aerosol property from other aerosols and clouds to assure that it has a capability during both daytime and nighttime.

MODIS-VIIRS Intercalibration for Dark Target Aerosol Retrieval Over Ocean

NASA Astrophysics Data System (ADS)

Sawyer, V. R.; Levy, R. C.; Mattoo, S.; Quinn, G.; Veglio, P.

2016-12-01

Any future climate record for satellite aerosol retrieval will require continuity over multiple decades, longer than the lifespan of an individual satellite instrument. The Dark Target algorithm was developed for MODIS, which began taking observations in 1999; the two MODIS instruments currently in orbit are not expected to continue taking observations beyond the early 2020s. However, the algorithm is portable, and a Dark Target product for VIIRS is scheduled for release December 2016. Because MODIS and VIIRS operate at different wavelengths, resolutions, fields of view and orbital timing, the transition can introduce artifacts that must be corrected. Without these corrections, it will be difficult to find any changes that may occur in the global aerosol climate record over time periods that span the transition from MODIS to VIIRS retrievals. The University of Wisconsin-Madison SIPS team found thousands of matches between 2012 and 2016 in which Aqua-MODIS and Suomi-NPP VIIRS observe the same location at similar times and view angles. These matched cases are used to identify corresponding matches in the Intermediate File Format (IFF) aerosol retrievals for MODIS and VIIRS, which are compared to one another in turn. Because most known sources of disagreement between the two instruments have already been corrected during the IFF retrieval, the direct comparison between near-collocated cases shows only the differences that remain at local and regional scales. The comparison is further restricted to clear-sky cases over ocean, so that the investigation of seasonal, diurnal and geographic variation is not affected by uncertainties in the land surface or cloud contamination.

Aerosol Size Distributions During ACE-Asia: Retrievals From Optical Thickness and Comparisons With In-situ Measurements

NASA Astrophysics Data System (ADS)

Kuzmanoski, M.; Box, M.; Box, G. P.; Schmidt, B.; Russell, P. B.; Redemann, J.; Livingston, J. M.; Wang, J.; Flagan, R. C.; Seinfeld, J. H.

2002-12-01

As part of the ACE-Asia experiment, conducted off the coast of China, Korea and Japan in spring 2001, measurements of aerosol physical, chemical and radiative characteristics were performed aboard the Twin Otter aircraft. Of particular importance for this paper were spectral measurements of aerosol optical thickness obtained at 13 discrete wavelengths, within 354-1558 nm wavelength range, using the AATS-14 sunphotometer. Spectral aerosol optical thickness can be used to obtain information about particle size distribution. In this paper, we use sunphotometer measurements to retrieve size distribution of aerosols during ACE-Asia. We focus on four cases in which layers influenced by different air masses were identified. Aerosol optical thickness of each layer was inverted using two different techniques - constrained linear inversion and multimodal. In the constrained linear inversion algorithm no assumption about the mathematical form of the distribution to be retrieved is made. Conversely, the multimodal technique assumes that aerosol size distribution is represented as a linear combination of few lognormal modes with predefined values of mode radii and geometric standard deviations. Amplitudes of modes are varied to obtain best fit of sum of optical thicknesses due to individual modes to sunphotometer measurements. In this paper we compare the results of these two retrieval methods. In addition, we present comparisons of retrieved size distributions with in situ measurements taken using an aerodynamic particle sizer and differential mobility analyzer system aboard the Twin Otter aircraft.

Consistency of aerosols above clouds characterization from A-Train active and passive measurements

NASA Astrophysics Data System (ADS)

Deaconu, Lucia T.; Waquet, Fabien; Josset, Damien; Ferlay, Nicolas; Peers, Fanny; Thieuleux, François; Ducos, Fabrice; Pascal, Nicolas; Tanré, Didier; Pelon, Jacques; Goloub, Philippe

2017-09-01

This study presents a comparison between the retrieval of optical properties of aerosol above clouds (AAC) from different techniques developed for the A-Train sensors CALIOP/CALIPSO and POLDER/PARASOL. The main objective is to analyse the consistency between the results derived from the active and the passive measurements. We compare the aerosol optical thickness (AOT) above optically thick clouds (cloud optical thickness (COT) larger than 3) and their Ångström exponent (AE). These parameters are retrieved with the CALIOP operational method, the POLDER operational polarization method and the CALIOP-based depolarization ratio method (DRM) - for which we also propose a calibrated version (denominated DRMSODA, where SODA is the Synergized Optical Depth of Aerosols). We analyse 6 months of data over three distinctive regions characterized by different types of aerosols and clouds. Additionally, for these regions, we select three case studies: a biomass-burning event over the South Atlantic Ocean, a Saharan dust case over the North Atlantic Ocean and a Siberian biomass-burning event over the North Pacific Ocean. Four and a half years of data are studied over the entire globe for distinct situations where aerosol and cloud layers are in contact or vertically separated. Overall, the regional analysis shows a good correlation between the POLDER and the DRMSODA AOTs when the microphysics of aerosols is dominated by fine-mode particles of biomass-burning aerosols from southern Africa (correlation coefficient (R2) of 0.83) or coarse-mode aerosols of Saharan dust (R2 of 0.82). A good correlation between these methods (R2 of 0.68) is also observed in the global treatment, when the aerosol and cloud layers are separated well. The analysis of detached layers also shows a mean difference in AOT of 0.07 at 532 nm between POLDER and DRMSODA at a global scale. The correlation between the retrievals decreases when a complex mixture of aerosols is expected (R2 of 0.37) - as in the East Asia region - and when the aerosol-cloud layers are in contact (R2 of 0.36). The correlation coefficient between the CALIOP operational method and POLDER is found to be low, as the CALIOP method largely underestimates the aerosol loading above clouds by a factor that ranges from 2 to 4. Potential biases on the retrieved AOT as a function of cloud properties are also investigated. For different types of scenes, the retrieval of above-cloud AOT from POLDER and from DRM are compared for different underlying cloud properties (droplet effective radius (reff) and COT retrieved with MODIS). The results reveal that DRM AOT vary with reff. When accounting for reff in the DRM algorithm, the consistency between the methods increases. The sensitivity study shows that an additional polarized signal coming from aerosols located within the cloud could affect the polarization method, which leads to an overestimation of the AOT retrieved with POLDER algorithm. In addition, the aerosols attached to or within the cloud can potentially impact the DRM retrievals through the modification of the cloud droplet chemical composition and its ability to backscatter light. The next step of this work is to combine POLDER and CALIOP to investigate the impacts of aerosols on clouds and climate when these particles are transported above or within clouds.

Comparison of a single-view and a double-view aerosol optical depth retrieval algorithm

NASA Astrophysics Data System (ADS)

Henderson, Bradley G.; Chylek, Petr

2003-11-01

We compare the results of a single-view and a double-view aerosol optical depth (AOD) retrieval algorithm applied to image pairs acquired over NASA Stennis Space Center, Mississippi. The image data were acquired by the Department of Energy's (DOE) Multispectral Thermal Imager (MTI), a pushbroom satellite imager with 15 bands from the visible to the thermal infrared. MTI has the ability to acquire imagery in pairs in which the first image is a near-nadir view and the second image is off-nadir with a zenith angle of approximately 60°. A total of 15 image pairs were used in the analysis. For a given image pair, AOD retrieval is performed twice---once using a single-view algorithm applied to the near-nadir image, then again using a double-view algorithm. Errors for both retrievals are computed by comparing the results to AERONET AOD measurements obtained at the same time and place. The single-view algorithm showed an RMS error about the mean of 0.076 in AOD units, whereas the double-view algorithm showed a modest improvement with an RMS error of 0.06. The single-view errors show a positive bias which is presumed to be a result of the empirical relationship used to determine ground reflectance in the visible. A plot of AOD error of the double-view algorithm versus time shows a noticeable trend which is interpreted to be a calibration drift. When this trend is removed, the RMS error of the double-view algorithm drops to 0.030. The single-view algorithm qualitatively appears to perform better during the spring and summer whereas the double-view algorithm seems to be less sensitive to season.

Orbiting Carbon Observatory-2 (OCO-2) Cloud Screening; Validation Against Collocated MODIS and Initial Comparison to CALIOP Data

NASA Technical Reports Server (NTRS)

Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip; Cronk, Heather W.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert; Crisp, David;

Statistical intercomparison and validation of multisensory aerosol optical depth retrievals over three AERONET sites in Kenya, East Africa

NASA Astrophysics Data System (ADS)

Boiyo, Richard; Kumar, K. Raghavendra; Zhao, Tianliang

2017-11-01

Over the last two decades, a number of space-borne sensors have been used to retrieve aerosol optical depth (AOD). The reliability of these datasets over East Africa (EA), however, is an important issue in the interpretation of regional aerosol variability. This study provides an intercomparison and validation of AOD retrievals from the MODIS-Terra (DT and DB), MISR and OMI sensors against ground-based measurements from the AERONET over three sites (CRPSM_Malindi, Nairobi, and ICIPE_Mbita) in Kenya, EA during the periods 2008-2013, 2005-2009 and 2006-2015, respectively. The analysis revealed that MISR performed better over the three sites with about 82.5% of paired AOD data falling within the error envelope (EE). MODIS-DT showed good agreement against AERONET with 59.05% of paired AOD falling within the sensor EE over terrestrial surfaces with relatively high vegetation cover. The comparison between MODIS-DB and AERONET revealed an overall lower performance with lower Gfraction (48.93%) and lower correlation r = 0.58; while AOD retrieved from OMI showed less correspondence with AERONET data with lower Gfraction (68.89%) and lowest correlation r = 0.31. The monthly evaluation of AODs retrieved from the sensors against AERONET AOD indicates that MODIS-DT has the best performance over the three sites with highest correlation (0.71-0.84), lowest RMSE and spread closer to the AERONET. Regarding seasonal analysis, MISR performed well during most seasons over Nairobi and Mbita; while MODIS-DT performed better than all other sensors during most seasons over Malindi. Furthermore, the best seasonal performance of most sensors relative to AERONET data occurred during June-August (JJA) attributed to modulations induced by a precipitation-vegetation factor to AOD satellite retrieval algorithms. The study revealed the strength and weakness of each of the retrieval algorithm and forms the basis for further research on the validation of satellite retrieved aerosol products over EA.

Joint Retrieval Of Surface Reflectance And Aerosol Properties: Application To MSG/SEVIRI in the framework of the aerosol_cci project

NASA Astrophysics Data System (ADS)

Luffarelli, Marta; Govaerts, Yves; Goossens, Cedric

2017-04-01

A new versatile algorithm for the joint retrieval of surface reflectance and aerosol properties has been developed and tested at Rayference. This algorithm, named Combined Inversion of Surface and Aerosols (CISAR), includes a fast physically-based Radiative Transfer Model (RTM) accounting for the surface reflectance anisotropy and its coupling with aerosol scattering. This RTM explicitly solves the radiative transfer equation during the inversion process, without relying on pre-calculated integrals stored in LUT, allowing for a continuous variation of the state variables in the solution space. The inversion is based on a Optimal Estimation (OE) approach, which seeks for the best balance between the information coming from the observation and the a priori information. The a priori information is any additional knowledge on the observed system and it can concern the magnitude of the state variable or constraints on temporal and spectral variability. Both observations and priori information are provided with the corresponding uncertainty. For each processed spectral band, CISAR delivers the surface Bidirectional Reflectance Factor (BRF) and aerosol optical thickness, discriminating the effects of small and large particles. It also provides the associated uncertainty covariance matrix for every processed pixels. In the framework of the ESA aerosol_cci project, CISAR is applied on TOA BRF acquired by SEVIRI onboard Meteosat Second Generation (MSG) in the VIS0.6, VIS0.8 and NIR1.6 spectral bands. SEVIRI observations are accumulated during several days to document the surface anisotropy and minimize the impact of clouds. While surface radiative properties are supposed constant during this accumulation period, aerosol properties are derived on an hourly basis. The information content of each MSG/SEVIRI band will be provided based on the analysis of the posterior uncertainty covariance matrix. The analysis will demonstrate in particular the capability of CISAR to decouple the fraction of TOA BRF signal coming from the surface from the one originating from the aerosols. The results of the algorithm are compared with independent data sets of AOD and surface reflectance. Comparison with ground observations from the AERONET network shows a good agreement between these data. The surface reflectance evaluation is performed comparing white-sky albedo retrieved by CISAR with the MODIS surface product. This evaluation shows a very good consistency. The retrieved aerosol optical depth is consistent also in term of spatial distribution, being comparable in terms of geographical location and intensity.

Principles in Remote Sensing of Aerosol from MODIS Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Chu, D. A.

1999-01-01

The well-calibrated spectral radiances measured by MODIS will be processed to retrieve daily aerosol properties that include optical thickness and mass loading over land and optical thickness, the mean particle size of the dominant mode and the ratio between aerosol modes over ocean. In addition, after launch, aerosol single scattering albedo will be calculated as an experimental product. The retrieval process over land is based on a dark target method that identifies appropriate targets in the mid-IR channels and uses an empirical relationship found between the mid-ER and the visible channels to estimate surface reflectance in the visible from the mid-HZ reflectance measured by satellite. The method employs new aerosol models for industrial, smoke and dust aerosol. The process for retrieving aerosol over the ocean makes use of the wide spectral band from 0.55-2.13 microns and a look-up table constructed from combinations of five accumulation modes and five coarse modes. Both the over land and over ocean algorithms have been validated with satellite and airborne radiance measurements. We estimate that MODIS will be able to measure aerosol optical thickness (t) to within 0.05 +/- 0.2t over land and to within 0.05 +/- 0.05t over ocean. Much of the earth's surface is located far from aerosol sources and experience very low aerosol optical thickness. Will the accuracy expected from MODIS retrievals be sufficient to measure the global aerosol direct and indirect forcing? We are attempting to answer this question using global model results and cloud climatology.

Multi-Satellite Synergy for Aerosol Analysis in the Asian Monsoon Region

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym

2012-01-01

Atmospheric aerosols represent one of the greatest uncertainties in environmental and climate research, particularly in tropical monsoon regions such as the Southeast Asian regions, where significant contributions from a variety of aerosol sources and types is complicated by unstable atmospheric dynamics. Although aerosols are now routinely retrieved from multiple satellite Sensors, in trying to answer important science questions about aerosol distribution, properties, and impacts, researchers often rely on retrievals from only one or two sensors, thereby running the risk of incurring biases due to sensor/algorithm peculiarities. We are conducting detailed studies of aerosol retrieval uncertainties from various satellite sensors (including Terra-/ Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, SeaWiFS, and Calipso-CALIOP), based on the collocation of these data products over AERONET and other important ground stations, within the online Multi-sensor Aerosol Products Sampling System (MAPSS) framework that was developed recently. Such analyses are aimed at developing a synthesis of results that can be utilized in building reliable unified aerosol information and climate data records from multiple satellite measurements. In this presentation, we will show preliminary results of. an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors, particularly focused on the Asian Monsoon region, along with some comparisons from the African Monsoon region.

Joint aerosol and water-leaving radiance retrieval from Airborne Multi-angle SpectroPolarimeter Imager

NASA Astrophysics Data System (ADS)

Xu, F.; Dubovik, O.; Zhai, P.; Kalashnikova, O. V.; Diner, D. J.

2015-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) [1] has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI typically acquires observations of a target area at 9 view angles between ±67° off the nadir. Its spectral channels are centered at 355, 380, 445, 470*, 555, 660*, and 865* nm, where the asterisk denotes the polarimetric bands. In order to retrieve information from the AirMSPI observations, we developed a efficient and flexible retrieval code that can jointly retrieve aerosol and water leaving radiance simultaneously. The forward model employs a coupled Markov Chain (MC) [2] and adding/doubling [3] radiative transfer method which is fully linearized and integrated with a multi-patch retrieval algorithm to obtain aerosol and water leaving radiance/Chl-a information. Various constraints are imposed to improve convergence and retrieval stability. We tested the aerosol and water leaving radiance retrievals using the AirMSPI radiance and polarization measurements by comparing to the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentration to the values reported by the USC SeaPRISM AERONET-OC site off the coast of Southern California. In addition, the MC-based retrievals of aerosol properties were compared with GRASP ([4-5]) retrievals for selected cases. The MC-based retrieval approach was then used to systematically explore the benefits of AirMSPI's ultraviolet and polarimetric channels, the use of multiple view angles, and constraints provided by inclusion of bio-optical models of the water-leaving radiance. References [1]. D. J. Diner, et al. Atmos. Meas. Tech. 6, 1717 (2013). [2]. F. Xu et al. Opt. Lett. 36, 2083 (2011). [3]. J. E. Hansen and L.D. Travis. Space Sci. Rev. 16, 527 (1974). [4]. O. Dubovik et al. Atmos. Meas. Tech., 4, 975 (2011). [5]. O. Dubovik et al. SPIE: Newsroom, DOI:10.1117/2.1201408.005558 (2014).

Assimilation of MODIS Dark Target and Deep Blue Observations in the Dust Aerosol Component of NMMB-MONARCH version 1.0

NASA Technical Reports Server (NTRS)

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Perez Garcia-Pando, Carlos

2017-01-01

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets.The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0

NASA Astrophysics Data System (ADS)

Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Pérez García-Pando, Carlos

2017-03-01

A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets. The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

Does the Madden-Julian Oscillation influence aerosol variability?

NASA Astrophysics Data System (ADS)

Tian, Baijun; Waliser, Duane E.; Kahn, Ralph A.; Li, Qinbin; Yung, Yuk L.; Tyranowski, Tomasz; Geogdzhayev, Igor V.; Mishchenko, Michael I.; Torres, Omar; Smirnov, Alexander

2008-06-01

We investigate the modulation of aerosols by the Madden-Julian Oscillation (MJO) using multiple, global satellite aerosol products: aerosol index (AI) from the Total Ozone Mapping Spectrometer (TOMS) on Nimbus-7, and aerosol optical thickness (AOT) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Advanced Very High Resolution Radiometer (AVHRR) on NOAA satellites. A composite MJO analysis indicates that large variations in the TOMS AI and MODIS/AVHRR AOT are found over the equatorial Indian and western Pacific Oceans where MJO convection is active, as well as the tropical Africa and Atlantic Ocean where MJO convection is weak but the background aerosol level is high. A strong inverse linear relationship between the TOMS AI and rainfall anomalies, but a weaker, less coherent positive correlation between the MODIS/AVHRR AOT and rainfall anomalies, were found. The MODIS/AVHRR pattern is consistent with ground-based Aerosol Robotic Network data. These results indicate that the MJO and its associated cloudiness, rainfall, and circulation variability systematically influence the variability in remote sensing aerosol retrieval results. Several physical and retrieval algorithmic factors that may contribute to the observed aerosol-rainfall relationships are discussed. Preliminary analysis indicates that cloud contamination in the aerosol retrievals is likely to be a major contributor to the observed relationships, although we cannot exclude possible contributions from other physical mechanisms. Future research is needed to fully understand these complex aerosol-rainfall relationships.

Error sources in the retrieval of aerosol information over bright surfaces from satellite measurements in the oxygen A band

NASA Astrophysics Data System (ADS)

Nanda, Swadhin; de Graaf, Martin; Sneep, Maarten; de Haan, Johan F.; Stammes, Piet; Sanders, Abram F. J.; Tuinder, Olaf; Pepijn Veefkind, J.; Levelt, Pieternel F.

2018-01-01

Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top-of-atmosphere reflectance spectrum in the oxygen A band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in the literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top-of-atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A band, and discusses its implications. The underlying physics are introduced by analysing the top-of-atmosphere reflectance spectrum as a sum of atmospheric path contribution and surface contribution, obtained using a radiative transfer model. Furthermore, error analysis of an aerosol layer height retrieval algorithm is conducted over dark and bright surfaces to show the dependence on surface reflectance. The analysis shows that the derivative with respect to aerosol layer height of the atmospheric path contribution to the top-of-atmosphere reflectance is opposite in sign to that of the surface contribution - an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these derivatives are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A band from the GOME-2 instrument on board the Metop-A satellite over the 2010 Russian wildfires incident.

Aerosol climate time series from ESA Aerosol_cci (Invited)

NASA Astrophysics Data System (ADS)

Holzer-Popp, T.

2013-12-01

Within the ESA Climate Change Initiative (CCI) the Aerosol_cci project (mid 2010 - mid 2013, phase 2 proposed 2014-2016) has conducted intensive work to improve algorithms for the retrieval of aerosol information from European sensors AATSR (3 algorithms), PARASOL, MERIS (3 algorithms), synergetic AATSR/SCIAMACHY, OMI and GOMOS. Whereas OMI and GOMOS were used to derive absorbing aerosol index and stratospheric extinction profiles, respectively, Aerosol Optical Depth (AOD) and Angstrom coefficient were retrieved from the other sensors. Global datasets for 2008 were produced and validated versus independent ground-based data and other satellite data sets (MODIS, MISR). An additional 17-year dataset is currently generated using ATSR-2/AATSR data. During the three years of the project, intensive collaborative efforts were made to improve the retrieval algorithms focusing on the most critical modules. The team agreed on the use of a common definition for the aerosol optical properties. Cloud masking was evaluated, but a rigorous analysis with a pre-scribed cloud mask did not lead to improvement for all algorithms. Better results were obtained using a post-processing step in which sudden transitions, indicative of possible occurrence of cloud contamination, were removed. Surface parameterization, which is most critical for the nadir only algorithms (MERIS and synergetic AATSR / SCIAMACHY) was studied to a limited extent. The retrieval results for AOD, Ångström exponent (AE) and uncertainties were evaluated by comparison with data from AERONET (and a limited amount of MAN) sun photometer and with satellite data available from MODIS and MISR. Both level2 and level3 (gridded daily) datasets were validated. Several validation metrics were used (standard statistical quantities such as bias, rmse, Pearson correlation, linear regression, as well as scoring approaches to quantitatively evaluate the spatial and temporal correlations against AERONET), and in some cases developed further, to evaluate the datasets and their regional and seasonal merits. The validation showed that most datasets have improved significantly and in particular PARASOL (ocean only) provides excellent results. The metrics for AATSR (land and ocean) datasets are similar to those of MODIS and MISR, with AATSR better in some land regions and less good in some others (ocean). However, AATSR coverage is smaller than that of MODIS due to swath width. The MERIS dataset provides better coverage than AATSR but has lower quality (especially over land) than the other datasets. Also the synergetic AATSR/SCIAMACHY dataset has lower quality. The evaluation of the pixel uncertainties shows first good results but also reveals that more work needs to be done to provide comprehensive information for data assimilation. Users (MACC/ECMWF, AEROCOM) confirmed the relevance of this additional information and encouraged Aerosol_cci to release the current uncertainties. The paper will summarize and discuss the results of three year work in Aerosol_cci, extract the lessons learned and conclude with an outlook to the work proposed for the next three years. In this second phase a cyclic effort of algorithm evolution, dataset generation, validation and assessment will be applied to produce and further improve complete time series from all sensors under investigation, new sensors will be added (e.g. IASI), and preparation for the Sentinel missions will be made.

Comparing MODIS C6 'Deep Blue' and 'Dark Target' Aerosol Data

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Sayer, A. M.; Bettenhausen, C.; Lee, J.; Levy, R. C.; Mattoo, S.; Munchak, L. A.; Kleidman, R.

2014-01-01

The MODIS Collection 6 Atmospheres product suite includes refined versions of both 'Deep Blue' (DB) and 'Dark Target' (DT) aerosol algorithms, with the DB dataset now expanded to include coverage over vegetated land surfaces. This means that, over much of the global land surface, users will have both DB and DT data to choose from. A 'merged' dataset is also provided, primarily for visualization purposes, which takes retrievals from either or both algorithms based on regional and seasonal climatologies of normalized difference vegetation index (NDVI). This poster present some comparisons of these two C6 aerosol algorithms, focusing on AOD at 550 nm derived from MODIS Aqua measurements, with each other and with Aerosol Robotic Network (AERONET) data, with the intent to facilitate user decisions about the suitability of the two datasets for their desired applications.

Simulation of the Ozone Monitoring Instrument Aerosol Index Using the NASA Goddard Earth Observing System Aerosol Reanalysis Products

NASA Technical Reports Server (NTRS)

Colarco, Peter R.; Gasso, Santiago; Ahn, Changwoo; Buchard, Virginie; Da Silva, Arlindo M.; Torres, Omar

2017-01-01

We provide an analysis of the commonly used Ozone Monitoring Instrument (OMI) aerosol index (AI) product for qualitative detection of the presence and loading of absorbing aerosols. In our analysis, simulated top-of-atmosphere (TOA) radiances are produced at the OMI footprints from a model atmosphere and aerosol profile provided by the NASA Goddard Earth Observing System (GEOS-5) Modern-Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). Having established the credibility of the MERRAero simulation of the OMI AI in a previous paper we describe updates in the approach and aerosol optical property assumptions. The OMI TOA radiances are computed in cloud-free conditions from the MERRAero atmospheric state, and the AI is calculated. The simulated TOA radiances are fed to the OMI aerosol retrieval algorithms, and its retrieved AI (OMAERUV AI) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining the OMI algorithm assumptions of the surface pressure, which are generally different from what the actual surface pressure of an observation is, and the other related to simplifying assumptions in the molecular atmosphere radiative transfer used in the OMI algorithms. Surface pressure assumptions lead to systematic biases in the OMAERUV AI, particularly over the oceans. Simplifications in the molecular radiative transfer lead to biases particularly in regions of topography intermediate to surface pressures of 600hPa and 1013.25hPa. Generally, the errors in the OMI AI due to these considerations are less than 0.2 in magnitude, though larger errors are possible, particularly over land. We recommend that future versions of the OMI algorithms use surface pressures from readily available atmospheric analyses combined with high-spatial resolution topographic maps and include more surface pressure nodal points in their radiative transfer lookup tables.

An algorithm for hyperspectral remote sensing of aerosols: 1. Development of theoretical framework

NASA Astrophysics Data System (ADS)

Hou, Weizhen; Wang, Jun; Xu, Xiaoguang; Reid, Jeffrey S.; Han, Dong

2016-07-01

This paper describes the first part of a series of investigations to develop algorithms for simultaneous retrieval of aerosol parameters and surface reflectance from a newly developed hyperspectral instrument, the GEOstationary Trace gas and Aerosol Sensor Optimization (GEO-TASO), by taking full advantage of available hyperspectral measurement information in the visible bands. We describe the theoretical framework of an inversion algorithm for the hyperspectral remote sensing of the aerosol optical properties, in which major principal components (PCs) for surface reflectance is assumed known, and the spectrally dependent aerosol refractive indices are assumed to follow a power-law approximation with four unknown parameters (two for real and two for imaginary part of refractive index). New capabilities for computing the Jacobians of four Stokes parameters of reflected solar radiation at the top of the atmosphere with respect to these unknown aerosol parameters and the weighting coefficients for each PC of surface reflectance are added into the UNified Linearized Vector Radiative Transfer Model (UNL-VRTM), which in turn facilitates the optimization in the inversion process. Theoretical derivations of the formulas for these new capabilities are provided, and the analytical solutions of Jacobians are validated against the finite-difference calculations with relative error less than 0.2%. Finally, self-consistency check of the inversion algorithm is conducted for the idealized green-vegetation and rangeland surfaces that were spectrally characterized by the U.S. Geological Survey digital spectral library. It shows that the first six PCs can yield the reconstruction of spectral surface reflectance with errors less than 1%. Assuming that aerosol properties can be accurately characterized, the inversion yields a retrieval of hyperspectral surface reflectance with an uncertainty of 2% (and root-mean-square error of less than 0.003), which suggests self-consistency in the inversion framework. The next step of using this framework to study the aerosol information content in GEO-TASO measurements is also discussed.

Spatial distribution of aerosol hygroscopicity and its effect on PM2.5 retrieval in East China

NASA Astrophysics Data System (ADS)

He, Qianshan; Zhou, Guangqiang; Geng, Fuhai; Gao, Wei; Yu, Wei

2016-03-01

The hygroscopic properties of aerosol particles have strong impact on climate as well as visibility in polluted areas. Understanding of the scattering enhancement due to water uptake is of great importance in linking dry aerosol measurements with relevant ambient measurements, especially for satellite retrievals. In this study, an observation-based algorithm combining meteorological data with the particulate matter (PM) measurement was introduced to estimate spatial distribution of indicators describing the integrated humidity effect in East China and the main factors impacting the hygroscopicity were explored. Investigation of 1 year data indicates that the larger mass extinction efficiency αext values (> 9.0 m2/g) located in middle and northern Jiangsu Province, which might be caused by particulate organic material (POM) and sulfate aerosol from industries and human activities. The high level of POM in Jiangsu Province might also be responsible for the lower growth coefficient γ value in this region. For the inland junction provinces of Jiangsu and Anhui, a considerable higher hygroscopic growth region in East China might be attributed to more hygroscopic particles mainly comprised of inorganic salts (e.g., sulfates and nitrates) from several large-scale industrial districts distributed in this region. Validation shows good agreement of calculated PM2.5 mass concentrations with in situ measurements in most stations with correlative coefficients of over 0.85, even if several defective stations induced by station location or seasonal variation of aerosol properties in this region. This algorithm can be used for more accurate surface level PM2.5 retrieval from satellite-based aerosol optical depth (AOD) with combination of the vertical correction for aerosol profile.

Utilization of O4 slant column density to derive aerosol layer height from a spaceborne UV-visible hyperspectral sensor: sensitivity and case study

NASA Astrophysics Data System (ADS)

Park, S. S.; Kim, J.; Lee, H.; Torres, O.; Lee, K.-M.; Lee, S. D.

2015-03-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using simulated radiances by a radiative transfer model, Linearized Discrete Ordinate Radiative Transfer (LIDORT), and Differential Optical Absorption Spectroscopy (DOAS) technique. The sensitivities of the O4 SCDs to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4 SCD at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 414 m (16.5%), 564 m (22.4%), and 1343 m (52.5%) for absorbing, dust, and non-absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution type. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). The retrieved aerosol effective heights are lower by approximately 300 m (27 %) compared to those obtained from the ground-based LIDAR measurements.

Coupled retrieval of water cloud and above-cloud aerosol properties using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, F.; van Harten, G.; Diner, D. J.; Rheingans, B. E.; Tosca, M.; Seidel, F. C.; Bull, M. A.; Tkatcheva, I. N.; McDuffie, J. L.; Garay, M. J.; Davis, A. B.; Jovanovic, V. M.; Brian, C.; Alexandrov, M. D.; Hostetler, C. A.; Ferrare, R. A.; Burton, S. P.

2017-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (*denotes polarimetric bands). In sweep mode, georectified images cover an area of 80-100 km (along track) by 10-25 km (across track) between ±66° off nadir, with a map-projected spatial resolution of 25 meters. An efficient and flexible retrieval algorithm has been developed using AirMSPI polarimetric bands for simultaneous retrieval of cloud and above-cloud aerosol microphysical properties. We design a three-step retrieval approach, namely 1) estimating effective droplet size distribution using polarimetric cloudbow observations and using it as initial guess for Step 2; 2) combining water cloud and aerosol above cloud retrieval by fitting polarimetric signals at all scattering angles (e.g. from 80° to 180°); and 3) constructing a lookup table of radiance for a set of cloud optical depth grids using aerosol and cloud information retrieved from Step 2 and then estimating pixel-scale cloud optical depth based on 1D radiative transfer (RT) theory by fitting the AirMSPI radiance. Retrieval uncertainty is formulated by accounting for instrumental errors and constraints imposed on spectral variations of aerosol and cloud droplet optical properties. As the forward RT model, a hybrid approach is developed to combine the computational strengths of Markov-chain and adding-doubling methods to model polarized RT in a coupled aerosol, Rayleigh and cloud system. Our retrieval approach is tested using 134 AirMSPI datasets acquired during NASA ORACLES field campaign in 09/2016, with low to high aerosol loadings. For validation, the retrieved aerosol optical depths and cloud-top heights are compared to coincident High Spectral Resolution Lidar-2 (HSRL-2) data, and the droplet size parameters including effective radius and effective variance and cloud optical thickness are compared to coincident Research Scanning Polarimeter (RSP) data.

A Seasonal Trend of Single Scattering Albedo in Southern African Biomass-burning Particles: Implications for Satellite Products and Estimates of Emissions for the World's Largest Biomass-burning Source

NASA Technical Reports Server (NTRS)

Eck, T. F.; Holben, B. N.; Reid, J. S.; Mukelabai, M. M.; Piketh, S. J.; Torres, O.; Jethva, H. T.; Hyer, E. J.; Ward, D. E.; Dubovik, O.;

The analysis to understand temporal variation and long-range transport of aerosol over Northeast-Asia Using COMS, MI

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, J.

2016-12-01

Numerous efforts to retrieve aerosol optical properties (AOPs) using satellite measurements have been accumulated for decades, resulted in several qualified data which can be used for the analysis of spatiotemporal characteristics of AOPs. However, the limitation in the instrument lifetime restricts temporal window of the analysis of long-term AOPs variation. In this point of view, single channel algorithm, which uses a single visible channel to retrieve aerosol optical depth (AOD), has an advantage to extent the time domain of the analysis. The Korean geostationary earth orbit (GEO) satellite, the Communication, Ocean and Meteorological Satellite (COMS) includes the single channel Meteorological Imager (MI), which can also be utilized for the retrieval of AOPs. Since the GEO satellite measurement has an advantage for continuous monitoring of AOPs over Northeast Asia, we can analyze the spatiotemporal characteristic of the aerosol using MI observations. In this study, we investigate the trend of AOD and also discuss the impact of long-range transport of aerosol on the temporal variation. Since the year 2010 when the COMS was launched, AODs over Northeast China and Yellow Sea region show 3.02 % and 2.74 % decrease per year, respectively, which are significant trends in spite of only 5-year short period. The decreasing behavior seems associated with the recent decreasing frequency of dust event over the region. But other Northeast Asia regions do not show clear temporal change. The accuracy of retrieved AOD can relates to the uncertainty of this trend analysis. According to the error analysis, cloud contamination and error in bright surface reflectance results in the accuracy of AOD. Therefore, improvements of cloud masking process and surface reflectance estimation in the developed single channel MI algorithm will be required for the future study.

Consistency of Global Modis Aerosol Optical Depths over Ocean on Terra and Aqua Ceres SSF Datasets

NASA Technical Reports Server (NTRS)

Ignatov, Alexander; Minnis, Patrick; Miller, Walter F.; Wielicki, Bruce A.; Remer, Lorraine

2006-01-01

Aerosol retrievals over ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side-by-side. The primary M product is generated by sub-setting and remapping the multi-spectral (0.47-2.1 micrometer) MODIS produced oceanic aerosol (MOD04/MYD04 for Terra/Aqua) onto CERES footprints. M*D04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary AVHRR-like A product is generated in only two MODIS bands 1 and 6 (on Aqua, bands 1 and 7). The A processing uses the CERES cloud screening algorithm, and NOAA/NESDIS glint identification, and single-channel aerosol retrieval algorithms. The M and A products have been documented elsewhere and preliminarily compared using 2 weeks of global Terra CERES SSF Edition 1A data in which the M product was based on MOD04 collection 3. In this study, the comparisons between the M and A aerosol optical depths (AOD) in MODIS band 1 (0.64 micrometers), tau(sub 1M) and tau(sub 1A) are re-examined using 9 days of global CERES SSF Terra Edition 2A and Aqua Edition 1B data from 13 - 21 October 2002, and extended to include cross-platform comparisons. The M and A products on the new CERES SSF release are generated using the same aerosol algorithms as before, but with different preprocessing and sampling procedures, lending themselves to a simple sensitivity check to non-aerosol factors. Both tau(sub 1M) and tau(sub 1A) generally compare well across platforms. However, the M product shows some differences, which increase with ambient cloud amount and towards the solar side of the orbit. Three types of comparisons conducted in this study - cross-platform, cross-product, and cross-release confirm the previously made observation that the major area for improvement in the current aerosol processing lies in a more formalized and standardized sampling (and most importantly, cloud screening) whereas optimization of the aerosol algorithm is deemed to be an important yet less critical element.

Stereoscopic Height and Wind Retrievals for Aerosol Plumes with the MISR INteractive eXplorer (MINX)

NASA Technical Reports Server (NTRS)

Nelson, D.L.; Garay, M.J.; Kahn, Ralph A.; Dunst, Ben A.

2013-01-01

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.

A Global, Decadal, Quantitative Record of Absorbing Aerosols above Cloud Using OMI's Near-UV Observations

NASA Astrophysics Data System (ADS)

Torres, O.; Jethva, H. T.; Ahn, C.

2016-12-01

Aerosol-cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of an adequate knowledge of the complex microphysical and radiative processes of the aerosol-cloud system. The situations when aerosols and clouds are found in the same atmospheric column, for instance, when light-absorbing aerosols such as biomass burning generated carbonaceous particles or wind-blown dust overlay low-level cloud decks, are commonly found over several regions of the world. Contrary to the known cooling effects of these aerosols in cloud-free scenario over dark surface, the overlapping situation of absorbing aerosols over cloud can potentially exert a significant level of atmospheric absorption and produces a positive radiative forcing (warming) at top-of-atmosphere. The magnitude of direct radiative effects of aerosols above cloud directly depends on the aerosol loading, microphysical and optical properties of the aerosol layer and the underlying cloud deck, and geometric cloud fraction. We help in addressing this problem by introducing a novel product of above-cloud aerosol optical depth (ACAOD) of absorbing aerosols retrieved from near-UV observations made by the Ozone Monitoring Instrument (OMI) on board NASA's Aura platform. Physically based on the strong `color ratio' effect in the near-UV caused by the spectral absorption of aerosols above cloud, the algorithm, formally named as OMACA, retrieves the optical depths of aerosols and clouds simultaneously under a prescribed state of atmosphere. Here, we present the algorithm architecture and results from an 11-year global record (2005-2015) including global climatology of frequency of occurrence and ACAOD. The theoretical uncertainty analysis and planned validation activities using measurements from upcoming field campaigns are also discussed.

A Ten-Year Global Record of Absorbing Aerosols Above Clouds from OMI's Near-UV Observations

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Ahn, Changwoo

2016-01-01

Aerosol-cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of an adequate knowledge of the complex microphysical and radiative processes associated with the aerosol-cloud system. The situations when aerosols and clouds are found in the same atmospheric column, for instance, when light-absorbing aerosols such as biomass burning generated carbonaceous particles or wind-blown dust overlay low-level cloud decks, are commonly found over several regional of the world. Contrary to the cloud-free scenario over dark surface, for which aerosols are known to produce a net cooling effect (negative radiative forcing) on climate, the overlapping situation of absorbing aerosols over cloud can potentially exert a significant level of atmospheric absorption and produces a positive radiative forcing at top-of-atmosphere. The magnitude of direct radiative effects of aerosols above cloud depends directly on the aerosol loading, microphysical-optical properties of the aerosol layer and the underlying cloud deck, and geometric cloud fraction. We help in addressing this problem by introducing a novel product of optical depth of absorbing aerosols above clouds retrieved from near-UV observations made by the Ozone Monitoring Instrument (OMI) on board NASA's Aura platform. The presence of absorbing aerosols above cloud reduces the upwelling radiation reflected by cloud and produces a strong 'color ratio' effect in the near-UV region, which can be unambiguously detected in the OMI measurements. Physically based on this effect, the OMACA algorithm retrieves the optical depths of aerosols and clouds simultaneously under a prescribed state of atmosphere. The algorithm architecture and results from a ten-year global record including global climatology of frequency of occurrence and above-cloud aerosol optical depth, and a discussion on related future field campaigns are presented.

MODIS Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms

NASA Technical Reports Server (NTRS)

Albayrak, Arif; Wei, Jennifer; Petrenko, Maksym; Lary, David; Leptoukh, Gregory

2011-01-01

To monitor the earth atmosphere and its surface changes, satellite based instruments collect continuous data. While some of the data is directly used, some others such as aerosol properties are indirectly retrieved from the observation data. While retrieved variables (RV) form very powerful products, they don't come without obstacles. Different satellite viewing geometries, calibration issues, dynamically changing atmospheric and earth surface conditions, together with complex interactions between observed entities and their environment affect them greatly. This results in random and systematic errors in the final products.

Simulating return signals of a spaceborne high-spectral resolution lidar channel at 532 nm

NASA Astrophysics Data System (ADS)

Xiao, Yu; Binglong, Chen; Min, Min; Xingying, Zhang; Lilin, Yao; Yiming, Zhao; Lidong, Wang; Fu, Wang; Xiaobo, Deng

2018-06-01

High spectral resolution lidar (HSRL) system employs a narrow spectral filter to separate the particulate (cloud/aerosol) and molecular scattering components in lidar return signals, which improves the quality of the retrieved cloud/aerosol optical properties. To better develop a future spaceborne HSRL system, a novel simulation technique was developed to simulate spaceborne HSRL return signals at 532 nm using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud/aerosol extinction coefficients product and numerical weather prediction data. For validating simulated data, a mathematical particulate extinction coefficient retrieval method for spaceborne HSRL return signals is described here. We compare particulate extinction coefficient profiles from the CALIPSO operational product with simulated spaceborne HSRL data. Further uncertainty analysis shows that relative uncertainties are acceptable for retrieving the optical properties of cloud and aerosol. The final results demonstrate that they agree well with each other. It indicates that the return signals of the spaceborne HSRL molecular channel at 532 nm will be suitable for developing operational algorithms supporting a future spaceborne HSRL system.

Aerosol Retrievals Using Channel 1 and 2 AVHRR Data

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.

1999-01-01

The effect of tropospheric aerosols on global climate via the direct and indirect radiative forcings is one of the largest remaining uncertainties in climate change studies. Current assessments of the direct aerosol radiative effect mainly focus on sulfate aerosols. It has become clear, however, that other aerosol types like soil dust and smoke from biomass burning are also likely to be important climate forcing factors. The magnitude and even the sign of the climate forcing caused by these aerosol types is still unknown. General circulation models (GCMs) can be used to estimate the climatic effect of the direct radiative forcing by tropospheric and stratospheric aerosols. Aerosol optical properties are already parameterized in the Goddard Institute for Space Studies GCM. Once the global distribution of aerosol properties (optical thickness, size distribution, and chemical composition) is available, the calculation of the direct aerosol forcing is rather straighfforward. However, estimates of the indirect aerosol effect require additional knowledge of the physics and chemistry of aerosol-cloud interactions which are still poorly understood. One of the main objectives of the Global Aerosol Climatology Project, established in 1998 as a joint initiative of NASA's Radiation Science Program and GEWEX, is to infer the global distribution of aerosols, their properties, and their seasonal and interannual variations for the full period of available satellite data. This will be accomplished primarily through a systematic application of multichannel aerosol retrieval algorithms to existing satellite data and advanced 3-dimensional aerosol chemistry/transport models. In this paper we outline the methodology of analyzing channel 1 and 2 AVHRR radiance data over the oceans and describe preliminary retrieval results.

Ocean observations with EOS/MODIS: Algorithm development and post launch studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1995-01-01

An investigation of the influence of stratospheric aerosol on the performance of the atmospheric correction algorithm was carried out. The results indicate how the performance of the algorithm is degraded if the stratospheric aerosol is ignored. Use of the MODIS 1380 nm band to effect a correction for stratospheric aerosols was also studied. The development of a multi-layer Monte Carlo radiative transfer code that includes polarization by molecular and aerosol scattering and wind-induced sea surface roughness has been completed. Comparison tests with an existing two-layer successive order of scattering code suggests that both codes are capable of producing top-of-atmosphere radiances with errors usually less than 0.1 percent. An initial set of simulations to study the effects of ignoring the polarization of the the ocean-atmosphere light field, in both the development of the atmospheric correction algorithm and the generation of the lookup tables used for operation of the algorithm, have been completed. An algorithm was developed that can be used to invert the radiance exiting the top and bottom of the atmosphere to yield the columnar optical properties of the atmospheric aerosol under clear sky conditions over the ocean, for aerosol optical thicknesses as large as 2. The algorithm is capable of retrievals with such large optical thicknesses because all significant orders of multiple scattering are included.

Indirect estimation of absorption properties for fine aerosol particles using AATSR observations: a case study of wildfires in Russia in 2010

NASA Astrophysics Data System (ADS)

Rodriguez, E.; Kolmonen, P.; Virtanen, T. H.; Sogacheva, L.; Sundstrom, A.-M.; de Leeuw, G.

2015-08-01

The Advanced Along-Track Scanning Radiometer (AATSR) on board the ENVISAT satellite is used to study aerosol properties. The retrieval of aerosol properties from satellite data is based on the optimized fit of simulated and measured reflectances at the top of the atmosphere (TOA). The simulations are made using a radiative transfer model with a variety of representative aerosol properties. The retrieval process utilizes a combination of four aerosol components, each of which is defined by their (lognormal) size distribution and a complex refractive index: a weakly and a strongly absorbing fine-mode component, coarse mode sea salt aerosol and coarse mode desert dust aerosol). These components are externally mixed to provide the aerosol model which in turn is used to calculate the aerosol optical depth (AOD). In the AATSR aerosol retrieval algorithm, the mixing of these components is decided by minimizing the error function given by the sum of the differences between measured and calculated path radiances at 3-4 wavelengths, where the path radiances are varied by varying the aerosol component mixing ratios. The continuous variation of the fine-mode components allows for the continuous variation of the fine-mode aerosol absorption. Assuming that the correct aerosol model (i.e. the correct mixing fractions of the four components) is selected during the retrieval process, also other aerosol properties could be computed such as the single scattering albedo (SSA). Implications of this assumption regarding the ratio of the weakly/strongly absorbing fine-mode fraction are investigated in this paper by evaluating the validity of the SSA thus obtained. The SSA is indirectly estimated for aerosol plumes with moderate-to-high AOD resulting from wildfires in Russia in the summer of 2010. Together with the AOD, the SSA provides the aerosol absorbing optical depth (AAOD). The results are compared with AERONET data, i.e. AOD level 2.0 and SSA and AAOD inversion products. The RMSE (root mean square error) is 0.03 for SSA and 0.02 for AAOD lower than 0.05. The SSA is further evaluated by comparison with the SSA retrieved from the Ozone Monitoring Instrument (OMI). The SSA retrieved from both instruments show similar features, with generally lower AATSR-estimated SSA values over areas affected by wildfires.

Validating MODIS above-cloud aerosol optical depth retrieved from "color ratio" algorithm using direct measurements made by NASA's airborne AATS and 4STAR sensors

NASA Astrophysics Data System (ADS)

Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rosenheimer, Michal; Spurr, Rob

2016-10-01

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the "color ratio" method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASA's airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne matchups revealed a good agreement (root-mean-square difference < 0.1), with most matchups falling within the estimated uncertainties associated the MODIS retrievals (about -10 to +50 %). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50 % for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite-based retrievals.

Validating MODIS Above-Cloud Aerosol Optical Depth Retrieved from Color Ratio Algorithm Using Direct Measurements Made by NASA's Airborne AATS and 4STAR Sensors

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rozenhaimer, Michal; Spurr, Rob

2016-01-01

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the color ratio method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASAs airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne match ups revealed a good agreement (root-mean-square difference less than 0.1), with most match ups falling within the estimated uncertainties associated with the MODIS retrievals (about -10 to +50 ). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50% for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite based retrievals.

The OMI Aerosol Absorption Product: An A-train application

NASA Astrophysics Data System (ADS)

Torres, O.; Jethva, H. T.; Ahn, C.

2017-12-01

Because of the uniquely large sensitivity of satellite-measured near-UV radiances to absorption by desert dust, carbonaceous and volcanic ash aerosols, observations by a variety of UV-capable sensors have been routinely used over the last forty years in both qualitative and quantitative applications for estimating the absorption properties of these aerosol types. In this presentation we will discuss a multi-sensor application involving observations from A-train sensors OMI, AIRS and CALIOP for the creation of a 13-year record of aerosol optical depth (AOD) and single scattering albedo (SSA). Determination of aerosol type, in terms of particle size distribution and refractive index, is an important algorithmic step that requires using external information. AIRS CO measurements are used as carbonaceous aerosols tracer to differentiate this aerosol type from desert dust. On the other hand, the height of the absorbing aerosol layer, an important parameter in UV aerosol retrievals, is prescribed using a CALIOP-based climatology. The combined use of these observations in the developments of the OMI long-term AOD/SSA record will be discussed along with an evaluation of retrieval results using independent observations.

Evaluation of VIIRS AOD over North China Plain: biases from aerosol models

NASA Astrophysics Data System (ADS)

Zhu, J.; Xia, X.; Wang, J.; Chen, H.; Zhang, J.; Oo, M. M.; Holz, R.

2014-12-01

With the launch of the Visible Infrared Imaging Radiometer Suit (VIIRS) instrument onboard Suomi National Polar-orbiting Partnership(S-NPP) in late 2011, the aerosol products of VIIRS are receiving much attention.To date, mostevaluations of VIIRS aerosol productswere carried out about aerosol optical depth (AOD). To further assess the VIIRS AOD in China which is a heavy polluted region in the world,we made a comparison between VIIRS AOD and CE-318 radiometerobservation at the following three sites overNorth China Plain (NCP): metropolis-Beijing (AERONET), suburbs-XiangHe (AERONET) and regional background site- Xinglong (CARSNET).The results showed the VIIRS AOD at 550 nm has a positive mean bias error (MBE) of 0.14-0.15 and root mean square error (RMBE) 0.20. Among three sites, Beijing is mainly a source of bias with MBE 0.17-0.18 and RMBE 0.23-0.24, and this bias is larger than some recent global statics recently published in the literature. Further analysis shows that this large bias in VIIRS AOD overNCP may be partly caused by the aerosol model selection in VIIRS aerosol inversion. According to the retrieval of sky radiance from CE-318 at three sites, aerosols in NCP have high mean real part of refractive indices (1.52-1.53), large volume mean radius (0.17-0.18) and low concentration (0.04-0.09) of fine aerosol, and small mean radius (2.86-2.92) and high concentration (0.06-0.16) of coarse mode aerosol. These observation-based aerosol single scattering properties and size of fine and coarse aerosols differ fromthe aerosol properties used in VIIRSoperational algorithm.The dominant aerosol models used in VIIRS algorithm for these three sites are less polluted urban aerosol in Beijing and low-absorption smoke in other two sites, all of which don't agree with the high imaginary part of refractive indices from CE-318 retrieval. Therefore, the aerosol models in VIIRS algorithm are likely to be refined in NCP region.

From OLS to VIIRS, an overview of nighttime satellite aerosol retrievals using artificial light sources

NASA Astrophysics Data System (ADS)

Zhang, J.; Miller, S. D.; Reid, J. S.; Hyer, E. J.; McHardy, T. M.

2015-12-01

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.

Snow and Ice Mask for the MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Remer, Lorraine; Kaufman, Yoram J.; Mattoo, Shana; Gao, Bo-Cai; Vermote, Eric

2005-01-01

The atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging SpectroRadiometers (MODIS) on board the NASA Terra and Aqua spacecrafts. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-IR channels centered near 0.86 and 1.24 pm and a thermal emission channel near 11 pm to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.

Atmospheric correction of short-wave hyperspectral imagery using a fast, full-scattering 1DVar retrieval scheme

NASA Astrophysics Data System (ADS)

Thelen, J.-C.; Havemann, S.; Taylor, J. P.

2012-06-01

Here, we present a new prototype algorithm for the simultaneous retrieval of the atmospheric profiles (temperature, humidity, ozone and aerosol) and the surface reflectance from hyperspectral radiance measurements obtained from air/space-borne, hyperspectral imagers such as the 'Airborne Visible/Infrared Imager (AVIRIS) or Hyperion on board of the Earth Observatory 1. The new scheme, proposed here, consists of a fast radiative transfer code, based on empirical orthogonal functions (EOFs), in conjunction with a 1D-Var retrieval scheme. The inclusion of an 'exact' scattering code based on spherical harmonics, allows for an accurate treatment of Rayleigh scattering and scattering by aerosols, water droplets and ice-crystals, thus making it possible to also retrieve cloud and aerosol optical properties, although here we will concentrate on non-cloudy scenes. We successfully tested this new approach using two hyperspectral images taken by AVIRIS, a whiskbroom imaging spectrometer operated by the NASA Jet Propulsion Laboratory.

Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, Feng; van Harten, Gerard; Diner, David J.; Davis, Anthony B.; Seidel, Felix C.; Rheingans, Brian; Tosca, Mika; Alexandrov, Mikhail D.; Cairns, Brian; Ferrare, Richard A.; Burton, Sharon P.; Fenn, Marta A.; Hostetler, Chris A.; Wood, Robert; Redemann, Jens

2018-03-01

An optimization algorithm is developed to retrieve liquid water cloud properties including cloud optical depth (COD), droplet size distribution and cloud top height (CTH), and above-cloud aerosol properties including aerosol optical depth (AOD), single-scattering albedo, and microphysical properties from sweep-mode observations by Jet Propulsion Laboratory's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument. The retrieval is composed of three major steps: (1) initial estimate of the mean droplet size distribution across the entire image of 80-100 km along track by 10-25 km across track from polarimetric cloudbow observations, (2) coupled retrieval of image-scale cloud and above-cloud aerosol properties by fitting the polarimetric data at all observation angles, and (3) iterative retrieval of 1-D radiative transfer-based COD and droplet size distribution at pixel scale (25 m) by establishing relationships between COD and droplet size and fitting the total radiance measurements. Our retrieval is tested using 134 AirMSPI data sets acquired during the National Aeronautics and Space Administration (NASA) field campaign ObseRvations of Aerosols above CLouds and their intEractionS. The retrieved above-cloud AOD and CTH are compared to coincident HSRL-2 (HSRL-2, NASA Langley Research Center) data, and COD and droplet size distribution parameters (effective radius reff and effective variance veff) are compared to coincident Research Scanning Polarimeter (RSP) (NASA Goddard Institute for Space Studies) data. Mean absolute differences between AirMSPI and HSRL-2 retrievals of above-cloud AOD at 532 nm and CTH are 0.03 and <0.5 km, respectively. At RSP's footprint scale ( 323 m), mean absolute differences between RSP and AirMSPI retrievals of COD, reff, and veff in the cloudbow area are 2.33, 0.69 μm, and 0.020, respectively. Neglect of smoke aerosols above cloud leads to an underestimate of image-averaged COD by 15%.

Case studies of aerosol and ocean color retrieval using a Markov chain radiative transfer model and AirMSPI measurements

NASA Astrophysics Data System (ADS)

Xu, F.; Diner, D. J.; Seidel, F. C.; Dubovik, O.; Zhai, P.

2014-12-01

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 and aerosol parametric models will also be discussed.

The Potential of Clear Sky Carbon Dioxide Satellite Retrievals

NASA Astrophysics Data System (ADS)

Nelson, R.; O'Dell, C.

2013-12-01

It has been shown that neglecting scattering and absorption by aerosols and thin clouds can lead to significant errors in retrievals of the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from space-based measurements of near-infrared reflected sunlight. These clear sky retrievals, which assume no aerosol effects, are desirable because of their high computational efficiency relative to common full physics retrievals. Further, clear sky retrievals may be able to make higher quality measurements relative to the full physics approach because they may introduce fewer potential biases under certain circumstances. These biases can appear when we try to retrieve clouds and aerosols in the full physics methods when there are none actually present. Recent work has shown that intelligent pre-screening can remove soundings with large light-path modifications over ocean surfaces. In this work, we test the hypothesis that intelligent pre-screening of soundings may be successfully used over land surfaces as well as oceans, which would allow clear sky retrievals to be applicable over all surfaces. We also test the hypothesis that major light path modification effects associated with aerosols can be identified based on spectral tests at 0.76, 1.6, and 2 microns. This presentation summarizes our study of both simulated data and satellite observations from the GOSAT instrument in order to assess the effectiveness of using a clear sky retrieval algorithm coupled with intelligent pre-screening to accurately measure carbon dioxide from space-borne instruments.

Remote Sensing of Aerosol and their Radiative Properties from the MODIS Instrument on EOS-Terra Satellite: First Results and Evaluation

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Holben, Brent; Lau, William K.-M. (Technical Monitor)

2001-01-01

The MODIS instrument was launched on the NASA Terra satellite in Dec. 1999. Since last Oct., the sensor and the aerosol algorithm reached maturity and provide global daily retrievals of aerosol optical thickness and properties. MODIS has 36 spectral channels in the visible to IR with resolution down to 250 m. This allows accurate cloud screening and multi-spectral aerosol retrievals. We derive the aerosol optical thickness over the ocean and most of the land areas, distinguishing between fine (mainly man-made aerosol) and coarse aerosol particles. The information is more precise over the ocean where we derive also the effective radius and scattering asymmetry parameter of the aerosol. New methods to derive the aerosol single scattering albedo are also being developed. These measurements are use to track different aerosol sources, transport and the radiative forcing at the top and bottom of the atmosphere. The AErosol RObotic NETwork of ground based radiometers is used for global validation of the satellite derived optical thickness, size parameters and single scattering albedo and measure additional aerosol parameters that cannot be derived from space.

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations: 2. Retrieval Evaluation

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Wind, Galina; Yang, Ping

2016-01-01

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 (tau) and effective radius (r(sub eff)) retrievals perform best for ice clouds having 0.5 < tau< 7 and r(sub eff) < 50microns. For global ice clouds, the averaged retrieval uncertainties of tau and r(sub eff) are 19% and 33%, respectively. For optically thick ice clouds with tau larger than 10, however, the tau and r(sub eff) retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48km. Relatively large h uncertainty (e.g., > 1km) occurs for tau < 0.5. Analysis of 1month of the OE-IR retrievals shows large tau and r(sub eff) 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 tau and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 r(sub eff) are found.

Space-Based Remote Sensing of Atmospheric Aerosols: The Multi-Angle Spectro-Polarimetric Frontier

NASA Technical Reports Server (NTRS)

Kokhanovsky, A. A.; Davis, A. B.; Cairns, B.; Dubovik, O.; Hasekamp, O. P.; Sano, I.; Mukai, S.; Rozanov, V. V.; Litvinov, P.; Lapyonok, T.;

Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

NASA Astrophysics Data System (ADS)

Patadia, Falguni; Levy, Robert C.; Mattoo, Shana

2018-06-01

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from the underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon the Moderate Resolution Imaging Spectroradiometer (MODIS, on board Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, on board Suomi-NPP) sensors, use wavelength bands in window regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper, we use the High-resolution TRANsmission (HITRAN) database and Line-By-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are similar, they are different enough that applying MODIS-specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases of up to 0.07. As recent studies have been attempting to create a long-term data record by joining multiple satellite data sets, including MODIS and VIIRS, the consistency of gas correction has become even more crucial.

Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

EPA Science Inventory

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...

Validating Above-cloud Aerosol Optical Depth Retrieved from MODIS using NASA Ames Airborne Sun-Tracking Photometric and Spectrometric (AATS and 4STAR) Measurements

NASA Astrophysics Data System (ADS)

Jethva, H. T.; Torres, O.; Remer, L. A.; Redemann, J.; Dunagan, S. E.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Segal-Rosenhaimer, M.

2014-12-01

Absorbing aerosols produced from biomass burning and dust outbreaks are often found to overlay the lower level cloud decks as evident in the satellite images. In contrast to the cloud-free atmosphere, in which aerosols generally tend to cool the atmosphere, the presence of absorbing aerosols above cloud poses greater potential of exerting positive radiative effects (warming) whose magnitude directly depends on the aerosol loading above cloud, optical properties of clouds and aerosols, and cloud fraction. In recent years, development of algorithms that exploit satellite-based passive measurements of ultraviolet (UV), visible, and polarized light as well as lidar-based active measurements constitute a major breakthrough in the field of remote sensing of aerosols. While the unprecedented quantitative information on aerosol loading above cloud is now available from NASA's A-train sensors, a greater question remains ahead: How to validate the satellite retrievals of above-cloud aerosols (ACA)? Direct measurements of ACA such as carried out by the NASA Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) can be of immense help in validating ACA retrievals. In this study, we validate the ACA optical depth retrieved using the 'color ratio' (CR) method applied to the MODIS cloudy-sky reflectance by using the airborne AATS and 4STAR measurements. A thorough search of the historic AATS-4STAR database collected during different field campaigns revealed five events where biomass burning, dust, and wildfire-emitted aerosols were found to overlay lower level cloud decks observed during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS-2013, respectively. The co-located satellite-airborne measurements revealed a good agreement (root-mean-square-error<0.1 for Aerosol Optical Depth (AOD) at 500 nm) with most matchups falling within the estimated uncertainties in the MODIS retrievals (-10% to +50%). An extensive validation of satellite-based ACA retrievals requires equivalent field measurements particularly over the regions where ACA are often observed from satellites, i.e., south-eastern Atlantic Ocean, tropical Atlantic Ocean, northern Arabian Sea, South-East and North-East Asia.

Characterization of Asian Dust Properties Near Source Region During ACE-Asia

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Hsu, N. Christina; King, Michael D.; Kaufman, Yoram J.; Herman, Jay R.

2004-01-01

Asian dust typically originates in desert areas far from polluted urban regions. During transport, dust layers can interact with anthropogenic sulfate and soot aerosols from heavily polluted urban areas. Added to the complex effects of clouds and natural marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from the source. Thus, understanding the unique temporal and spatial variations of Asian aerosols is of special importance in regional-to-global climate issues such as radiative forcing, the hydrological cycle, and primary biological productivity in the mid-Pacific Ocean. During ACE-Asia campaign, we have acquired ground- based (temporal) and satellite (spatial) measurements to infer aerosol physical/optical/radiative properties, column precipitable water amount, and surface reflectivity over this region. The inclusion of flux measurements permits the determination of aerosol radiative flux in addition to measurements of loading and optical depth. At the time of the Terra/MODIS, SeaWiFS, TOMS and other satellite overpasses, these ground-based observations can provide valuable data to compare with satellite retrievals over land. In this paper, we will demonstrate new capability of the Deep Blue algorithm to track the evolution of the Asian dust storm from sources to sinks. Although there are large areas often covered by clouds in the dust season in East Asia, this algorithm is able to distinguish heavy dust from clouds over the entire regions. Examination of the retrieved daily maps of dust plumes over East Asia clearly identifies the sources contributing to the dust loading in the atmosphe. We have compared the satellite retrieved aerosol optical thickness to the ground-based measurements and obtained a reasonable agreement between these two. Our results also indicate that there is a large difference in the retrieved value of spectral single scattering albedo of windblown dust between different sources in East Asia.

Retrieval of the scattering and microphysical properties of aerosols from ground-based optical measurements including polarization. I. Method.

PubMed

Vermeulen, A; Devaux, C; Herman, M

2000-11-20

A method has been developed for retrieving the scattering and microphysical properties of atmospheric aerosol from measurements of solar transmission, aureole, and angular distribution of the scattered and polarized sky light in the solar principal plane. Numerical simulations of measurements have been used to investigate the feasibility of the method and to test the algorithm's performance. It is shown that the absorption and scattering properties of an aerosol, i.e., the single-scattering albedo, the phase function, and the polarization for single scattering of incident unpolarized light, can be obtained by use of radiative transfer calculations to correct the values of scattered radiance and polarized radiance for multiple scattering, Rayleigh scattering, and the influence of ground. The method requires only measurement of the aerosol's optical thickness and an estimate of the ground's reflectance and does not need any specific assumption about properties of the aerosol. The accuracy of the retrieved phase function and polarization of the aerosols is examined at near-infrared wavelengths (e.g., 0.870 mum). The aerosol's microphysical properties (size distribution and complex refractive index) are derived in a second step. The real part of the refractive index is a strong function of the polarization, whereas the imaginary part is strongly dependent on the sky's radiance and the retrieved single-scattering albedo. It is demonstrated that inclusion of polarization data yields the real part of the refractive index.

Aerosol Retrievals from ARM SGP MFRSR Data

DOE Data Explorer

Alexandrov, Mikhail

2008-01-15

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.

Global Long-Term SeaWiFS Deep Blue Aerosol Products available at NASA GES DISC

NASA Technical Reports Server (NTRS)

Shen, Suhung; Sayer, A. M.; Bettenhausen, Corey; Wei, Jennifer C.; Ostrenga, Dana M.; Vollmer, Bruce E.; Hsu, Nai-Yung; Kempler, Steven J.

2012-01-01

Long-term climate data records about aerosols are needed in order to improve understanding of air quality, radiative forcing, and for many other applications. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides a global well-calibrated 13- year (1997-2010) record of top-of-atmosphere radiance, suitable for use in retrieval of atmospheric aerosol optical depth (AOD). Recently, global aerosol products derived from SeaWiFS with Deep Blue algorithm (SWDB) have become available for the entire mission, as part of the NASA Making Earth Science data records for Use in Research for Earth Science (MEaSUREs) program. The latest Deep Blue algorithm retrieves aerosol properties not only over bright desert surfaces, but also vegetated surfaces, oceans, and inland water bodies. Comparisons with AERONET observations have shown that the data are suitable for quantitative scientific use [1],[2]. The resolution of Level 2 pixels is 13.5x13.5 km2 at the center of the swath. Level 3 daily and monthly data are composed by using best quality level 2 pixels at resolution of both 0.5ox0.5o and 1.0ox1.0o. Focusing on the southwest Asia region, this presentation shows seasonal variations of AOD, and the result of comparisons of 5-years (2003- 2007) of AOD from SWDB (Version 3) and MODIS Aqua (Version 5.1) for Dark Target (MYD-DT) and Deep Blue (MYD-DB) algorithms.

Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Cairns, Brian; Emde, Claudia; Ackerman, Andrew S.; vanDiedenhove, Bastiaan

2012-01-01

We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260 nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135deg and 165deg, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

Validation of high-resolution MAIAC aerosol product over South America

NASA Astrophysics Data System (ADS)

Martins, V. S.; Lyapustin, A.; de Carvalho, L. A. S.; Barbosa, C. C. F.; Novo, E. M. L. M.

2017-07-01

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD550 was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (RTerra:0.956 and RAqua: 0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 ( 66%) of retrievals are within the expected error (EE = ±(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset 0.006). Additionally, MAIAC CWV presents quantitative information with R 0.97 and more than 70% of retrievals within error (±15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Korkin, S.; Wang, Y.; Quayle, B.; Laszlo, I.

2012-01-01

The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

Application of an Optimal Estimation Method to the Retrieval of Aerosol Properties Using Multispectral, Multiangle Polarimetric Measurements From the Research Scanning Polarimeter.

NASA Astrophysics Data System (ADS)

Waquet, F.; Cairns, B.; Chowdhary, J.; Knobelspiesse, K.; Mishchenko, M. I.; Travis, L. D.

2006-12-01

Aerosols affect the climate directly by means of reflecting and absorbing sunlight, and indirectly by means of changing the formation and evolution of clouds. The uncertainties associated with these forcing are however highly uncertain, and may add up to be equal in magnitude but opposite in sign to the climate forcing caused by greenhouse gasses. To reduce these uncertainties, accurate retrievals of the effective size of the particles, their complex refractive index and the column number density are required. Intensity-based techniques for aerosol remote sensing from space only partially meet these requirements because they provide reasonable estimates of only the aerosol size distribution and optical thickness, and only over ocean. Laboratory and theoretical studies, on the other hand, show that the multi-angle, multi-spectral behavior of polarization of light scattered by aerosol particles contains sufficient information to provide all the relevant properties of these particles. The Research Scanning Polarimeter (RSP) instrument provides an opportunity to extend such studies to the polarimetric retrieval of aerosol properties from actual remote sensing data. This instrument provides photo-polarimetric measurements of a scene in 152 viewing angles covering an angular range of 120 degrees, and in 9 spectral bands covering a spectral range of 0.41 to 2.25 micrometers. It was recently deployed in the ALIVE field experiment in Oklahoma and the MILAGRO field experiment near Mexico City, in conjunction with many other space-, air-, and ground-based sensors, to study aerosols over land and ocean. The purpose of this study is to use data acquired during these field experiments by the RSP instrument and various other sensors to evaluate a new method for aerosol polarimetry over land. Our approach follows one of the so-called optimal methods described by Rodger (2004) with a few modifications. We describe the optimal method selected and modified for RSP-type data sets, and also how to include the noise and accuracy (including relative angular and relative spectral accuracy) of RSP measurements in the optimal estimate. This approach has been used for aerosol retrievals over ocean, and is now being extended to aerosol retrievals over land since multi-spectral polarized measurements allow the surface and aerosol properties to be retrieved simultaneously, as recently shown in Waquet et al. (2006). We present results of our RSP-based aerosol retrievals and compare them with independent retrievals for various atmospheric conditions that span from low aerosols loads dominated by spherical particles to high aerosol loads dominated by wind blown non-spherical soil particles. This study constitutes an important step in the validation of new algorithms for aerosol remote sensing using polarization measurements in preparation for the GLORY mission.

Comparison of MAX-DOAS profiling algorithms during CINDI-2 - Part 1: aerosols

NASA Astrophysics Data System (ADS)

Friess, Udo; Hendrick, Francois; Tirpitz, Jan-Lukas; Apituley, Arnoud; van Roozendael, Michel; Kreher, Karin; Richter, Andreas; Wagner, Thomas

2017-04-01

The second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) took place at the Cabauw Experimental Site for Atmospheric Research (CESAR; Utrecht area, The Netherlands) from 25 August until 7 October 2016. CINDI-2 was aiming at assessing the consistency of MAX-DOAS slant column density measurements of tropospheric species (NO2, HCHO, O3, and O4) relevant for the validation of future ESA atmospheric Sentinel missions, through coordinated operation of a large number of DOAS and MAXDOAS instruments from all over the world. An important objective of the campaign was to study the relationship between remote-sensing column and profile measurements of the above species and collocated reference ancillary observations. For this purpose, the CINDI-2 Profiling Task Team (CPTT) was created, involving 22 groups performing aerosol and trace gas vertical profile inversion using dedicated MAX-DOAS profiling algorithms, as well as the teams responsible for ancillary profile and surface concentration measurements (NO2 analysers, NO2 sondes, NO2 and Raman LIDARs, CAPS, Long-Path DOAS, sun photometer, nephelometer, etc). The main purpose of the CPTT is to assess the consistency of the different profiling tools for retrieving aerosol extinction and trace gas vertical profiles through comparison exercises using commonly defined settings and to validate the retrievals with correlative observations. In this presentation, we give an overview of the MAX-DOAS vertical profile comparison results, focusing on the retrieval of aerosol extinction profiles, with the trace gas retrievals being presented in a companion abstract led by F. Hendrick. The performance of the different algorithms is investigated with respect to the variable visibility and cloud conditions encountered during the campaign. The consistency between optimal-estimation-based and parameterized profiling tools is also evaluated for these different conditions, together with the level of agreement with available ancillary aerosol observations, including sun photometer, nephelometer and LIDAR. This comparison study will be put in the perspective of the development of a centralized MAX-DOAS processing system within the framework of the ESA Fiducial Reference Measurements (FRM) project.

Retrieval of AOD and PM2.5 Concentrations over Urban Areas of Shenyang City using MODIS Data

NASA Astrophysics Data System (ADS)

Wang, Z.

2016-12-01

Atmospheric aerosols play an important part in the Earth's radiation balance as well as global climate change, aerosols also have very important impact on environment as well as human and other organisms' health, PM2.5 and other small particle aerosols, can enter bronchi directly, thus causing bronchitis, cardiovascular disease, asthma and so on.Detection of AOD by satellite and remote sensing is currently one of the hotest issues , diffierent from the traditional monitoring method, this method has much more advantanges, for emample wide area coverage, fast and convenient etc. So it is possible for people to know the regional changes of AOD real time over large area. Now, detection aerosol by RS technology has reached a high level in marine and dense vegetation land areas, but result is not ideal for urban areas, the higher surface reflectance in urban areas is a bottleneck of AOD retrieval. Focus on the high surface reflectance and low accuracy of the AOD products of urban areas, this paper propose an algorithm coupled with surface reflectance to get red band surface reflectance, based on Dens Dark Vegetation algorithm and geometrical optics model theory, to distinguish urban reflectivity from other targets. Considering the appropriate aerosol model which adapt to season and other proper parameters, this paper uses 6S model to establish look-up table, thus retrieve AOD for urban as well as other high reflectance areas. This paper take Shenyang region as pilot area, then retrieve the AOD and PM2.5 concentration of Shenyang in 2015 based on MODIS data, thus get 1km resolution distribution map, and then analyzed the results in spatial, intensity and temporal. At last, real-time monitoring data from the ground monitor station is used to verify the outcome, the results have good accuracy and the the correlation reached 0.9004 when the weather is sunny. The research shows that this algorithm has relatively higher precision and certain universality. This method has better applicability to retrieve AOD and PM2.5 concentration by remote sensing in Shenyang and Liaoning Provience, and owes guiding and reference significance, and it has a high value in terms of atmospheric environment monitoring.

Simultaneous determination of aerosol optical thickness and water-leaving radiance from multispectral measurements in coastal waters

NASA Astrophysics Data System (ADS)

Shi, Chong; Nakajima, Teruyuki

2018-03-01

Retrieval of aerosol optical properties and water-leaving radiance over ocean is challenging since the latter mostly accounts for ˜ 10 % of the satellite-observed signal and can be easily influenced by the atmospheric scattering. Such an effort would be more difficult in turbid coastal waters due to the existence of optically complex oceanic substances or high aerosol loading. In an effort to solve such problems, we present an optimization approach for the simultaneous determination of aerosol optical thickness (AOT) and normalized water-leaving radiance (nLw) from multispectral satellite measurements. In this algorithm, a coupled atmosphere-ocean radiative transfer model combined with a comprehensive bio-optical oceanic module is used to jointly simulate the satellite-observed reflectance at the top of atmosphere and water-leaving radiance just above the ocean surface. Then, an optimal estimation method is adopted to retrieve AOT and nLw iteratively. The algorithm is validated using Aerosol Robotic Network - Ocean Color (AERONET-OC) products selected from eight OC sites distributed over different waters, consisting of observations that covered glint and non-glint conditions from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Results show a good consistency between retrieved and in situ measurements at each site. It is demonstrated that more accurate AOTs are determined based on the simultaneous retrieval method, particularly in shorter wavelengths and sunglint conditions, where the averaged percentage difference (APD) of retrieved AOT is generally reduced by approximate 10 % in visible bands compared with those derived from the standard atmospheric correction (AC) scheme, since all the spectral measurements can be used jointly to increase the information content in the inversion of AOT, and the wind speed is also simultaneously retrieved to compensate the specular reflectance error estimated from the rough ocean surface model. For the retrieval of nLw, atmospheric overcorrection can be avoided in order to have a significant improvement of the inversion of nLw at 412 nm. Furthermore, generally better estimates of band ratios of nLw(443) / nLw(554) and nLw(488) / nLw(554) are obtained using the simultaneous retrieval approach with lower root mean square errors and relative differences than those derived from the standard AC approach in comparison to the AERONET-OC products, as well as the APD values of retrieved Chl which decreased by about 5 %. On the other hand, the standard AC scheme yields a more accurate retrieval of nLw at 488 nm, prompting a further optimization of the oceanic bio-optical module of the current model.

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm through Intercomparison with VIIRS Aerosol Products and AERONET

NASA Technical Reports Server (NTRS)

Superczynski, Stephen D.; Kondragunta, Shobha; Lyapustin, Alexei I.

2017-01-01

The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data. from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and un-matched seasonally gridded data are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with AERONET Level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of -0.01; however there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products capability over the Western Hemisphere. and meet the levels of accuracy needed for aerosol monitoring.

Evaluation of the multi-angle implementation of atmospheric correction (MAIAC) aerosol algorithm through intercomparison with VIIRS aerosol products and AERONET

NASA Astrophysics Data System (ADS)

Superczynski, Stephen D.; Kondragunta, Shobha; Lyapustin, Alexei I.

2017-03-01

The multi-angle implementation of atmospheric correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and unmatched seasonally gridded data, are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with Aerosol Robotic Network level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of -0.01; however, there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products' capability over the Western Hemisphere.

A modeling approach for aerosol optical depth analysis during forest fire events

NASA Astrophysics Data System (ADS)

Aube, Martin P.; O'Neill, Normand T.; Royer, Alain; Lavoue, David

2004-10-01

Measurements of aerosol optical depth (AOD) are important indicators of aerosol particle behavior. Up to now the two standard techniques used for retrieving AOD are; (i) sun photometry which provides measurements of high temporal frequency and sparse spatial frequency, and (ii) satellite based approaches such as DDV (Dense Dark Vegetation) based inversion algorithms which yield AOD over dark targets in remotely sensed imagery. Although the latter techniques allow AOD retrieval over appreciable spatial domains, the irregular spatial pattern of dark targets and the typically low repeat frequencies of imaging satellites exclude the acquisition of AOD databases on a continuous spatio-temporal basis. We attempt to fill gaps in spatio-temporal AOD measurements using a new assimilation methodology that links AOD measurements and the predictions of a particulate matter Transport Model. This modelling package (AODSEM V2.0 for Aerosol Optical Depth Spatio-temporal Evolution Model) uses a size and aerosol type segregated semi-Lagrangian trajectory algorithm driven by analysed meteorological data. Its novelty resides in the fact that the model evolution may be tied to both ground based and satellite level AOD measurement and all physical processes have been optimized to track this important and robust parameter. We applied this methodology to a significant smoke event that occurred over the eastern part of North America in July 2002.

Microphysical particle properties derived from inversion algorithms developed in the framework of EARLINET

NASA Astrophysics Data System (ADS)

Müller, Detlef; Böckmann, Christine; Kolgotin, Alexei; Schneidenbach, Lars; Chemyakin, Eduard; Rosemann, Julia; Znak, Pavel; Romanov, Anton

2016-10-01

We present a summary on the current status of two inversion algorithms that are used in EARLINET (European Aerosol Research Lidar Network) for the inversion of data collected with EARLINET multiwavelength Raman lidars. These instruments measure backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. Development of these two algorithms started in 2000 when EARLINET was founded. The algorithms are based on a manually controlled inversion of optical data which allows for detailed sensitivity studies. The algorithms allow us to derive particle effective radius as well as volume and surface area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light absorption needs to be known with high accuracy. It is an extreme challenge to retrieve the real part with an accuracy better than 0.05 and the imaginary part with accuracy better than 0.005-0.1 or ±50 %. Single-scattering albedo can be computed from the retrieved microphysical parameters and allows us to categorize aerosols into high- and low-absorbing aerosols. On the basis of a few exemplary simulations with synthetic optical data we discuss the current status of these manually operated algorithms, the potentially achievable accuracy of data products, and the goals for future work. One algorithm was used with the purpose of testing how well microphysical parameters can be derived if the real part of the complex refractive index is known to at least 0.05 or 0.1. The other algorithm was used to find out how well microphysical parameters can be derived if this constraint for the real part is not applied. The optical data used in our study cover a range of Ångström exponents and extinction-to-backscatter (lidar) ratios that are found from lidar measurements of various aerosol types. We also tested aerosol scenarios that are considered highly unlikely, e.g. the lidar ratios fall outside the commonly accepted range of values measured with Raman lidar, even though the underlying microphysical particle properties are not uncommon. The goal of this part of the study is to test the robustness of the algorithms towards their ability to identify aerosol types that have not been measured so far, but cannot be ruled out based on our current knowledge of aerosol physics. We computed the optical data from monomodal logarithmic particle size distributions, i.e. we explicitly excluded the more complicated case of bimodal particle size distributions which is a topic of ongoing research work. Another constraint is that we only considered particles of spherical shape in our simulations. We considered particle radii as large as 7-10 µm in our simulations where the Potsdam algorithm is limited to the lower value. We considered optical-data errors of 15 % in the simulation studies. We target 50 % uncertainty as a reasonable threshold for our data products, though we attempt to obtain data products with less uncertainty in future work.

Aerosol Optical Depth as Observed by the Mars Science Laboratory REMS UV Photodiodes

NASA Technical Reports Server (NTRS)

Smith, M. D.; Zorzano, M.-P.; Lemmon, M.; Martin-Torres, J.; Mendaza de Cal, T.

2017-01-01

Systematic observations taken by the REMS UV photodiodes on a daily basis throughout the landed Mars Science Laboratory mission provide a highly useful tool for characterizing aerosols above Gale Crater. Radiative transfer modeling is used to model the approximately two Mars Years of observations taken to date taking into account multiple scattering from aerosols and the extended field of view of the REMS UV photodiodes. The retrievals show in detail the annual cycle of aerosol optical depth, which is punctuated with numerous short timescale events of increased optical depth. Dust deposition onto the photodiodes is accounted for by comparison with aerosol optical depth derived from direct imaging of the Sun by Mastcam. The effect of dust on the photodiodes is noticeable, but does not dominate the signal. Cleaning of dust from the photodiodes was observed in the season around Ls=270deg, but not during other seasons. Systematic deviations in the residuals from the retrieval fit are indicative of changes in aerosol effective particle size, with larger particles present during periods of increased optical depth. This seasonal dependence of aerosol particle size is expected as dust activity injects larger particles into the air, while larger aerosols settle out of the atmosphere more quickly leading to a smaller average particle size over time. A full description of these observations, the retrieval algorithm, and the results can be found in Smith et al. (2016).

The New MODIS-Terra, and the Proposed COBRA Mission: First Global Aerosol Distribution and Properties Over Land and Ocean, and Plans to Measure Global Black Carbon Absorption Over the Ocean Glint

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Tanre, Didier; Remer, Lorraine; Martins, Vanderlei; Schoeberl, Mark; Lau, William K. M. (Technical Monitor)

2001-01-01

The MODIS instrument was launched on the NASA Terra satellite in Dec. 1999. Since last Oct, the sensor and the aerosol algorithm reached maturity and provide global daily retrievals of aerosol optical thickness and properties. MODIS has 36 spectral channels in the visible to IR with resolution down to 250 m. This allows accurate cloud screening and multi-spectral aerosol retrievals. We derive the aerosol optical thickness over the ocean and most of the land areas, distinguishing between fine (mainly man-made aerosol) and coarse (mainly natural) aerosol particles. New methods to derive the aerosol absorption of sunlight are also being developed. These measurements are use to track different aerosol sources, transport and the radiative forcing at the top and bottom of the atmosphere. However MODIS or any present satellite sensor cannot measure absorption by Black Carbon over the oceans, a critical component in studying climate change and human health. For this purpose we propose the COBRA mission that observes the ocean at glint and off glint simultaneously measuring the spectral polarized light and deriving precisely the aerosol absorption.

A New Algorithm for Detecting Cloud Height using OMPS/LP Measurements

NASA Technical Reports Server (NTRS)

Chen, Zhong; DeLand, Matthew; Bhartia, Pawan K.

2016-01-01

The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) ozone product requires the determination of cloud height for each event to establish the lower boundary of the profile for the retrieval algorithm. We have created a revised cloud detection algorithm for LP measurements that uses the spectral dependence of the vertical gradient in radiance between two wavelengths in the visible and near-IR spectral regions. This approach provides better discrimination between clouds and aerosols than results obtained using a single wavelength. Observed LP cloud height values show good agreement with coincident Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements.

Utilization of O4 slant column density to derive aerosol layer height from a space-borne UV-visible hyperspectral sensor: sensitivity and case study

NASA Astrophysics Data System (ADS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-02-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the differential optical absorption spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 1040 molecules2 cm-5, to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 m for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80 % of retrieved aerosol effective heights are within the error range of 1 km compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Utilization of O4 Slant Column Density to Derive Aerosol Layer Height from a Space-Borne UV-Visible Hyperspectral Sensor: Sensitivity and Case Study

NASA Technical Reports Server (NTRS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-01-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the differential optical absorption spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 10(sup 40) molecules (sup 2) per centimeters(sup -5), to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nanometers, the O4 absorption band at 477 nanometers is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nanometers is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 meters for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80 percent of retrieved aerosol effective heights are within the error range of 1 kilometer compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Utilization of O4 Slant Column Density to Derive Aerosol Layer Height from a Spaceborne UV-Visible Hyperspectral Sensor: Sensitivity and Case Study

NASA Technical Reports Server (NTRS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-01-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the Differential Optical Absorption Spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 10(exp 40) sq molecules cm(exp -5), to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 m for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80% of retrieved aerosol effective heights are within the error range of 1 km compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Derivation of Aerosol Columnar Mass from MODIS Optical Depth

NASA Technical Reports Server (NTRS)

Gasso, Santiago; Hegg, Dean A.

2003-01-01

In order to verify performance, aerosol transport models (ATM) compare aerosol columnar mass (ACM) with those derived from satellite measurements. The comparison is inherently indirect since satellites derive optical depths and they use a proportionality constant to derive the ACM. Analogously, ATMs output a four dimensional ACM distribution and the optical depth is linearly derived. In both cases, the proportionality constant requires a direct intervention of the user by prescribing the aerosol composition and size distribution. This study introduces a method that minimizes the direct user intervention by making use of the new aerosol products of MODIS. A parameterization is introduced for the derivation of columnar aerosol mass (AMC) and CCN concentration (CCNC) and comparisons between sunphotometer, MODIS Airborne Simulator (MAS) and in-measurements are shown. The method still relies on the scaling between AMC and optical depth but the proportionality constant is dependent on the MODIS derived r$_{eff}$,\\eta (contribution of the accumulation mode radiance to the total radiance), ambient RH and an assumed constant aerosol composition. The CCNC is derived fkom a recent parameterization of CCNC as a function of the retrieved aerosol volume. By comparing with in-situ data (ACE-2 and TARFOX campaigns), it is shown that retrievals in dry ambient conditions (dust) are improved when using a proportionality constant dependent on r$ {eff}$ and \\eta derived in the same pixel. In high humidity environments, the improvement inthe new method is inconclusive because of the difficulty in accounting for the uneven vertical distribution of relative humidity. Additionally, two detailed comparisons of AMC and CCNC retrieved by the MAS algorithm and the new method are shown. The new method and MAS retrievals of AMC are within the same order of magnitude with respect to the in-situ measurements of aerosol mass. However, the proposed method is closer to the in-situ measurements than the MODIS retrievals. The retrievals of CCNC are also within the same order of magnitude for both methods. The new method is applied to an actual MODIS retrieval and although no in-situ data is available to compare, it is shown that the proposed method yields more credible values than the MODIS retrievals. In addition, recent data available from the PRIDE (Puerto Rico Dust Experiment, July 2000) will be shown by comparing sunphotometer, MODIS and in-situ data.

Estimation of atmospheric columnar organic matter (OM) mass concentration from remote sensing measurements of aerosol spectral refractive indices

NASA Astrophysics Data System (ADS)

Zhang, Ying; Li, Zhengqiang; Sun, Yele; Lv, Yang; Xie, Yisong

2018-04-01

Aerosols have adverse effects on human health and air quality, changing Earth's energy balance and lead to climate change. The components of aerosol are important because of the different spectral characteristics. Based on the low hygroscopic and high scattering properties of organic matter (OM) in fine modal atmospheric aerosols, we develop an inversion algorithm using remote sensing to obtain aerosol components including black carbon (BC), organic matter (OM), ammonium nitrate-like (AN), dust-like (DU) components and aerosol water content (AW). In the algorithm, the microphysical characteristics (i.e. volume distribution and complex refractive index) of particulates are preliminarily separated to fine and coarse modes, and then aerosol components are retrieved using bimodal parameters. We execute the algorithm using remote sensing measurements of sun-sky radiometer at AERONET site (Beijing RADI) in a period from October of 2014 to January of 2015. The results show a reasonable distribution of aerosol components and a good fit for spectral feature calculations. The mean OM mass concentration in atmospheric column is account for 14.93% of the total and 56.34% of dry and fine-mode aerosol, being a fairly good correlation (R = 0.56) with the in situ observations near the surface layer.

Aerosol polarization effects on atmospheric correction and aerosol retrievals in ocean color remote sensing.

PubMed

Wang, Menghua

2006-12-10

The current ocean color data processing system for the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and the moderate resolution imaging spectroradiometer (MODIS) uses the Rayleigh lookup tables that were generated using the vector radiative transfer theory with inclusion of the polarization effects. The polarization effects, however, are not accounted for in the aerosol lookup tables for the ocean color data processing. I describe a study of the aerosol polarization effects on the atmospheric correction and aerosol retrieval algorithms in the ocean color remote sensing. Using an efficient method for the multiple vector radiative transfer computations, aerosol lookup tables that include polarization effects are generated. Simulations have been carried out to evaluate the aerosol polarization effects on the derived ocean color and aerosol products for all possible solar-sensor geometries and the various aerosol optical properties. Furthermore, the new aerosol lookup tables have been implemented in the SeaWiFS data processing system and extensively tested and evaluated with SeaWiFS regional and global measurements. Results show that in open oceans (maritime environment), the aerosol polarization effects on the ocean color and aerosol products are usually negligible, while there are some noticeable effects on the derived products in the coastal regions with nonmaritime aerosols.

High temporal resolution aerosol retrieval using Geostationary Ocean Color Imager: application and initial validation

NASA Astrophysics Data System (ADS)

Zhang, Yuhuan; Li, Zhengqiang; Zhang, Ying; Hou, Weizhen; Xu, Hua; Chen, Cheng; Ma, Yan

2014-01-01

The Geostationary Ocean Color Imager (GOCI) provides multispectral imagery of the East Asia region hourly from 9:00 to 16:00 local time (GMT+9) and collects multispectral imagery at eight spectral channels (412, 443, 490, 555, 660, 680, 745, and 865 nm) with a spatial resolution of 500 m. Thus, this technology brings significant advantages to high temporal resolution environmental monitoring. We present the retrieval of aerosol optical depth (AOD) in northern China based on GOCI data. Cross-calibration was performed against Moderate Resolution Imaging Spectrometer (MODIS) data in order to correct the land calibration bias of the GOCI sensor. AOD retrievals were then accomplished using a look-up table (LUT) strategy with assumptions of a quickly varying aerosol and a slowly varying surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of a series of observations in a short period of time, such as several days. The monitoring of hourly AOD variations was implemented, and the retrieved AOD agreed well with AErosol RObotic NETwork (AERONET) ground-based measurements with a good R2 of approximately 0.74 at validation sites at the cities of Beijing and Xianghe, although intercept bias may be high in specific cases. The comparisons with MODIS products also show a good agreement in AOD spatial distribution. This work suggests that GOCI imagery can provide high temporal resolution monitoring of atmospheric aerosols over land, which is of great interest in climate change studies and environmental monitoring.

Cape of Good Hope

Atmospheric Science Data Center

2013-04-16

... will misregister because of parallax and therefore the radiance vs. angle should not be smooth. But this algorithm fails for ... product by removing ozone absorption, clear atmosphere (Rayleigh) scattering, and scattering from the retrieved aerosol. These data ...

GOME-2 Tropospheric Ozone Profile Retrievals from Joint UV/Visible Measurement

NASA Astrophysics Data System (ADS)

Liu, X.; Zoogman, P.; Chance, K.; Cai, Z.; Nowlan, C. R.; Huang, G.; Gonzalez Abad, G.

2016-12-01

It has been shown from sensitivity studies that adding visible measurements in the Chappuis ozone band to UV measurements in the Hartley/Huggins ozone bands can significantly enhance retrieval sensitivity to lower tropospheric ozone from backscattered solar radiances due to deeper photon penetration in the visible to the surface than in the ultraviolet. The first NASA EVI (Earth Venture Instrument) TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument is being developed to measure backscattered solar radiation in two channels ( 290-490 and 540-740 nm) and make atmospheric pollution measurements over North America from the Geostationary orbit. However, this retrieval enhancement has yet to be demonstrated from existing measurements due to the weak ozone absorption in the visible and strong interferences from surface reflectance and aerosols and the requirement of accurate radiometric calibration across different spectral channels. We present GOME-2 retrievals from joint UV/visible measurements using the SAO ozone profile retrieval algorithm, to directly explore the retrieval improvement in lower tropospheric ozone from additional visible measurements. To reduce the retrieval interference from surface reflectance, we add characterization of surface spectral reflectance in the visible based on combining EOFs (Empirical Orthogonal Functions) derived from ASTER and other surface reflectance spectra with MODIS BRDF climatology into the ozone profile algorithm. The impacts of various types of aerosols and surface BRDF on the retrievals will be investigated. In addition, we will also perform empirical radiometric calibration of the GOME-2 data based on radiative transfer simulations. We will evaluate the retrieval improvement of joint UV/visible retrieval over the UV retrieval based on fitting quality and validation against ozonesonde observations.

Towards PACE Atmospheric Correction, Aerosol and Cloud Products: Making Use of Expanded Spectral, Angular and Polarimetric Information.

NASA Astrophysics Data System (ADS)

Remer, L. A.; Boss, E.; Ahmad, Z.; Cairns, B.; Chowdhary, J.; Coddington, O.; Davis, A. B.; Dierssen, H. M.; Diner, D. J.; Franz, B. A.; Frouin, R.; Gao, B. C.; Garay, M. J.; Heidinger, A.; Ibrahim, A.; Kalashnikova, O. V.; Knobelspiesse, K. D.; Levy, R. C.; Omar, A. H.; Meyer, K.; Platnick, S. E.; Seidel, F. C.; van Diedenhoven, B.; Werdell, J.; Xu, F.; Zhai, P.; Zhang, Z.

2017-12-01

NASA's Science Team for the Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission is concluding three years of study exploring the science potential of expanded spectral, angular and polarization capability for space-based retrievals of water leaving radiance, aerosols and clouds. The work anticipates future development of retrievals to be applied to the PACE Ocean Color Instrument (OCI) and/or possibly a PACE Multi-Angle Polarimeter (MAP). In this presentation we will report on the Science Team's accomplishments associated with the atmosphere (significant efforts are also directed by the ST towards the ocean). Included in the presentation will be sensitivity studies that explore new OCI capabilities for aerosol and cloud layer height, aerosol absorption characterization, cloud property retrievals, and how we intend to move from heritage atmospheric correction algorithms to make use of and adjust to OCI's hyperspectral and UV wavelengths. We will then address how capabilities will improve with the PACE MAP, how these capabilities from both OCI and MAP correspond to specific societal benefits from the PACE mission, and what is still needed to close the gaps in our understanding before the PACE mission can realize its full potential.

Combined Retrievals of Boreal Forest Fire Aerosol Properties with a Polarimeter and Lidar

NASA Technical Reports Server (NTRS)

Knobelspiesse, K.; Cairns, B.; Ottaviani, M.; Ferrare, R.; Haire, J.; Hostetler, C.; Obland, M.; Rogers, R.; Redemann, J.; Shinozuka, Y.;

Evaluation of MODIS aerosol optical depth for semi­-arid environments in complex terrain

NASA Astrophysics Data System (ADS)

Holmes, H.; Loria Salazar, S. M.; Panorska, A. K.; Arnott, W. P.; Barnard, J.

2015-12-01

The use of satellite remote sensing to estimate spatially resolved ground level air pollutant concentrations is increasing due to advancements in remote sensing technology and the limited number of surface observations. Satellite retrievals provide global, spatiotemporal air quality information and are used to track plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Ground level PM2.5 concentrations can be estimated using columnar aerosol optical depth (AOD) from MODIS, where the satellite retrieval serves as a spatial surrogate to simulate surface PM2.5 gradients. The spatial statistical models and MODIS AOD retrieval algorithms have been evaluated for the dark, vegetated eastern US, while the semi-arid western US continues to be an understudied region with associated complexity due to heterogeneous emissions, smoke from wildfires, and complex terrain. The objective of this work is to evaluate the uncertainty of MODIS AOD retrievals by comparing with columnar AOD and surface PM2.5 measurements from AERONET and EPA networks. Data is analyzed from multiple stations in California and Nevada for three years where four major wildfires occurred. Results indicate that MODIS retrievals fail to estimate column-integrated aerosol pollution in the summer months. This is further investigated by quantifying the statistical relationships between MODIS AOD, AERONET AOD, and surface PM2.5 concentrations. Data analysis indicates that the distribution of MODIS AOD is significantly (p<0.05) different than AERONET AOD. Further, using the results of distributional and association analysis the impacts of MODIS AOD uncertainties on the spatial gradients are evaluated. Additionally, the relationships between these uncertainties and physical parameters in the retrieval algorithm (e.g., surface reflectance, Ångström Extinction Exponent) are discussed.

Development and Applications of a New, High-Resolution, Operational MISR Aerosol Product

NASA Astrophysics Data System (ADS)

Garay, M. J.; Diner, D. J.; Kalashnikova, O.

2014-12-01

Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been providing aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution. Capitalizing on the capabilities provided by multi-angle viewing, the operational MISR algorithm performs well, with about 75% of MISR AOD retrievals falling within 0.05 or 20% × AOD of the paired validation data from the ground-based Aerosol Robotic Network (AERONET), and is able to distinguish aerosol particles by size and sphericity, over both land and water. These attributes enable a variety of applications, including aerosol transport model validation and global air quality assessment. Motivated by the adverse impacts of aerosols on human health at the local level, and taking advantage of computational speed advances that have occurred since the launch of Terra, we have implemented an operational MISR aerosol product with 4.4 km spatial resolution that maintains, and sometimes improves upon, the quality of the 17.6 km resolution product. We will describe the performance of this product relative to the heritage 17.6 km product, the global AERONET validation network, and high spatial density AERONET-DRAGON sites. Other changes that simplify product content, and make working with the data much easier for users, will also be discussed. Examples of how the new product demonstrates finer spatial variability of aerosol fields than previously retrieved, and ways this new dataset can be used for studies of local aerosol effects, will be shown.

A Laboratory Experiment for the Statistical Evaluation of Aerosol Retrieval (STEAR) Algorithms

NASA Astrophysics Data System (ADS)

Schuster, G. L.; Espinosa, R.; Ziemba, L. D.; Beyersdorf, A. J.; Rocha Lima, A.; Anderson, B. E.; Martins, J. V.; Dubovik, O.; Ducos, F.; Fuertes, D.; Lapyonok, T.; Shook, M.; Derimian, Y.; Moore, R.

2016-12-01

We have developed a method for validating Aerosol Robotic Network (AERONET) retrieval algorithms by mimicking atmospheric extinction and radiance measurements in a laboratory experiment. This enables radiometric retrievals that utilize the same sampling volumes, relative humidities, and particle size ranges as observed by other in situ instrumentation in the experiment. We utilize three Cavity Attenuated Phase Shift (CAPS) monitors for extinction and UMBC's three-wavelength Polarized Imaging Nephelometer (PI-Neph) for angular scattering measurements. We subsample the PI-Neph radiance measurements to angles that correspond to AERONET almucantar scans, with solar zenith angles ranging from 50 to 77 degrees. These measurements are then used as input to the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm, which retrieves size distributions, complex refractive indices, single-scatter albedos (SSA), and lidar ratios for the in situ samples. We obtained retrievals with residuals R < 10% for 100 samples. The samples that we tested include Arizona Test Dust, Arginotec NX, Senegal clay, Israel clay, montmorillonite, hematite, goethite, volcanic ash, ammonium nitrate, ammonium sulfate, and fullerene soot. Samples were alternately dried or humidified, and size distributions were limited to diameters of 1.0 or 2.5 um by using a cyclone. The SSA at 532 nm for these samples ranged from 0.59 to 1.00 when computed with CAPS extinction and PSAP absorption measurements. The GRASP retrieval provided SSAs that are highly correlated with the in situ SSAs, and the correlation coefficients ranged from 0.955 to 0.976, depending upon the simulated solar zenith angle. The GRASP SSAs exhibited an average absolute bias of +0.023 +/-0.01 with respect to the extinction and absorption measurements for the entire dataset. Although our apparatus was not capable of measuring backscatter lidar ratio, we did measure bistatic lidar ratios at a scattering angle of 173 deg. The GRASP bistatic lidar ratios had correlations of 0.488 to 0.735 (depending upon simulated SZA) with respect to in situ measurements, positive relative biases of 6-10%, and average absolute biases of 4.0-6.6 sr. We also compared the GRASP size distributions to aerodynamic particle size measurements.

Retrieval of Aerosol Microphysical Properties Based on the Optimal Estimation Method: Information Content Analysis for Satellite Polarimetric Remote Sensing Measurements

NASA Astrophysics Data System (ADS)

Hou, W. Z.; Li, Z. Q.; Zheng, F. X.; Qie, L. L.

2018-04-01

This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM) with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.

Cloud and Aerosol Retrieval for the 2001 GLAS Satellite Lidar Mission

NASA Technical Reports Server (NTRS)

Hart, William D.; Palm, Stephen P.; Spinhirne, James D.

2000-01-01

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.

Assessment of OMI Near-UV Aerosol Optical Depth over Land

NASA Technical Reports Server (NTRS)

Ahn, Changwoo; Torres, Omar; Jethva, Hiren

2014-01-01

This is the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the near-UV observations by the Ozone Monitoring Instrument (OMI) onboard the Aura satellite. The OMI-retrieved AOD by the ultraviolet (UV) aerosol algorithm (OMAERUV version 1.4.2) was evaluated using collocated Aerosol Robotic Network (AERONET) level 2.0 direct Sun AOD measurements over 8 years (2005-2012). A time series analysis of collocated satellite and ground-based AOD observations over 8 years shows no discernible drift in OMI's calibration. A rigorous validation analysis over 4 years (2005-2008) was carried out at 44 globally distributed AERONET land sites. The chosen locations are representative of major aerosol types such as smoke from biomass burning or wildfires, desert mineral dust, and urban/industrial pollutants. Correlation coefficient (p) values of 0.75 or better were obtained at 50 percent of the sites with about 33 percent of the sites in the analysis reporting regression line slope values larger than 0.70 but always less than unity. The combined AERONET-OMAERUV analysis of the 44 sites yielded a p of 0.81, slope of 0.79, Y intercept of 0.10, and 65 percent OMAERUV AOD falling within the expected uncertainty range (largest of 30 percent or 0.1) at 440 nanometers. The most accurate OMAERUV retrievals are reported over northern Africa locations where the predominant aerosol type is desert dust and cloud presence is less frequent. Reliable retrievals were documented at many sites characterized by urban-type aerosols with low to moderate AOD values, concentrated in the boundary layer. These results confirm that the near-ultraviolet observations are sensitive to the entire aerosol column. A simultaneous comparison of OMAERUV, Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue, and Multiangle Imaging Spectroradiometer (MISR) AOD retrievals to AERONET measurements was also carried out to evaluate the OMAERUV accuracy in relation to those of the standard aerosol satellite products. The outcome of the comparison indicates that OMAERUV, MODIS Deep Blue, and MISR retrieval accuracies in arid and semiarid environments are statistically comparable.

Validation of High-Resolution MAIAC Aerosol Product over South America

NASA Technical Reports Server (NTRS)

Martins, V. S.; Lyapustin, A.; de Carvalho, L. A. S.; Barbosa, C. C. F.; Novo, E. M. L. M.

2017-01-01

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD(sub 550) was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (R(sub Terra):0.956 and R(sub Aqua):0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 (approximately 66%) of retrievals are within the expected error (EE = +/-(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset approximately 0.006). Additionally, MAIAC CWV presents quantitative information with R approximatley 0.97 and more than 70% of retrievals within error (+/-15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Development of the atmospheric correction algorithm for the next generation geostationary ocean color sensor data

NASA Astrophysics Data System (ADS)

Lee, Kwon-Ho; Kim, Wonkook

2017-04-01

The geostationary ocean color imager-II (GOCI-II), designed to be focused on the ocean environmental monitoring with better spatial (250m for local and 1km for full disk) and spectral resolution (13 bands) then the current operational mission of the GOCI-I. GOCI-II will be launched in 2018. This study presents currently developing algorithm for atmospheric correction and retrieval of surface reflectance over land to be optimized with the sensor's characteristics. We first derived the top-of-atmosphere radiances as the proxy data derived from the parameterized radiative transfer code in the 13 bands of GOCI-II. Based on the proxy data, the algorithm has been made with cloud masking, gas absorption correction, aerosol inversion, computation of aerosol extinction correction. The retrieved surface reflectances are evaluated by the MODIS level 2 surface reflectance products (MOD09). For the initial test period, the algorithm gave error of within 0.05 compared to MOD09. Further work will be progressed to fully implement the GOCI-II Ground Segment system (G2GS) algorithm development environment. These atmospherically corrected surface reflectance product will be the standard GOCI-II product after launch.

Retrieval Algorithms for the Halogen Occultation Experiment

NASA Technical Reports Server (NTRS)

Thompson, Robert E.; Gordley, Larry L.

2009-01-01

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.

New Approach to Monitor Transboundary Particulate Pollution over Northeast Asia

NASA Technical Reports Server (NTRS)

Park, M. E.; Song, C. H.; Park, R. S.; Lee, Jaehwa; Kim, J.; Lee, S.; Woo, J. H.; Carmichael, G. R.; Eck, Thomas F.; Holben, Brent N.;

New approach to monitor transboundary particulate pollution over Northeast Asia

NASA Astrophysics Data System (ADS)

Park, M. E.; Song, C. H.; Park, R. S.; Lee, J.; Kim, J.; Lee, S.; Woo, J.-H.; Carmichael, G. R.; Eck, T. F.; Holben, B. N.; Lee, S.-S.; Song, C. K.; Hong, Y. D.

2014-01-01

A new approach to more accurately monitor and evaluate transboundary particulate matter (PM) pollution is introduced based on aerosol optical products from Korea's Geostationary Ocean Color Imager (GOCI). The area studied is Northeast Asia (including eastern parts of China, the Korean peninsula and Japan), where GOCI has been monitoring since June 2010. The hourly multi-spectral aerosol optical data that were retrieved from GOCI sensor onboard geostationary satellite COMS (Communication, Ocean, and Meteorology Satellite) through the Yonsei aerosol retrieval algorithm were first presented and used in this study. The GOCI-retrieved aerosol optical data are integrated with estimated aerosol distributions from US EPA Models-3/CMAQ (Community Multi-scale Air Quality) v4.5.1 model simulations via data assimilation technique, thereby making the aerosol data spatially continuous and available even for cloud contamination cells. The assimilated aerosol optical data are utilized to provide quantitative estimates of transboundary PM pollution from China to the Korean peninsula and Japan. For the period of 1 April to 31 May, 2011 this analysis yields estimates that AOD as a proxy for PM2.5 or PM10 during long-range transport events increased by 117-265% compared to background average AOD (aerosol optical depth) at the four AERONET sites in Korea, and average AOD increases of 121% were found when averaged over the entire Korean peninsula. This paper demonstrates that the use of multi-spectral AOD retrievals from geostationary satellites can improve estimates of transboundary PM pollution. Such data will become more widely available later this decade when new sensors such as the GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI-2 are scheduled to be launched.

Automatic remote sensing detection of the convective boundary layer structure over flat and complex terrain using the novel PathfinderTURB algorithm

NASA Astrophysics Data System (ADS)

Poltera, Yann; Martucci, Giovanni; Hervo, Maxime; Haefele, Alexander; Emmenegger, Lukas; Brunner, Dominik; Henne, stephan

2016-04-01

We have developed, applied and validated a novel algorithm called PathfinderTURB for the automatic and real-time detection of the vertical structure of the planetary boundary layer. The algorithm has been applied to a year of data measured by the automatic LIDAR CHM15K at two sites in Switzerland: the rural site of Payerne (MeteoSwiss station, 491 m, asl), and the alpine site of Kleine Scheidegg (KSE, 2061 m, asl). PathfinderTURB is a gradient-based layer detection algorithm, which in addition makes use of the atmospheric variability to detect the turbulent transition zone that separates two low-turbulence regions, one characterized by homogeneous mixing (convective layer) and one above characterized by free tropospheric conditions. The PathfinderTURB retrieval of the vertical structure of the Local (5-10 km, horizontal scale) Convective Boundary Layer (LCBL) has been validated at Payerne using two established reference methods. The first reference consists of four independent human-expert manual detections of the LCBL height over the year 2014. The second reference consists of the values of LCBL height calculated using the bulk Richardson number method based on co-located radio sounding data for the same year 2014. Based on the excellent agreement with the two reference methods at Payerne, we decided to apply PathfinderTURB to the complex-terrain conditions at KSE during 2014. The LCBL height retrievals are obtained by tilting the CHM15K at an angle of 19 degrees with respect to the horizontal and aiming directly at the Sphinx Observatory (3580 m, asl) on the Jungfraujoch. This setup of the CHM15K and the processing of the data done by the PathfinderTURB allows to disentangle the long-transport from the local origin of gases and particles measured by the in-situ instrumentation at the Sphinx Observatory. The KSE measurements showed that the relation amongst the LCBL height, the aerosol layers above the LCBL top and the gas + particle concentration is all but trivial. Retrieving the structure of the LCBL along the line of sight connecting KSE to the Sphinx Observatory allows to monitor when the LCBL top reaches the altitude of the in-situ instrumentation at the Sphinx and to relate the measured gas + particle concentration with the locally-produced aerosols. On the other hand, when the LCBL top is lower than the Sphinx altitude, the measured concentration of gas + particle at the Sphinx is either due to long transport of aerosols (>100 km) or to the residual aerosol layer reaching the Sphinx's height or to non-local (> 5 km and <100 km) CBL aerosols advected at the Sphinx's height. Except when the aerosol layer is decoupled from the LCBL underneath, for all the other cases the CHM15K sees the probed layer as a continuous (not necessarily well-mixed) aerosol layer starting at the KSE surface. The depth of this continuous layer has been retrieved by the PathfinderTURB and related with the black carbon absorption coefficient measured at Sphinx. The result of the comparison shows clearly that the depth of the layer is well correlated with the absorption coefficient measured at the Sphinx. This is an important result that allows not only to retrieve real-time CBL heights in an automatic and trustworthy way, but also to adapt the retrievals to complex-terrain and complex-atmospheric conditions with customized tilted instrument settings.

Determination of nocturnal aerosol properties from a combination of lunar photometer and lidar observations

NASA Astrophysics Data System (ADS)

Li, Donghui; Li, Zhengqiang; Lv, Yang; Zhang, Ying; Li, Kaitao; Xu, Hua

2015-10-01

Aerosol plays a key role in the assessment of global climate change and environmental health, while observation is one of important way to deepen the understanding of aerosol properties. In this study, the newly instrument - lunar photometer is used to measure moonlight and nocturnal column aerosol optical depth (AOD, τ) is retrieved. The AOD algorithm is test and verified with sun photometer both in high and low aerosol loading. Ångström exponent (α) and fine/coarse mode AOD (τf, τc) 1 is derived from spectral AOD. The column aerosol properties (τ, α, τf, τc) inferred from the lunar photometer is analyzed based on two month measurement in Beijing. Micro-pulse lidar has advantages in retrieval of aerosol vertical distribution, especially in night. However, the typical solution of lidar equation needs lidar ratio(ratio of aerosol backscatter and extinction coefficient) assumed in advance(Fernald method), or constrained by AOD2. Yet lidar ratio is varied with aerosol type and not easy to fixed, and AOD is used of daylight measurement, which is not authentic when aerosol loading is different from day and night. In this paper, the nocturnal AOD measurement from lunar photometer combined with mie scattering lidar observations to inverse aerosol extinction coefficient(σ) profile in Beijing is discussed.

Comparisons of Satellite Retrieval of Aerosol Properties from SeaWiFS and TOMS to the AERONET Measurements during ACE-Asia

NASA Technical Reports Server (NTRS)

Hsu, Christina N.; Tsay, Si-Chee; Herman, R.; Holben, Brent; Bhartia, P. K. (Technical Monitor)

2002-01-01

The primary goal of the ACE (Aerosol Characterization Experiment)-Asia mission is to increase our understanding of how atmospheric aerosol particles over the Asian-Pacific region affect the Earth climate system. In support of the day-to-day flight planning of ACE-Asia, we built a near real-time system to provide satellite data from the polar-orbiting instruments Earth Probe TOMS (Total Ozone Mapping Spectrometer) (in the form of absorbing aerosol index) and SeaWiFS (Sea-Viewing Wide Field-of-View Sensor) (in the form of aerosol optical thickness and Angstrom exponent). The results were available via web access. These satellite data provide a 'big picture' of aerosol distribution in the region, which is complementary to the ground based measurements. In this paper, we will briefly discuss the algorithms used to generate these data. The retrieved aerosol optical thickness and Angstrom exponent from SeaWiFS will be compared with those obtained from various AERONET (Aerosol Robotic Network) sites over the Asian-Pacific region. The TOMS aerosol index will also be compared with AERONET aerosol optical thickness over different aerosol conditions. Finally, we will discuss the climate implication of our studies using the combined satellite and AERONET observations.

MISR Global Aerosol Product Assessment by Comparison with AERONET

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Gaitley, Barbara J.; Garay, Michael J.; Diner, David J.; Eck, Thomas F.; Smirnov, Alexander; Holben, Brent N.

2010-01-01

A statistical approach is used to assess the quality of the MISR Version 22 (V22) aerosol products. Aerosol Optical Depth (AOD) retrieval results are improved relative to the early post- launch values reported by Kahn et al. [2005a], varying with particle type category. Overall, about 70% to 75% of MISR AOD retrievals fall within 0.05 or 20% AOD of the paired validation data, and about 50% to 55% are within 0.03 or 10% AOD, except at sites where dust, or mixed dust and smoke, are commonly found. Retrieved particle microphysical properties amount to categorical values, such as three groupings in size: "small," "medium," and "large." For particle size, ground-based AERONET sun photometer Angstrom Exponents are used to assess statistically the corresponding MISR values, which are interpreted in terms of retrieved size categories. Coincident Single-Scattering Albedo (SSA) and fraction AOD spherical data are too limited for statistical validation. V22 distinguishes two or three size bins, depending on aerosol type, and about two bins in SSA (absorbing vs. non-absorbing), as well as spherical vs. non-spherical particles, under good retrieval conditions. Particle type sensitivity varies considerably with conditions, and is diminished for mid-visible AOD below about 0.15 or 0.2. Based on these results, specific algorithm upgrades are proposed, and are being investigated by the MISR team for possible implementation in future versions of the product.

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; Colarco, Peter R.; Hlavka, Dennis; Levy, Robert C.; Vaughan, Mark A.; daSilva, Arlindo

2007-01-01

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Validation of aerosol optical depth uncertainties within the ESA Climate Change Initiative

NASA Astrophysics Data System (ADS)

Stebel, Kerstin; Povey, Adam; Popp, Thomas; Capelle, Virginie; Clarisse, Lieven; Heckel, Andreas; Kinne, Stefan; Klueser, Lars; Kolmonen, Pekka; de Leeuw, Gerrit; North, Peter R. J.; Pinnock, Simon; Sogacheva, Larisa; Thomas, Gareth; Vandenbussche, Sophie

2017-04-01

Uncertainty is a vital component of any climate data record as it provides the context with which to understand the quality of the data and compare it to other measurements. Therefore, pixel-level uncertainties are provided for all aerosol products that have been developed in the framework of the Aerosol_cci project within ESA's Climate Change Initiative (CCI). Validation of these estimated uncertainties is necessary to demonstrate that they provide a useful representation of the distribution of error. We propose a technique for the statistical validation of AOD (aerosol optical depth) uncertainty by comparison to high-quality ground-based observations and present results for ATSR (Along Track Scanning Radiometer) and IASI (Infrared Atmospheric Sounding Interferometer) data records. AOD at 0.55 µm and its uncertainty was calculated with three AOD retrieval algorithms using data from the ATSR instruments (ATSR-2 (1995-2002) and AATSR (2002-2012)). Pixel-level uncertainties were calculated through error propagation (ADV/ASV, ORAC algorithms) or parameterization of the error's dependence on the geophysical retrieval conditions (SU algorithm). Level 2 data are given as super-pixels of 10 km x 10 km. As validation data, we use direct-sun observations of AOD from the AERONET (AErosol RObotic NETwork) and MAN (Maritime Aerosol Network) sun-photometer networks, which are substantially more accurate than satellite retrievals. Neglecting the uncertainty in AERONET observations and possible issues with their ability to represent a satellite pixel area, the error in the retrieval can be approximated by the difference between the satellite and AERONET retrievals (herein referred to as "error"). To evaluate how well the pixel-level uncertainty represents the observed distribution of error, we look at the distribution of the ratio D between the "error" and the ATSR uncertainty. If uncertainties are well represented, D should be normally distributed and 68.3% of values should fall within the range [-1, +1]. A non-zero mean of D indicates the presence of residual systematic errors. If the fraction is smaller than 68%, uncertainties are underestimated; if it is larger, uncertainties are overestimated. For the three ATSR algorithms, we provide statistics and an evaluation at a global scale (separately for land and ocean/coastal regions), for high/low AOD regimes, and seasonal and regional statistics (e.g. Europe, N-Africa, East-Asia, N-America). We assess the long-term stability of the uncertainty estimates over the 17-year time series, and the consistency between ATSR-2 and AATSR results (during their period of overlap). Furthermore, we exploit the possibility to adapt the uncertainty validation concept to the IASI datasets. Ten-year data records (2007-2016) of dust AOD have been generated with four algorithms using IASI observations over the greater Sahara region [80°W - 120°E, 0°N - 40°N]. For validation, the coarse mode AOD at 0.55 μm from the AERONET direct-sun spectral deconvolution algorithm (SDA) product may be used as a proxy for desert dust. The uncertainty validation results for IASI are still tentative, as larger IASI pixel sizes and the conversion of the IASI AOD values from infrared to visible wavelengths for comparison to ground-based observations introduces large uncertainties.

The Dynamics of Fine Mode Aerosol Optical Properties in South Korea from AERONET and Aircraft Observations with a Focus on Cases with Large Cloud Fraction and/or Fog During KORUS-AQ

NASA Astrophysics Data System (ADS)

Eck, T. F.; Holben, B. N.; Kim, J.; Choi, M.; Giles, D. M.; Schafer, J.; Smirnov, A.; Slutsker, I.; Sinyuk, A.; Sorokin, M. G.; Kraft, J.; Beyersdorf, A. J.; Anderson, B. E.; Thornhill, K. L., II; Crawford, J. H.

2017-12-01

The focus of our investigation is of major fine mode aerosol pollution events in South Korea, particularly when cloud fraction is high. This work includes the analysis of AERONET data utilizing the Spectral Deconvolution Algorithm to enable detection of fine mode aerosol optical depth (AOD) near to clouds. Additionally we analyze the newly developed AERONET V3 data sets that have significant changes to cloud screening algorithms. Comparisons of aerosol optical depth are made between AERONET Versions 2 and 3 for both long-term climatology data and for specific 2016 cases, especially in May and June 2016 during the KORUS-AQ field campaign. In general the Version 3 cloud screening allows many more fine mode AOD observations to reach Level 2 when cloud amount is high, as compared to Version 2, thereby enabling more thorough analysis of these types of cases. Particular case studies include May 25-26, 2016 when cloud fraction was very high over much of the peninsula, associated with a frontal passage and advection of pollution from China. Another interesting case is June 9, 2016 when there was fog over the West Sea, and this seems to have affected aerosol properties well downwind over the Korean peninsula. Both of these days had KORUS-AQ research aircraft flights that provided observations of aerosol absorption, particle size distributions and vertical profiles of extinction. AERONET retrievals and aircraft in situ measurements both showed high single scattering albedo (weak absorption) on these cloudy days. We also investigate the relationship between aerosol fine mode radius and AOD and the relationship between aerosol single scattering albedo and fine mode particle radius from the AERONET almucantar retrievals for the interval of April through June 2016 for 17 AERONET sites in South Korea. Strongly increasing fine mode radius (leading to greater scattering efficiency) as fine mode AOD increased is one factor contributing to a trend of increasing single scattering albedo as fine AOD increased. Additionally, the new AERONET Hybrid sky radiance scan retrievals that allow for inversions to be made at much smaller solar zenith angles are analyzed and compared to almucantar retrievals.

Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results

NASA Astrophysics Data System (ADS)

Eichmann, Kai-Uwe; Lelli, Luca; von Savigny, Christian; Sembhi, Harjinder; Burrows, John P.

2016-03-01

Cloud top heights (CTHs) are retrieved for the period 1 January 2003 to 7 April 2012 using height-resolved limb spectra measured with the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on board ENVISAT (ENVIronmental SATellite). In this study, we present the retrieval code SCODA (SCIAMACHY cloud detection algorithm) based on a colour index method and test the accuracy of the retrieved CTHs in comparison to other methods. Sensitivity studies using the radiative transfer model SCIATRAN show that the method is capable of detecting cloud tops down to about 5 km and very thin cirrus clouds up to the tropopause. Volcanic particles can be detected that occasionally reach the lower stratosphere. Upper tropospheric ice clouds are observable for a nadir cloud optical thickness (COT) ≥ 0.01, which is in the subvisual range. This detection sensitivity decreases towards the lowermost troposphere. The COT detection limit for a water cloud top height of 5 km is roughly 0.1. This value is much lower than thresholds reported for passive cloud detection methods in nadir-viewing direction. Low clouds at 2 to 3 km can only be retrieved under very clean atmospheric conditions, as light scattering of aerosol particles interferes with the cloud particle scattering. We compare co-located SCIAMACHY limb and nadir cloud parameters that are retrieved with the Semi-Analytical CloUd Retrieval Algorithm (SACURA). Only opaque clouds (τN,c > 5) are detected with the nadir passive retrieval technique in the UV-visible and infrared wavelength ranges. Thus, due to the frequent occurrence of thin clouds and subvisual cirrus clouds in the tropics, larger CTH deviations are detected between both viewing geometries. Zonal mean CTH differences can be as high as 4 km in the tropics. The agreement in global cloud fields is sufficiently good. However, the land-sea contrast, as seen in nadir cloud occurrence frequency distributions, is not observed in limb geometry. Co-located cloud top height measurements of the limb-viewing Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on ENVISAT are compared for the period from January 2008 to March 2012. The global CTH agreement of about 1 km is observed, which is smaller than the vertical field of view of both instruments. Lower stratospheric aerosols from volcanic eruptions occasionally interfere with the cloud retrieval and inhibit the detection of tropospheric clouds. The aerosol impact on cloud retrievals was studied for the volcanoes Kasatochi (August 2008), Sarychev Peak (June 2009), and Nabro (June 2011). Long-lasting aerosol scattering is detected after these events in the Northern Hemisphere for heights above 12.5 km in tropical and polar latitudes. Aerosol top heights up to about 22 km are found in 2009 and the enhanced lower stratospheric aerosol layer persisted for about 7 months. In August 2009 about 82 % of the lower stratosphere between 30 and 70° N was filled with scattering particles and nearly 50 % in October 2008.

Inversion of multiwavelength Raman lidar data for retrieval of bimodal aerosol size distribution

NASA Astrophysics Data System (ADS)

Veselovskii, Igor; Kolgotin, Alexei; Griaznov, Vadim; Müller, Detlef; Franke, Kathleen; Whiteman, David N.

2004-02-01

We report on the feasibility of deriving microphysical parameters of bimodal particle size distributions from Mie-Raman lidar based on a triple Nd:YAG laser. Such an instrument provides backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The inversion method employed is Tikhonov's inversion with regularization. Special attention has been paid to extend the particle size range for which this inversion scheme works to ~10 μm, which makes this algorithm applicable to large particles, e.g., investigations concerning the hygroscopic growth of aerosols. Simulations showed that surface area, volume concentration, and effective radius are derived to an accuracy of ~50% for a variety of bimodal particle size distributions. For particle size distributions with an effective radius of <1 μm the real part of the complex refractive index was retrieved to an accuracy of +/-0.05, the imaginary part was retrieved to 50% uncertainty. Simulations dealing with a mode-dependent complex refractive index showed that an average complex refractive index is derived that lies between the values for the two individual modes. Thus it becomes possible to investigate external mixtures of particle size distributions, which, for example, might be present along continental rims along which anthropogenic pollution mixes with marine aerosols. Measurement cases obtained from the Institute for Tropospheric Research six-wavelength aerosol lidar observations during the Indian Ocean Experiment were used to test the capabilities of the algorithm for experimental data sets. A benchmark test was attempted for the case representing anthropogenic aerosols between a broken cloud deck. A strong contribution of particle volume in the coarse mode of the particle size distribution was found.

Inversion of multiwavelength Raman lidar data for retrieval of bimodal aerosol size distribution.

PubMed

Veselovskii, Igor; Kolgotin, Alexei; Griaznov, Vadim; Müller, Detlef; Franke, Kathleen; Whiteman, David N

2004-02-10

We report on the feasibility of deriving microphysical parameters of bimodal particle size distributions from Mie-Raman lidar based on a triple Nd:YAG laser. Such an instrument provides backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The inversion method employed is Tikhonov's inversion with regularization. Special attention has been paid to extend the particle size range for which this inversion scheme works to approximately 10 microm, which makes this algorithm applicable to large particles, e.g., investigations concerning the hygroscopic growth of aerosols. Simulations showed that surface area, volume concentration, and effective radius are derived to an accuracy of approximately 50% for a variety of bimodal particle size distributions. For particle size distributions with an effective radius of < 1 microm the real part of the complex refractive index was retrieved to an accuracy of +/- 0.05, the imaginary part was retrieved to 50% uncertainty. Simulations dealing with a mode-dependent complex refractive index showed that an average complex refractive index is derived that lies between the values for the two individual modes. Thus it becomes possible to investigate external mixtures of particle size distributions, which, for example, might be present along continental rims along which anthropogenic pollution mixes with marine aerosols. Measurement cases obtained from the Institute for Tropospheric Research six-wavelength aerosol lidar observations during the Indian Ocean Experiment were used to test the capabilities of the algorithm for experimental data sets. A benchmark test was attempted for the case representing anthropogenic aerosols between a broken cloud deck. A strong contribution of particle volume in the coarse mode of the particle size distribution was found.

First Results of AirMSPI Imaging Polarimetry at ORACLES 2016: Aerosol and Water Cloud Retrievals

NASA Astrophysics Data System (ADS)

van Harten, G.; Xu, F.; Diner, D. J.; Rheingans, B. E.; Tosca, M.; Seidel, F.; Bull, M. A.; Tkatcheva, I. N.; McDuffie, J. L.; Garay, M. J.; Jovanovic, V. M.; Cairns, B.; Alexandrov, M. D.; Hostetler, C. A.; Ferrare, R. A.; Burton, S. P.

2017-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) is a remote sensing instrument for the characterization of atmospheric aerosols and clouds. We will report on the successful deployment and resulting data products of AirMSPI in the 2016 field campaign as part of NASA's ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES). The goal of this five-year investigation is to study the impacts of African biomass burning aerosols on the radiative properties of the subtropical stratocumulus cloud deck over the southeast Atlantic Ocean. On board the NASA ER-2 high-altitude aircraft, AirMSPI collected over 4000 high-resolution images on 16 days. The observations are performed in two different modes: step-and-stare mode, in which a 10x10 km target is observed from 9 view angles at 10 m resolution, and sweep mode, where a 80-100 km along-track by 10-25 km across-track target is observed with continuously changing view angle between ±67° at 25 m resolution. This Level 1B2 calibrated and georectified imagery is publically available at the NASA Langley Atmospheric Science Data Center (ASDC)*. We will then describe the Level 2 water cloud products that will be made publically available, viz. optical depth and droplet size distribution, which are retrieved using a polarimetric algorithm. Finally, we will present the results of a recently developed research algorithm for the simultaneous retrieval of these cloud properties and above-cloud aerosols, and validations using collocated High Spectral Resolution Lidar-2 (HSRL-2) and Research Scanning Polarimeter (RSP) products. * https://eosweb.larc.nasa.gov/project/airmspi/airmspi_table

Advantages and Challenges in using Multi-Sensor Data for Studying Aerosols from Space

NASA Astrophysics Data System (ADS)

Leptoukh, Gregory

We are living now in the golden era of numerous sensors measuring aerosols from space, e.g., MODIS, MISR, MERIS, OMI, POLDER, etc. Data from multiple sensors provide a more complete coverage of physical phenomena than data from a single sensor. These sensors are rather different from each other, are sensitive to various parts of the atmosphere, use different aerosol models and treat surface differently when retrieving aerosols. However, they complement each other thus providing more information about spatial, vertical and temporal distribution of aerosols. In addition to differences in instrumentation, retrieval algorithms and calibration, there are quite substantial differences in processing algorithms from Level 0 up to Level 3 and 4. Some of these differences in processing steps, at times not well documented and not widely known by users, can lead to quite significant differences in final products. Without documenting all the steps leading to the final product, data users will not trust the data and/or may use data incorrectly. Data by themselves without quality assessment and provenance are not sufficient to make accurate scientific conclusions. In this paper we provide examples of striking differences between aerosol optical depth data from MODIS, MISR, and MERIS that can be attributed to differences in a certain threshold, aggregation methods, and the dataday definition. We talk about challenges in developing processing provenance. Also, we address issues of harmonization of data, quality and provenance that is needed to guide the multi-sensor data usage and avoid apples-to-oranges comparison and fusion.

Retrieval, Inter-Comparison, and Validation of Above-Cloud Aerosol Optical Depth from A-train Sensors

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Bhartia, Pawan K.; Remer, Lorraine; Redemann, Jens; Dunagan, Stephen E.; Livingston, John; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal-Rosenbeimer, Michal;

A Numerical Testbed for Remote Sensing of Aerosols, and its Demonstration for Evaluating Retrieval Synergy from a Geostationary Satellite Constellation of GEO-CAPE and GOES-R

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael I.

2014-01-01

We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEOCAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the synergic use of two future geostationary satellites, GOES-R (Geostationary Operational Environmental Satellite R-series) and TEMPO (Tropospheric Emissions: Monitoring of Pollution). Strong synergy between GEOS-R and TEMPO are found especially in their characterization of surface bi-directional reflectance, and thereby, can potentially improve the AOD retrieval to the accuracy required by GEO-CAPE.

Retrieval of high-spectral-resolution lidar for atmospheric aerosol optical properties profiling

NASA Astrophysics Data System (ADS)

Liu, Dong; Luo, Jing; Yang, Yongying; Cheng, Zhongtao; Zhang, Yupeng; Zhou, Yudi; Duan, Lulin; Su, Lin

2015-10-01

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.

Long-term Satellite Observations of Asian Dust Storm: Source, Pathway, and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina

2008-01-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. Outbreaks of Asian dust storms occur often in the arid and semi-arid areas of northwestern China -about 1.6x10(exp 6) square kilometers including the Gobi and Taklimakan deserts- with continuous expanding of spatial coverage. These airborne dust particles, originating in desert areas far from polluted regions, interact with anthropogenic sulfate and soot aerosols emitted from Chinese megacities during their transport over the mainland. Adding the intricate effects of clouds and marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from their sources. Furthermore, these aerosols, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol properties (e.g., optical thickness, 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. This new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS 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. Reasonable agreements have been achieved between Deep Blue retrievals of aerosol optical thickness and those directly from AERONET sunphotometers over desert and semi-desert regions. New Deep Blue products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. Long-term satellite measurements (1998 - 2007) from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with the Asian dust storm outbreaks. In addition, monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products

NASA Astrophysics Data System (ADS)

Toth, Travis D.; Campbell, James R.; Reid, Jeffrey S.; Tackett, Jason L.; Vaughan, Mark A.; Zhang, Jianglong; Marquis, Jared W.

2018-01-01

Due to instrument sensitivities and algorithm detection limits, level 2 (L2) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 532 nm aerosol extinction profile retrievals are often populated with retrieval fill values (RFVs), which indicate the absence of detectable levels of aerosol within the profile. In this study, using 4 years (2007-2008 and 2010-2011) of CALIOP version 3 L2 aerosol data, the occurrence frequency of daytime CALIOP profiles containing all RFVs (all-RFV profiles) is studied. In the CALIOP data products, the aerosol optical thickness (AOT) of any all-RFV profile is reported as being zero, which may introduce a bias in CALIOP-based AOT climatologies. For this study, we derive revised estimates of AOT for all-RFV profiles using collocated Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT) and, where available, AErosol RObotic NEtwork (AERONET) data. Globally, all-RFV profiles comprise roughly 71 % of all daytime CALIOP L2 aerosol profiles (i.e., including completely attenuated profiles), accounting for nearly half (45 %) of all daytime cloud-free L2 aerosol profiles. The mean collocated MODIS DT (AERONET) 550 nm AOT is found to be near 0.06 (0.08) for CALIOP all-RFV profiles. We further estimate a global mean aerosol extinction profile, a so-called noise floor, for CALIOP all-RFV profiles. The global mean CALIOP AOT is then recomputed by replacing RFV values with the derived noise-floor values for both all-RFV and non-all-RFV profiles. This process yields an improvement in the agreement of CALIOP and MODIS over-ocean AOT.

Intercomparison of Desert Dust Optical Depth from Satellite Measurements

NASA Technical Reports Server (NTRS)

Carboni, E.; Thomas, G. E.; Sayer, A. M.; Siddans, R.; Poulsen, C. A.; Grainger, R. G.; Ahn, C.; Antoine, D.; Bevan, S.; Braak, R.;

ACE Objectives, Current Status and the 2017 Decadal Survey

NASA Technical Reports Server (NTRS)

Da Silva, Arlindo

2018-01-01

In this talk we present an overview of the Aerosol-Cloud-Ecosystems (ACE) preformulation studies, a tier-2 satellite mission recommended by the 2007 Decadal Survey. We discuss the current status of ACE measurement concepts and associated retrieval algorithms. We conclude with a brief discussion of the recommendations by the 2017 Decadal Survey and how ACE accomplishments can inform the future Aerosol and Cloud, Convection & Precipitation Designated Observables.

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm through Intercomparison with VIIRS Aerosol Products and AERONET

PubMed Central

Superczynski, Stephen D.; Kondragunta, Shobha; Lyapustin, Alexei I.

2018-01-01

The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and un-matched seasonally gridded data are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with AERONET Level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of −0.01; however there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products capability over the Western Hemisphere. PMID:29796366

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm through Intercomparison with VIIRS Aerosol Products and AERONET.

PubMed

Superczynski, Stephen D; Kondragunta, Shobha; Lyapustin, Alexei I

2017-03-16

The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and un-matched seasonally gridded data are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with AERONET Level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of -0.01; however there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products capability over the Western Hemisphere.

Retrieval of volcanic ash properties from the Infrared Atmospheric Sounding Interferometer (IASI)

NASA Astrophysics Data System (ADS)

Ventress, Lucy; Carboni, Elisa; Smith, Andrew; Grainger, Don; Dudhia, Anu; Hayer, Catherine

2014-05-01

The Infrared Atmospheric Sounding Interferometer (IASI), on board both the MetOp-A and MetOp-B platforms, is a Fourier transform spectrometer covering the mid-infrared (IR) from 645-2760cm-1 (3.62-15.5 μm) with a spectral resolution of 0.5cm-1 (apodised) and a pixel diameter at nadir of 12km. These characteristics allow global coverage to be achieved twice daily for each instrument and make IASI a very useful tool for the observation of larger aerosol particles (such as desert dust and volcanic ash) and the tracking of volcanic plumes. In recent years, following the eruption of Eyjafjallajökull, interest in the the ability to detect and characterise volcanic ash plumes has peaked due to the hazards to aviation. The thermal infrared spectra shows a rapid variation with wavelength due to absorption lines from atmospheric and volcanic gases as well as broad scale features principally due to particulate absorption. The ash signature depends upon both the composition and size distribution of ash particles as well as the altitude of the volcanic plume. To retrieve ash properties, IASI brightness temperature spectra are analysed using an optimal estimation retrieval scheme and a forward model based on RTTOV. Initially, IASI pixels are flagged for the presence of volcanic ash using a linear retrieval detection method based on departures from a background state. Given a positive ash signal, the RTTOV output for a clean atmosphere (containing atmospheric gases but no cloud or aerosol/ash) is combined with an ash/cloud layer using the same scheme as for the Oxford-RAL Retrieval of Aerosol and Cloud (ORAC) algorithm. The retrieved parameters are ash optical depth (at a reference wavelength of 550nm), ash effective radius, layer altitude and surface temperature. The potential for distinguishing between different ash types is explored and a sensitivity study of the retrieval algorithm is presented. Results are shown from studies of the evolution and composition of ash plumes for recent volcanic eruptions.

The 2015 Indonesian biomass-burning season with extensive peat fires: Remote sensing measurements of biomass burning aerosol optical properties from AERONET and MODIS satellite data

NASA Astrophysics Data System (ADS)

Eck, T. F.; Holben, B. N.; Giles, D. M.; Smirnov, A.; Slutsker, I.; Sinyuk, A.; Schafer, J.; Sorokin, M. G.; Reid, J. S.; Sayer, A. M.; Hsu, N. Y. C.; Levy, R. C.; Lyapustin, A.; Wang, Y.; Rahman, M. A.; Liew, S. C.; Salinas Cortijo, S. V.; Li, T.; Kalbermatter, D.; Keong, K. L.; Elifant, M.; Aditya, F.; Mohamad, M.; Mahmud, M.; Chong, T. K.; Lim, H. S.; Choon, Y. E.; Deranadyan, G.; Kusumaningtyas, S. D. A.

2016-12-01

The strong El Nino event in 2015 resulted in below normal rainfall throughout Indonesia, which in turn allowed for exceptionally large numbers of biomass burning fires (including much peat burning) from Aug though Oct 2015. Over the island of Borneo, three AERONET sites measured monthly mean fine mode aerosol optical depth (AOD) at 500 nm from the spectral deconvolution algorithm in Sep and Oct ranging from 1.6 to 3.7, with daily average AOD as high as 6.1. In fact, the AOD was sometimes too high to obtain significant signal at mid-visible, therefore a newly developed algorithm in the AERONET Version 3 database was invoked to retain the measurements in as many of the longer wavelengths as possible. The AOD at longer wavelengths were then utilized to provide estimates of AOD at 550 nm with maximum values of 9 to 11. Additionally, satellite retrievals of AOD at 550 nm from MODIS data and the Dark Target, Deep Blue, and MAIAC algorithms were analyzed and compared to AERONET measured AOD. The AOD was sometimes too high for the satellite algorithms to make retrievals in the densest smoke regions. Since the AOD was often extremely high there was often insufficient AERONET direct sun signal at 440 nm for the larger solar zenith angles (> 50 degrees) required for almucantar retrievals. However, new hybrid sky radiance scans can attain sufficient scattering angle range even at small solar zenith angles when 440 nm direct beam irradiance can be accurately measured, thereby allowing for more retrievals and at higher AOD levels. The retrieved volume median radius of the fine mode increased from 0.18 to 0.25 micron as AOD increased from 1 to 3 (at 440 nm). These are very large size particles for biomass burning aerosol and are similar in size to smoke particles measured in Alaska during the very dry years of 2004 and 2005 (Eck et al. 2009) when peat soil burning also contributed to the fuel burned. The average single scattering albedo over the wavelength range of 440 to 1020 nm was very high ranging from 0.96 to 0.98 (spectrally flat), indicative of dominant smoldering phase combustion which produces very little black carbon. Additionally, we have analyzed measured (pyranometer) and modeled total solar flux at ground level for these extremely high aerosol loadings that resulted in significant attenuation of downwelling solar energy.

Empirical retrieval of sea spray aerosol production using satellite microwave radiometry

NASA Astrophysics Data System (ADS)

Savelyev, I. B.; Yelland, M. J.; Norris, S. J.; Salisbury, D.; Pascal, R. W.; Bettenhausen, M. H.; Prytherch, J.; Anguelova, M. D.; Brooks, I. M.

2017-12-01

This study presents a novel approach to obtaining global sea spray aerosol (SSA) production source term by relying on direct satellite observations of the ocean surface, instead of more traditional approaches driven by surface meteorology. The primary challenge in developing this empirical algorithm is to compile a calibrated, consistent dataset of SSA surface flux collected offshore over a variety of conditions (i.e., regions and seasons), thus representative of the global SSA production variability. Such dataset includes observations from SEASAW, HiWASE, and WAGES field campaigns, during which the SSA flux was measured from the bow of a research vessel using consistent and state-of-the-art eddy covariance methodology. These in situ data are matched to observations of the state of the ocean surface from Windsat polarimetric microwave satellite radiometer. Previous studies demonstrated the ability of WindSat to detect variations in surface waves slopes, roughness and foam, which led to the development of retrieval algorithms for surface wind vector and more recently whitecap fraction. Similarly, in this study, microwave emissions from the ocean surface are matched to and calibrated against in situ observations of the SSA production flux. The resulting calibrated empirical algorithm is applicable for retrieval of SSA source term throughout the duration of Windsat mission, from 2003 to present.

Evaluation of the MODIS Aerosol Retrievals over Ocean and Land during CLAMS.

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.; Martins, J. V.; Kaufman, Y. J.; Plana-Fattori, A.; Redemann, J.; Wenny, B.

2005-04-01

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 climatology for the MODIS lookup table over land, it is shown that the low bias for larger aerosol loadings can also be corrected. Understanding and improving MODIS retrievals over the East Coast may point to strategies for correction in other locations, thus improving the global quality of MODIS. Improvements in regional aerosol detection could also lead to the use of MODIS for monitoring air pollution.

Comparison of Coincident Multiangle Imaging Spectroradiometer and Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depths over Land and Ocean Scenes Containing Aerosol Robotic Network Sites

NASA Technical Reports Server (NTRS)

Abdou, Wedad A.; Diner, David J.; Martonchik, John V.; Bruegge, Carol J.; Kahn, Ralph A.; Gaitley, Barbara J.; Crean, Kathleen A.; Remer, Lorraine A.; Holben, Brent

2005-01-01

The Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), launched on 18 December 1999 aboard the Terra spacecraft, are making global observations of top-of-atmosphere (TOA) radiances. Aerosol optical depths and particle properties are independently retrieved from these radiances using methodologies and algorithms that make use of the instruments corresponding designs. This paper compares instantaneous optical depths retrieved from simultaneous and collocated radiances measured by the two instruments at locations containing sites within the Aerosol Robotic Network (AERONET). A set of 318 MISR and MODIS images, obtained during the months of March, June, and September 2002 at 62 AERONET sites, were used in this study. The results show that over land, MODIS aerosol optical depths at 470 and 660 nm are larger than those retrieved from MISR by about 35% and 10% on average, respectively, when all land surface types are included in the regression. The differences decrease when coastal and desert areas are excluded. For optical depths retrieved over ocean, MISR is on average about 0.1 and 0.05 higher than MODIS in the 470 and 660 nm bands, respectively. Part of this difference is due to radiometric calibration and is reduced to about 0.01 and 0.03 when recently derived band-to-band adjustments in the MISR radiometry are incorporated. Comparisons with AERONET data show similar patterns.

Mixing weight determination for retrieving optical properties of polluted dust with MODIS and AERONET data

NASA Astrophysics Data System (ADS)

Chang, Kuo-En; Hsiao, Ta-Chih; Hsu, N. Christina; Lin, Neng-Huei; Wang, Sheng-Hsiang; Liu, Gin-Rong; Liu, Chian-Yi; Lin, Tang-Huang

2016-08-01

In this study, an approach in determining effective mixing weight of soot aggregates from dust-soot aerosols is proposed to improve the accuracy of retrieving properties of polluted dusts by means of satellite remote sensing. Based on a pre-computed database containing several variables (such as wavelength, refractive index, soot mixing weight, surface reflectivity, observation geometries and aerosol optical depth (AOD)), the fan-shaped look-up tables can be drawn out accordingly for determining the mixing weights, AOD and single scattering albedo (SSA) of polluted dusts simultaneously with auxiliary regional dust properties and surface reflectivity. To validate the performance of the approach in this study, 6 cases study of polluted dusts (dust-soot aerosols) in Lower Egypt and Israel were examined with the ground-based measurements through AErosol RObotic NETwork (AERONET). The results show that the mean absolute differences could be reduced from 32.95% to 6.56% in AOD and from 2.67% to 0.83% in SSA retrievals for MODIS aerosol products when referenced to AERONET measurements, demonstrating the soundness of the proposed approach under different levels of dust loading, mixing weight and surface reflectivity. Furthermore, the developed algorithm is capable of providing the spatial distribution of the mixing weights and removing the requirement to assume that the dust plume properties are uniform. The case study further shows the spatially variant dust-soot mixing weight would improve the retrieval accuracy in AODmixture and SSAmixture about 10.0% and 1.4% respectively.

A study of aerosol absorption and height retrievals with a hyperspectral (UV to NIR) passive sensor

NASA Astrophysics Data System (ADS)

Gasso, S.

2017-12-01

With the deployment of the first sensor (TOMS, in 1978) with capabilities to detect aerosol absorption (AA) from space, there has been a continuous evolution in hardware and algorithms used to measured this property. Although with TOMS and its more advanced successors (such as OMI) made significant progress in globally characterizing AA , there is room for improvement especially by taking advantage of sensors with extended spectral coverage (UV to NIR) and high spatial resolution (<1 km). While such unique sensor does not exist yet, the collocation of observations from different platforms that jointly fulfill those characteristics (e.g. A-Train, S-NPP) confirm that it is possible to fully retrieve all AA parameters that modulate absorption in the upwelling radiance (AOD, SSA and aerosol layer height). However, such combined approaches still have some drawbacks such as the difficulty to account for cloud contamination. The upcoming deployment of satellite detectors with the desired features all in one sensor (PACE, TropOMI, GEMS) prompt a revision of the AA retrieval technique used in past approaches. In particular,the TropOMI mission, a hyperspectral UV-to-NIR sensor with moderate ( 5km nadir pixel) spatial resolution to be launched in Fall 2017. In addition , the sensor will include sensing capabilities for the wavelength range of the Oxygen bands A and B at very high wavelength resolution. This study will be centered on the aerosol detection capabilities of TropOMI. Because the spectral range covered, it is theoretically possible to simultaneously retrieve the aerosol optical depth, the single scattering albedo and aerosol mean height without assuming any of them as it was the case with previous retrieval approaches. Specifically, we intend to present a theoretical study based on simulated radiances at selected UV, VIS and near-IR bands (including the Oxygen bands) and evaluate the sensitivity of this sensor to different levels of aerosol concentration, height and absorption properties (imaginary index) along with particle size distribution.

Detection of haze and/or cloud

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Sano, Itaru; Mukai, Makiko; Kokhanovsky, Alexander

2015-04-01

It is highly likely that large-scale air pollution will continue to occur because air pollution becomes severe due to both the increasing emissions of the anthropogenic aerosols and the complicated behavior of natural aerosols, especially in Asia. It is natural to consider that incident solar light multiply interacts with the atmospheric aerosols due to dense radiation field in such a heavy haze. Accordingly efficient and practical algorithms for radiation simulation are indispensable to retrieve aerosol characteristics in a hazy atmosphere. It has been shown that aerosol retrieval in the hazy atmosphere is achieved based on MSOS (method of successive order of scattering) [1]. The satellite polarimetric sensor POLDER-1, 2, 3 has shown that the spectro-photopolarimetry of the terrestrial atmosphere is very useful for the observation of the Earth, especially for atmospheric particles. JAXA has been developing the new Earth observing system, GCOM satellite. GCOM-C will board the polarimetric sensor SGLI (second-generation global imager) in 2017. The SGLI has two polarization channels at near-infrared wavelengths of 670 and 870 nm. Furthermore, EUMETSAT plans to collect polarization measurements with a POLDER follow on 3MI/EPS-SG in 2021. Then the efficient algorithms for radiation simulation in the optically thick atmosphere by using polarization information denoted by Stokes parameters are shown in this work. It is of interest to mention that multi-spectral data are available for detection and/or distinction of hazy aerosol and/or cloud. In this work our MSOS is expected to be available for atmospheric particle retrieval in a mixture case of cloud and haze. The MSOS is available for the radiation simulation reflected from the optically semi-infinite atmosphere.[1]. Here we intend to improve MSOS-scalar into more efficient and practical form, and further into MSOS-vector form. We show here that a dense aerosol episode can be well simulated by a semi-infinite radiation model. For an example it is shown that the biomass burning haze observed by Parasol/POLDER and Aqua/MODIS in Asia is well interpreted with our code [2]. [1] Mukai, S., T. Yokomae, I. Sano, M. Nakata, and A. Kokhanovsky,2012:Multiple scattering in a dense aerosol atmosphere," Atmospheric Measurement Techniques Discussions, vol.5, 881-907. [2] Mukai, S., M. Yasumoto and M. Nakata, 2014: Estimation of biomass burning influence on air pollution around Beijing from an aerosol retrieval model. The Scientific World Journal, Article ID 649648.

Aerosol variation over Continental Europe from 1980 to 2015 Using ALAD Aerosol Retrievals

NASA Astrophysics Data System (ADS)

Che, Yahui; Xue, Yong; Mei, Linlu; Guang, Jie; She, Lu

2017-04-01

The Advanced Very High Resolution Radiometer (AVHRR) on-board National Oceanic and Atmospheric Administration (NOAA) series satellites has been used to observe the Earth and is the only spaceborne instrument which can provide users continuous long time series global coverage for more than 35 years since 1979. The initial purpose of AVHRR is for cloud detection and monitoring thermal emission of the Earth so that it lacks visible channels (only 0.64μm) and spaceborne which is unignorably unfavourable to its applications in aerosol retrieving over bright and inhomogeneous surface. Using AVHRR data, an Algorithm for the retrieval over Land of the Aerosol optical Depth (ALAD) was developed data which has great potential to be used to retrieve long time series aerosol globally from 1979 to now. The core of ALAD is to assume that the contribution of aerosol at 3.75μm wavelength to reflectance at top of the atmosphere (TOA) is negligible. At this basis, one stable and firm relationship between surface reflectance at 0.64μm and 3.75μm will be found by regression analysis at different land types after separating reflectance from radiance at 3.75μm. Then, an atmospheric transfer model is applied to calculate AOD at 0.64μm. In this study, we recalibrate AVHRR Global Area Coverage (GAC) data and then apply ALAD to calculate AOD over continental Europe (30°N to 80°N, 170°W to 40°E) to investigate aerosol changes and possible reason in past 35 years from 1981 to 2015. The retrieved AOD has been validated with ground-based data from Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) and AErosol RObotic NETwork (AERONET). The correlation of ALAD AOD with AERONET and ACTRIS is 0.77 and 0.66, respectively. Further, we also make long time series comparison of monthly averaged ALAD AOD with AERONET, ACTRIS and MODIS, showing that ALAD underestimate AOD a little. Finally, we find that the AOD over most areas in Continental Europe are less than 0.3, even less than 0.1, changing little without any obvious increase.

Multi-sensor measurements of mixed-phase clouds above Greenland

NASA Astrophysics Data System (ADS)

Stillwell, Robert A.; Shupe, Matthew D.; Thayer, Jeffrey P.; Neely, Ryan R.; Turner, David D.

2018-04-01

Liquid-only and mixed-phase clouds in the Arctic strongly affect the regional surface energy and ice mass budgets, yet much remains unknown about the nature of these clouds due to the lack of intensive measurements. Lidar measurements of these clouds are challenged by very large signal dynamic range, which makes even seemingly simple tasks, such as thermodynamic phase classification, difficult. This work focuses on a set of measurements made by the Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland and its retrieval algorithms, which use both analog and photon counting as well as orthogonal and non-orthogonal polarization retrievals to extend dynamic range and improve overall measurement quality and quantity. Presented here is an algorithm for cloud parameter retrievals that leverages enhanced dynamic range retrievals to classify mixed-phase clouds. This best guess retrieval is compared to co-located instruments for validation.

Vertical variability of aerosol single-scattering albedo and equivalent black carbon concentration based on in-situ and remote sensing techniques during the iAREA campaigns in Ny-Ålesund

NASA Astrophysics Data System (ADS)

Markowicz, K. M.; Ritter, C.; Lisok, J.; Makuch, P.; Stachlewska, I. S.; Cappelletti, D.; Mazzola, M.; Chilinski, M. T.

2017-09-01

This work presents a methodology for obtaining vertical profiles of aerosol single scattering properties based on a combination of different measurement techniques. The presented data were obtained under the iAREA (Impact of absorbing aerosols on radiative forcing in the European Arctic) campaigns conducted in Ny-Ålesund (Spitsbergen) during the spring seasons of 2015-2017. The retrieval uses in-situ observations of black carbon concentration and absorption coefficient measured by a micro-aethalometer AE-51 mounted onboard a tethered balloon, as well as remote sensing data obtained from sun photometer and lidar measurements. From a combination of the balloon-borne in-situ and the lidar data, we derived profiles of single scattering albedo (SSA) as well as absorption, extinction, and aerosol number concentration. Results have been obtained in an altitude range from about 400 m up to 1600 m a.s.l. and for cases with increased aerosol load during the Arctic haze seasons of 2015 and 2016. The main results consist of the observation of increasing values of equivalent black carbon (EBC) and absorption coefficient with altitude, and the opposite trend for aerosol concentration for particles larger than 0.3 μm. SSA was retrieved with the use of lidar Raman and Klett algorithms for both 532 and 880 nm wavelengths. In most profiles, SSA shows relatively high temporal and altitude variability. Vertical variability of SSA computed from both methods is consistent; however, some discrepancy is related to Raman retrieval uncertainty and absorption coefficient estimation from AE-51. Typically, very low EBC concentration in Ny-Ålesund leads to large error in the absorbing coefficient. However, SSA uncertainty for both Raman and Klett algorithms seems to be reasonable, e.g. SSA of 0.98 and 0.95 relate to an error of ±0.01 and ± 0.025, respectively.

A weighted least squares approach to retrieve aerosol layer height over bright surfaces applied to GOME-2 measurements of the oxygen A band for forest fire cases over Europe

NASA Astrophysics Data System (ADS)

Nanda, Swadhin; Pepijn Veefkind, J.; de Graaf, Martin; Sneep, Maarten; Stammes, Piet; de Haan, Johan F.; Sanders, Abram F. J.; Apituley, Arnoud; Tuinder, Olaf; Levelt, Pieternel F.

2018-06-01

This paper presents a weighted least squares approach to retrieve aerosol layer height from top-of-atmosphere reflectance measurements in the oxygen A band (758-770 nm) over bright surfaces. A property of the measurement error covariance matrix is discussed, due to which photons travelling from the surface are given a higher preference over photons that scatter back from the aerosol layer. This is a potential source of biases in the estimation of aerosol properties over land, which can be mitigated by revisiting the design of the measurement error covariance matrix. The alternative proposed in this paper, which we call the dynamic scaling method, introduces a scene-dependent and wavelength-dependent modification in the measurement signal-to-noise ratio in order to influence this matrix. This method is generally applicable to other retrieval algorithms using weighted least squares. To test this method, synthetic experiments are done in addition to application to GOME-2A and GOME-2B measurements of the oxygen A band over the August 2010 Russian wildfires and the October 2017 Portugal wildfire plume over western Europe.

How do A-train Sensors Inter-Compare in the Retrieval of Above-Cloud Aerosol Optical Depth? A Case Study based Assessment

NASA Astrophysics Data System (ADS)

Jethva, H. T.; Torres, O.; Waquet, F.; Chand, D.

2013-12-01

Atmospheric aerosols are known to produce a net cooling effect in the cloud-free conditions. However, when present over the reflective cloud decks, absorbing aerosols such as biomass burning generated smoke and wind-blown dust can potentially exert a large positive forcing through enhanced atmospheric heating resulting from cloud-aerosol radiative interactions. The interest on this aspect of aerosol science has grown significantly in the recent years. Particularly, development of the satellite-based retrieval techniques and unprecedented knowledge on the above-cloud aerosol optical depth (ACAOD) is of great relevance. A direct validation of satellite ACAOD is a difficult task primarily due to lack of ample in situ and/or remote sensing measurements of aerosols above cloud. In these circumstances, a comparative analysis on the inter-satellite ACAOD retrievals can be performed for the sack of consistency check. Here, we inter-compare the ACAOD of biomass burning plumes observed from different A-train sensors, i.e., MODIS [Jethva et al., 2013], CALIOP [Chand et al., 2008], POLDER [Waquet et al., 2009], and OMI [Torres et al., 2012]. These sensors have been shown to acquire sensitivity and independent capabilities to detect and retrieve aerosol loading above marine stratocumulus clouds--a kind of situation often found over the southeastern Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods retrieve comparable ACAOD over homogeneous cloud fields. The high-resolution sensors (MODIS and CALIOP) are able to retrieve aerosols over thin clouds but with larger discrepancies. Given the different types of sensor measurements processed with different algorithms, a reasonable agreement between them is encouraging. A direct validation of satellite-based ACAOD remains an open challenge for which dedicated field measurements over the region of frequent aerosol/cloud overlap are a prime requirement. Jethva, H., O. Torres, L. A. Remer, P. K. Bhartia (2013), A Color Ratio Method for Simultaneous Retrieval of Aerosol and Cloud Optical Thickness of Above-Cloud Absorbing Aerosols From Passive Sensors: Application to MODIS Measurements, Geoscience and Remote Sensing, IEEE Transactions on, 51(7), pp. 3862-3870, doi: 10.1109/TGRS.2012.2230008. Chand, D., T. L. Anderson, R. Wood, R. J. Charlson, Y. Hu, Z. Liu, and M. Vaughan (2008), Quantifying above-cloud aerosol using spaceborne lidar for improved understanding of cloudy-sky direct climate forcing, J. Geophys. Res., 113, D13206, doi:10.1029/2007JD009433. Waquet, F., J. Riedi, L. C. Labonnote, P. Goloub, B. Cairns, J.-L. Deuzeand, and D. Tanre (2009), Aerosol remote sensing over clouds using a-train observations, J. Atmos. Sci., 66(8), 2468-2480, doi: http://dx.doi.org/10.1175/2009JAS3026.1 Torres, O., H. Jethva, and P. K. Bhartia (2012), Retrieval of aerosol optical depth above clouds from OMI observations: Sensitivity analysis and case studies, J. Atmos. Sci., 69(3), 1037-1053, doi: http://dx.doi.org/10.1175/JAS-D-11-0130.

Ozone and Aerosol Retrieval from Backscattered Ultraviolet Radiation

NASA Technical Reports Server (NTRS)

Bhartia, Pawan K.

2012-01-01

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".

Validation of MODIS aerosol optical depth product over China using CARSNET measurements

NASA Astrophysics Data System (ADS)

Xie, Yong; Zhang, Yan; Xiong, Xiaoxiong; Qu, John J.; Che, Huizheng

2011-10-01

This study evaluates Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) retrievals with ground measurements collected by the China Aerosol Remote Sensing NETwork (CARSNET). In current stage, the MODIS Collection 5 (C5) AODs are retrieved by two distinct algorithms: the Dark Target (DT) and the Deep Blue (DB). The CARSNET AODs are derived with measurements of Cimel Electronique CE-318, the same instrument deployed by the AEROsol Robotic Network (AEROENT). The collocation is performed by matching each MODIS AOD pixel (10 × 10 km 2) to CARSNET AOD mean within 7.5 min of satellite overpass. Four-year comparisons (2005-2008) of MODIS/CARSNET at ten sites show the performance of MODIS AOD retrieval is highly dependent on the underlying land surface. The MODIS DT AODs are on average lower than the CARSNET AODs by 6-30% over forest and grassland areas, but can be higher by up to 54% over urban area and 95% over desert-like area. More than 50% of the MODIS DT AODs fall within the expected error envelope over forest and grassland areas. The MODIS DT tends to overestimate for small AOD at urban area. At high vegetated area it underestimates for small AOD and overestimates for large AOD. Generally, its quality reduces with the decreasing AOD value. The MODIS DB is capable of retrieving AOD over desert but with a significant underestimation at CARSNET sites. The best retrieval of the MODIS DB is over grassland area with about 70% retrievals within the expected error. The uncertainties of MODIS AOD retrieval from spatial-temporal collocation and instrument calibration are discussed briefly.

Retrieval of cloud properties from POLDER-3 data using the neural network approach

NASA Astrophysics Data System (ADS)

Di Noia, A.; Hasekamp, O. P.

2017-12-01

Satellite multi-angle spectroplarimetry is a useful technique for observing the microphysical properties of clouds and aerosols. Most of the algorithms for the retrieval of cloud and aerosol properties from satellite measurements require multiple calls to radiative transfer models, which make the retrieval computationally expensive. A traditional alternative to these schemes is represented by lookup-tables (LUTs), where the retrieval is performed by choosing, within a predefined database of combinations of clouds or aerosol properties, the combination that best fits the measurements. LUT retrievals are quicker than full-physics, iterative retrievals, but their accuracy is limited by the number of entries stored in the LUT. Another retrieval method capable of producing very quick retrievals without a big sacrifice in accuracy is the neural network method. Neural network methods are routinely applied to several types of satellite measurements, but their application to multi-angle spectropolarimetric data is still in its early stage, because of the difficulty of accounting for the angular variability of the measurements in the training process. We have recently developed a neural network scheme for the retrieval of cloud properties from POLDER-3 data. The neural network retrieval is trained using synthetic measurements performed for realistic combinations of cloud properties and measurement angles, and is able to process an entire orbit in about 20 seconds. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products during one year show encouraging retrieval performance for cloud optical thickness and effective radius. A discussion of the setup of the neural network and of the validation results will be the main topic of our presentation.

Global Aerosol Remote Sensing from MODIS

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram J.; Remer, Lorraine A.; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Martins, Jose V.; Lau, William K. M. (Technical Monitor)

2002-01-01

The physical characteristics, composition, abundance, spatial distribution and dynamics of global aerosols are still very poorly known, and new data from satellite sensors have long been awaited to improve current understanding and to give a boost to the effort in future climate predictions. The derivation of aerosol parameters from the MODerate resolution Imaging Spectro-radiometer (MODIS) sensors aboard the Earth Observing System (EOS) Terra and Aqua polar-orbiting satellites ushers in a new era in aerosol remote sensing from space. Terra and Aqua were launched on December 18, 1999 and May 4, 2002 respectively, with daytime equator crossing times of approximately 10:30 am and 1:30 pm respectively. Several aerosol parameters are retrieved at 10-km spatial resolution (level 2) from MODIS daytime data. The MODIS aerosol algorithm employs different approaches to retrieve parameters over land and ocean surfaces, because of the inherent differences in the solar spectral radiance interaction with these surfaces. The parameters retrieved include: aerosol optical thickness (AOT) at 0.47, 0.55 and 0.66 micron wavelengths over land, and at 0.47, 0.55, 0.66, 0.87, 1.2, 1.6, and 2.1 micron over ocean; Angstrom exponent over land and ocean; and effective radii, and the proportion of AOT contributed by the small mode aerosols over ocean. To ensure the quality of these parameters, a substantial part of the Terra-MODIS aerosol products were validated globally and regionally, based on cross correlation with corresponding parameters derived from ground-based measurements from AERONET (AErosol RObotic NETwork) sun photometers. Similar validation efforts are planned for the Aqua-MODIS aerosol products. The MODIS level 2 aerosol products are operationally aggregated to generate global daily, eight-day (weekly), and monthly products at one-degree spatial resolution (level 3). MODIS aerosol data are used for the detailed study of local, regional, and global aerosol concentration, distribution, and temporal dynamics, as well as for radiative forcing calculations. We show several examples of these results and comparisons with model output.

An Accuracy Assessment of the CALIOP/CALIPSO Version 2/Version 3 Daytime Aerosol Extinction Product Based on a Detailed Multi-Sensor, Multi-Platform Case Study

NASA Technical Reports Server (NTRS)

Kacenelenbogen, M.; Vaughan, M. A.; Redemann, J.; Hoff, R. M.; Rogers, R. R.; Ferrare, R. A.; Russell, P. B.; Hostetler, C. A.; Hair, J. W.; Holben, B. N.

2011-01-01

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. The goal of this study is 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 have been introduced in the next version of CALIOP data (version 3, released in June 2010). To help illustrate the potential factors contributing to the uncertainty of the CALIOP aerosol extinction retrieval, we focus on a one-day, multi-instrument, multiplatform comparison study during the CALIPSO and Twilight Zone (CATZ) validation campaign on 4 August 2007. On that day, we observe a consistency in the Aerosol Optical Depth (AOD) values recorded by four different instruments (i.e. spaceborne MODerate Imaging Spectroradiometer, MODIS: 0.67 and POLarization and Directionality of Earth s Reflectances, POLDER: 0.58, airborne High Spectral Resolution Lidar, HSRL: 0.52 and ground-based AErosol RObotic NETwork, AERONET: 0.48 to 0.73) while CALIOP AOD is a factor of two lower (0.32 at 532 nm). This case study illustrates the following potential sources of uncertainty in the 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 aerosol extinction-to-backscatter ratio (Sa) used in CALIOP s extinction retrievals; and (iv) calibration coefficient biases in the CALIOP daytime attenuated backscatter coefficient profiles. The use of version 3 CALIOP extinction retrieval for our case study seems to partially fix factor (i) although the aerosol retrieved by CALIOP is still somewhat lower than the profile measured by HSRL; the cloud contamination (ii) appears to be corrected; no particular change is apparent in the observation-based CALIOP Sa value (iii). Our case study also showed very little difference in version 2 and version 3 CALIOP attenuated backscatter coefficient profiles, illustrating a minor change in the calibration scheme (iv).

Radiative transfer codes for atmospheric correction and aerosol retrieval: intercomparison study.

PubMed

Kotchenova, Svetlana Y; Vermote, Eric F; Levy, Robert; Lyapustin, Alexei

2008-05-01

Results are summarized for a scientific project devoted to the comparison of four atmospheric radiative transfer codes incorporated into different satellite data processing algorithms, namely, 6SV1.1 (second simulation of a satellite signal in the solar spectrum, vector, version 1.1), RT3 (radiative transfer), MODTRAN (moderate resolution atmospheric transmittance and radiance code), and SHARM (spherical harmonics). The performance of the codes is tested against well-known benchmarks, such as Coulson's tabulated values and a Monte Carlo code. The influence of revealed differences on aerosol optical thickness and surface reflectance retrieval is estimated theoretically by using a simple mathematical approach. All information about the project can be found at http://rtcodes.ltdri.org.

Radiative transfer codes for atmospheric correction and aerosol retrieval: intercomparison study

NASA Astrophysics Data System (ADS)

Kotchenova, Svetlana Y.; Vermote, Eric F.; Levy, Robert; Lyapustin, Alexei

2008-05-01

Results are summarized for a scientific project devoted to the comparison of four atmospheric radiative transfer codes incorporated into different satellite data processing algorithms, namely, 6SV1.1 (second simulation of a satellite signal in the solar spectrum, vector, version 1.1), RT3 (radiative transfer), MODTRAN (moderate resolution atmospheric transmittance and radiance code), and SHARM (spherical harmonics). The performance of the codes is tested against well-known benchmarks, such as Coulson's tabulated values and a Monte Carlo code. The influence of revealed differences on aerosol optical thickness and surface reflectance retrieval is estimated theoretically by using a simple mathematical approach. All information about the project can be found at http://rtcodes.ltdri.org.

Validation of MODIS aerosol optical depth over the Mediterranean Coast

NASA Astrophysics Data System (ADS)

Díaz-Martínez, J. Vicente; Segura, Sara; Estellés, Víctor; Utrillas, M. Pilar; Martínez-Lozano, J. Antonio

2013-04-01

Atmospheric aerosols, due to their high spatial and temporal variability, are considered one of the largest sources of uncertainty in different processes affecting visibility, air quality, human health, and climate. Among their effects on climate, they play an important role in the energy balance of the Earth. On one hand they have a direct effect by scattering and absorbing solar radiation; on the other, they also have an impact in precipitation, modifying clouds, or affecting air quality. The application of remote sensing techniques to investigate aerosol effects on climate has advanced significatively over last years. In this work, the products employed have been obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS is a sensor located onboard both Earth Observing Systems (EOS) Terra and Aqua satellites, which provide almost complete global coverage every day. These satellites have been acquiring data since early 2000 (Terra) and mid 2002 (Aqua) and offer different products for land, ocean and atmosphere. Atmospheric aerosol products are presented as level 2 products with a pixel size of 10 x 10 km2 in nadir. MODIS aerosol optical depth (AOD) is retrieved by different algorithms depending on the pixel surface, distinguishing between land and ocean. For its validation, ground based sunphotometer data from AERONET (Aerosol Robotic Network) has been employed. AERONET is an international operative network of Cimel CE318 sky-sunphotometers that provides the most extensive aerosol data base globally available of ground-based measurements. The ground sunphotometric technique is considered the most accurate for the retrieval of radiative properties of aerosols in the atmospheric column. In this study we present a validation of MODIS C051 AOD employing AERONET measurements over different Mediterranean coastal sites centered over an area of 50 x 50 km2, which includes both pixels over land and ocean. The validation is done comparing spatial statistics from MODIS with corresponding temporal statistics from AERONET, as proposed by Ichoku et al. (2002). Eight Mediterranean coastal sites (in Spain, France, Italy, Crete, Turkey and Israel) with available AERONET and MODIS data have been used. These stations have been selected following QA criteria (minimum 1000 days of level 2.0 data) and a maximum distance of 8 km from the coast line. Results of the validation over each site show analogous behaviour, giving similar results regarding to the accuracy of the algorithms. Greatest differences are found for the AOD obtained over land, especially for drier regions, where the surface tends to be brighter. In general, the MODIS AOD has better a agreement with AERONET retrievals for the ocean algorithm than the land algorithm when validated over coastal sites, and the agreement is within the expected uncertainty estimated for MODIS data. References: - C. Ichoku et al., "A spatio-temporal approach for global validation and analysis of MODIS aerosol products", Geophysical Research Letters, 219, 12, 10.1029/2001GL013206, 2002.

Simulations of the observation of clouds and aerosols with the Experimental Lidar in Space Equipment system.

PubMed

Liu, Z; Voelger, P; Sugimoto, N

2000-06-20

We carried out a simulation study for the observation of clouds and aerosols with the Japanese Experimental Lidar in Space Equipment (ELISE), which is a two-wavelength backscatter lidar with three detection channels. The National Space Development Agency of Japan plans to launch the ELISE on the Mission Demonstrate Satellite 2 (MDS-2). In the simulations, the lidar return signals for the ELISE are calculated for an artificial, two-dimensional atmospheric model including different types of clouds and aerosols. The signal detection processes are simulated realistically by inclusion of various sources of noise. The lidar signals that are generated are then used as input for simulations of data analysis with inversion algorithms to investigate retrieval of the optical properties of clouds and aerosols. The results demonstrate that the ELISE can provide global data on the structures and optical properties of clouds and aerosols. We also conducted an analysis of the effects of cloud inhomogeneity on retrievals from averaged lidar profiles. We show that the effects are significant for space lidar observations of optically thick broken clouds.

Contributions to the Understanding of Aerosol Microphysics Towards Improving the Assessment of Climate Radiative Forcing

NASA Astrophysics Data System (ADS)

Dawson, Kyle William

The study of climate and the associated impacts imposed by human activity has garnered the attention of scientists and policy makers since the 1950s. Research into the various atmospheric constituents that interact with solar radiation thus modulating Earth's radiative budget has been largely focused on the contributions from greenhouse gases and later focused on the role of atmospheric aerosol. The role of atmospheric aerosol, i.e. a solid or aqueous phase particulate, is complex and presents an opportunity for bettering the assessments of climate radiative forcing (i.e. the fraction of climate change due to anthropogenic, rather than natural, activities) in several ways. First, motivated to better understand the radiative effects of the Earth's background aerosol state to improve the assessment of anthropogenic effects, an experimental study on the water uptake ability of xanthan gum as a proxy for marine hydrogel, a component of natural primary emitted seaspray aerosol, is presented. Marine hydrogel comprises an organic component of the ocean surface microlayer that is released to the atmosphere via the bursting of bubbles generated by entrainment of air through crashing waves. This study investigates the water uptake ability (i.e. hygroscopicity) of these particles when exposed to a range of relative humidity (RH). The hydration characteristics of aerosolized pure xanthan gum as well as xanthan gum/salt mixtures were studied using a hygroscopic tandem differential mobility analyzer (HTDMA) and cloud condensation nuclei counter (CCNc). The hygroscopicity of the various solutions were compared to theoretical thermodynamic calculations accounting for the component volume fractions as a function of relative humidity. The data show that pure xanthan gum aerosol hygroscopicity behaves as other organic polysaccharides and, when combined with salts, is reasonably approximated by the volume fraction mixing rules above 90% RH. Deviations occur below 90% RH as well as for CCNc measured hygroscopicity and HTDMA measured hygroscopicity at 90% RH, and are discussed in terms of hydration regimes associated with structural changes imposed by polymer/salt crosslinks. Second, motivated by a necessity to provide better constraints for climate model assessments of radiative forcing, a computational study for developing a link between climate models and observations from remote sensing techniques is presented. The Creating Aerosol Types from CHemistry (CATCH) algorithm has been developed for providing atmospheric models with estimated aerosol types, analogous to those that are retrieved by remote sensing methods. To date, the link between models and remote sensing retrievals is crude and is based on the total column attenuation of radiation by aerosol called the aerosol optical depth (AOD). In this study, through multivariate clustering techniques, this link is expanded to produce model-calculated aerosol types of dusty mix, maritime, urban, smoke, and fresh smoke, that are analogous to those retrieved by remote sensing. The CATCH algorithm shows that vertically-resolved aerosol types compare well to those measured by aircraft-mounted High Spectral Resolution Lidar - version 1 (HSRL-1) during the Ship-Aircraft Bio-Optical Research (SABOR) field campaign during July/August of 2014. Flight-by-flight comparisons of the type-apportioned AOD and vertically-resolved aerosol extinction also compare well. The CATCH algorithm is then applied to a high-resolution nested grid domain over North America and found to produce encouraging results of spatially relevant aerosol types such as dusty mix aerosol over the Caribbean, maritime aerosol over oceans, urban aerosol over large cities, smoke aerosol over weak forest fires, and fresh smoke aerosol over strong forest fires.

The MODIS Aerosol Algorithm: Critical Evaluation and Plans for Collection 6

NASA Technical Reports Server (NTRS)

Remer, Lorraine

2010-01-01

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.

UV-Vis-IR spectral complex refractive indices and optical properties of brown carbon aerosol from biomass burning

NASA Astrophysics Data System (ADS)

Sumlin, Benjamin J.; Heinson, Yuli W.; Shetty, Nishit; Pandey, Apoorva; Pattison, Robert S.; Baker, Stephen; Hao, Wei Min; Chakrabarty, Rajan K.

2018-02-01

Constraining the complex refractive indices, optical properties and size of brown carbon (BrC) aerosols is a vital endeavor for improving climate models and satellite retrieval algorithms. Smoldering wildfires are the largest source of primary BrC, and fuel parameters such as moisture content, source depth, geographic origin, and fuel packing density could influence the properties of the emitted aerosol. We measured in situ spectral (375-1047 nm) optical properties of BrC aerosols emitted from smoldering combustion of Boreal and Indonesian peatlands across a range of these fuel parameters. Inverse Lorenz-Mie algorithms used these optical measurements along with simultaneously measured particle size distributions to retrieve the aerosol complex refractive indices (m = n + iκ). Our results show that the real part n is constrained between 1.5 and 1.7 with no obvious functionality in wavelength (λ), moisture content, source depth, or geographic origin. With increasing λ from 375 to 532 nm, κ decreased from 0.014 to 0.003, with corresponding increase in single scattering albedo (SSA) from 0.93 to 0.99. The spectral variability of κ follows the Kramers-Kronig dispersion relation for a damped harmonic oscillator. For λ ≥ 532 nm, both κ and SSA showed no spectral dependency. We discuss differences between this study and previous work. The imaginary part κ was sensitive to changes in FPD, and we hypothesize mechanisms that might help explain this observation.

Ocean observations with EOS/MODIS: Algorithm development and post launch studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1996-01-01

An investigation of the influence of stratospheric aerosol on the performance of the atmospheric correction algorithm is nearly complete. The results indicate how the performance of the algorithm is degraded if the stratospheric aerosol is ignored. Use of the MODIS 1380 nm band to effect a correction for stratospheric aerosols was also studied. Simple algorithms such as subtracting the reflectance at 1380 nm from the visible and near infrared bands can significantly reduce the error; however, only if the diffuse transmittance of the aerosol layer is taken into account. The atmospheric correction code has been modified for use with absorbing aerosols. Tests of the code showed that, in contrast to non absorbing aerosols, the retrievals were strongly influenced by the vertical structure of the aerosol, even when the candidate aerosol set was restricted to a set appropriate to the absorbing aerosol. This will further complicate the problem of atmospheric correction in an atmosphere with strongly absorbing aerosols. Our whitecap radiometer system and solar aureole camera were both tested at sea and performed well. Investigation of a technique to remove the effects of residual instrument polarization sensitivity were initiated and applied to an instrument possessing (approx.) 3-4 times the polarization sensitivity expected for MODIS. Preliminary results suggest that for such an instrument, elimination of the polarization effect is possible at the required level of accuracy by estimating the polarization of the top-of-atmosphere radiance to be that expected for a pure Rayleigh scattering atmosphere. This may be of significance for design of a follow-on MODIS instrument. W.M. Balch participated on two month-long cruises to the Arabian sea, measuring coccolithophore abundance, production, and optical properties. A thorough understanding of the relationship between calcite abundance and light scatter, in situ, will provide the basis for a generic suspended calcite algorithm.

Retrieval of Aerosol Properties from the Hyper Angular Rainbow Polarimeter (HARP) during the LMOS Campaign

NASA Astrophysics Data System (ADS)

Barbosa, H. M.; Martins, J. V.; McBride, B.; Espinosa, R.; Fernandez Borda, R. A.; Remer, L.; Dubovik, O.

2017-12-01

The largest impediments to estimating climate change revolve around a lack of quantitative information on aerosol forcing and our poor understanding of aerosol-cloud processes and cloud feedbacks in the climate system. This is so because global aerosol and cloud data come from satellite sensors that, today, measure limited subsets of the full Stokes parameters. Most measure only spectral intensity at one geometry, or at a severely limited set of geometries, or measure polarization non-simultaneously using a filter wheel, with a low spatial resolution. To overcome this scientific gap, the Laboratory for Aerosols, Clouds and Optics (LACO) of UMBC developed the Hyper Angular Rainbow Polarimeter (HARP): a very simple but highly effective sensor that can simultaneously measure 3 angles of polarization, at 4 different wavelengths, to observe the same target with up to 60 viewing angles, with no moving parts. The HARP-Cubesat mission will fly next January, with the main objective of proving the on-flight capabilities of a highly accurate wide FOV hyperangle imaging polarimeter for characterizing aerosol and cloud properties. AirHARP is an exact copy of the HARP sensor but prepared to fly on aircrafts. Here we report on preliminary aerosol data analysis from its first measurements during the Lake Michigan Ozone Study (LMOS) field campaign last June. We will discuss how the polarization measurements are inverted using the GRASP (Generalized Retrieval of Aerosol and Surface Properties) inversion algorithm to obtain the aerosol size distribution, complex index of refraction and sphericity. For the flights on June 8th and 12th, we will compare the retrievals with those from the Aeronet station LMOS-ZION, specially setup for the campaign.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

Observations of the vertical distributions of summertime atmospheric pollutants and the corresponding ozone production in Shanghai, China

NASA Astrophysics Data System (ADS)

Xing, Chengzhi; Liu, Cheng; Wang, Shanshan; Chan, Ka Lok; Gao, Yang; Huang, Xin; Su, Wenjing; Zhang, Chengxin; Dong, Yunsheng; Fan, Guangqiang; Zhang, Tianshu; Chen, Zhenyi; Hu, Qihou; Su, Hang; Xie, Zhouqing; Liu, Jianguo

2017-12-01

Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) and lidar measurements were performed in Shanghai, China, during May 2016 to investigate the vertical distribution of summertime atmospheric pollutants. In this study, vertical profiles of aerosol extinction coefficient, nitrogen dioxide (NO2) and formaldehyde (HCHO) concentrations were retrieved from MAX-DOAS measurements using the Heidelberg Profile (HEIPRO) algorithm, while vertical distribution of ozone (O3) was obtained from an ozone lidar. Sensitivity study of the MAX-DOAS aerosol profile retrieval shows that the a priori aerosol profile shape has significant influences on the aerosol profile retrieval. Aerosol profiles retrieved from MAX-DOAS measurements with Gaussian a priori profile demonstrate the best agreements with simultaneous lidar measurements and vehicle-based tethered-balloon observations among all a priori aerosol profiles. Tropospheric NO2 vertical column densities (VCDs) measured with MAX-DOAS show a good agreement with OMI satellite observations with a Pearson correlation coefficient (R) of 0.95. In addition, measurements of the O3 vertical distribution indicate that the ozone productions do not only occur at surface level but also at higher altitudes (about 1.1 km). Planetary boundary layer (PBL) height and horizontal and vertical wind field information were integrated to discuss the ozone formation at upper altitudes. The results reveal that enhanced ozone concentrations at ground level and upper altitudes are not directly related to horizontal and vertical transportation. Similar patterns of O3 and HCHO vertical distributions were observed during this campaign, which implies that the ozone productions near the surface and at higher altitudes are mainly influenced by the abundance of volatile organic compounds (VOCs) in the lower troposphere.

Improving Satellite Retrieved Infrared Sea Surface Temperatures in Aerosol-Contaminated Regions

NASA Astrophysics Data System (ADS)

Luo, B.; Minnett, P. J.; Szczodrak, G.; Kilpatrick, K. A.

2017-12-01

Infrared satellite observations of sea surface temperature (SST) have become essential for many applications in meteorology, climatology, and oceanography. Applications often require high accuracy SST data: for climate research and monitoring an absolute uncertainty of 0.1K and stability of better than 0.04K per decade are required. Tropospheric aerosol concentrations increase infrared signal attenuation and prevent the retrieval of accurate satellite SST. We compare satellite-derived skin SST with measurements from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) deployed on ships during the Aerosols and Ocean Science Expeditions (AEROSE) and with quality-controlled drifter temperatures. After match-up with in-situ SST and filtering of cloud contaminated data, the results indicate that SST retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the Terra and Aqua satellites have negative (cool) biases compared to shipboard radiometric measurements. There is also a pronounced negative bias in the Saharan outflow area that can introduce SST errors >1 K at aerosol optical depths > 0.5. In this study, we present a new method to derive night-time Saharan Dust Index (SDI) algorithms based on simulated brightness temperatures at infrared wavelengths of 3.9, 10.8 and 12.0 μm, derived using RTTOV. We derived correction coefficients for Aqua MODIS measurements by regression of the SST errors against the SDI. The biases and standard deviations are reduced by 0.25K and 0.19K after the SDI correction. The goal of this study is to understand better the characteristics and physical mechanisms of aerosol effects on satellite retrieved infrared SST, as well as to derive empirical formulae for improved accuracies in aerosol-contaminated regions.

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, Pathway, and Interannual Variability

NASA Astrophysics Data System (ADS)

Hsu, N.; Tsay, S.; Jeong, M.; Holben, B.

2006-12-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of spring-time cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such popu-lation centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. 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 dif-ficult 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, 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 desert and semi-desert regions. The compari-sons show reasonable agreements between these two. These new satellite prod-ucts will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly av-eraged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, pathway and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina

2007-01-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. 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, 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 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. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, Pathway, and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, S.-C.; Bettenhausen, C.; Salustro, C.; Jeong, M. J.

2010-01-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochernical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. 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, 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 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. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, Pathway, and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, S.-C.; Bettenhausen, C.; Sayer, A.

2011-01-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces peop Ie indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be tran sported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over brightreflecting 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 Sea WiFS and MODIS 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 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 Sea WiFS and MODISlike instruments. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Evaluation of Daytime Measurements of Aerosols and Water Vapor made by an Operational Raman Lidar over the Southern Great Plains

NASA Technical Reports Server (NTRS)

Ferrare, Richard; Turner, David; Clayton, Marian; Schmid, Beat; Covert, David; Elleman, Robert; Orgren, John; Andrews, Elisabeth; Goldsmith, John E. M.; Jonsson, Hafidi

2006-01-01

Raman lidar water vapor and aerosol extinction profiles acquired during the daytime over the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in northern Oklahoma (36.606 N, 97.50 W, 315 m) are evaluated using profiles measured by in situ and remote sensing instruments deployed during the May 2003 Aerosol Intensive Operations Period (IOP). The automated algorithms used to derive these profiles from the Raman lidar data were first modified to reduce the adverse effects associated with a general loss of sensitivity of the Raman lidar since early 2002. The Raman lidar water vapor measurements, which are calibrated to match precipitable water vapor (PWV) derived from coincident microwave radiometer (MWR) measurements were, on average, 5-10% (0.3-0.6 g/m(exp 3) higher than the other measurements. Some of this difference is due to out-of-date line parameters that were subsequently updated in the MWR PWV retrievals. The Raman lidar aerosol extinction measurements were, on average, about 0.03 km(exp -1) higher than aerosol measurements derived from airborne Sun photometer measurements of aerosol optical thickness and in situ measurements of aerosol scattering and absorption. This bias, which was about 50% of the mean aerosol extinction measured during this IOP, decreased to about 10% when aerosol extinction comparisons were restricted to aerosol extinction values larger than 0.15 km(exp -1). The lidar measurements of the aerosol extinction/backscatter ratio and airborne Sun photometer measurements of the aerosol optical thickness were used along with in situ measurements of the aerosol size distribution to retrieve estimates of the aerosol single scattering albedo (omega(sub o)) and the effective complex refractive index. Retrieved values of omega(sub o) ranged from (0.91-0.98) and were in generally good agreement with omega(sub o) derived from airborne in situ measurements of scattering and absorption. Elevated aerosol layers located between about 2.6 and 3.6 km were observed by the Raman lidar on May 25 and May 27. The airborne measurements and lidar retrievals indicated that these layers, which were likely smoke produced by Siberian forest fires, were primarily composed of relatively large particles (r(sub eff) approximately 0.23 micrometers), and that the layers were relatively nonabsorbing (omega(sub o) approximately 0.96-0.98). Preliminary results show that major modifications that were made to the Raman lidar system during 2004 have dramatically improved the sensitivity in the aerosol and water vapor channels and reduced random errors in the aerosol scattering ratio and water vapor retrievals by an order of magnitude.

Response to Toward Unified Satellite Climatology of Aerosol Properties. 3; MODIS versus MISR versus AERONET

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Garay, Michael J.; Nelson, David L.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Hansen, Earl G.; Remer, Lorraine A.; Tanre, Didler

2010-01-01

A recent paper by Mishchenko et al. compares near-coincident MISR, MODIS, and AERONET aerosol optical depth (AOD), and gives a much less favorable impression of the utility of the satellite products than that presented by the instrument teams and other groups. We trace the reasons for the differing pictures to whether known and previously documented limitations of the products are taken into account in the assessments. Specifically, the analysis approaches differ primarily in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account. Mishchenko et al. also do not distinguish between observational sampling differences and retrieval algorithm error. We assess the implications of the different analysis approaches, and cite examples demonstrating how the MISR and MODIS aerosol products have been applied successfully to a range of scientific investigations.

Raman LIDAR for UHECR experiments: an overview of the L'Aquila (Italy) lidar station experience for the retrieval of quality-assured data

NASA Astrophysics Data System (ADS)

Iarlori, Marco; Rizi, Vincenzo; D'Amico, Giuseppe; Freudenthaler, Volker; Wandinger, Ulla; Grillo, Aurelio

L'Aquila (Italy) lidar station is part of the EARLINET (European Aerosol Research Lidar Network) since its beginning in the 2000. In the EARLINET community great efforts are devoted to the quality-assurance of the aerosol optical properties inserted in the database. To this end, each lidar station performed intercomparisons with reference instruments, a series of internal hardware checks in order to assess the quality of their instruments and exercises to test the algorithms used to retrieve the aerosol optical parameters. In this paper we give an overview of our experience within EARLINET qualityassurance (QA) program, which was adopted for the Raman lidar (RL) operated in the AUGER Observatory. This program could be systematically adopted for the lidar systems needed for the current and upcoming UHECR experiments, like CTA (Cherenkov Telescope Array).

Empirical Corrections for MISR Calibration Temporal Trends, Point-Spread Function, Flat-Fielding, and Ghosting

NASA Astrophysics Data System (ADS)

Limbacher, J.; Kahn, R. A.

2015-12-01

MISR aerosol optical depth retrievals are fairly robust to small radiometric calibration artifacts, due to the multi-angle observations. However, even small errors in the MISR calibration, especially structured artifacts in the imagery, have a disproportionate effect on the retrieval of aerosol properties from these data. Using MODIS, POLDER-3, AERONET, MAN, and MISR lunar images, we diagnose and correct various calibration and radiometric artifacts found in the MISR radiance (Level 1) data, using empirical image analysis. The calibration artifacts include temporal trends in MISR top-of-atmosphere reflectance at relatively stable desert sites and flat-fielding artifacts detected by comparison to MODIS over bright, low-contrast scenes. The radiometric artifacts include ghosting (as compared to MODIS, POLDER-3, and forward model results) and point-spread function mischaracterization (using the MISR lunar data and MODIS). We minimize the artifacts to the extent possible by parametrically modeling the artifacts and then removing them from the radiance (reflectance) data. Validation is performed using non-training scenes (reflectance comparison), and also by using the MISR Research Aerosol retrieval algorithm results compared to MAN and AERONET.

SAGE II Measurements of Stratospheric Aerosol Properties at Non-Volcanic Levels

NASA Technical Reports Server (NTRS)

Thomason, Larry W.; Burton, Sharon P.; Luo, Bei-Ping; Peter, Thomas

2008-01-01

Since 2000, stratospheric aerosol levels have been relatively stable and at the lowest levels observed in the historical record. Given the challenges of making satellite measurements of aerosol properties at these levels, we have performed a study of the sensitivity of the product to the major components of the processing algorithm used in the production of SAGE II aerosol extinction measurements and the retrieval process that produces the operational surface area density (SAD) product. We find that the aerosol extinction measurements, particularly at 1020 nm, remain robust and reliable at the observed aerosol levels. On the other hand, during background periods, the SAD operational product has an uncertainty of at least a factor of 2 during due to the lack of sensitivity to particles with radii less than 100 nm.

Susceptibility of Aerosol Retrievals to Cirrus Contamination during the BASE-ASIA Campaign and at Global View

NASA Astrophysics Data System (ADS)

Huang, J.; Hsu, C.; Tsay, S.; Jeong, M.; Holben, B.; Berkoff, T.; Welton, E. J.

2010-12-01

Cirrus clouds, particularly subvisual high thin cirrus with low optical thickness, are difficult to be screened out in the operational aerosol retrieval algorithms. In this study, we jointly used ground measurements (AERONET, aerosol robotic network; MPLNET, micro-pulse lidar network) and satellite data (MODIS, moderate resolution imaging spectroradiometer; CALIPSO, cloud-aerosol lidar and infrared pathfinder satellite observations) to closely examine the susceptibility of satellite retrieved and ground measured aerosol optical thickness (AOT) to cirrus contamination. Special cases were selected at Phimai (102.56°E, 15.18°N, also known as Pimai), Thailand, during the Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment (BASE-ASIA) campaign (February-May 2006). By taking advantage of space-borne and ground lidars in detecting cirrus clouds, we conducted the statistical analysis by matching up concurrent cirrus and aerosol observations at four levels: MPLNET vs AERONET, MPLNET vs MODIS, CALIPSO vs AERONET, and CALIPSO vs MODIS. Results suggest that the susceptibility of current operational AERONET and MODIS AOT products to cirrus features strong regional and seasonal variability, particularly in cirrus prevailing regions. The values of AOT and aerosol particle size appear to be larger for cirrus-susceptible cases than those for confidently non-cirrus cases, a possible signature of cirrus contamination. To further assess cirrus-screening algorithms, we tested 8 MODIS-derived cirrus screening parameters against lidar observations for their performance and robustness on cirrus screening: apparent reflectance at 1.38μm (R1.38), cirrus reflectance at 0.66μm (CR0.66), CR0.66 cirrus flag, reflectance ratio between 1.38μm and 0.66μm (RR1.38/0.66), reflectance ratio between 1.38μm and 1.24μm (RR1.38/1.24), brightness temperature difference between 8.6μm and 11μm (BTD8.6-11), brightness temperature difference between 11μm and 12μm (BTD11-12), and cloud phase infrared approach (CPIR). The quantitative findings from the study suggest that particular caution and careful evaluations on cirrus contamination in the satellite and ground AOT measurements should be exercised before they are used for aerosol related climatic forcing studies.

Aerosol observation using multi-wavelength Mie-Raman lidars of the Ad-Net and aerosol component analysis

NASA Astrophysics Data System (ADS)

Nishizawa, Tomoaki; Sugimoto, Nobuo; Shimizu, Atsushi; Uno, Itsushi; Hara, Yukari; Kudo, Rei

2018-04-01

We deployed multi-wavelength Mie-Raman lidars (MMRL) at three sites of the AD-Net and have conducted continuous measurements using them since 2013. To analyze the MMRL data and better understand the externally mixing state of main aerosol components (e.g., dust, sea-salt, and black carbon) in the atmosphere, we developed an integrated package of aerosol component retrieval algorithms, which have already been developed or are being developed, to estimate vertical profiles of the aerosol components. This package applies to the other ground-based lidar network data (e.g., EARLINET) and satellite-borne lidar data (e.g., CALIOP/CALIPSO and ATLID/EarthCARE) as well as the other lidar data of the AD-Net.

Simultaneous Retrieval of Aerosol Optical Depth and Surface Reflectance over Land within Short Temporal Interval Using MSG Data

NASA Astrophysics Data System (ADS)

Li, C.; Xue, Y.; Li, Y. J.; Yang, L. K.; Hou, T. T.

2012-04-01

Aerosols cause a major uncertainty in the research of climatology and global change, whereas satellite aerosol remote sensing over land still remains a big challenge. Due to their short time repeat cycle, geostationary satellites are capable of monitoring the temporal features of aerosols, while its limited number of visible bands is an obstacle. On the other hand, a main uncertainty in aerosol retrieval is the difficulty to separate the relatively weaker contribution of the atmosphere to the signal received by the satellite from the contribution of the Earth's surface. In this paper, an analytical retrieval strategy is presented to solve the both problems above. For the lack of surface reflectance, we use the Ross-Li BRDF (Bidirectional Reflectance Distribution Function) model and assume that the surface reflective property changes mainly due to the change of illumination geometry in a short time interval while the kernals of Ross-Li model remain the same. For the limited visible band, we take advantage of the Aerosol Optical Depth (AOD) consistence within short distances, thus to reduce the number of unknown parameters. A parameterization of the atmospheric radiative transfer model is used which is proved to be proper to retrieve aerosol and surface parameters by sensitivity analysis. Taking the three kernels of kernel-driven BRDF model and AOD as unknown parameters and based on prior knowledge of aerosol types, a series of nonlinear equations can be established then. Both AOD and surface reflectance can be obtained by using a numerical method to solve these equations. By applying this method, called LABITS-MSG (Land Aerosol and Bidirectional reflectance Inversion by Time Series technique for MSG), to data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations on board Meteosat Second Generation (MSG), we obtain regional maps of AOD and surface reflectance in July 11, 2010 within a temporal interval of as short as 1 hour, and a spatial resolution of 10 km. Preliminary validation results by comparing our retrieved AOD with Aerosol Robotic Network (AERONET) data show that the correlation coefficient R is about 0.81, the root-mean-square error (RMSE) is less than 0.1, and the uncertainty is found to be Δτ = ± 0.05 ± 0.20τ. Time serial comparison of MSG and AERONET AODs on Granada site also shows a good fitting. To conclude, this algorithm shows its potential to retrieve real-time AODs over land from geostationary satellites.

Remote sensing of atmospheric aerosols with the SPEX spectropolarimeter

NASA Astrophysics Data System (ADS)

van Harten, G.; Rietjens, J.; Smit, M.; Snik, F.; Keller, C. U.; di Noia, A.; Hasekamp, O.; Vonk, J.; Volten, H.

2013-12-01

Characterizing atmospheric aerosols is key to understanding their influence on climate through their direct and indirect radiative forcing. This requires long-term global coverage, at high spatial (~km) and temporal (~days) resolution, which can only be provided by satellite remote sensing. Aerosol load and properties such as particle size, shape and chemical composition can be derived from multi-wavelength radiance and polarization measurements of sunlight that is scattered by the Earth's atmosphere at different angles. The required polarimetric accuracy of ~10^(-3) is very challenging, particularly since the instrument is located on a rapidly moving platform. Our Spectropolarimeter for Planetary EXploration (SPEX) is based on a novel, snapshot spectral modulator, with the intrinsic ability to measure polarization at high accuracy. It exhibits minimal instrumental polarization and is completely solid-state and passive. An athermal set of birefringent crystals in front of an analyzer encodes the incoming linear polarization into a sinusoidal modulation in the intensity spectrum. Moreover, a dual beam implementation yields redundancy that allows for a mutual correction in both the spectrally and spatially modulated data to increase the measurement accuracy. A partially polarized calibration stimulus has been developed, consisting of a carefully depolarized source followed by tilted glass plates to induce polarization in a controlled way. Preliminary calibration measurements show an accuracy of SPEX of well below 10^(-3), with a sensitivity limit of 2*10^(-4). We demonstrate the potential of the SPEX concept by presenting retrievals of aerosol properties based on clear sky measurements using a prototype satellite instrument and a dedicated ground-based SPEX. The retrieval algorithm, originally designed for POLDER data, performs iterative fitting of aerosol properties and surface albedo, where the initial guess is provided by a look-up table. The retrieved aerosol properties, including aerosol optical thickness, single scattering albedo, size distribution and complex refractive index, will be compared with the on-site AERONET sun-photometer, lidar, particle counter and sizer, and PM10 and PM2.5 monitoring instruments. Retrievals of the aerosol layer height based on polarization measurements in the O2A absorption band will be compared with lidar profiles. Furthermore, the possibility of enhancing the retrieval accuracy by replacing the look-up table with a neural network based initial guess will be discussed, using retrievals from simulated ground-based data.

Evaluation of applicability of high-resolution multiangle imaging photo-polarimetric observations for aerosol atmospheric correction

NASA Astrophysics Data System (ADS)

Kalashnikova, Olga; Garay, Michael; Xu, Feng; Diner, David; Seidel, Felix

2016-07-01

Multiangle spectro-polarimetric measurements have been advocated as an additional tool for better understanding and quantifying the aerosol properties needed for atmospheric correction for ocean color retrievals. The central concern of this work is the assessment of the effects of absorbing aerosol properties on remote sensing reflectance measurement uncertainty caused by neglecting UV-enhanced absorption of carbonaceous particles and by not accounting for dust nonsphericity. In addition, we evaluate the polarimetric sensitivity of absorbing aerosol properties in light of measurement uncertainties achievable for the next generation of multi-angle polarimetric imaging instruments, and demonstrate advantages and disadvantages of wavelength selection in the UV/VNIR range. In this work a vector Markov Chain radiative transfer code including bio-optical models was used to quantitatively evaluate in water leaving radiances between atmospheres containing realistic UV-enhanced and non-spherical aerosols and the SEADAS carbonaceous and dust-like aerosol models. The phase matrices for the spherical smoke particles were calculated using a standard Mie code, while those for non-spherical dust particles were calculated using the numerical approach developed for modeling dust for the AERONET network of ground-based sunphotometers. As a next step, we have developed a retrieval code that employs a coupled Markov Chain (MC) and adding/doubling radiative transfer method for joint retrieval of aerosol properties and water leaving radiance from Airborne Multiangle SpectroPolarimetric Imager-1 (AirMSPI-1) polarimetric observations. The AirMSPI-1 instrument has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI typically acquires observations of a target area at 9 view angles between ±67° at 10 m resolution. AirMSPI spectral channels are centered at 355, 380, 445, 470, 555, 660, and 865 nm, with 470, 660, and 865 reporting linear polarization. We tested prototype retrievals by comparing the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentrations from Airborne Multiangle SpectroPolarimetric Imager-1 (AirMSPI-1) observations to values reported by the USC SeaPRISM AERONET-OC site off the coast of California. The retrieval was then applied to a variety of costal regions in California to evaluate variability in the water-leaving radiance under different atmospheric conditions. We will present results, and will discuss algorithm sensitivity and potential applications for future space-borne coastal monitoring.

Automated retrieval of cloud and aerosol properties from the ARM Raman lidar, part 1: feature detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorsen, Tyler J.; Fu, Qiang; Newsom, Rob K.

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 expectedmore » 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.« less

Aerosol optical properties inferred from in-situ and path-averaged measurements

NASA Astrophysics Data System (ADS)

van Binsbergen, Sven A.; Grossmann, Peter; Cohen, Leo H.; van Eijk, Alexander M. J.; Stein, Karin U.

2017-09-01

This paper compares in-situ and path-averaged measurements of the electro-optical transmission, with emphasis on aerosol effects. The in-situ sensors consisted of optical particle counters (OPC) and a visibility meter, the path-averaged data was provided by a 7-wavelength transmissometer (MSRT) and a scintillometer (BLS). Data was collected at a test site in Northern Germany. A retrieval algorithm was developed to infer characteristics of the aerosol size distribution (Junge approximation) from the MSRT data. A comparison of the various sensors suggests that the optical particle counters are over-optimistic in their estimate of the transmission.

Derivation of cloud-free-region atmospheric motion vectors from FY-2E thermal infrared imagery

NASA Astrophysics Data System (ADS)

Wang, Zhenhui; Sui, Xinxiu; Zhang, Qing; Yang, Lu; Zhao, Hang; Tang, Min; Zhan, Yizhe; Zhang, Zhiguo

2017-02-01

The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors (AMVs) in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference (NEdT) performance of FY-2E split window (10.3-11.5 μm, 11.6-12.8 μm) channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference (SD) methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the "truth". The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.

Ozone and Aerosol Retrieval from Backscattered Ultraviolet Radiation

NASA Technical Reports Server (NTRS)

Bhartia, Pawan K.

2004-01-01

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.

Photopolarimetric Retrievals of Snow Properties

NASA Technical Reports Server (NTRS)

Ottaviani, M.; van Diedenhoven, B.; Cairns, B.

2015-01-01

Polarimetric observations of snow surfaces, obtained in the 410-2264 nm range with the Research Scanning Polarimeter onboard the NASA ER-2 high-altitude aircraft, are analyzed and presented. These novel measurements are of interest to the remote sensing community because the overwhelming brightness of snow plagues aerosol and cloud retrievals based on airborne and spaceborne total reflection measurements. The spectral signatures of the polarized reflectance of snow are therefore worthwhile investigating in order to provide guidance for the adaptation of algorithms currently employed for the retrieval of aerosol properties over soil and vegetated surfaces. At the same time, the increased information content of polarimetric measurements allows for a meaningful characterization of the snow medium. In our case, the grains are modeled as hexagonal prisms of variable aspect ratios and microscale roughness, yielding retrievals of the grains' scattering asymmetry parameter, shape and size. The results agree with our previous findings based on a more limited data set, with the majority of retrievals leading to moderately rough crystals of extreme aspect ratios, for each scene corresponding to a single value of the asymmetry parameter.

Monitoring and Quantifying Particles Emissions around Industrial Sites with Scanning Doppler Lidar

NASA Astrophysics Data System (ADS)

Thobois, L.; Royer, P.; Parmentier, R.; Brooks, M.; Knoepfle, A.; Alexander, J.; Stidwell, P.; Kumar, R.

2018-04-01

Scanning Coherent Doppler Lidars have been used over the last decade for measuring wind for applications in wind energy [1], meteorology [2] and aviation [3]. They allow for accurate measurements of wind speeds up to a distance of 10 km based on the Doppler shift effect of aerosols. The signal reflectivity (CNR or Carrier-to-Noise Ratio) profiles can also be retrieved from the strength of the Lidar signal. In this study, we will present the developments of algorithm for retrieving aerosol optical properties like the relative attenuated backscatter coefficient and the mass concentration of particles. The use of these algorithms during one operational trial in Point Samson, Western Australia to monitor fugitive emissions over a mine will be presented. This project has been initiated by the Australian Department of Environment Regulations to better determine the impact of the Port on the neighboring town. During the trial in Summer, the strong impact of turbulence refractive index on Lidar performances has been observed. Multiple methodologies have been applied to reduce this impact with more or less success. At the end, a dedicated setup and configuration have been established that allow to properly observe the plumes of the mine with the scanning Lidar. The Lidar data has also been coupled to beta attenuation in-situ sensors for retrieving mass concentration maps. A few case of dispersion of plumes will be presented showing the necessity to combine both the wind and aerosol data.

Arrange and average algorithm for the retrieval of aerosol parameters from multiwavelength high-spectral-resolution lidar/Raman lidar data.

PubMed

Chemyakin, Eduard; Müller, Detlef; Burton, Sharon; Kolgotin, Alexei; Hostetler, Chris; Ferrare, Richard

2014-11-01

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 unsupervised processing; the arrange and average algorithm can be used as a preclassifier to further improve its speed and precision. First tests of the performance of arrange and average algorithm are encouraging. We used a set of 48 different monomodal particle size distributions, 4 real parts and 15 imaginary parts of the complex refractive index. All in all we tested 2880 different optical data sets for 0%, 10%, and 20% Gaussian measurement noise (one-standard deviation). In the case of the "3β+2α" configuration with 10% measurement noise, we retrieve the particle effective radius to within 27% for 1964 (68.2%) of the test optical data sets. The number concentration is obtained to 76%, the surface area concentration to 16%, and the volume concentration to 30% precision. The "3β" configuration performs significantly poorer. The performance of the "3β+1α" and "2β+1α" configurations is intermediate between the "3β+2α" and the "3β."

Spaceborne Remote Sensing of Aerosol Type: Global Distribution, Model Evaluation and Translation into Chemical Speciation

NASA Astrophysics Data System (ADS)

Kacenelenbogen, M. S.; Tan, Q.; Johnson, M. S.; Burton, S. P.; Redemann, J.; Hasekamp, O. P.; Dawson, K. W.; Hair, J. W.; Ferrare, R. A.; Butler, C. F.; Holben, B. N.; Beyersdorf, A. J.; Ziemba, L. D.; Froyd, K. D.; Dibb, J. E.; Shingler, T.; Sorooshian, A.; Jimenez, J. L.; Campuzano Jost, P.; Jacob, D.; Kim, P. S.; Travis, K.; Lacagnina, C.

2016-12-01

It is essential to evaluate and refine aerosol classification methods applied to passive satellite remote sensing. We have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground-based passive remote sensing instruments [1]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrial/developed economy, urban-industrial/developing economy, dark biomass smoke, light biomass smoke and pure marine. We apply the SCMC method to inversions from the ground-based AErosol RObotic NETwork (AERONET [2]) and retrievals from the space-borne Polarization and Directionality of Earth's Reflectances instrument (POLDER, [3]). The POLDER retrievals that we use differ from the standard POLDER retrievals [4] as they make full use of multi-angle, multispectral polarimetric data [5]. We analyze agreement in the aerosol types inferred from both AERONET and POLDER and evaluate GEOS-Chem [6] simulations over the globe. Finally, we use in-situ observations from the SEAC4RS airborne field experiment to bridge the gap between remote sensing-inferred qualitative SCMC aerosol types and their corresponding quantitative chemical speciation. We apply the SCMC method to airborne in-situ observations from the NASA Langley Aerosol Research Group Experiment (LARGE, [7]) and the Differential Aerosol Sizing and Hygroscopicity Spectrometer Probe (DASH-SP, [8]) instruments; we then relate each coarsely defined SCMC type to a sum of percentage of individual aerosol species, using in-situ observations from the Particle Analysis by Laser Mass Spectrometry (PALMS, [9]), the Soluble Acidic Gases and Aerosol (SAGA, [10]), and the High - Resolution Time - of - Flight Aerosol Mass Spectrometer (HR ToF AMS, [11]). [1] Russell P. B., et al., JGR, 119.16 (2014) [2] Holben B. N., et al., RSE, 66.1 (1998) [3] Tanré D., et al., AMT, 4.7 (2011) [4] Deuzé J. L., et al., JGR, 106.D5 (2001) [5] Hasekamp O. P., et al., JGR, 116.D14 (2011) [6] Bey I., et al., JGR, 106.D19 (2001) [7] Ziemba L. D., et al., GRL, 40.2 (2013) [8] Sorooshian A., et al., AST, 42.6 (2008) [9] Murphy D. M., et al., JGR, 111.D23 (2006) [10] Dibb J. E., et al., JGR, 108.D21 (2003) [11] DeCarlo P. F., et al., AC, 78.24 (2006)

Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements

NASA Technical Reports Server (NTRS)

Vaughan, Mark A.; Powell, Kathleen A.; Kuehn, Ralph E.; Young, Stuart A.; Winker, David M.; Hostetler, Chris A.; Hunt, William H.; Liu, Zhaoyan; McGill, Matthew J.; Getzewich, Brian J.

2009-01-01

Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth s atmosphere is critical in assessing the planet s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanner into an iterated multiresolution spatial averaging scheme. This paper provides an in-depth overview of the architecture and performance of the SIBYL algorithm. It begins with a brief review of the theory of target detection in noise-contaminated signals, and an enumeration of the practical constraints levied on the retrieval scheme by the design of the lidar hardware, the geometry of a space-based remote sensing platform, and the spatial variability of the measurement targets. Detailed descriptions are then provided for both the adaptive threshold algorithm used to detect features of interest within individual lidar profiles and the fully automated multiresolution averaging engine within which this profile scanner functions. The resulting fusion of profile scanner and averaging engine is specifically designed to optimize the trade-offs between the widely varying signal-to-noise ratio of the measurements and the disparate spatial resolutions of the detection targets. Throughout the paper, specific algorithm performance details are illustrated using examples drawn from the existing CALIPSO dataset. Overall performance is established by comparisons to existing layer height distributions obtained by other airborne and space-based lidars.

Ground based measurements on reflectance towards validating atmospheric correction algorithms on IRS-P6 AWiFS data

NASA Astrophysics Data System (ADS)

Rani Sharma, Anu; Kharol, Shailesh Kumar; Kvs, Badarinath; Roy, P. S.

In Earth observation, the atmosphere has a non-negligible influence on the visible and infrared radiation which is strong enough to modify the reflected electromagnetic signal and at-target reflectance. Scattering of solar irradiance by atmospheric molecules and aerosol generates path radiance, which increases the apparent surface reflectance over dark surfaces while absorption by aerosols and other molecules in the atmosphere causes loss of brightness to the scene, as recorded by the satellite sensor. In order to derive precise surface reflectance from satellite image data, it is indispensable to apply the atmospheric correction which serves to remove the effects of molecular and aerosol scattering. In the present study, we have implemented a fast atmospheric correction algorithm to IRS-P6 AWiFS satellite data which can effectively retrieve surface reflectance under different atmospheric and surface conditions. The algorithm is based on MODIS climatology products and simplified use of Second Simulation of Satellite Signal in Solar Spectrum (6S) radiative transfer code, which is used to generate look-up-tables (LUTs). The algorithm requires information on aerosol optical depth for correcting the satellite dataset. The proposed method is simple and easy to implement for estimating surface reflectance from the at sensor recorded signal, on a per pixel basis. The atmospheric correction algorithm has been tested for different IRS-P6 AWiFS False color composites (FCC) covering the ICRISAT Farm, Patancheru, Hyderabad, India under varying atmospheric conditions. Ground measurements of surface reflectance representing different land use/land cover, i.e., Red soil, Chick Pea crop, Groundnut crop and Pigeon Pea crop were conducted to validate the algorithm and found a very good match between surface reflectance and atmospherically corrected reflectance for all spectral bands. Further, we aggregated all datasets together and compared the retrieved AWiFS reflectance with aggregated ground measurements which showed a very good correlation of 0.96 in all four spectral bands (i.e. green, red, NIR and SWIR). In order to quantify the accuracy of the proposed method in the estimation of the surface reflectance, the root mean square error (RMSE) associated to the proposed method was evaluated. The analysis of the ground measured versus retrieved AWiFS reflectance yielded smaller RMSE values in case of all four spectral bands. EOS TERRA/AQUA MODIS derived AOD exhibited very good correlation of 0.92 and the data sets provides an effective means for carrying out atmospheric corrections in an operational way. Keywords: Atmospheric correction, 6S code, MODIS, Spectroradiometer, Sun-Photometer

Retrieval of Aerosol Phase Function and Polarized Phase Function from Polarization of Skylight for Different Observation Geometries

NASA Astrophysics Data System (ADS)

Li, L.; Qie, L. L.; Xu, H.; Li, Z. Q.

2018-04-01

The phase function and polarized phase function are important optical parameters, which describe scattering properties of atmospheric aerosol particles. Polarization of skylight induced by the scattering processes is sensitive to the scattering properties of aerosols. The Stokes parameters I, Q, U and the polarized radiance Lp of skylight measured by the CIMEL dual-polar sun-sky radiometer CE318- DP can be use to retrieve the phase function and polarized phase function, respectively. Two different observation geometries (i.e., the principal plane and almucantar) are preformed by the CE318-DP to detect skylight polarization. Polarization of skylight depends on the illumination and observation geometries. For the same solar zenith angle, retrievals of the phase function and the polarized phase function are still affected by the observation geometry. The performance of the retrieval algorithm for the principal plane and almucantar observation geometries was assessed by the numerical experiments at two typical high and low sun's positions (i.e. solar zenith angles are equal to 45° and 65°). Comparing the results for the principal plane and almucantar geometries, it is recommended to utilize the principal plane observations to retrieve the phase function when the solar zenith angle is small. The Stokes parameter U and the polarized radiance Lp from the almucantar observations are suggested to retrieve the polarized phase function, especially for short wavelength channels (e.g., 440 and 500 nm).

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert

2011-01-01

We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

Linear Estimation of Particle Bulk Parameters from Multi-Wavelength Lidar Measurements

NASA Technical Reports Server (NTRS)

Veselovskii, Igor; Dubovik, Oleg; Kolgotin, A.; Korenskiy, M.; Whiteman, D. N.; Allakhverdiev, K.; Huseyinoglu, F.

2012-01-01

An algorithm for linear estimation of aerosol bulk properties such as particle volume, effective radius and complex refractive index from multiwavelength lidar measurements is presented. The approach uses the fact that the total aerosol concentration can well be approximated as a linear combination of aerosol characteristics measured by multiwavelength lidar. Therefore, the aerosol concentration can be estimated from lidar measurements without the need to derive the size distribution, which entails more sophisticated procedures. The definition of the coefficients required for the linear estimates is based on an expansion of the particle size distribution in terms of the measurement kernels. Once the coefficients are established, the approach permits fast retrieval of aerosol bulk properties when compared with the full regularization technique. In addition, the straightforward estimation of bulk properties stabilizes the inversion making it more resistant to noise in the optical data. Numerical tests demonstrate that for data sets containing three aerosol backscattering and two extinction coefficients (so called 3 + 2 ) the uncertainties in the retrieval of particle volume and surface area are below 45% when input data random uncertainties are below 20 %. Moreover, using linear estimates allows reliable retrievals even when the number of input data is reduced. To evaluate the approach, the results obtained using this technique are compared with those based on the previously developed full inversion scheme that relies on the regularization procedure. Both techniques were applied to the data measured by multiwavelength lidar at NASA/GSFC. The results obtained with both methods using the same observations are in good agreement. At the same time, the high speed of the retrieval using linear estimates makes the method preferable for generating aerosol information from extended lidar observations. To demonstrate the efficiency of the method, an extended time series of observations acquired in Turkey in May 2010 was processed using the linear estimates technique permitting, for what we believe to be the first time, temporal-height distributions of particle parameters.

Type of Aerosols Determination Over Malaysia by AERONET Data

NASA Astrophysics Data System (ADS)

Lim, H.; Tan, F.; Abdullah, K.; Holben, B. N.

2013-12-01

Aerosols are one of the most interesting studies by the researchers due to the complicated of their characteristic and are not yet well quantified. Besides that there still have huge uncertainties associated with changes in Earth's radiation budget. The previous study by other researchers shown a lot of difficulties and challenges in quantifying aerosol influences arise. As well as the heterogeneity from the aerosol loading and properties: spatial, temporal, size, and composition. In this study, we were investigated the aerosol characteristics over two regions with different environmental conditions and aerosol sources contributed. The study sites are Penang and Kuching, Malaysia where ground-based AErosol RObotic NETwork (AERONET) sun-photometer was deployed. The types of the aerosols for both study sites were identified by analyzing aerosol optical depth, angstrom parameter and spectral de-convolution algorithm product from sun-photometer. The analysis was carried out associated with the in-situ meteorological data of relative humidity, visibility and air pollution index. The major aerosol type over Penang found in this study was hydrophobic aerosols. Whereas the hydrophilic type of the aerosols was highly distributed in Kuching. The major aerosol size distributions for both regions were identified in this study. The result also shows that the aerosol optical properties were affected by the types and characteristic of aerosols. Therefore, in this study we generated an algorithm to determine the aerosols in Malaysia by considered the environmental factors. From this study we found that the source of aerosols should always being consider in to retrieve the accurate information of aerosol for air quality study.

Retrieval of volcanic ash height from satellite-based infrared measurements

NASA Astrophysics Data System (ADS)

Zhu, Lin; Li, Jun; Zhao, Yingying; Gong, He; Li, Wenjie

2017-05-01

A new algorithm for retrieving volcanic ash cloud height from satellite-based measurements is presented. This algorithm, which was developed in preparation for China's next-generation meteorological satellite (FY-4), is based on volcanic ash microphysical property simulation and statistical optimal estimation theory. The MSG satellite's main payload, a 12-channel Spinning Enhanced Visible and Infrared Imager, was used as proxy data to test this new algorithm. A series of eruptions of Iceland's Eyjafjallajökull volcano during April to May 2010 and the Puyehue-Cordón Caulle volcanic complex eruption in the Chilean Andes on 16 June 2011 were selected as two typical cases for evaluating the algorithm under various meteorological backgrounds. Independent volcanic ash simulation training samples and satellite-based Cloud-Aerosol Lidar with Orthogonal Polarization data were used as validation data. It is demonstrated that the statistically based volcanic ash height algorithm is able to rapidly retrieve volcanic ash heights, globally. The retrieved ash heights show comparable accuracy with both independent training data and the lidar measurements, which is consistent with previous studies. However, under complicated background, with multilayers in vertical scale, underlying stratus clouds tend to have detrimental effects on the final retrieval accuracy. This is an unresolved problem, like many other previously published methods using passive satellite sensors. Compared with previous studies, the FY-4 ash height algorithm is independent of simultaneous atmospheric profiles, providing a flexible way to estimate volcanic ash height using passive satellite infrared measurements.

Combing Visible and Infrared Spectral Tests for Dust Identification

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Levy, Robert; Kleidman, Richard; Remer, Lorraine; Mattoo, Shana

2016-01-01

The MODIS Dark Target aerosol algorithm over Ocean (DT-O) uses spectral reflectance in the visible, near-IR and SWIR wavelengths to determine aerosol optical depth (AOD) and Angstrom Exponent (AE). Even though DT-O does have "dust-like" models to choose from, dust is not identified a priori before inversion. The "dust-like" models are not true "dust models" as they are spherical and do not have enough absorption at short wavelengths, so retrieved AOD and AE for dusty regions tends to be biased. The inference of "dust" is based on postprocessing criteria for AOD and AE by users. Dust aerosol has known spectral signatures in the near-UV (Deep blue), visible, and thermal infrared (TIR) wavelength regions. Multiple dust detection algorithms have been developed over the years with varying detection capabilities. Here, we test a few of these dust detection algorithms, to determine whether they can be useful to help inform the choices made by the DT-O algorithm. We evaluate the following methods: The multichannel imager (MCI) algorithm uses spectral threshold tests in (0.47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 micrometer) channels and spatial uniformity test [Zhao et al., 2010]. The NOAA dust aerosol index (DAI) uses spectral contrast in the blue channels (412nm and 440nm) [Ciren and Kundragunta, 2014]. The MCI is already included as tests within the "Wisconsin" (MOD35) Cloud mask algorithm.

Effective resolution concepts for lidar observations

NASA Astrophysics Data System (ADS)

Iarlori, M.; Madonna, F.; Rizi, V.; Trickl, T.; Amodeo, A.

2015-05-01

Since its first establishment in 2000, EARLINET (European Aerosol Research Lidar NETwork) has been devoted to providing, through its database, exclusively quantitative aerosol properties, such as aerosol backscatter and aerosol extinction coefficients, the latter only for stations able to retrieve it independently (from Raman or High Spectral Resolution Lidars). As these coefficients are provided in terms of vertical profiles, EARLINET database must also include the details on the range resolution of the submitted data. In fact, the algorithms used in the lidar data analysis often alter the spectral content of the data, mainly working as low pass filters with the purpose of noise damping. Low pass filters are mathematically described by the Digital Signal Processing (DSP) theory as a convolution sum. As a consequence, this implies that each filter's output, at a given range (or time) in our case, will be the result of a linear combination of several lidar input data relative to different ranges (times) before and after the given range (time): a first hint of loss of resolution of the output signal. The application of filtering processes will also always distort the underlying true profile whose relevant features, like aerosol layers, will then be affected both in magnitude and in spatial extension. Thus, both the removal of noise and the spatial distortion of the true profile produce a reduction of the range resolution. This paper provides the determination of the effective resolution (ERes) of the vertical profiles of aerosol properties retrieved starting from lidar data. Large attention has been addressed to provide an assessment of the impact of low-pass filtering on the effective range resolution in the retrieval procedure.

Effective resolution concepts for lidar observations

NASA Astrophysics Data System (ADS)

Iarlori, M.; Madonna, F.; Rizi, V.; Trickl, T.; Amodeo, A.

2015-12-01

Since its establishment in 2000, EARLINET (European Aerosol Research Lidar NETwork) has provided, through its database, quantitative aerosol properties, such as aerosol backscatter and aerosol extinction coefficients, the latter only for stations able to retrieve it independently (from Raman or high-spectral-resolution lidars). These coefficients are stored in terms of vertical profiles, and the EARLINET database also includes the details of the range resolution of the vertical profiles. In fact, the algorithms used in the lidar data analysis often alter the spectral content of the data, mainly acting as low-pass filters to reduce the high-frequency noise. Data filtering is described by the digital signal processing (DSP) theory as a convolution sum: each filtered signal output at a given range is the result of a linear combination of several signal input data samples (relative to different ranges from the lidar receiver), and this could be seen as a loss of range resolution of the output signal. Low-pass filtering always introduces distortions in the lidar profile shape. Thus, both the removal of high frequency, i.e., the removal of details up to a certain spatial extension, and the spatial distortion produce a reduction of the range resolution. This paper discusses the determination of the effective resolution (ERes) of the vertical profiles of aerosol properties retrieved from lidar data. Large attention has been dedicated to providing an assessment of the impact of low-pass filtering on the effective range resolution in the retrieval procedure.

Observing a Severe Dust Storm Event over China using Multiple Satellite Data

NASA Astrophysics Data System (ADS)

Xu, Hui; Xue, Yong; Guang, Jie; Mei, Linlu

2013-04-01

A severe dust storm (SDS) event occurred from 19 to 21 March 2010 in China, originated in western China and Mongolia and propagated into eastern/southern China, affecting human's life in a large area. As reported by National Meteorological Center of CMA (China Meteorological Administration), 16 provinces (cities) of China were hit by the dust storm (Han et al., 2012). Satellites can provide global measurements of desert dust and have particular importance in remote areas where there is a lack of in situ measurements (Carboni et al., 2012). To observe a dust, it is necessary to estimate the spatial and temporal distributions of dust aerosols. An important metric in the characterisation of aerosol distribution is the aerosol optical depth (AOD) (Adhikary et al., 2008). Satellite aerosol retrievals have improved considerably in the last decade, and numerous satellite sensors and algorithms have been generated. Reliable retrievals of dust aerosol over land were made using POLarization and Directionality of the Earth's Reflectance instrument-POLDER (Deuze et al., 2001), Moderate Resolution Imaging Spectroradiometer-MODIS (Kaufman et al., 1997; Hsu et al., 2004), Multiangle Imaging Spectroradiometer-MISR (Martonchik et al., 1998), and Cloud-aerosol Lidar and infrared pathfinder satellite observations (CALIPSO). However, intercomparison exercises (Myhre et al., 2005) have revealed that discrepancies between satellite measurements are particularly large during events of heavy aerosol loading. The reason is that different AOD retrieval algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. For MISR, POLDER and MODIS instrument, the multi-angle approaches, the polarization measurements and single-view approaches were used to retrieval AOD respectively. Combining of multi-sensor AOD data can potentially create a more consistent, reliable and complete picture of the space-time evolution of dust storms (Ehlers, 1991). In order to make use of all useful satellite data to observe one severe dust procedure, multi-sensor and multi-algorithm AOD data were combined. In this paper, the satellite instruments considered are MISR, MODIS, POLDER and CALIPSO. In addition, air pollution index (API) data were used to validate the satellite AOD data. We chose the study region with a longitude range from 76°N to 136°N and a latitude range from 15°E to 60°E. Index Terms—aerosol optical depth, dust, satellite REFERENCES Adhikary, B., Kulkarni, S., Dallura A., Tang, Y., Chai, T., Leung, L. R., Qian, Y., Chung, C. E., Ramanathan,V. and Carmichael, G. R., 2008, A regional scale chemical transport modeling of Asian aerosols with data assimilation of AOD observations using optimal interpolation technique, Atmospheric Environment, 42(37), 8600-8615. Carboni, E., Thomas, G. E., Sayer, A. M., Siddans, R., Poulsen, C. A., Grainger, R. G., Ahn, C., Antoine, D., Bevan, S., Braak, R., Brindley, H., DeSouza-Machado, S., Deuz'e, J. L., Diner, D., Ducos, F., Grey, W., Hsu, C., Kalashnikova, O. V., Kahn, R., North, P. R. J., Salustro, C., Smith, A., Tanr'e, D., Torres, O., and Veihelmann, B., 2012, Intercomparison of desert dust optical depth from satellite measurements, Atmospheric Measurement Techniques, 5, 1973-2002. Deuze', J. L., Bre'on, F. M., Devaux, C., Goloub, Herman, M., Lafrance, B., Maignan, F., Marchand, A.,Nadal, F., Perry, G., and Tanre', D., 2001, Remote sensing of aerosols over land surfaces from POLDER-ADEOS-1 polarized measurements, Journal of Geophysical Research, 106(D5), 4913-4926. Ehlers, M., 1991, Multisensor image fusion techniques in remote sensing, ISPRS Journal of Photogrammetry and Remote Sensing, 46, 19-30. Han, X., Ge. C., Tao, J. H., Zhang, M. G., Zhang, R. J., 2012, Air Quality Modeling for a Strong Dust Event in East Asia in March 2010, Aerosol and Air Quality Research, 12: 615-628. Hsu, N. C., Tsay, S. C., King, M. D. and Herman, J. R., 2004, Aerosol Properties over Bright-Reflecting Source Regions, IEEE Transactions on Geoscience and Remote Sensing, 42(3), 557-569. Martonchik, J. V., Diner, D. J., Kahn, R., Ackerman, T. P., Verstraete, M. M., Pinty, B., and Gordon, H. R., 1998, Techniques for the retrieval of aerosol properties over land and ocean using multiangle imaging, IEEE Transactions on Geoscience and Remote Sensing, 36(4), 1212-1227. Myhre, G., Stordal, F., Johnsrud, M., Diner, D. J., Geogdzhayev, I. V., Haywood, J. M., Holben, B. N., Holzer-Popp, T., Ignatov, A., Kahn, R. A., Kaufman, Y. J., Loeb, N., Martonchik, J. V., Mishchenko, M. I., Nalli, N. R., Remer, L. A., Schroedter-Homscheidt, M., Tanr'e, D., Torres, O., and Wang, M., 2005, Intercomparison of satellite retrieved aerosol optical depth over ocean during the period September 1997 to December 2000, Atmospheric Chemistry and Physics, 5, 1697-1719. Kaufman, Y.J., Tanre', D., Remer, L.A., Vermote, E.F., Chu, A., and Holben, B.N., 1997, Operationalremote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer, Journal of Geophysical Research, 102(D14), 17,051-17,067.

Constraints on Global Aerosol Types: Past, Present, and Near-Future

NASA Astrophysics Data System (ADS)

Kahn, Ralph

2014-05-01

Although the recent IPCC fifth assessment report (AR5) suggests that confidence in estimated direct aerosol radiative forcing (DARF) is high, indications are that there is little agreement among current climate models about the global distribution of aerosol single-scattering albedo (SSA). SSA must be associated with specific surface albedo and aerosol optical depth (AOD) values to calculate DARF with confidence, and global-scale constraints on aerosol type, including SSA, are poor at present. Yet, some constraints on aerosol type have been demonstrated for several satellite instruments, including the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR). The time-series of approximately once-weekly, global MISR observations has grown to about 14 years. The MISR capability amounts to three-to-five bins in particle size, two-to-four bins in SSA, and spherical vs. non-spherical particle distinctions, under good retrieval conditions. As the record of coincident, suborbital validation data has increased steadily, it has become progressively more feasible to assess and to improve the operational algorithm constraints on aerosol type. This presentation will discuss planned refinements to the MISR operational algorithm, and will highlight recent efforts at using MISR results to help better represent wildfire smoke, volcanic ash, and urban pollution in climate models.

Use of the ARM Measurement of Spectral Zenith Radiance For Better Understanding Of 3D Cloud-Radiation Processes and Aerosol-Cloud Interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiu, Jui-Yuan

2010-10-19

Our proposal focuses on cloud-radiation processes in a general 3D cloud situation, with particular emphasis on cloud optical depth and effective particle size. We also focus on zenith radiance measurements, both active and passive. The proposal has three main parts. Part One exploits the "solar-background" mode of ARM lidars to allow them to retrieve cloud optical depth not just for thin clouds but for all clouds. This also enables the study of aerosol cloud interactions with a single instrument. Part Two exploits the large number of new wavelengths offered by ARM's zenith-pointing ShortWave Spectrometer (SWS), especially during CLASIC, to developmore » better retrievals not only of cloud optical depth but also of cloud particle size. We also propose to take advantage of the SWS's 1 Hz sampling to study the "twilight zone" around clouds where strong aerosol-cloud interactions are taking place. Part Three involves continuing our cloud optical depth and cloud fraction retrieval research with ARM's 2NFOV instrument by, first, analyzing its data from the AMF-COPS/CLOWD deployment, and second, making our algorithms part of ARM's operational data processing.« less

Comparison of MAX-DOAS profiling algorithms during CINDI-2 - Part 2: trace gases

NASA Astrophysics Data System (ADS)

Hendrick, Francois; Friess, Udo; Tirpitz, Lukas; Apituley, Arnoud; Van Roozendael, Michel; Kreher, Karin; Richter, Andreas; Wagner, Thomas

2017-04-01

The second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) took place at the Cabauw Experimental Site for Atmospheric Research (CESAR; Utrecht area, The Netherlands) from 25 August until 7 October 2016. CINDI-2 was aiming at assessing the consistency of MAX-DOAS slant column density measurements of tropospheric species (NO2, HCHO, O3, and O4) relevant for the validation of future ESA atmospheric Sentinel missions, through coordinated operation of a large number of DOAS and MAXDOAS instruments from all over the world. An important objective of the campaign was to study the relationship between remote-sensing column and profile measurements of the above species and collocated reference ancillary observations. For this purpose, the CINDI-2 Profiling Task Team (CPTT) was created, involving 22 groups performing aerosol and trace gas vertical profile inversion using dedicated MAX-DOAS profiling algorithms, as well as the teams responsible for ancillary profile and surface concentration measurements (NO2 analysers, NO2 sondes, NO2 and Raman LIDARs, CAPS, Long-Path DOAS, sunphotometer, nephelometer, etc). The main purpose of the CPTT is to assess the consistency of the different profiling tools for retrieving aerosol extinction and trace gas vertical profiles through comparison exercises using commonly defined settings and to validate the retrievals with correlative observations. In this presentation, we give an overview of the MAX-DOAS vertical profile comparison results, focusing on NO2 and HCHO, the aerosol retrievals being presented in a companion abstract led by U. Frieß. The performance of the different algorithms is investigated with respect to the various sky and weather conditions and aerosol loadings encountered during the campaign. The consistency between optimal-estimation-based and parameterized profiling tools is also evaluated for these different conditions, together with the level of agreement with available NO2 and HCHO ancillary observations. This comparison study will be put in the perspective of the development of a centralized MAX-DOAS processing system within the framework of the ESA Fiducial Reference Measurements (FRM) project.

Uncertainties of aerosol retrieval from neglecting non-sphericity of dust aerosols

NASA Astrophysics Data System (ADS)

Li, Chi; Xue, Yong; Yang, Leiku; Guang, Jie

2013-04-01

The Mie theory is conventionally applied to calculate aerosol optical properties in satellite remote sensing applications, while dust aerosols cannot be well modeled by the Mie calculation for their non-sphericity. It has been cited in Mishchenko et al. (1995; 1997) that neglecting non-sphericity can severely influence aerosol optical depth (AOD, ?) retrieval in case of dust aerosols because of large difference of phase functions under spherical and non-spherical assumptions, whereas this uncertainty has not been thoroughly studied. This paper aims at a better understanding of uncertainties on AOD retrieval caused by aerosol non-sphericity. A dust aerosol model with known refractive index and size distribution is generated from long-term AERONET observations since 1999 over China. Then aerosol optical properties, such as the extinction, phase function, single scattering albedo (SSA) are calculated respectively in the assumption of spherical and non-spherical aerosols. Mie calculation is carried out for spherical assumption, meanwhile for non-spherical aerosol modeling, we adopt the pre-calculated scattering kernels and software package presented by Dubovik et al. (2002; 2006), which describes dust as a shape mixture of randomly oriented polydisperse spheroids. Consequently we generate two lookup tables (LUTspheric and LUTspheroid) from simulated satellite received reflectance at top of atmosphere (TOA) under varieties of observing conditions and aerosol loadings using Second Simulation of a Satellite Signal in the Solar Spectrum - Vector (6SV) code. All the simulations are made at 550 nm, and for simplicity the Lambertian surface is assumed. Using the obtained LUTs we examine the differences of TOA reflectance (Δ?TOA = ?spheric - ?spheroid) under different surface reflectance and aerosol loadings. Afterwards AOD is retrieved using LUTspheric from the simulated TOA reflectance by LUTspheroid in order to detect the retrieval errors (Δ? = ?retreived -?input) induced 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 Travis, L. D. (1995). Nonsphericity of dust-like aerosols: Implications for aerosol remote sensing and climate modeling, Geophyscal Research Letters, 22, 1077- 1080. Mishchenko, M. I., Travis, L. D., Kahn, R. A., and West, R. A. (1997). Modeling phase functions for dustlike tropospheric aerosols using a shape mixture of randomly oriented polydisperse spheroids, Journal of Geophysical Research, 102, 16831- 16847.

Martian atmospheric O3 retrieval development for the NOMAD-UVIS spectrometer

NASA Astrophysics Data System (ADS)

Hewson, W.; Mason, J. P.; Leese, M.; Hathi, B.; Holmes, J.; Lewis, S. R.; Iriwin, P. G. J.; Patel, M. R.

2017-09-01

The composition of atmospheric trace gases and aerosols is a highly variable and poorly constrained component of the martian atmosphere, and by affecting martian climate and UV surface dose, represents a key parameter in the assessment of suitability for martian habitability. The ExoMars Trace Gas Orbiter (TGO) carries the Open University (OU) designed Ultraviolet and VIsible Spectrometer (UVIS) instrument as part of the Belgian-led Nadir and Occultation for MArs Discovery (NOMAD) spectrometer suite. NOMAD will begin transmitting science observations of martian surface and atmosphere back-scattered UltraViolet (UV) and visible radiation in Spring 2018, which will be processed to derive spatially and temporally averaged atmospheric trace gas and aerosol concentrations, intended to provide a better understanding of martian atmospheric photo-chemistry and dynamics, and will also improve models of martian atmospheric chemistry, climate and habitability. Work presented here illustrates initial development and testing of the OU's new retrieval algorithm for determining O3 and aerosol concentrations from the UVIS instrument.

Comparison of full-sky polarization and radiance observations to radiative transfer simulations which employ AERONET products.

PubMed

Pust, Nathan J; Dahlberg, Andrew R; Thomas, Michael J; Shaw, Joseph A

2011-09-12

Visible-band and near infrared polarization and radiance images measured with a ground-based full-sky polarimeter are compared against a successive orders of scattering (SOS) radiative transfer model for 2009 summer cloud-free days in Bozeman, Montana, USA. The polarimeter measures radiance and polarization in 10-nm bands centered at 450 nm, 490 nm, 530 nm, 630 nm, and 700 nm. AERONET products are used to represent aerosols in the SOS model, while MISR satellite BRF products are used for the surface reflectance. While model results generally agree well with observation, the simulated degree of polarization is typically higher than observed data. Potential sources of this difference may include cloud contamination and/or underestimation of the AERONET-retrieved aerosol real refractive index. Problems with the retrieved parameters are not unexpected given the low aerosol optical depth range (0.025 to 0.17 at 500 nm) during the study and the corresponding difficulties that these conditions pose to the AERONET inversion algorithm.

A climatology of fine absorbing biomass burning, urban and industrial aerosols detected from satellites

NASA Astrophysics Data System (ADS)

Kalaitzi, Nikoleta; Hatzianastassiou, Nikos; Gkikas, Antonis; Papadimas, Christos D.; Torres, Omar; Mihalopoulos, Nikos

2017-04-01

Natural biomass burning (BB) along with anthropogenic urban and industrial aerosol particles, altogether labeled here as BU aerosols, contain black and brown carbon which both absorb strongly the solar radiation. Thus, BU aerosols warm significantly the atmosphere also causing adjustments to cloud properties, which traditionally are known as cloud indirect and semi-direct effects. Given the role of the effects of BU aerosols for contemporary and future climate change, and the uncertainty associated with BU, both ascertained by the latest IPCC reports, there is an urgent need for improving our knowledge on the spatial and temporal variability of BU aerosols all over the globe. Over the last few decades, thanks to the rapid development of satellite observational techniques and retrieval algorithms it is now possible to detect BU aerosols based on satellite measurements. However, care must be taken in order to ensure the ability to distinguish BU from other aerosol types usually co-existing in the Earth's atmosphere. In the present study, an algorithm is presented, based on a synergy of different satellite measurements, aiming to identify and quantify BU aerosols over the entire globe and during multiple years. The objective is to build a satellite-based climatology of BU aerosols intended for use for various purposes. The produced regime, namely the spatial and temporal variability of BU aerosols, emphasizes the BU frequency of occurrence and their intensity, in terms of aerosol optical depth (AOD). The algorithm is using the following aerosol optical properties describing the size and atmospheric loading of BU aerosols: (i) spectral AOD, (ii) Ångström Exponent (AE), (iii) Fine Fraction (FF) and (iv) Aerosol Index (AI). The relevant data are taken from Collection 006 MODIS-Aqua, except for AI which is taken from OMI-Aura. The identification of BU aerosols by the algorithm is based on a specific thresholding technique, with AI≥1.5, AE≥1.2 and FF≥0.6 threshold values. The study spans the 11-year period 2005-2015, which enables to examine the inter-annual variability and possible changes of BU aerosols. Emphasis is given on specific world areas known to be sources of BU emissions. An effort is also made to separate with the algorithm the BB from BU aerosols, aiming to create a satellite database of biomass burning aerosols. The results of the algorithm, as to BB aerosols and the ability to separate them, are evaluated through comparisons against the global satellite databases of MODIS active fire counts as well as AIRS carbon monoxide (CO), which is a key indicator of presence of biomass burning activities. The algorithm estimates frequencies of occurrence of BU aerosols reaching up to 10 days/year and AOD values up to 1.5 or even larger. The results indicate the existence of seasonal cycles of biomass burning in south and central Africa as well as in South America (Amazonia), with highest BU frequencies during June-September, December-February and August-October, respectively, whereas they successfully reproduce features like the export of African BB aerosols into the Atlantic Ocean.

Satellite remote sensing of volcanic plume from Infrared Atmospheric Sounding Interferometer (IASI): results for recent eruptions.

NASA Astrophysics Data System (ADS)

Carboni, Elisa; Smith, Andrew; Grainger, Roy; Dudhia, Anu; Thomas, Gareth; Peters, Daniel; Walker, Joanne; Siddans, Richard

2013-04-01

The IASI high resolution infrared spectra is exploited to study volcanic emission of ash and sulphur dioxide (SO2). IASI is a Fourier transform spectrometer that covers the spectral range 645 to 2760 cm-1 (3.62-15.5 μm). The IASI field of view consists of four circles of 12 km inside a square of 50 x 50 km, and nominally it can achieve global coverage in 12 hours. The thermal infrared spectra of volcanic plumes shows a rapid variation with wavelength due to absorption lines from atmospheric and volcanic gases as well as broad scale features principally due to particulate absorption. IASI spectra also contain information about the atmospheric profile (temperature, gases, aerosol and cloud) and radiative properties of the surface. In particular the ash signature depends on the composition and size distribution of ash particles as well on their altitude. The sulphur dioxide signature depends on SO2 amount and vertical profile. The results from a new algorithm for the retrieval of sulphur dioxide (SO2) from the Infrared Atmospheric Sounding Interferometer (IASI) data will be presented. The SO2 retrieval follows the method of Carboni et al. (2012) and retrieves SO2 amount and altitude together with a pixel by pixel comprehensive error budget analysis. IASI brightness temperature spectra are analysed, to retrieve ash properties, using an optimal estimation retrieval scheme and a forward model based on RTTOV. The RTTOV output for a clean atmosphere (containing gas but not cloud or aerosol/ash) will be combined with an ash layer using the same scheme as for the Oxford-RAL Retrieval of Aerosol and Cloud (ORAC) algorithm. We exploit the IASI measurements in the atmospheric window spectral range together with the SO2 absorption bands (at 7.3 and 8.7 μm) to study the evolution of ash and SO2 volcanic plume for recent volcanic eruptions case studies. Particular importance is given to investigation of mismatching between the forward model and IASI measurements which can be due, for example, to imperfect knowledge of ash optical properties.

Retrieval of Vertical Aerosol and Trace Gas Distributions from Polarization Sensitive Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS)

NASA Astrophysics Data System (ADS)

Tirpitz, Jan-Lukas; Friess, Udo; Platt, Ulrich

2017-04-01

An accurate knowledge of the vertical distribution of trace gases and aerosols is crucial for our understanding of the chemical and dynamical processes in the lower troposphere. Their accurate determination is typically only possible by means of laborious and expensive airborne in-situ measurements but in the recent decades, numerous promising ground-based remote sensing approaches have been developed. One of them is to infer vertical distributions from "Differential Optical Absorption Spectroscopy" (DOAS) measurements. DOAS is a technique to analyze UV- and visible radiation spectra of direct or scattered sunlight, which delivers information on different atmospheric parameters, integrated over the light path from space to the instrument. An appropriate set of DOAS measurements, recorded under different viewing directions (Multi-Axis DOAS) and thus different light path geometries, provides information on the atmospheric state. The vertical profiles of aerosol properties and trace gas concentrations can be retrieved from such a set by numerical inversion techniques, incorporating radiative transfer models. The information content of measured data is rarely sufficient for a well-constrained retrieval, particularly for atmospheric layers above 1 km. We showed in first simulations that, apart from spectral properties, the polarization state of skylight is likely to provide a significant amount of additional information on the atmospheric state and thus to enhance retrieval quality. We present first simulations, expectations and ideas on how to implement and characterize a polarization sensitive Multi-Axis DOAS instrument and a corresponding profile retrieval algorithm.

EARLINET Single Calculus Chain - overview on methodology and strategy

NASA Astrophysics Data System (ADS)

D'Amico, G.; Amodeo, A.; Baars, H.; Binietoglou, I.; Freudenthaler, V.; Mattis, I.; Wandinger, U.; Pappalardo, G.

2015-11-01

In this paper we describe the EARLINET Single Calculus Chain (SCC), a tool for the automatic analysis of lidar measurements. The development of this tool started in the framework of EARLINET-ASOS (European Aerosol Research Lidar Network - Advanced Sustainable Observation System); it was extended within ACTRIS (Aerosol, Clouds and Trace gases Research InfraStructure Network), and it is continuing within ACTRIS-2. The main idea was to develop a data processing chain that allows all EARLINET stations to retrieve, in a fully automatic way, the aerosol backscatter and extinction profiles starting from the raw lidar data of the lidar systems they operate. The calculus subsystem of the SCC is composed of two modules: a pre-processor module which handles the raw lidar data and corrects them for instrumental effects and an optical processing module for the retrieval of aerosol optical products from the pre-processed data. All input parameters needed to perform the lidar analysis are stored in a database to keep track of all changes which may occur for any EARLINET lidar system over the time. The two calculus modules are coordinated and synchronized by an additional module (daemon) which makes the whole analysis process fully automatic. The end user can interact with the SCC via a user-friendly web interface. All SCC modules are developed using open-source and freely available software packages. The final products retrieved by the SCC fulfill all requirements of the EARLINET quality assurance programs on both instrumental and algorithm levels. Moreover, the manpower needed to provide aerosol optical products is greatly reduced and thus the near-real-time availability of lidar data is improved. The high-quality of the SCC products is proven by the good agreement between the SCC analysis, and the corresponding independent manual retrievals. Finally, the ability of the SCC to provide high-quality aerosol optical products is demonstrated for an EARLINET intense observation period.

Coupled Retrieval of Aerosol Properties and Surface Reflection Using the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, F.; van Harten, G.; Kalashnikova, O. V.; Diner, D. J.; Seidel, F. C.; Garay, M. J.; Dubovik, O.

2016-12-01

The Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI) [1] has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 10 km and is observed from 9 view angles between ±67° off of nadir. We have developed an efficient and flexible code that uses the information content of AirMSPI data for a coupled retrieval of aerosol properties and surface reflection. The retrieval was built based on the multi-pixel optimization concept [2], with the use of a hybrid radiative transfer model [3] that combines the Markov Chain [4] and adding/doubling methods [5]. The convergence and robustness of our algorithm is ensured by applying constraints on (a) the spectral variation of the Bidirectional Polarization Distribution Function (BPDF) and angular shape of the Bidirectional Reflectance Distribution Function (BRDF); (b) the spectral variation of aerosol optical properties; and (c) the spatial variation of aerosol parameters across neighboring image pixels. Our retrieval approach has been tested using over 20 AirMSPI datasets having low to moderately high aerosol loadings ( 0.02550-nm< 0.45) and acquired during several field campaigns. Results are compared with AERONET aerosol reference data. We also explore the benefits of AirMSPI's ultraviolet and polarimetric bands as well as the use of multiple view angles. References[1]. D. J. Diner, et al. Atmos. Meas. Tech. 6, 1717 (2013). [2]. O. Dubovik et al. Atmos. Meas. Tech. 4, 975 (2011). [3]. F. Xu et al. Atmos. Meas. Tech. 9, 2877 (2016). [4]. F. Xu et al. Opt. Lett. 36, 2083 (2011). [5]. J. E. Hansen and L.D. Travis. Space Sci. Rev. 16, 527 (1974).

What We are Learning from (and About) the 10 Plus Year MISR Aerosol Data Record

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2010-01-01

Having a 10+ year data record from the Multi-angle Imaging SpectroRadiometer (MISR) significantly improves our opportunities to validate the retrieved aerosol optical depth (AOD) and especially particle microphysical property products. It also begins to raise the possibility of using the data to look for changes or even trends, at least on a regional basis. Further, we have had the opportunity to expand the database of wildfire smoke plume heights derived from the multiangle observations. This presentation will review the latest aerosol validation results and algorithm upgrades under consideration by the MISR team, and will summarize the current status of MISR global aerosol air mass type, and regional dust transport and smoke injection height products. The strengths and limitations of these data for constraining aerosol transport model simulations will receive special emphasis.

Performance Evaluation of Machine Learning Methods for Leaf Area Index Retrieval from Time-Series MODIS Reflectance Data

PubMed Central

Wang, Tongtong; Xiao, Zhiqiang; Liu, Zhigang

2017-01-01

Leaf area index (LAI) is an important biophysical parameter and the retrieval of LAI from remote sensing data is the only feasible method for generating LAI products at regional and global scales. However, most LAI retrieval methods use satellite observations at a specific time to retrieve LAI. Because of the impacts of clouds and aerosols, the LAI products generated by these methods are spatially incomplete and temporally discontinuous, and thus they cannot meet the needs of practical applications. To generate high-quality LAI products, four machine learning algorithms, including back-propagation neutral network (BPNN), radial basis function networks (RBFNs), general regression neutral networks (GRNNs), and multi-output support vector regression (MSVR) are proposed to retrieve LAI from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data in this study and performance of these machine learning algorithms is evaluated. The results demonstrated that GRNNs, RBFNs, and MSVR exhibited low sensitivity to training sample size, whereas BPNN had high sensitivity. The four algorithms performed slightly better with red, near infrared (NIR), and short wave infrared (SWIR) bands than red and NIR bands, and the results were significantly better than those obtained using single band reflectance data (red or NIR). Regardless of band composition, GRNNs performed better than the other three methods. Among the four algorithms, BPNN required the least training time, whereas MSVR needed the most for any sample size. PMID:28045443

Performance Evaluation of Machine Learning Methods for Leaf Area Index Retrieval from Time-Series MODIS Reflectance Data.

PubMed

Wang, Tongtong; Xiao, Zhiqiang; Liu, Zhigang

2017-01-01

Leaf area index (LAI) is an important biophysical parameter and the retrieval of LAI from remote sensing data is the only feasible method for generating LAI products at regional and global scales. However, most LAI retrieval methods use satellite observations at a specific time to retrieve LAI. Because of the impacts of clouds and aerosols, the LAI products generated by these methods are spatially incomplete and temporally discontinuous, and thus they cannot meet the needs of practical applications. To generate high-quality LAI products, four machine learning algorithms, including back-propagation neutral network (BPNN), radial basis function networks (RBFNs), general regression neutral networks (GRNNs), and multi-output support vector regression (MSVR) are proposed to retrieve LAI from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data in this study and performance of these machine learning algorithms is evaluated. The results demonstrated that GRNNs, RBFNs, and MSVR exhibited low sensitivity to training sample size, whereas BPNN had high sensitivity. The four algorithms performed slightly better with red, near infrared (NIR), and short wave infrared (SWIR) bands than red and NIR bands, and the results were significantly better than those obtained using single band reflectance data (red or NIR). Regardless of band composition, GRNNs performed better than the other three methods. Among the four algorithms, BPNN required the least training time, whereas MSVR needed the most for any sample size.

Effects of local meteorology and aerosols on ozone and nitrogen dioxide retrievals from OMI and pandora spectrometers in Maryland, USA during DISCOVER-AQ 2011.

PubMed

Reed, Andra J; Thompson, Anne M; Kollonige, Debra E; Martins, Douglas K; Tzortziou, Maria A; Herman, Jay R; Berkoff, Timothy A; Abuhassan, Nader K; Cede, Alexander

An analysis is presented for both ground- and satellite-based retrievals of total column ozone and nitrogen dioxide levels from the Washington, D.C., and Baltimore, Maryland, metropolitan area during the NASA-sponsored July 2011 campaign of D eriving I nformation on S urface CO nditions from Column and VER tically Resolved Observations Relevant to A ir Q uality (DISCOVER-AQ). Satellite retrievals of total column ozone and nitrogen dioxide from the Ozone Monitoring Instrument (OMI) on the Aura satellite are used, while Pandora spectrometers provide total column ozone and nitrogen dioxide amounts from the ground. We found that OMI and Pandora agree well (residuals within ±25 % for nitrogen dioxide, and ±4.5 % for ozone) for a majority of coincident observations during July 2011. Comparisons with surface nitrogen dioxide from a Teledyne API 200 EU NO x Analyzer showed nitrogen dioxide diurnal variability that was consistent with measurements by Pandora. However, the wide OMI field of view, clouds, and aerosols affected retrievals on certain days, resulting in differences between Pandora and OMI of up to ±65 % for total column nitrogen dioxide, and ±23 % for total column ozone. As expected, significant cloud cover (cloud fraction >0.2) was the most important parameter affecting comparisons of ozone retrievals; however, small, passing cumulus clouds that do not coincide with a high (>0.2) cloud fraction, or low aerosol layers which cause significant backscatter near the ground affected the comparisons of total column nitrogen dioxide retrievals. Our results will impact post-processing satellite retrieval algorithms and quality control procedures.

Global aerosol typing from a combination of A-Train satellite observations in clear-sky and above clouds

NASA Astrophysics Data System (ADS)

Kacenelenbogen, M. S.; Russell, P. B.; Vaughan, M.; Redemann, J.; Shinozuka, Y.; Livingston, J. M.; Zhang, Q.

2014-12-01

According to the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), the model estimates of Radiative Forcing due to aerosol-radiation interactions (RFari) for individual aerosol types are less certain than the total RFari [Boucher et al., 2013]. For example, the RFari specific to Black Carbon (BC) is uncertain due to an underestimation of its mass concentration near source regions [Koch et al., 2009]. Several recent studies have evaluated chemical transport model (CTM) predictions using observations of aerosol optical properties such as Aerosol Optical Depth (AOD) or Single Scattering Albedo (SSA) from satellite or ground-based instruments (e.g., Huneeus et al., [2010]). However, most passive remote sensing instruments fail to provide a comprehensive assessment of the particle type without further analysis and combination of measurements. To improve the predictions of aerosol composition in CTMs, we have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground based passive remote sensing instruments [Russell et al., 2014]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrial/developed economy, urban-industrial/developing economy, dark biomass smoke, light biomass smoke and pure marine. First, we apply the SCMC method to five years of clear-sky space-borne POLDER observations over Greece. We then use the aerosol extinction and SSA spectra retrieved from a combination of MODIS, OMI and CALIOP clear-sky observations to infer the aerosol type over the globe in 2007. Finally, we will extend the spaceborne aerosol classification from clear-sky to above low opaque water clouds using a combination of CALIOP AOD and backscatter observations and OMI absorption AOD values from near-by clear-sky pixels.

Modeling of Aerosol Optical Depth Variability during the 1998 Canadian Forest Fire Smoke Event

NASA Astrophysics Data System (ADS)

Aubé, M.; O`Neill, N. T.; Royer, A.; Lavoué, D.

2003-04-01

Monitoring of aerosol optical depth (AOD) is of particular importance due to the significant role of aerosols in the atmospheric radiative budget. Up to now the two standard techniques used for retrieving AOD are; (i) sun photometry which provides measurements of high temporal frequency and sparse spatial frequency, and (ii) satellite based approaches such as based DDV (Dense Dark Vegetation) inversion algorithms which extract AOD over dark targets in remotely sensed imagery. Although the latter techniques allow AOD retrieval over appreciable spatial domains, the irregular spatial pattern of dark targets and the typically low repeat frequencies of imaging satellites exclude the acquisition of AOD databases on a continuous spatio-temporal basis. We attempt to fill gaps in spatio-temporal AOD measurements using a new methodology that links AOD measurements and particulate matter Transport Model using a data assimilation approach. This modelling package (AODSEM for Aerosol Optical Depth Spatio-temporal Evolution Model) uses a size and aerosol type segregated semi-Lagrangian-Eulerian trajectory algorithm driven by analysed meteorological data. Its novelty resides in the fact that the model evolution is tied to both ground based and satellite level AOD measurement and all physical processes have been optimized to track this important but crude parameter. We applied this methodology to a significant smoke event that occurred over Canada in august 1998. The results show the potential of this approach inasmuch as residuals between AODSEM assimilated analysis and measurements are smaller than typical errors associated to remotely sensed AOD (satellite or ground based). The AODSEM assimilation approach also gives better results than classical interpolation techniques. This improvement is especially evident when the available number of AOD measurements is small.

Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

NASA Technical Reports Server (NTRS)

Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

2010-01-01

Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

Aircraft Measurements of Aerosol Phase Matrix Elements by the Polarized Imaging Nephelometer (Invited)

NASA Astrophysics Data System (ADS)

Dolgos, G.; Martins, J.; Espinosa, R.; Dubovik, O.; Beyersdorf, A. J.; Ziemba, L. D.; Hair, J. W.

2013-12-01

Aerosols have a significant impact on the radiative balance and water cycle of our planet through influencing atmospheric radiation. Remote sensing of aerosols relies on scattering phase matrix information to retrieve aerosol properties with frequent global coverage, the assumed phase matrices must be validated by measurements. At the Laboratory for Aerosols, Clouds and Optics (LACO) at the University of Maryland, Baltimore County (UMBC) we developed a new technique to directly measure the aerosol phase function (P11), the degree of linear polarization of the scattered light (-P12/P11), and the volume scattering coefficient (SCAT). We designed and built a portable instrument called the Polarized Imaging Nephelometer (PI-Neph), shown in Figure 1 (a). The PI-Neph successfully participated in dozens of flights of the NASA Development and Evaluation of satellite ValidatiOn Tools by Experimenters (DEVOTE) project and the Deep Convective Clouds and Chemistry (DC3) project and the January and February deployment of the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (Discover-AQ) mission. The ambient aerosol enters the PI-Neph through an inlet and the sample is illuminated by laser light (wavelength of 532 nm); the scattered light is imaged by a stationary wide field of view camera in the scattering angle range of 2° to 178° (in some cases stray light limited the scattering angle range to 3° to 176°). Data for P11, P12, and SCAT were taken every 12 seconds, example datasets from DEVOTE of P11 times SCAT are shown on Figure 1 (b). The talk will highlight results from the three field deployments and will show microphysical retrievals from the scattering data. The size distribution and the average complex refractive index of the ambient aerosol ensemble can be retrieved from the data by an algorithm similar to that of AERONET, as illustrated in Figure 1 (c). Particle sphericity can potentially be retrieved as well, this will be investigated in the near future. The instrument will be applied to the validation of aerosol retrievals of AERONET and airborne polarimeters. The PI-Neph instrument has recently been upgraded to three wavelengths, and a second instrument was built as well. The LACO group is active in developing an advanced open path version of the Imaging Nephelometer that does not require an inlet but measures undisturbed particles under the aircraft wing. Figure 1. (a) The Polarized Imaging Nephelometer instrument inside the B200 aircraft of NASA Langley. (b) Phase function times volume scattering coefficient data from DEVOTE. (c) Retrievals of particle size distribution based on the data in panel (b).

Towards a true aerosol-and-cloud retrieval scheme

NASA Astrophysics Data System (ADS)

Thomas, Gareth; Poulsen, Caroline; Povey, Adam; McGarragh, Greg; Jerg, Matthias; Siddans, Richard; Grainger, Don

2014-05-01

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.

Retrieval of aerosol optical depth over bare soil surfaces using time series of MODIS imagery

NASA Astrophysics Data System (ADS)

Yuan, Zhengwu; Yuan, Ranyin; Zhong, Bo

2014-11-01

Aerosol Optical Depth (AOD) is one of the key parameters which can not only reflect the characterization of atmospheric turbidity, but also identify the climate effects of aerosol. The current MODIS aerosol estimation algorithm over land is based on the "dark-target" approach which works only over densely vegetated surfaces. For non-densely vegetated surfaces (such as snow/ice, desert, and bare soil surfaces), this method will be failed. In this study, we develop an algorithm to derive AOD over the bare soil surfaces. Firstly, this method uses the time series of MODIS imagery to detect the " clearest" observations during the non-growing season in multiple years for each pixel. Secondly, the "clearest" observations after suitable atmospheric correction are used to fit the bare soil's bidirectional reflectance distribution function (BRDF) using Kernel model. As long as the bare soil's BRDF is established, the surface reflectance of "hazy" observations can be simulated. Eventually, the AOD over the bare soil surfaces are derived. Preliminary validation results by comparing with the ground measurements from AERONET at Xianghe sites show a good agreement.

Polarimetric method of estimation of vertical aerosol distribution in application to observations of ozone and NO2

NASA Technical Reports Server (NTRS)

Elansky, Nikolay F.; Kadyshevich, Elena A.; Savastyuk, Vladimir V.

1994-01-01

The degree of polarization of skylight at the zenith during twilight depends on the aerosol content in the atmosphere. The long-term observations at the high-mountain research station 'Kislovodsk' (North Caucasus) have shown that the variation of the degree of polarization after the eruption of the El Chichon volcano can serve as the effective parameter characterizing the vertical aerosol stratification in the atmosphere. The results of the measurements are confirmed by the numerical calculations. The algorithm of the retrieval of the vertical aerosol distribution on the base of the measurements of the degree of polarization is proposed. This method can be applied for the increasing of the precision of O3, NO2, and other gas content measurements.

A Climatology of Global Aerosol Mixtures to Support Sentinel-5P and Earthcare Mission Applications

NASA Astrophysics Data System (ADS)

Taylor, M.; Kazadzis, S.; Amaridis, V.; Kahn, R. A.

2015-11-01

Since constraining aerosol type with satellite remote sensing continues to be a challenge, we present a newly derived global climatology of aerosol mixtures to support atmospheric composition studies that are planned for Sentinel-5P and EarthCARE.The global climatology is obtained via application of iterative cluster analysis to gridded global decadal and seasonal mean values of the aerosol optical depth (AOD) of sulfate, biomass burning, mineral dust and marine aerosol as a proportion of the total AOD at 500nm output from the Goddard Chemistry Aerosol Radiation and Transport (GOCART). For both the decadal and seasonal means, the number of aerosol mixtures (clusters) identified is ≈10. Analysis of the percentage contribution of the component aerosol types to each mixture allowed development of a straightforward naming convention and taxonomy, and assignment of primary colours for the generation of true colour-mixing and easy-to-interpret maps of the spatial distribution of clusters across the global grid. To further help characterize the mixtures, aerosol robotic network (AERONET) Level 2.0 Version 2 inversion products were extracted from each cluster‟s spatial domain and used to estimate climatological values of key optical and microphysical parameters.The aerosol type climatology represents current knowledge that would be enhanced, possibly corrected, and refined by high temporal and spectral resolution, cloud-free observations produced by Sentinel-5P and EarthCARE instruments. The global decadal mean and seasonal gridded partitions comprise a preliminary reference framework and global climatology that can help inform the choice of components and mixtures in aerosol retrieval algorithms used by instruments such as TROPOMI and ATLID, and to test retrieval results.

MPL-Net data products available at co-located AERONET sites and field experiment locations

NASA Astrophysics Data System (ADS)

Welton, E. J.; Campbell, J. R.; Berkoff, T. A.

2002-05-01

Micro-pulse lidar (MPL) systems are small, eye-safe lidars capable of profiling the vertical distribution of aerosol and cloud layers. There are now over 20 MPL systems around the world, and they have been used in numerous field experiments. A new project was started at NASA Goddard Space Flight Center in 2000. The new project, MPL-Net, is a coordinated network of long-time MPL sites. The network also supports a limited number of field experiments each year. Most MPL-Net sites and field locations are co-located with AERONET sunphotometers. At these locations, the AERONET and MPL-Net data are combined together to provide both column and vertically resolved aerosol and cloud measurements. The MPL-Net project coordinates the maintenance and repair for all instruments in the network. In addition, data is archived and processed by the project using common, standardized algorithms that have been developed and utilized over the past 10 years. These procedures ensure that stable, calibrated MPL systems are operating at sites and that the data quality remains high. Rigorous uncertainty calculations are performed on all MPL-Net data products. Automated, real-time level 1.0 data processing algorithms have been developed and are operational. Level 1.0 algorithms are used to process the raw MPL data into the form of range corrected, uncalibrated lidar signals. Automated, real-time level 1.5 algorithms have also been developed and are now operational. Level 1.5 algorithms are used to calibrate the MPL systems, determine cloud and aerosol layer heights, and calculate the optical depth and extinction profile of the aerosol boundary layer. The co-located AERONET sunphotometer provides the aerosol optical depth, which is used as a constraint to solve for the extinction-to-backscatter ratio and the aerosol extinction profile. Browse images and data files are available on the MPL-Net web-site. An overview of the processing algorithms and initial results from selected sites and field experiments will be presented. The capability of the MPL-Net project to produce automated real-time (next day) profiles of aerosol extinction will be shown. Finally, early results from Level 2.0 and Level 3.0 algorithms currently under development will be presented. The level 3.0 data provide continuous (day/night) retrievals of multiple aerosol and cloud heights, and optical properties of each layer detected.

Creating a consistent dark-target aerosol optical depth record from MODIS and VIIRS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Mattoo, S.; Munchak, L. A.; Patadia, F.; Holz, R.

2014-12-01

To answer fundamental questions about our changing climate, we must quantify how aerosols are changing over time. This is a global question that requires regional characterization, because in some places aerosols are increasing and in others they are decreasing. Although NASA's Moderate resolution Imaging Spectrometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, the creation of an aerosol climate data record (CDR) requires consistent multi-decadal data. With the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, there is potential to continue the MODIS aerosol time series. Yet, since the operational VIIRS aerosol product is produced by a different algorithm, it is not suitable to continue MODIS to create an aerosol CDR. Therefore, we have applied the MODIS Dark-target (DT) algorithm to VIIRS observations, taking into account the slight differences in wavelengths, resolutions and geometries between the two sensors. More specifically, we applied the MODIS DT algorithm to a dataset known as the Intermediate File Format (IFF), created by the University of Wisconsin. The IFF is produced for both MODIS and VIIRS, with the idea that a single (MODIS-like or ML) algorithm can be run either dataset, which can in turn be compared to the MODIS Collection 6 (M6) retrieval that is run on standard MODIS data. After minimizing or characterizing remaining differences between ML on MODIS-IFF (or ML-M) and M6, we have performed apples-to-apples comparison between ML-M and ML on VIIRS IFF (ML-V). Examples of these comparisons include time series of monthly global mean, monthly and seasonal global maps at 1° resolution, and collocations as compared to AERONET. We concentrate on the overlapping period January 2012 through June 2014, and discuss some of the remaining discrepancies between the ML-V and ML-M datasets.

Simulation of the Ozone Monitoring Instrument aerosol index using the NASA Goddard Earth Observing System aerosol reanalysis products

NASA Astrophysics Data System (ADS)

Colarco, Peter R.; Gassó, Santiago; Ahn, Changwoo; Buchard, Virginie; da Silva, Arlindo M.; Torres, Omar

2017-11-01

We provide an analysis of the commonly used Ozone Monitoring Instrument (OMI) aerosol index (AI) product for qualitative detection of the presence and loading of absorbing aerosols. In our analysis, simulated top-of-atmosphere (TOA) radiances are produced at the OMI footprints from a model atmosphere and aerosol profile provided by the NASA Goddard Earth Observing System (GEOS-5) Modern-Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). Having established the credibility of the MERRAero simulation of the OMI AI in a previous paper we describe updates in the approach and aerosol optical property assumptions. The OMI TOA radiances are computed in cloud-free conditions from the MERRAero atmospheric state, and the AI is calculated. The simulated TOA radiances are fed to the OMI near-UV aerosol retrieval algorithms (known as OMAERUV) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining to the OMI algorithm assumptions of the surface pressure, which are generally different from what the actual surface pressure of an observation is, and the other related to simplifying assumptions in the molecular atmosphere radiative transfer used in the OMI algorithms. Surface pressure assumptions lead to systematic biases in the OMAERUV AI, particularly over the oceans. Simplifications in the molecular radiative transfer lead to biases particularly in regions of topography intermediate to surface pressures of 600 and 1013.25 hPa. Generally, the errors in the OMI AI due to these considerations are less than 0.2 in magnitude, though larger errors are possible, particularly over land. We recommend that future versions of the OMI algorithms use surface pressures from readily available atmospheric analyses combined with high-spatial-resolution topographic maps and include more surface pressure nodal points in their radiative transfer lookup tables.

Evaluation of the OMI Cloud Pressures Derived from Rotational Raman Scattering by Comparisons with other Satellite Data and Radiative Transfer Simulations

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Joiner, Joanna; Spurr, Robert; Bhartia, Pawan K.; Levelt, Pieternel; Stephens, Graeme

2009-01-01

In this paper we examine differences between cloud pressures retrieved from the Ozone Monitoring Instrument (OMI) using the ultraviolet rotational Raman scattering (RRS) algorithm and those from the thermal infrared (IR) Aqua/MODIS. Several cloud data sets are currently being used in OMI trace gas retrieval algorithms including climatologies based on IR measurements and simultaneous cloud parameters derived from OMI. From a validation perspective, it is important to understand the OMI retrieved cloud parameters and how they differ with those derived from the IR. To this end, we perform radiative transfer calculations to simulate the effects of different geophysical conditions on the OMI RRS cloud pressure retrievals. We also quantify errors related to the use of the Mixed Lambert-Equivalent Reflectivity (MLER) concept as currently implemented of the OMI algorithms. Using properties from the Cloudsat radar and MODIS, we show that radiative transfer calculations support the following: (1) The MLER model is adequate for single-layer optically thick, geometrically thin clouds, but can produce significant errors in estimated cloud pressure for optically thin clouds. (2) In a two-layer cloud, the RRS algorithm may retrieve a cloud pressure that is either between the two cloud decks or even beneath the top of the lower cloud deck because of scattering between the cloud layers; the retrieved pressure depends upon the viewing geometry and the optical depth of the upper cloud deck. (3) Absorbing aerosol in and above a cloud can produce significant errors in the retrieved cloud pressure. (4) The retrieved RRS effective pressure for a deep convective cloud will be significantly higher than the physical cloud top pressure derived with thermal IR.

Evidence of a Weakly Absorbing Intermediate Mode of Aerosols in AERONET Data from Saharan and Sahelian Sites

NASA Technical Reports Server (NTRS)

Gianelli, Scott M.; Lacis, Andrew A.; Carlson, Barbara E.; Hameed, Sultan

2013-01-01

Accurate retrievals of aerosol size distribution are necessary to estimate aerosols' impact on climate and human health. The inversions of the Aerosol Robotic Network (AERONET) usually retrieve bimodal distributions. However, when the inversion is applied to Saharan and Sahelian dust, an additional mode of intermediate size between the coarse and fine modes is sometimes seen. This mode explains peculiarities in the behavior of the Angstrom exponent, along with the fine mode fraction retrieved using the spectral deconvolution algorithm, observed in a March 2006 dust storm. For this study, 15 AERONET sites in northern Africa and on the Atlantic are examined to determine the frequency and properties of the intermediate mode. The mode is observed most frequently at Ilorin in Nigeria. It is also observed at Capo Verde and multiple sites located within the Sahel but much less frequently at sites in the northern Sahara and the Canary Islands. The presence of the intermediate mode coincides with increases in Angstrom exponent, fine mode fraction, single-scattering albedo, and to a lesser extent percent sphericity. The Angstrom exponent decreases with increasing optical depth at most sites when the intermediate mode is present, but the fine mode fraction does not. Single-scattering albedo does not steadily decrease with fine mode fraction when the intermediate mode is present, as it does in typical mixtures of dust and biomass-burning aerosols. Continued investigation is needed to further define the intermediate mode's properties, determine why it differs from most Saharan dust, and identify its climate and health effects.

Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

NASA Technical Reports Server (NTRS)

Feng, Qian; Hsu, N. Christina; Yang, Ping; Tsay, Si-Chee

2011-01-01

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

Advancing Littoral Zone Aerosol Prediction via Holistic Studies in Regime-Dependent Flows: August 3-9, 2016 Middle East Dust Event

NASA Astrophysics Data System (ADS)

Solbrig, J. E.; Miller, S. D.; van den Heever, S. C.; Kreidenweis, S. M.; Oo, M. M.; Zupanski, M.; Zhang, J.; Wang, J.; Holz, R.; Albers, S. C.; Grasso, L. D.; Kliewer, A.; Bukowski, J.; Park, J.; Saleeby, S. M.; Wu, T. C.

2017-12-01

Coastal regions represent a complex environment for meteorological processes, their effect on aerosol distributions, and the resulting impacts of those aerosols. These regions are rife with discontinuities that make dynamical processes difficult to predict and confound optical retrieval algorithms with highly variable and poorly characterized backgrounds. Local dynamics can be complicated by interactions between maritime and continental airmasses and the presence of coastal terrain. Additionally, coastal shallow water and high-turbidity produce backgrounds with high water leaving radiance which biases results from remote sensing retrievals. Here we present the highlights of the first two years of work from a Multi-disciplinary University Research Initiative entitled Holistic Analysis of Aerosol in Littoral Environments (HAALE-MURI) with specific focus on a dust event that occurred during the period of August 3-9 2016. During this period, two large dust plumes were observed advecting across the Arabian Peninsula. The first, embedded in a dry airmass, moved across the peninsula from north-west to south-east. This plume eventually stalls as it encounters a moist airmass, likely driven by the sea breeze. Embedded in the moist airmass is a second dust plume lofted from Oman, which then advects northwards over the Persian Gulf. This case presents significant challenges for forecasting, remote sensing, and data assimilation due to a complex meteorological environment and variable coastal bright-water backgrounds. The project team, who endeavor to advance our fundamental understanding of the factors that govern aerosol distribution, optical properties, and microphysical properties in the coastal regions, have focused on this case as our first in-depth case study. We demonstrate new retrieval techniques during both day and night including retrievals over bright coastal waters, a novel approach to in-line data assimilation of aerosol properties including AOT, and the results of model sensitivity studies. We take a holistic approach to better understanding aerosol processes in a coupled system as opposed to stand-alone analyses that fail to account for the myriad of covariances that exist in any real-world scenario.

Satellite Remote Sensing of Aerosol Forcing

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Kaufman, Yoram; Ramaprasad, Jaya; Procopio, Aline; Levin, Zev

1999-01-01

The role of aerosol forcing remains one of the largest uncertainties in estimating man's impact on the global climate system. One school of thought suggests that remote sensing by satellite sensors will provide the data necessary to narrow these uncertainties. While satellite measurements of direct aerosol forcing appear to be straightforward, satellite measurements of aerosol indirect forcing will be more complicated. Pioneering studies identified indirect aerosol forcing using AVHRR data in the biomass burning regions of Brazil. We have expanded this analysis with AVHRR to include an additional year of data and assimilated water vapor fields. The results show similar latitudinal dependence as reported by Kaufman and Fraser, but by using water vapor observations we conclude that latitude is not a proxy for water vapor and the strength of the indirect effect is not correlated to water vapor amounts. In addition to the AVHRR study we have identified indirect aerosol forcing in Brazil at much smaller spatial scales using the MODIS Airborne Simulator. The strength of the indirect effect appears to be related to cloud type and cloud dynamics. There is a suggestion that some of the cloud dynamics may be influenced by smoke destabilization of the atmospheric column. Finally, this study attempts to quantify remote sensing limitations due to the accuracy limits of the retrieval algorithms. We use a combination of numerical aerosol transport models, ground-based AERONET data and ISCCP cloud climatology to determine how much of the forcing occurs in regions too clean to determine from satellite retrievals.

Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table

NASA Astrophysics Data System (ADS)

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

2016-07-01

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 the observation period.

Nowcast and Short-Term Forecast of Solar Radiation for Photovoltaic power and Solar thermal using 3rd generation geostationary satellite.

NASA Astrophysics Data System (ADS)

Takenaka, H.; Teruyuki, N.; Nakajima, T. Y.; Higurashi, A.; Hashimoto, M.; Suzuki, K.; Uchida, J.; Nagao, T. M.; Shi, C.; Inoue, T.

2017-12-01

It is important to estimate the earth's radiation budget accurately for understanding of climate. Clouds can cool the Earth by reflecting solar radiation but also maintain warmth by absorbing and emitting terrestrial radiation. similarly aerosols also have an effect on radiation budget by absorption and scattering of Solar radiation. In this study, we developed the high speed and accurate algorithm for shortwave (SW) radiation budget and it's applied to geostationary satellite for rapid analysis. It enabled highly accurate monitoring of solar radiation and photo voltaic (PV) power generation. Next step, we try to update the algorithm for retrieval of Aerosols and Clouds. It indicates the accurate atmospheric parameters for estimation of solar radiation. (This research was supported in part by CREST/EMS).

Aerosol optical properties over the Svalbard region of Arctic: ground-based measurements and satellite remote sensing

NASA Astrophysics Data System (ADS)

Gogoi, Mukunda M.; Babu, S. Suresh

2016-05-01

In view of the increasing anthropogenic presence and influence of aerosols in the northern polar regions, long-term continuous measurements of aerosol optical parameters have been investigated over the Svalbard region of Norwegian Arctic (Ny-Ålesund, 79°N, 12°E, 8 m ASL). This study has shown a consistent enhancement in the aerosol scattering and absorption coefficients during spring. The relative dominance of absorbing aerosols is more near the surface (lower single scattering albedo), compared to that at the higher altitude. This is indicative of the presence of local anthropogenic activities. In addition, long-range transported biomass burning aerosols (inferred from the spectral variation of absorption coefficient) also contribute significantly to the higher aerosol absorption in the Arctic spring. Aerosol optical depth (AOD) estimates from ground based Microtop sun-photometer measurements reveals that the columnar abundance of aerosols reaches the peak during spring season. Comparison of AODs between ground based and satellite remote sensing indicates that deep blue algorithm of Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals over Arctic snow surfaces overestimate the columnar AOD.

Biomass Burning Aerosol Absorption Measurements with MODIS Using the Critical Reflectance Method

NASA Technical Reports Server (NTRS)

Zhu, Li; Martins, Vanderlei J.; Remer, Lorraine A.

2010-01-01

This research uses the critical reflectance technique, a space-based remote sensing method, to measure the spatial distribution of aerosol absorption properties over land. Choosing two regions dominated by biomass burning aerosols, a series of sensitivity studies were undertaken to analyze the potential limitations of this method for the type of aerosol to be encountered in the selected study areas, and to show that the retrieved results are relatively insensitive to uncertainties in the assumptions used in the retrieval of smoke aerosol. The critical reflectance technique is then applied to Moderate Resolution Imaging Spectrometer (MODIS) data to retrieve the spectral aerosol single scattering albedo (SSA) in South African and South American 35 biomass burning events. The retrieved results were validated with collocated Aerosol Robotic Network (AERONET) retrievals. One standard deviation of mean MODIS retrievals match AERONET products to within 0.03, the magnitude of the AERONET uncertainty. The overlap of the two retrievals increases to 88%, allowing for measurement variance in the MODIS retrievals as well. The ensemble average of MODIS-derived SSA for the Amazon forest station is 0.92 at 670 nm, and 0.84-0.89 for the southern African savanna stations. The critical reflectance technique allows evaluation of the spatial variability of SSA, and shows that SSA in South America exhibits higher spatial variation than in South Africa. The accuracy of the retrieved aerosol SSA from MODIS data indicates that this product can help to better understand 44 how aerosols affect the regional and global climate.

Inversion Schemes to Retrieve Atmospheric and Oceanic Parameters from SeaWiFS Data

NASA Technical Reports Server (NTRS)

Deschamps, P.-Y.; Frouin, R.

1997-01-01

The investigation focuses on two key issues in satellite ocean color remote sensing, namely the presence of whitecaps on the sea surface and the validity of the aerosol models selected for the atmospheric correction of SeaWiFS data. Experiments were designed and conducted at the Scripps Institution of Oceanography to measure the optical properties of whitecaps and to study the aerosol optical properties in a typical mid-latitude coastal environment. CIMEL Electronique sunphotometers, now integrated in the AERONET network, were also deployed permanently in Bermuda and in Lanai, calibration/validation sites for SeaWiFS and MODIS. Original results were obtained on the spectral reflectance of whitecaps and on the choice of aerosol models for atmospheric correction schemes and the type of measurements that should be made to verify those schemes. Bio-optical algorithms to remotely sense primary productivity from space were also evaluated, as well as current algorithms to estimate PAR at the earth's surface.

A Combined Retrieval of Aerosol Microphysical Properties using active HSRL and Passive Polarimeter Multi-sensor Data

NASA Astrophysics Data System (ADS)

Liu, X.; Stamnes, S.; Ferrare, R. A.; Hostetler, C. A.; Burton, A. S.; Chemyakin, E.; Sawamura, P.; Mueller, D.

2017-12-01

Vertically resolved measurements of aerosol optical, microphysical, and macrophysical parameters are required to better understand the influence of aerosols on climate and air quality. We will describe an Optimal Estimation (OE) retrieval framework which can perform aerosol property retrievals in three modes: 1) lidar-only, 2) polarimeter-only, and 3) combined lidar-polarimeter muti-sensor system. The lidar data can be profile measurements by any high spectral resolution lidar (HSRL) and/or Raman lidar with multiple wavelengths of aerosol backscattering (β) and extinction (α). The polarimeter data can be any multi-angle and multi-wavelength measurements with 2 or 3 polarization components. We will show aerosol microphysical retrieval results from the HSRL-2 data measured from various NASA airborne field campaigns including the recent ORACLES mission. We will also show the OE retrieval results from the polarimeter-only mode. Finally, we will demonstrate how the information content of the aerosol microphysical retrieval is increased by combining the active HSRL and passive polarimeter data in our simultaneous OE retrieval system.

Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia

NASA Astrophysics Data System (ADS)

Liu, Zhiquan; Liu, Quanhua; Lin, Hui-Chuan; Schwartz, Craig S.; Lee, Yen-Huei; Wang, Tijian

2011-12-01

Assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) retrieval products (at 550 nm wavelength) from both Terra and Aqua satellites have been developed within the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) data assimilation system. This newly developed algorithm allows, in a one-step procedure, the analysis of 3-D mass concentration of 14 aerosol variables from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module. The Community Radiative Transfer Model (CRTM) was extended to calculate AOD using GOCART aerosol variables as input. Both the AOD forward model and corresponding Jacobian model were developed within the CRTM and used in the 3DVAR minimization algorithm to compute the AOD cost function and its gradient with respect to 3-D aerosol mass concentration. The impact of MODIS AOD data assimilation was demonstrated by application to a dust storm from 17 to 24 March 2010 over East Asia. The aerosol analyses initialized Weather Research and Forecasting/Chemistry (WRF/Chem) model forecasts. Results indicate that assimilating MODIS AOD substantially improves aerosol analyses and subsequent forecasts when compared to MODIS AOD, independent AOD observations from the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and surface PM10 (particulate matter with diameters less than 10 μm) observations. The newly developed AOD data assimilation system can serve as a tool to improve simulations of dust storms and general air quality analyses and forecasts.

Smoke aerosol properties and ageing effects for Northern temperate and boreal regions derived from AERONET source and age attribution

NASA Astrophysics Data System (ADS)

Nikonovas, Tadas; North, Peter; Doerr, Stefan H.

2015-04-01

Particulate emissions from wildfires impact human health and have a large but uncertain effect on climate. Modelling schemes depend on information about emission factors, emitted particle microphysical and optical properties and ageing effects, while satellite retrieval algorithms make use of characteristic aerosol models to improve retrieval. Ground based remote sensing provides detailed aerosol characterisation, but does not contain information on source. A new method is presented to estimate plume origin land cover type and age for AERONET aerosol observations, employing trajectory modelling using the HYSPLIT model, and satellite active fire and aerosol optical thickness (AOT) observations from MODIS and AATSR. It is applied to AERONET stations located in or near Northern temperate and boreal forests, for the period 2002-2013. The results from 629 fire attributions indicate significant differences insize distributions and particle optical properties between different land cover types. Smallest fine mode median radius are attributed to plumes from cropland/natural vegetation mosaic (0.143 μm) and grasslands (0.147 μm) fires. Evergreen needleleaf forest emissions show a significantly smaller fine mode median radius (0.164 μm) than plumes from woody savannas (0.184 μm) and mixed forest (0.193 μm) fires. Smoke plumes are predominantly scattering for all of the classes with median single scattering albedo at 440 nm (SSA(440)) values close to 0.95 except the cropland emissions which have SSA(440) value of 0.9. Overall fine mode volume median radius increase rate is 0.0095μm per day for the first 4 days of ageing and 0.0084 μm per day for seven days of ageing. Changes in size were consistent with a decrease in Angstrom Exponent and increase in Asymmetry parameter. No significant changes in SSA(λ) with ageing were found. The implications of this work for improved modeling of aerosol radiative effects, which are relevant to both climate modelling and satellite aerosol retrieval schemes, are also discussed.

Satellite Monitoring of Long-Range Transport of Asian Dust Storms from Sources to Sinks

NASA Astrophysics Data System (ADS)

Hsu, N.; Tsay, S.; Jeong, M.; King, M.; Holben, B.

2007-05-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of spring-time cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such popu-lation centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. 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 dif-ficult 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, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. Deep Blue algorithm has recently been integrated into the MODIS processing stream and began to provide aerosol products over land as part of the opera-tional MYD04 products. In this talk, we will show the comparisons of the MODIS Deep Blue products with data from AERONET sunphotometers on a global ba-sis. The results indicate reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources and their evolution along transport pathway using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. We will also utilize the multiyear satellite measurements from MODIS and SeaWiFS to investigate the interannual variability of source strength, pathway, and radia-tive forcing associated with these dust outbreaks in East Asia.

Reflections on current and future applications of multiangle imaging to aerosol and cloud remote sensing

NASA Astrophysics Data System (ADS)

Diner, David

2010-05-01

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global Earth data from NASA's Terra satellite since February 2000. With its 9 along-track view angles, 4 spectral bands, intrinsic spatial resolution of 275 m, and stable radiometric and geometric calibration, no instrument that combines MISR's attributes has previously flown in space, nor is there is a similar capability currently available on any other satellite platform. Multiangle imaging offers several tools for remote sensing of aerosol and cloud properties, including bidirectional reflectance and scattering measurements, stereoscopic pattern matching, time lapse sequencing, and potentially, optical tomography. Current data products from MISR employ several of these techniques. Observations of the intensity of scattered light as a function of view angle and wavelength provide accurate measures of aerosol optical depths (AOD) over land, including bright desert and urban source regions. Partitioning of AOD according to retrieved particle classification and incorporation of height information improves the relationship between AOD and surface PM2.5 (fine particulate matter, a regulated air pollutant), constituting an important step toward a satellite-based particulate pollution monitoring system. Stereoscopic cloud-top heights provide a unique metric for detecting interannual variability of clouds and exceptionally high quality and sensitivity for detection and height retrieval for low-level clouds. Using the several-minute time interval between camera views, MISR has enabled a pole-to-pole, height-resolved atmospheric wind measurement system. Stereo imagery also makes possible global measurement of the injection heights and advection speeds of smoke plumes, volcanic plumes, and dust clouds, for which a large database is now available. To build upon what has been learned during the first decade of MISR observations, we are evaluating algorithm updates that not only refine retrieval accuracies but also include enhancements (e.g., finer spatial resolution) that would have been computationally prohibitive just ten years ago. In addition, we are developing technological building blocks for future sensors that enable broader spectral coverage, wider swath, and incorporation of high-accuracy polarimetric imaging. Prototype cameras incorporating photoelastic modulators have been constructed. To fully capitalize on the rich information content of the current and next-generation of multiangle imagers, several algorithmic paradigms currently employed need to be re-examined, e.g., the use of aerosol look-up tables, neglect of 3-D effects, and binary partitioning of the atmosphere into "cloudy" or "clear" designations. Examples of progress in algorithm and technology developments geared toward advanced application of multiangle imaging to remote sensing of aerosols and clouds will be presented.

Adapting MODIS Dust Mask Algorithm to Suomi NPP VIIRS for Air Quality Applications

NASA Astrophysics Data System (ADS)

Ciren, P.; Liu, H.; Kondragunta, S.; Laszlo, I.

2012-12-01

Despite pollution reduction control strategies enforced by the Environmental Protection Agency (EPA), large regions of the United States are often under exceptional events such as biomass burning and dust outbreaks that lead to non-attainment of particulate matter standards. This has warranted the National Weather Service (NWS) to provide smoke and dust forecast guidance to the general public. The monitoring and forecasting of dust outbreaks relies on satellite data. Currently, Aqua/MODIS (MODerate resolution Imaging Spectrometer) and Terra/MODIS provide measurements needed to derive dust mask and Aerosol Optical Thickness (AOT) products. The newly launched Suomi NPP VIIRS (Visible/Infrared Imaging Radiometer Suite) instrument has a Suspended Matter (SM) product that indicates the presence of dust, smoke, volcanic ash, sea salt, and unknown aerosol types in a given pixel. The algorithm to identify dust is different over land and ocean but for both, the information comes from AOT retrieval algorithm. Over land, the selection of dust aerosol model in the AOT retrieval algorithm indicates the presence of dust and over ocean a fine mode fraction smaller than 20% indicates dust. Preliminary comparisons of VIIRS SM to CALIPSO Vertical Feature Mask (VFM) aerosol type product indicate that the Probability of Detection (POD) is at ~10% and the product is not mature for operational use. As an alternate approach, NESDIS dust mask algorithm developed for NWS dust forecast verification that uses MODIS deep blue, visible, and mid-IR channels using spectral differencing techniques and spatial variability tests was applied to VIIRS radiances. This algorithm relies on the spectral contrast of dust absorption at 412 and 440 nm and an increase in reflectivity at 2.13 μm when dust is present in the atmosphere compared to a clear sky. To avoid detecting bright desert surface as airborne dust, the algorithm uses the reflectances at 1.24 μm and 2.25 μm to flag bright pixels. The algorithm flags pixels that fall into the glint region so sun glint is not picked up as dust. The algorithm also has a spatial variability test that uses reflectances at 0.86 μm to screen for clouds over water. Analysis of one granule for a known dust event on May 2, 2012 shows that the agreement between VIIRS and MODIS is 82% and VIIRS and CALIPSO is 71%. The probability of detection for VIIRS when compared to MODIS and CALIPSO is 53% and 45% respectively whereas the false alarm ratio for VIIRS when compared to MODIS and CALIPSO is 20% and 37% respectively. The algorithm details, results from the test cases, and the use of the dust flag product in NWS applications will be presented.

Campaign datasets for Two-Column Aerosol Project (TCAP)

DOE Data Explorer

Berg,Larry; Mei,Fan; Cairns,Brian; Chand,Duli; Comstock,Jennifer; Cziczo,Daniel; Hostetler,Chris; Hubbe,John; Long,Chuck; Michalsky,Joseph; Pekour,Mikhail; Russell,Phil; Scott,Herman; Sedlacek,Arthur; Shilling,John; Springston,Stephen; Tomlinson,Jason; Watson,Thomas; Zelenyuk-Imre,Alla

2013-12-30

This campaign was designed to provide a detailed set of observations with which to 1) perform radiative and cloud condensation nuclei (CCN) closure studies, 2) evaluate a new retrieval algorithm for aerosol optical depth (AOD) in the presence of clouds using passive remote sensing 3) extend a previously developed technique to investigate aerosol indirect effects, and 4) evaluate the performance of a detailed regional-scale model and a more parameterized global-scale model in simulating particle activation and AOD associated with the aging of anthropogenic aerosols. To meet these science objectives, the ARM Mobile Facility (AMF) and the Mobile Aerosol Observing System (MAOS) was deployed on Cape Cod, Massachusetts for a 12-month period starting in the summer of 2012 in order to quantify aerosol properties, radiation and cloud characteristics at a location subject to both clear- and cloudy- conditions, and clean- and polluted-conditions. These observations were supplemented by two aircraft intensive observation periods (IOPS), one in the summer and a second in the winter. Each IOP required two aircraft.

Role of near ultraviolet wavelength measurements in the detection and retrieval of absorbing aerosols from space

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Fujito, Toshiyuki; Nakata, Makiko; Sano, Itaru

2017-10-01

Aerosol remote sensing by ultraviolet (UV) wavelength is established by a Total Ozone Mapping Spectrometer (TOMS) mounted on the long-life satellite Nimbus-7 and continues to make observations using Ozone monitoring instrument (OMI) located on the Aura satellite. For example, TOMS demonstrated that UV radiation (0.331 and 0.360 μm) could easily detect absorbing particles such as mineral dust or smoke aerosols. TOMS-AI (absorbing aerosol index) has been used to identify the absorbing aerosols from space. For an upcoming mission, JAXA/GCOM-C will have the polarization sensor SGLI boarded in December 2017. The SGLI has multi (19)-channels including near UV (0.380 μm) and violet (0.412 μm) wavelengths. This work intends to examine the role of near UV data in the detection of absorbing aerosols similar to TOMS-AI played. In practice, the measurements by GLI mounted on the short Japanese mission JAXA/ADEOS-2, whose data archive period was just 8 months from April to October in 2003, are available for simulation of SGLI data because ADEOS-2/GLI installed near UV and violet channels. First of all, the ratio of data at 0.412 μm to that at 0.380 μm is examined as an indicator to detect absorbing aerosols on a global scale during ADEOS-2 era. It is noted that our research group has developed an efficient algorithm for aerosol retrieval in hazy episodes (dense concentrations of atmospheric aerosols). It can be said that at least this work is an attempt to grasp the biomass burning plumes from the satellite.

Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) Science Plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jian; Dong, Xiquan; Wood, Robert

With their extensive coverage, low clouds greatly impact global climate. Presently, low clouds are poorly represented in global climate models (GCMs), and the response of low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The poor representations of low clouds in GCMs are in part due to inadequate observations of their microphysical and macrophysical structures, radiative effects, and the associated aerosol distribution and budget in regions where the aerosol impact is the greatest. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary-layer (MBL) clouds,more » whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. Boundary-layer aerosol in the ENA region is influenced by a variety of sources, leading to strong variations in cloud condensation nuclei (CCN) concentration and aerosol optical properties. Recently a permanent ENA site was established by the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility on Graciosa Island in the Azores, providing invaluable information on MBL aerosol and low clouds. At the same time, the vertical structures and horizontal variabilities of aerosol, trace gases, cloud, drizzle, and atmospheric thermodynamics are critically needed for understanding and quantifying the budget of MBL aerosol, the radiative properties, precipitation efficiency, and lifecycle of MBL clouds, and the cloud response to aerosol perturbations. Much of this data can be obtained only through aircraft-based measurements. In addition, the interconnected aerosol and cloud processes are best investigated by a study involving simultaneous in situ aerosol, cloud, and thermodynamics measurements. Furthermore, in situ measurements are also necessary for validating and improving ground-based retrieval algorithms at the ENA site. This project is motivated by the need for comprehensive in situ characterizations of boundary-layer structure, and associated vertical distributions and horizontal variabilities of low clouds and aerosol over the Azores. ARM Aerial Facility (AAF) Gulfstream-1 (G-1) aircraft will be deployed at the ENA site during two intensive operational periods (IOPs) of early summer (June to July) of 2017 and winter (January to February) of 2018, respectively. Deployments during both seasons allow for examination of key aerosol and cloud processes under a variety of representative meteorological and cloud conditions. The science themes for the deployments include: 1) Budget of MBL CCN and its seasonal variation; 2) Effects of aerosol on cloud and precipitation; 3) Cloud microphysical and macrophysical structures, and entrainment mixing; 4) Advancing retrievals of turbulence, cloud, and drizzle; and 5) Model evaluation and processes studies. A key advantage of the deployments is the strong synergy between the measurements onboard the G-1 and the routine measurements at the ENA site, including state-of-the-art profiling and scanning radars. The 3D cloud structures provided by the scanning radars will put the detailed in situ measurements into mesoscale and cloud lifecycle contexts. On the other hand, high quality in situ measurements will enable validation and improvements of ground-based retrieval algorithms at the ENA site, leading to high-quality and statistically robust data sets from the routine measurements. The deployments, combined with the routine measurements at the ENA site, will have a long lasting impact on the research and modeling of low clouds and aerosols in the remote marine environment.« less

Temperature and dust profiles in Martian dust storm conditions retrieved from Mars Climate Sounder measurements

NASA Astrophysics Data System (ADS)

Kleinboehl, A.; Kass, D. M.; Schofield, J. T.; McCleese, D. J.

2013-12-01

Mars Climate Sounder (MCS) is a mid- and far-infrared thermal emission radiometer on board the Mars Reconnaissance Orbiter. It measures radiances in limb and nadir/on-planet geometry from which vertical profiles of atmospheric temperature, water vapor, dust and condensates can be retrieved in an altitude range from 0 to 80 km and with a vertical resolution of ~5 km. Due to the limb geometry used as the MCS primary observation mode, retrievals in conditions with high aerosol loading are challenging. We have developed several modifications to the MCS retrieval algorithm that will facilitate profile retrievals in high-dust conditions. Key modifications include a retrieval option that uses a surface pressure climatology if a pressure retrieval is not possible in high dust conditions, an extension of aerosol retrievals to higher altitudes, and a correction to the surface temperature climatology. In conditions of a global dust storm, surface temperatures tend to be lower compared to standard conditions. Taking this into account using an adaptive value based on atmospheric opacity leads to improved fits to the radiances measured by MCS and improves the retrieval success rate. We present first results of these improved retrievals during the global dust storm in 2007. Based on the limb opacities observed during the storm, retrievals are typically possible above ~30 km altitude. Temperatures around 240 K are observed in the middle atmosphere at mid- and high southern latitudes after the onset of the storm. Dust appears to be nearly homogeneously mixed at lower altitudes. Significant dust opacities are detected at least up to 70 km altitude. During much of the storm, in particular at higher altitudes, the retrieved dust profiles closely resemble a Conrath-profile.

Assessment of capabilities of multiangle imaging photo-polarimetry for atmospheric correction in presence of absorbing aerosols

NASA Astrophysics Data System (ADS)

Kalashnikova, O. V.; Garay, M. J.; Xu, F.; Seidel, F. C.; Diner, D. J.

2015-12-01

Satellite remote sensing of ocean color is a critical tool for assessing the productivity of marine ecosystems and monitoring changes resulting from climatic or environmental influences. Yet water-leaving radiance comprises less than 10% of the signal measured from space, making correction for absorption and scattering by the intervening atmosphere imperative. Traditional ocean color retrieval algorithms utilize a standard set of aerosol models and the assumption of negligible water-leaving radiance in the near-infrared. Modern improvements have been developed to handle absorbing aerosols such as urban particulates in coastal areas and transported desert dust over the open ocean, where ocean fertilization can impact biological productivity at the base of the marine food chain. Even so, imperfect knowledge of the absorbing aerosol optical properties or their height distribution results in well-documented sources of error. In the UV, the problem of UV-enhanced absorption and nonsphericity of certain aerosol types are amplified due to the increased Rayleigh and aerosol optical depth, especially at off-nadir view angles. Multi-angle spectro-polarimetric measurements have been advocated as an additional tool to better understand and retrieve the aerosol properties needed for atmospheric correction for ocean color retrievals. The central concern of the work to be described is the assessment of the effects of absorbing aerosol properties on water leaving radiance measurement uncertainty by neglecting UV-enhanced absorption of carbonaceous particles and by not accounting for dust nonsphericity. In addition, we evaluate the polarimetric sensitivity of absorbing aerosol properties in light of measurement uncertainties achievable for the next generation of multi-angle polarimetric imaging instruments, and demonstrate advantages and disadvantages of wavelength selection in the UV/VNIR range. The phase matrices for the spherical smoke particles were calculated using a standard Mie code, while those for non-spherical dust particles were calculated using the numerical approach described by Dubovik et al., 2006. A vector Markov Chain radiative transfer code including bio-optical models was used to evaluate TOA and water leaving radiances.

Estimate of the Impact of Absorbing Aerosol Over Cloud on the MODIS Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path

NASA Technical Reports Server (NTRS)

Wilcox, Eric M.; Harshvardhan; Platnick, Steven

2009-01-01

Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA Aqua satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (MODIS) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the MODIS retrieval over oceans, cloud reflectance in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the MODIS tau retrieval may result from reductions in the 0.86-micrometer reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. MODIS LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and MODIS LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus MODIS) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean MODIS LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the average LWP difference and the estimated bias in MODIS cloud optical thickness attributable to the impact of overlaying biomass burning aerosol exceed the instantaneous uncertainty in the retrievals.

Regional uncertainty of GOSAT XCO2 retrievals in China: quantification and attribution

NASA Astrophysics Data System (ADS)

Bie, Nian; Lei, Liping; Zeng, ZhaoCheng; Cai, Bofeng; Yang, Shaoyuan; He, Zhonghua; Wu, Changjiang; Nassar, Ray

2018-03-01

The regional uncertainty of the column-averaged dry air mole fraction of CO2 (XCO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a latitude band of 37-42° N segmented into 8 cells in a grid of 5° from west to east (80-120° E) in China, where typical land surface types and geographic conditions exist. The former includes desert, grassland and built-up areas mixed with cropland; and the latter includes anthropogenic emissions that change from small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from four algorithms (ACOS, NIES, OCFP and SRFP) by intercomparison. These retrievals are then specifically compared with simulated XCO2 from the high-resolution nested model in East Asia of the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem). We also introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the four algorithms demonstrate smaller absolute biases of 0.7-1.1 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells (1.0-1.6 ppm) with a high-brightness surface from the pairwise comparison results of XCO2 retrievals. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values from ACOS and SRFP have better agreement, while values from OCFP are the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS and SRFP demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the four algorithms is the smallest in eastern cells in the study area, where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the four algorithms presented in western deserts which displays a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols scattering and surface albedo.

Satellite-based retrieval of particulate matter concentrations over the United Arab Emirates (UAE)

NASA Astrophysics Data System (ADS)

Zhao, Jun; Temimi, Marouane; Hareb, Fahad; Eibedingil, Iyasu

2016-04-01

In this study, an empirical algorithm was established to retrieve particulate matter (PM) concentrations (PM2.5 and PM10) using satellite-derived aerosol optical depth (AOD) over the United Arab Emirates (UAE). Validation of the proposed algorithm using ground truth data demonstrates its good accuracy. Time series of in situ measured PM concentrations between 2014 and 2015 showed high values in summer and low values in winter. Estimated and in situ measured PM concentrations were higher in 2015 than 2014. Remote sensing is an essential tool to reveal and back track the seasonality and inter-annual variations of PM concentrations and provide valuable information on the protection of human health and the response of air quality to anthropogenic activities and climate change.

Quantifying the sensitivity of aerosol optical depths retrieved from MSG SEVIRI to a priori data

NASA Astrophysics Data System (ADS)

Bulgin, C. E.; Palmer, P. I.; Merchant, C. J.; Siddans, R.; Poulsen, C.; Grainger, R. G.; Thomas, G.; Carboni, E.; McConnell, C.; Highwood, E.

2009-12-01

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-Chem and those chosen based on the smallest cost function.

Optical Properties of Aerosols from Long Term Ground-Based Aeronet Measurements

NASA Technical Reports Server (NTRS)

Holben, B. N.; Tanre, D.; Smirnov, A.; Eck, T. F.; Slutsker, I.; Dubovik, O.; Lavenu, F.; Abuhassen, N.; Chatenet, B.

1999-01-01

AERONET is an optical ground-based aerosol monitoring network and data archive supported by NASA's Earth Observing System and expanded by federation with many non-NASA institutions including AEROCAN (AERONET CANada) and PHOTON (PHOtometrie pour le Traiteinent Operatonnel de Normalisation Satellitaire). The network hardware consists of identical automatic sun-sky scanning spectral radiometers owned by national agencies and universities purchased for their own monitoring and research objectives. Data are transmitted hourly through the data collection system (DCS) on board the geostationary meteorological satellites GMS, GOES and METEOSAT and received in a common archive for daily processing utilizing a peer reviewed series of algorithms thus imposing a standardization and quality control of the product data base. Data from this collaboration provides globally distributed near real time observations of aerosol spectral optical depths, aerosol size distributions, and precipitable water in diverse aerosol regimes. Access to the AERONET data base has shifted from the interactive program 'demonstrat' (reserved for PI's) to the AERONET homepage allowing faster access and greater development for GIS object oriented retrievals and analysis with companion geocoded data sets from satellites, LIDAR and solar flux measurements for example. We feel that a significant yet under utilized component of the AERONET data base are inversion products made from hourly principal plane and almucanter measurements. The current inversions have been shown to retrieve aerosol volume size distributions. A significant enhancement to the inversion code has been developed and is presented in these proceedings.

A novel method to improve MODIS AOD retrievals in cloudy pixels using an analog ensemble approach

NASA Astrophysics Data System (ADS)

Kumar, R.; Raman, A.; Delle Monache, L.; Alessandrini, S.; Cheng, W. Y. Y.; Gaubert, B.; Arellano, A. F.

2016-12-01

Particulate matter (PM) concentrations are one of the fundamental indicators of air quality. Earth orbiting satellite platforms acquire column aerosol abundance that can in turn provide information about the PM concentrations. One of the serious limitations of column aerosol retrievals from low earth orbiting satellites is that these algorithms are based on clear sky assumptions. They do not retrieve AOD in cloudy pixels. After filtering cloudy pixels, these algorithms also arbitrarily remove brightest and darkest 25% of remaining pixels over ocean and brightest and darkest 50% pixels over land to filter any residual contamination from clouds. This becomes a critical issue especially in regions that experience monsoon, like Asia and North America. In case of North America, monsoon season experiences wide variety of extreme air quality events such as fires in California and dust storms in Arizona. Assessment of these episodic events warrants frequent monitoring of aerosol observations from remote sensing retrievals. In this study, we demonstrate a method to fill in cloudy pixels in Moderate Imaging Resolution Spectroradiometer (MODIS) AOD retrievals based on ensembles generated using an analog-based approach (AnEn). It provides a probabilistic distribution of AOD in cloudy pixels using historical records of model simulations of meteorological predictors such as AOD, relative humidity, and wind speed, and past observational records of MODIS AOD at a given target site. We use simulations from a coupled community weather forecasting model with chemistry (WRF-Chem) run at a resolution comparable to MODIS AOD. Analogs selected from summer months (June, July) of 2011-2013 from model and corresponding observations are used as a training dataset. Then, missing AOD retrievals in cloudy pixels in the last 31 days of the selected period are estimated. Here, we use AERONET stations as target sites to facilitate comparison against in-situ measurements. We use two approaches to evaluate the estimated AOD: 1) by comparing against reanalysis AOD, 2) by inverting AOD to PM10 concentrations and then comparing those with measured PM10. AnEn is an efficient approach to generate an ensemble as it involves only one model run and provides an estimate of uncertainty that complies with the physical and chemical state of the atmosphere.

Validation of Long-Term Global Aerosol Climatology Project Optical Thickness Retrievals Using AERONET and MODIS Data

NASA Technical Reports Server (NTRS)

Geogdzhayev, Igor V.; Mishchenko, Michael I.

2015-01-01

A comprehensive set of monthly mean aerosol optical thickness (AOT) data from coastal and island AErosol RObotic NETwork (AERONET) stations is used to evaluate Global Aerosol Climatology Project (GACP) retrievals for the period 1995-2009 during which contemporaneous GACP and AERONET data were available. To put the GACP performance in broader perspective, we also compare AERONET and MODerate resolution Imaging Spectroradiometer (MODIS) Aqua level-2 data for 2003-2009 using the same methodology. We find that a large mismatch in geographic coverage exists between the satellite and ground-based datasets, with very limited AERONET coverage of open-ocean areas. This is especially true of GACP because of the smaller number of AERONET stations at the early stages of the network development. Monthly mean AOTs from the two over-the-ocean satellite datasets are well-correlated with the ground-based values, the correlation coefficients being 0.81-0.85 for GACP and 0.74-0.79 for MODIS. Regression analyses demonstrate that the GACP mean AOTs are approximately 17%-27% lower than the AERONET values on average, while the MODIS mean AOTs are 5%-25% higher. The regression coefficients are highly dependent on the weighting assumptions (e.g., on the measure of aerosol variability) as well as on the set of AERONET stations used for comparison. Comparison of over-the-land and over-the-ocean MODIS monthly mean AOTs in the vicinity of coastal AERONET stations reveals a significant bias. This may indicate that aerosol amounts in coastal locations can differ significantly from those in adjacent open-ocean areas. Furthermore, the color of coastal waters and peculiarities of coastline meteorological conditions may introduce biases in the GACP AOT retrievals. We conclude that the GACP and MODIS over-the-ocean retrieval algorithms show similar ranges of discrepancy when compared to available coastal and island AERONET stations. The factors mentioned above may limit the performance of the validation procedure and cause us to caution against a direct extrapolation of the presented validation results to the entirety of the GACP dataset.

Retrieval of ozone profiles from OMPS limb scattering observations

NASA Astrophysics Data System (ADS)

Arosio, Carlo; Rozanov, Alexei; Malinina, Elizaveta; Eichmann, Kai-Uwe; von Clarmann, Thomas; Burrows, John P.

2018-04-01

This study describes a retrieval algorithm developed at the University of Bremen to obtain vertical profiles of ozone from limb observations performed by the Ozone Mapper and Profiler Suite (OMPS). This algorithm is based on the technique originally developed for use with data from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument. As both instruments make limb measurements of the scattered solar radiation in the ultraviolet (UV) and visible (Vis) spectral ranges, an underlying objective of the study is to obtain consolidated and consistent ozone profiles from the two satellites and to produce a combined data set. The retrieval algorithm uses radiances in the UV and Vis wavelength ranges normalized to the radiance at an upper tangent height to obtain ozone concentrations in the altitude range of 12-60 km. Measurements at altitudes contaminated by clouds in the instrument field of view are identified and filtered out. An independent aerosol retrieval is performed beforehand and its results are used to account for the stratospheric aerosol load in the ozone inversion. The typical vertical resolution of the retrieved profiles varies from ˜ 2.5 km at lower altitudes ( < 30 km) to ˜ 1.5 km (about 45 km) and becomes coarser at upper altitudes. The retrieval errors resulting from the measurement noise are estimated to be 1-4 % above 25 km, increasing to 10-30 % in the upper troposphere. OMPS data are processed for the whole of 2016. The results are compared with the NASA product and validated against profiles derived from passive satellite observations or measured in situ by balloon-borne sondes. Between 20 and 60 km, OMPS ozone profiles typically agree with data from the Microwave Limb Sounder (MLS) v4.2 within 5-10 %, whereas in the lower altitude range the bias becomes larger, especially in the tropics. The comparison of OMPS profiles with ozonesonde measurements shows differences within ±5 % between 13 and 30 km at northern middle and high latitudes. At southern middle and high latitudes, an agreement within 5-7 % is also achieved in the same altitude range. An unexpected bias of approximately 10-20 % is detected in the lower tropical stratosphere. The processing of the 2013 data set using the same retrieval settings and its validation against ozonesondes reveals a much smaller bias; a possible reason for this behaviour is discussed.

Validation of ozone profile retrievals derived from the OMPS LP version 2.5 algorithm against correlative satellite measurements

NASA Astrophysics Data System (ADS)

Kramarova, Natalya A.; Bhartia, Pawan K.; Jaross, Glen; Moy, Leslie; Xu, Philippe; Chen, Zhong; DeLand, Matthew; Froidevaux, Lucien; Livesey, Nathaniel; Degenstein, Douglas; Bourassa, Adam; Walker, Kaley A.; Sheese, Patrick

2018-05-01

The Limb Profiler (LP) is a part of the Ozone Mapping and Profiler Suite launched on board of the Suomi NPP satellite in October 2011. The LP measures solar radiation scattered from the atmospheric limb in ultraviolet and visible spectral ranges between the surface and 80 km. These measurements of scattered solar radiances allow for the retrieval of ozone profiles from cloud tops up to 55 km. The LP started operational observations in April 2012. In this study we evaluate more than 5.5 years of ozone profile measurements from the OMPS LP processed with the new NASA GSFC version 2.5 retrieval algorithm. We provide a brief description of the key changes that had been implemented in this new algorithm, including a pointing correction, new cloud height detection, explicit aerosol correction and a reduction of the number of wavelengths used in the retrievals. The OMPS LP ozone retrievals have been compared with independent satellite profile measurements obtained from the Aura Microwave Limb Sounder (MLS), Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Odin Optical Spectrograph and InfraRed Imaging System (OSIRIS). We document observed biases and seasonal differences and evaluate the stability of the version 2.5 ozone record over 5.5 years. Our analysis indicates that the mean differences between LP and correlative measurements are well within required ±10 % between 18 and 42 km. In the upper stratosphere and lower mesosphere (> 43 km) LP tends to have a negative bias. We find larger biases in the lower stratosphere and upper troposphere, but LP ozone retrievals have significantly improved in version 2.5 compared to version 2 due to the implemented aerosol correction. In the northern high latitudes we observe larger biases between 20 and 32 km due to the remaining thermal sensitivity issue. Our analysis shows that LP ozone retrievals agree well with the correlative satellite observations in characterizing vertical, spatial and temporal ozone distribution associated with natural processes, like the seasonal cycle and quasi-biennial oscillations. We found a small positive drift ˜ 0.5 % yr-1 in the LP ozone record against MLS and OSIRIS that is more pronounced at altitudes above 35 km. This pattern in the relative drift is consistent with a possible 100 m drift in the LP sensor pointing detected by one of our altitude-resolving methods.

Development of GK-2A cloud optical and microphysical properties retrieval algorithm

NASA Astrophysics Data System (ADS)

Yang, Y.; Yum, S. S.; Um, J.

2017-12-01

Cloud and aerosol radiative forcing is known to be one of the the largest uncertainties in climate change prediction. To reduce this uncertainty, remote sensing observation of cloud radiative and microphysical properties have been used since 1970s and the corresponding remote sensing techniques and instruments have been developed. As a part of such effort, Geo-KOMPSAT-2A (Geostationary Korea Multi-Purpose Satellite-2A, GK-2A) will be launched in 2018. On the GK-2A, the Advanced Meteorological Imager (AMI) is primary instrument which have 3 visible, 3 near-infrared, and 10 infrared channels. To retrieve optical and microphysical properties of clouds using AMI measurements, the preliminary version of new cloud retrieval algorithm for GK-2A was developed and several validation tests were conducted. This algorithm retrieves cloud optical thickness (COT), cloud effective radius (CER), liquid water path (LWP), and ice water path (IWP), so we named this algorithm as Daytime Cloud Optical thickness, Effective radius and liquid and ice Water path (DCOEW). The DCOEW uses cloud reflectance at visible and near-infrared channels as input data. An optimal estimation (OE) approach that requires appropriate a-priori values and measurement error information is used to retrieve COT and CER. LWP and IWP are calculated using empirical relationships between COT/CER and cloud water path that were determined previously. To validate retrieved cloud properties, we compared DCOEW output data with other operational satellite data. For COT and CER validation, we used two different data sets. To compare algorithms that use cloud reflectance at visible and near-IR channels as input data, MODIS MYD06 cloud product was selected. For the validation with cloud products that are based on microwave measurements, COT(2B-TAU)/CER(2C-ICE) data retrieved from CloudSat cloud profiling radar (W-band, 94 GHz) was used. For cloud water path validation, AMSR-2 Level-3 Cloud liquid water data was used. Detailed results will be shown at the conference.

New Satellite Project Aerosol-UA: Remote Sensing of Aerosols in the Terrestrial Atmosphere

NASA Technical Reports Server (NTRS)

Milinevsky, G.; Yatskiv, Ya.; Degtyaryov, O.; Syniavskyi, I.; Mishchenko, Michael I.; Rosenbush, V.; Ivanov, Yu.; Makarov, A.; Bovchaliuk, A.; Danylevsky, V.;

Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

NASA Astrophysics Data System (ADS)

Poulsen, C. A.; Siddans, R.; Thomas, G. E.; Sayer, A. M.; Grainger, R. G.; Campmany, E.; Dean, S. M.; Arnold, C.; Watts, P. D.

2012-08-01

Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud) which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick, greater than 50 optical depths, where the cloud begins to saturate. The cost proved a good indicator of multi-layer scenarios. Both the retrieval cost and the error need to be considered together in order to evaluate the quality of the retrieval. This algorithm in the configuration described here has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of the GRAPE (Global Retrieval and cloud Product Evaluation) project to produce a 14 yr consistent record for climate research.

Aerosol Retrieval from Multiangle Multispectral Photopolarimetric Measurements: Importance of Spectral Range and Angular Resolution

NASA Technical Reports Server (NTRS)

Wu, L.; Hasekamp, O.; Van Diedenhoven, B.; Cairns, B.

2015-01-01

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.

Simultaneous Retrieval of Multiple Aerosol Parameters Using a Multi-Angular Approach

NASA Technical Reports Server (NTRS)

Kuo, K. S.; Weger, R. C.; Welch, R. M.

1997-01-01

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.

Evaluation of Cloud and Aerosol Screening of Early Orbiting Carbon Observatory-2 (OCO-2) Observations with Collocated MODIS Cloud Mask

NASA Astrophysics Data System (ADS)

Nelson, R. R.; Taylor, T.; O'Dell, C.; Cronk, H. Q.; Partain, P.; Frankenberg, C.; Eldering, A.; Crisp, D.; Gunson, M. R.; Chang, A.; Fisher, B.; Osterman, G. B.; Pollock, H. R.; Savtchenko, A.; Rosenthal, E. J.

2015-12-01

Effective cloud and aerosol screening is critically important to the Orbiting Carbon Observatory-2 (OCO-2), which can accurately determine column averaged dry air mole fraction of carbon dioxide (XCO2) only when scenes are sufficiently clear of scattering material. It is crucial to avoid sampling biases, in order to maintain a globally unbiased XCO2 record for inversion modeling to determine sources and sinks of carbon dioxide. This work presents analysis from the current operational B7 data set, which is identifying as clear approximately 20% of the order one million daily soundings. Of those soundings that are passed to the L2 retrieval algorithm, we find that almost 80% are yielding XCO2 estimates that converge. Two primary preprocessor algorithms are used to cloud screen the OCO-2 soundings. The A-Band Preprocessor (ABP) uses measurements in the Oxygen-A band near 0.76 microns (mm) to determine scenes with large photon path length modifications due to scattering by aerosol and clouds. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) algorithm (IDP) computes ratios of retrieved CO2 (and H2O) in the 1.6mm (weak CO2) and 2.0mm (strong CO2) spectral bands to determine scenes with spectral differences, indicating contamination by scattering materials. We demonstrate that applying these two algorithms in tandem provides robust cloud screening of the OCO-2 data set. We compare the OCO-2 cloud screening results to collocated Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask data and show that agreement between the two sensors is approximately 85-90%. A detailed statistical analysis is performed on a winter and spring 16-day repeat cycle for the nadir-land, glint-land and glint-water viewing geometries. No strong seasonal, spatial or footprint dependencies are found, although the agreement tends to be worse at high solar zenith angles and for snow and ice covered surfaces.

Optimal estimation for global ground-level fine particulate matter concentrations

NASA Astrophysics Data System (ADS)

Donkelaar, Aaron; Martin, Randall V.; Spurr, Robert J. D.; Drury, Easan; Remer, Lorraine A.; Levy, Robert C.; Wang, Jun

2013-06-01

We develop an optimal estimation (OE) algorithm based on top-of-atmosphere reflectances observed by the MODIS satellite instrument to retrieve near-surface fine particulate matter (PM2.5). The GEOS-Chem chemical transport model is used to provide prior information for the Aerosol Optical Depth (AOD) retrieval and to relate total column AOD to PM2.5. We adjust the shape of the GEOS-Chem relative vertical extinction profiles by comparison with lidar retrievals from the CALIOP satellite instrument. Surface reflectance relationships used in the OE algorithm are indexed by land type. Error quantities needed for this OE algorithm are inferred by comparison with AOD observations taken by a worldwide network of sun photometers (AERONET) and extended globally based upon aerosol speciation and cross correlation for simulated values, and upon land type for observational values. Significant agreement in PM2.5 is found over North America for 2005 (slope = 0.89; r = 0.82; 1-σ error = 1 µg/m3 + 27%), with improved coverage and correlation relative to previous work for the same region and time period, although certain subregions, such as the San Joaquin Valley of California are better represented by previous estimates. Independently derived error estimates of the OE PM2.5 values at in situ locations over North America (of ±(2.5 µg/m3 + 31%) and Europe of ±(3.5 µg/m3 + 30%) are corroborated by comparison with in situ observations, although globally (error estimates of ±(3.0 µg/m3 + 35%), may be underestimated. Global population-weighted PM2.5 at 50% relative humidity is estimated as 27.8 µg/m3 at 0.1° × 0.1° resolution.

Surface roughness considerations for atmospheric correction of ocean color sensors. I - The Rayleigh-scattering component. II - Error in the retrieved water-leaving radiance

NASA Technical Reports Server (NTRS)

Gordon, Howard R.; Wang, Menghua

1992-01-01

The first step in the Coastal Zone Color Scanner (CZCS) atmospheric-correction algorithm is the computation of the Rayleigh-scattering (RS) contribution, L sub r, to the radiance leaving the top of the atmosphere over the ocean. In the present algorithm, L sub r is computed by assuming that the ocean surface is flat. Calculations of the radiance leaving an RS atmosphere overlying a rough Fresnel-reflecting ocean are presented to evaluate the radiance error caused by the flat-ocean assumption. Simulations are carried out to evaluate the error incurred when the CZCS-type algorithm is applied to a realistic ocean in which the surface is roughened by the wind. In situations where there is no direct sun glitter, it is concluded that the error induced by ignoring the Rayleigh-aerosol interaction is usually larger than that caused by ignoring the surface roughness. This suggests that, in refining algorithms for future sensors, more effort should be focused on dealing with the Rayleigh-aerosol interaction than on the roughness of the sea surface.

Sensitivity of atmospheric correction to loading and model of the aerosol

NASA Astrophysics Data System (ADS)

Bassani, Cristiana; Braga, Federica; Bresciani, Mariano; Giardino, Claudia; Adamo, Maria; Ananasso, Cristina; Alberotanza, Luigi

2013-04-01

The physically-based atmospheric correction requires knowledge of the atmospheric conditions during the remotely data acquisitions [Guanter et al., 2007; Gao et al., 2009; Kotchenova et al. 2009; Bassani et al., 2010]. The propagation of solar radiation in the atmospheric window of visible and near-infrared spectral domain, depends on the aerosol scattering. The effects of solar beam extinction are related to the aerosol loading, by the aerosol optical thickness @550nm (AOT) parameter [Kaufman et al., 1997; Vermote et al., 1997; Kotchenova et al., 2008; Kokhanovsky et al. 2010], and also to the aerosol model. Recently, the atmospheric correction of hyperspectral data is considered sensitive to the micro-physical and optical characteristics of aerosol, as reported in [Bassani et al., 2012]. Within the framework of CLAM-PHYM (Coasts and Lake Assessment and Monitoring by PRISMA HYperspectral Mission) project, funded by Italian Space Agency (ASI), the role of the aerosol model on the accuracy of the atmospheric correction of hyperspectral image acquired over water target is investigated. In this work, the results of the atmospheric correction of HICO (Hyperspectral Imager for the Coastal Ocean) images acquired on Northern Adriatic Sea in the Mediterranean are presented. The atmospheric correction has been performed by an algorithm specifically developed for HICO sensor. The algorithm is based on the equation presented in [Vermote et al., 1997; Bassani et al., 2010] by using the last generation of the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer code [Kotchenova et al., 2008; Vermote et al., 2009]. The sensitive analysis of the atmospheric correction of HICO data is performed with respect to the aerosol optical and micro-physical properties used to define the aerosol model. In particular, a variable mixture of the four basic components: dust- like, oceanic, water-soluble, and soot, has been considered. The water reflectance, obtained from the atmospheric correction with variable model and fixed loading of the aerosol, has been compared. The results highlight the requirements to define the aerosol characteristics, loading and model, to simulate the radiative field in the atmosphere system for an accurate atmospheric correction of hyperspectral data, improving the accuracy of the results for surface reflectance process over water, a dark-target. As conclusion, the aerosol model plays a crucial role for an accurate physically-based atmospheric correction of hyperspectral data over water. Currently, the PRISMA mission provides valuable opportunities to study aerosol and their radiative effects on the hyperspectral data. Bibliography Guanter, L.; Estellès, V.; Moreno, J. Spectral calibration and atmospheric correction of ultra-fine spectral and spatial resolution remote sensing data. Application to CASI-1500 data. Remote Sens. Environ. 2007, 109, 54-65. Gao, B.-C.; Montes, M.J.; Davis, C.O.; Goetz, A.F.H. Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean. Remote Sens. Environ. 2009, 113, S17-S24. Kotchenova, S. Atmospheric correction for the monitoring of land surfaces. J. Geophys. Res. 2009, 113, D23. Bassani C.; Cavalli, R.M.; Pignatti S. Aerosol optical retrieval and surface reflectance from airborne remote sensing data over land. Sens. 2010, 10, 6421-6438. Kaufman, Y. J., Tanrè, D., Gordon H. R., Nakajima T., Lenoble J., Frouin R., Grassl H., Herman B.M., King M., and Teillet P.M.: Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer, J. Geophys. Res., 102(D14), 17051-17067, 1997. Vermote, E.F.; Tanrè , D.; Deuzè´ , J.L.; Herman M.; Morcrette J.J. Second simulation of the satellite signal in the solar spectrum, 6S: An overview. IEEE Trans. Geosci. Remote Sens. 1997, 35, 675-686. Kotchenova, S.Y.; Vermote, E.F.; Levy, R.; Lyapustin, A. Radiative transfer codes for atmospheric correction and aerosol retrieval: Intercomparison study. Appl. Optics 2008, 47, 2215-2226. Kokhanovsky A.A., Deuzè J.L., Diner D.J., Dubovik O., Ducos F., Emde C., Garay M.J., Grainger R.G., Heckel A., Herman M., Katsev I.L., Keller J., Levy R., North P.R.J., Prikhach A.S., Rozanov V.V., Sayer A.M., Ota Y., Tanrè D., Thomas G.E., Zege E.P. The inter-comparison of major satellite aerosol retrieval algorithms using simulated intensity and polarization characteristics of reflected light. Atmos. Meas. Tech., 3, 909-932, 2010. Bassani C.; Cavalli, R.M.; Antonelli, P. Influence of aerosol and surface reflectance variability on hyperspectral observed radiance. Atmos. Meas. Tech. 2012, 5, 1193-1203. Vermote , E.F.; Kotchenova, S. Atmospheric correction for the monitoring of land surfaces. J. Geophys. Res. 2009, 113, D23.

Mechanical Properties of the Surface Material of Comet 67P/Churyumov-Gerasimenko Measured By the Casse Instrument Onboard the Philae Lander

NASA Astrophysics Data System (ADS)

Knapmeyer, M.; Fischer, H. H.; Seidensticker, K. J.; Arnold, W.; Faber, C.; Möhlmann, D.; Thiel, K.

2014-12-01

Satellite remote sensing of ocean color is a critical tool for assessing the productivity of marine ecosystems and monitoring changes resulting from climatic or environmental influences. Yet water-leaving radiance comprises less than 10% of the signal measured from space, making correction for absorption and scattering by the intervening atmosphere imperative. Traditional ocean color retrieval algorithms utilize a standard set of aerosol models and the assumption of negligible water-leaving radiance in the near-infrared. Modern improvements have been developed to handle absorbing aerosols such as urban particulates in coastal areas and transported desert dust over the open ocean, where ocean fertilization can impact biological productivity at the base of the marine food chain. Even so, imperfect knowledge of the absorbing aerosol optical properties or their height distribution results in well-documented sources of error. In the UV, the problem of UV-enhanced absorption and nonsphericity of certain aerosol types are amplified due to the increased Rayleigh and aerosol optical depth, especially at off-nadir view angles. Multi-angle spectro-polarimetric measurements have been advocated as an additional tool to better understand and retrieve the aerosol properties needed for atmospheric correction for ocean color retrievals. The central concern of the work to be described is the assessment of the effects of absorbing aerosol properties on water leaving radiance measurement uncertainty by neglecting UV-enhanced absorption of carbonaceous particles and by not accounting for dust nonsphericity. In addition, we evaluate the polarimetric sensitivity of absorbing aerosol properties in light of measurement uncertainties achievable for the next generation of multi-angle polarimetric imaging instruments, and demonstrate advantages and disadvantages of wavelength selection in the UV/VNIR range. The phase matrices for the spherical smoke particles were calculated using a standard Mie code, while those for non-spherical dust particles were calculated using the numerical approach described by Dubovik et al., 2006. A vector Markov Chain radiative transfer code including bio-optical models was used to evaluate TOA and water leaving radiances.

Retrieval of aerosol profiles combining sunphotometer and ceilometer measurements in GRASP code

NASA Astrophysics Data System (ADS)

Román, R.; Benavent-Oltra, J. A.; Casquero-Vera, J. A.; Lopatin, A.; Cazorla, A.; Lyamani, H.; Denjean, C.; Fuertes, D.; Pérez-Ramírez, D.; Torres, B.; Toledano, C.; Dubovik, O.; Cachorro, V. E.; de Frutos, A. M.; Olmo, F. J.; Alados-Arboledas, L.

2018-05-01

In this paper we present an approach for the profiling of aerosol microphysical and optical properties combining ceilometer and sun/sky photometer measurements in the GRASP code (General Retrieval of Aerosol and Surface Properties). For this objective, GRASP is used with sun/sky photometer measurements of aerosol optical depth (AOD) and sky radiances, both at four wavelengths and obtained from AErosol RObotic NETwork (AERONET), and ceilometer measurements of range corrected signal (RCS) at 1064 nm. A sensitivity study with synthetic data evidences the capability of the method to retrieve aerosol properties such as size distribution and profiles of volume concentration (VC), especially for coarse particles. Aerosol properties obtained by the mentioned method are compared with airborne in-situ measurements acquired during two flights over Granada (Spain) within the framework of ChArMEx/ADRIMED (Chemistry-Aerosol Mediterranean Experiment/Aerosol Direct Radiative Impact on the regional climate in the MEDiterranean region) 2013 campaign. The retrieved aerosol VC profiles agree well with the airborne measurements, showing a mean bias error (MBE) and a mean absolute bias error (MABE) of 0.3 μm3/cm3 (12%) and 5.8 μm3/cm3 (25%), respectively. The differences between retrieved VC and airborne in-situ measurements are within the uncertainty of GRASP retrievals. In addition, the retrieved VC at 2500 m a.s.l. is shown and compared with in-situ measurements obtained during summer 2016 at a high-atitude mountain station in the framework of the SLOPE I campaign (Sierra Nevada Lidar AerOsol Profiling Experiment). VC from GRASP presents high correlation (r = 0.91) with the in-situ measurements, but overestimates them, MBE and MABE being equal to 23% and 43%.

Tomographic reconstruction of an aerosol plume using passive multiangle observations from the MISR satellite instrument

NASA Astrophysics Data System (ADS)

Garay, Michael J.; Davis, Anthony B.; Diner, David J.

2016-12-01

We present initial results using computed tomography to reconstruct the three-dimensional structure of an aerosol plume from passive observations made by the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite. MISR views the Earth from nine different angles at four visible and near-infrared wavelengths. Adopting the 672 nm channel, we treat each view as an independent measure of aerosol optical thickness along the line of sight at 1.1 km resolution. A smoke plume over dark water is selected as it provides a more tractable lower boundary condition for the retrieval. A tomographic algorithm is used to reconstruct the horizontal and vertical aerosol extinction field for one along-track slice from the path of all camera rays passing through a regular grid. The results compare well with ground-based lidar observations from a nearby Micropulse Lidar Network site.

Potential Retrieval of Aerosol Microphysics From Multistatic Space-Borne Lidar

NASA Astrophysics Data System (ADS)

Levitan, Nathaniel; Gross, Barry; Moshary, Fred; Wu, Yonghua

2018-04-01

HSRL lidars are being considered for deployment to space to retrieve aerosol microphysics. The literature is mostly focused on the monostatic configuration; but, in this paper, we explore whether additional information for the retrieval of microphysics can be obtained by adding a second detector in a bistatic configuration. The information gained from the additional measurements can under certain conditions reduce the ill-posed nature of aerosol microphysics retrieval and reducing the uncertainty in the retrievals.

LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET

NASA Astrophysics Data System (ADS)

Amiridis, V.; Marinou, E.; Tsekeri, A.; Wandinger, U.; Schwarz, A.; Giannakaki, E.; Mamouri, R.; Kokkalis, P.; Binietoglou, I.; Solomos, S.; Herekakis, T.; Kazadzis, S.; Gerasopoulos, E.; Proestakis, E.; Kottas, M.; Balis, D.; Papayannis, A.; Kontoes, C.; Kourtidis, K.; Papagiannopoulos, N.; Mona, L.; Pappalardo, G.; Le Rille, O.; Ansmann, A.

2015-07-01

We present LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies), a 3-D multi-wavelength global aerosol and cloud optical database, optimized to be used for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. The LIVAS database provides averaged profiles of aerosol optical properties for the potential spaceborne laser operating wavelengths of 355, 532, 1064, 1570 and 2050 nm and of cloud optical properties at the wavelength of 532 nm. The global database is based on CALIPSO observations at 532 and 1064 nm and on aerosol-type-dependent backscatter- and extinction-related Ångström exponents, derived from EARLINET (European Aerosol Research Lidar Network) ground-based measurements for the UV and scattering calculations for the IR wavelengths, using a combination of input data from AERONET, suitable aerosol models and recent literature. The required spectral conversions are calculated for each of the CALIPSO aerosol types and are applied to CALIPSO backscatter and extinction data corresponding to the aerosol type retrieved by the CALIPSO aerosol classification scheme. A cloud optical database based on CALIPSO measurements at 532 nm is also provided, neglecting wavelength conversion due to approximately neutral scattering behavior of clouds along the spectral range of LIVAS. Averages of particle linear depolarization ratio profiles at 532 nm are provided as well. Finally, vertical distributions for a set of selected scenes of specific atmospheric phenomena (e.g., dust outbreaks, volcanic eruptions, wild fires, polar stratospheric clouds) are analyzed and spectrally converted so as to be used as case studies for spaceborne lidar performance assessments. The final global data set includes 4-year (1 January 2008-31 December 2011) time-averaged CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) data on a uniform grid of 1° × 1° with the original high vertical resolution of CALIPSO in order to ensure realistic simulations of the atmospheric variability in lidar end-to-end simulations.

Retrieval of Absorbing Aerosols Above Clouds retrieval over the South East Atlantic Ocean from MSG/SEVIRI

NASA Astrophysics Data System (ADS)

Peers, F.; Haywood, J. M.; Francis, P. N.; Meyer, K.; Platnick, S. E.

2017-12-01

Over the South East Atlantic Ocean, biomass burning aerosols from Southern Africa are frequently observed above clouds during fire season. However, the quantification of their interactions with both radiations and clouds remains uncertain because of a lack of information on aerosol properties and on their interaction process. In the last decade, methods have been developed to retrieve aerosol optical properties above clouds from satellite measurements, especially over the South East Atlantic Ocean. Most of these methods have been applied to polar orbiting instruments which prevent the analysis of aerosols and clouds at a sub-daily scale. With its wide spatial coverage and its high temporal resolution, the geostationary instrument SEVIRI, on board the MSG platform, offers a unique opportunity to monitor aerosols in this region and to evaluate their impact on clouds and their radiative effects. In this study, we will investigate the possibility of retrieving simultaneously aerosol and cloud properties (i.e. aerosol and cloud optical thicknesses and cloud droplet effective radius) when aerosols are located above clouds. The retrieved properties will then be compared with the ones obtained from MODIS [Meyer et al., 2015] as well as observations from the CLARIFY-2017 field campaign.

Comparison of different Aethalometer correction schemes and a reference multi-wavelength absorption technique for ambient aerosol data

NASA Astrophysics Data System (ADS)

Saturno, Jorge; Pöhlker, Christopher; Massabò, Dario; Brito, Joel; Carbone, Samara; Cheng, Yafang; Chi, Xuguang; Ditas, Florian; Hrabě de Angelis, Isabella; Morán-Zuloaga, Daniel; Pöhlker, Mira L.; Rizzo, Luciana V.; Walter, David; Wang, Qiaoqiao; Artaxo, Paulo; Prati, Paolo; Andreae, Meinrat O.

2017-08-01

Deriving absorption coefficients from Aethalometer attenuation data requires different corrections to compensate for artifacts related to filter-loading effects, scattering by filter fibers, and scattering by aerosol particles. In this study, two different correction schemes were applied to seven-wavelength Aethalometer data, using multi-angle absorption photometer (MAAP) data as a reference absorption measurement at 637 nm. The compensation algorithms were compared to five-wavelength offline absorption measurements obtained with a multi-wavelength absorbance analyzer (MWAA), which serves as a multiple-wavelength reference measurement. The online measurements took place in the Amazon rainforest, from the wet-to-dry transition season to the dry season (June-September 2014). The mean absorption coefficient (at 637 nm) during this period was 1.8 ± 2.1 Mm-1, with a maximum of 15.9 Mm-1. Under these conditions, the filter-loading compensation was negligible. One of the correction schemes was found to artificially increase the short-wavelength absorption coefficients. It was found that accounting for the aerosol optical properties in the scattering compensation significantly affects the absorption Ångström exponent (åABS) retrievals. Proper Aethalometer data compensation schemes are crucial to retrieve the correct åABS, which is commonly implemented in brown carbon contribution calculations. Additionally, we found that the wavelength dependence of uncompensated Aethalometer attenuation data significantly correlates with the åABS retrieved from offline MWAA measurements.

Pre-launch Performance Assessment of the VIIRS Ice Surface Temperature Algorithm

NASA Astrophysics Data System (ADS)

Ip, J.; Hauss, B.

2008-12-01

The VIIRS Ice Surface Temperature (IST) environmental data product provides the surface temperature of sea-ice at VIIRS moderate resolution (750m) during both day and night. To predict the IST, the retrieval algorithm utilizes a split-window approach with Long-wave Infrared (LWIR) channels at 10.76 μm (M15) and 12.01 μm (M16) to correct for atmospheric water vapor. The split-window approach using these LWIR channels is AVHRR and MODIS heritage, where the MODIS formulation has a slightly modified functional form. The algorithm relies on the VIIRS Cloud Mask IP for identifying cloudy and ocean pixels, the VIIRS Ice Concentration IP for identifying ice pixels, and the VIIRS Aerosol Optical Thickness (AOT) IP for excluding pixels with AOT greater than 1.0. In this paper, we will report the pre-launch performance assessment of the IST retrieval. We have taken two separate approaches to perform this assessment, one based on global synthetic data and the other based on proxy data from Terra MODIS. Results of the split- window algorithm have been assessed by comparison either to synthetic "truth" or results of the MODIS retrieval. We will also show that the results of the assessment with proxy data are consistent with those obtained using the global synthetic data.

Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer

NASA Astrophysics Data System (ADS)

Kaufman, Y. J.; Tanré, D.; Remer, L. A.; Vermote, E. F.; Chu, A.; Holben, B. N.

1997-07-01

Daily distribution of the aerosol optical thickness and columnar mass concentration will be derived over the continents, from the EOS moderate resolution imaging spectroradiometer (MODIS) using dark land targets. Dark land covers are mainly vegetated areas and dark soils observed in the red and blue channels; therefore the method will be limited to the moist parts of the continents (excluding water and ice cover). After the launch of MODIS the distribution of elevated aerosol concentrations, for example, biomass burning in the tropics or urban industrial aerosol in the midlatitudes, will be continuously monitored. The algorithm takes advantage of the MODIS wide spectral range and high spatial resolution and the strong spectral dependence of the aerosol opacity for most aerosol types that result in low optical thickness in the mid-IR (2.1 and 3.8 μm). The main steps of the algorithm are (1) identification of dark pixels in the mid-IR; (2) estimation of their reflectance at 0.47 and 0.66 μm; and (3) derivation of the optical thickness and mass concentration of the accumulation mode from the detected radiance. To differentiate between dust and aerosol dominated by accumulation mode particles, for example, smoke or sulfates, ratios of the aerosol path radiance at 0.47 and 0.66 μm are used. New dynamic aerosol models for biomass burning aerosol, dust and aerosol from industrial/urban origin, are used to determine the aerosol optical properties used in the algorithm. The error in the retrieved aerosol optical thicknesses, τa is expected to be Δτa = 0.05±0.2τa. Daily values are stored on a resolution of 10×10 pixels (1 km nadir resolution). Weighted and gridded 8-day and monthly composites of the optical thickness, the aerosol mass concentration and spectral radiative forcing are generated for selected scattering angles to increase the accuracy. The daily aerosol information over land and oceans [Tanré et al., this issue], combined with continuous aerosol remote sensing from the ground, will be used to study aerosol climatology, to monitor the sources and sinks of specific aerosol types, and to study the interaction of aerosol with water vapor and clouds and their radiative forcing of climate. The aerosol information will also be used for atmospheric corrections of remotely sensed surface reflectance. In this paper, examples of applications and validations are provided.

Role of passive remote sensors. Sensor System Panel report

NASA Astrophysics Data System (ADS)

1982-06-01

Capabilities of present passive systems are described and the development of passive remote sensing systems for the more abundant tropospheric trace species is recommended. The combination of nadir-viewing spectrometers and solar occultation for tropospheric measurement of those gases having large stratospheric burdens is discussed. Development of a nadir-viewing instrument capable of obtaining continuous spectra in narrower bands is recommended. Gas filter radiometers for species specific measurements and development of a spectral survey instrument are discussed. Further development of aerosol retrieval algorithms, including polarization techniques, for obtaining aerosol thickness and size distributions is advised. Recommendations of specific investigations to be pursued are presented.