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All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

CART and GSFC raman lidar measurements of atmospheric aerosol backscattering and extinction profiles for EOS validation and ARM radiation studies

The aerosol retrieval algorithms used by the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Multi-Angle Imaging SpectroRadiometer (MISR) sensors on the Earth Observing Satellite (EOS) AM-1 platform operate by comparing measured radiances with tabulated radiances that have been computed for specific aerosol models. These aerosol models are based almost entirely on surface and/or column averaged measurements and so may not accurately represent the ambient aerosol properties. Therefore, to validate these EOS algorithms and to determine the effects of aerosols on the clear-sky radiative flux, we have begun to evaluate the vertical variability of ambient aerosol properties using the aerosol backscattering and extinction profiles measured by the Cloud and Radiation Testbed (CART) and NASA Goddard Space Flight Center (GSFC) Raman Lidars. Using the procedures developed for the GSFC Scanning Raman Lidar (SRL), we have developed and have begun to implement algorithms for the CART Raman Lidar to routinely provide profiles of aerosol extinction and backscattering during both nighttime and ,daytime operations. Aerosol backscattering and extinction profiles are computed for both lidar systems using data acquired during the 1996 and 1997 Water Vapor Intensive Operating Periods (IOPs). By integrating these aerosol extinction profiles, we derive measurements of aerosol optical thickness and compare these with coincident sun photometer measurements. We also use these measurements to measure the aerosol extinction/backscatter ratio S(sub a) (i.e. 'lidar ratio'). Furthermore, we use the simultaneous water vapor measurements acquired by these Raman lidars to investigate the effects of water vapor on aerosol optical properties.

Ferrare, R. A.↗
NASA NTRS2004

A New, More Physically Based Algorithm, for Retrieving Aerosol Properties over Land from MODIS

The MOD Imaging Spectrometer (MODIS) has been successfully retrieving aerosol properties, beginning in early 2000 from Terra and from mid 2002 from Aqua. Over land, the retrieval algorithm makes use of three MODIS channels, in the blue, red and infrared wavelengths. As part of the validation exercises, retrieved spectral aerosol optical thickness (AOT) has been compared via scatterplots against spectral AOT measured by the global Aerosol Robotic NETwork (AERONET). On one hand, global and long term validation looks promising, with two-thirds (average plus and minus one standard deviation) of all points falling between published expected error bars. On the other hand, regression of these points shows a positive y-offset and a slope less than 1.0. For individual regions, such as along the U.S. East Coast, the offset and slope are even worse. Here, we introduce an overhaul of the algorithm for retrieving aerosol properties over land. Some well-known weaknesses in the current aerosol retrieval from MODIS include: a) rigid assumptions about the underlying surface reflectance, b) limited aerosol models to choose from, c) simplified (scalar) radiative transfer (RT) calculations used to simulate satellite observations, and d) assumption that aerosol is transparent in the infrared channel. The new algorithm attempts to address all four problems: a) The new algorithm will include surface type information, instead of fixed ratios of the reflectance in the visible channels to the mid-IR reflectance. b) It will include updated aerosol optical properties to reflect the growing aerosol retrieved from eight-plus years of AERONE". operation. c) The effects of polarization will be including using vector RT calculations. d) Most importantly, the new algorithm does not assume that aerosol is transparent in the infrared channel. It will be an inversion of reflectance observed in the three channels (blue, red, and infrared), rather than iterative single channel retrievals. Thus, this new formulation of the MODIS aerosol retrieval over land includes more physically based surface, aerosol and radiative transfer with fewer potentially erroneous assumptions.

Levy, Robert C.↗
NASA NTRS2021

Observation of absorbing aerosols above clouds over the South-East Atlantic Ocean from the geostationary satellite SEVIRI - Part 2: Comparison with MODIS and aircraft measurements from the CLARIFY-2017 field campaign

To evaluate the SEVIRI retrieval for aerosols above clouds presented in Part 1 of the companion paper, the algorithm is applied over the south-east Atlantic Ocean during the CLARIFY-2017 field campaign period. The first step of our analysis compares the retrieved aerosol and cloud properties against equivalent products from the MODIS MOD06ACAERO retrieval (Meyer et al., 2015). While the correlation between the two satellite retrievals of the above-cloud aerosol optical thickness (AOT) is good (R = 0.78), the AOT retrieved by SEVIRI is 20.3 % smaller than that obtained from the MODIS retrieval. This difference in AOT is attributed mainly to the more absorbing aerosol model assumed for the SEVIRI retrieval compared to MODIS. The underlying cloud optical thickness (COT) derived from the two satellites is in good agreement (R = 0.90). The cloud droplet effective radius (CER) retrieved by SEVIRI is consistently smaller than MODIS by 2.2 µm, which is mainly caused by the use of different spectral bands of the satellite instruments. In the second part of our analysis, we compare the forecast water vapour profiles used for the SEVIRI atmospheric correction as well as the aforementioned aerosol and cloud products with in situ measurements made from the Facility for Airborne Atmospheric Measurements (FAAM) aircraft platform during the CLARIFY-2017 campaign. Around Ascension Island, the column water vapour used to correct the SEVIRI signal is overestimated by 3.1 mm in the forecast compared to that measured by dropsondes. However, the evidence suggests that the accuracy of the atmospheric correction improves closer to the African coast. Consistency is observed between the SEVIRI above-cloud AOT and in situ measurements (from cavity ring-down spectroscopy instruments) when the measured single-scattering albedo is close to that assumed in the retrieval algorithm. On the other hand, the satellite retrieval overestimates the AOT when the assumed aerosol model is not absorbing enough. Consistency is also found between the cloud properties retrieved by SEVIRI and the CER measured by a cloud droplet probe and the liquid water path derived from a microwave radiometer. Despite the instrumental limitations of the geostationary satellite, the consistency obtained between SEVIRI, MODIS and the aircraft measurements demonstrates the ability of the retrieval in providing additional information on the temporal evolution of the aerosol properties above clouds.

absorbing aerosols↗
NASA NTRS2012

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

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.

Lyapustin, A.↗
DOE OSTI2022

Estimation of Sea Spray Aerosol Surface Area Over the Southern Ocean Using Scattering Measurements

This study focuses on methods to estimate dry marine aerosol surface area (SA) from bulk optical measurements. Aerosol SA is used in many models' ice nucleating particle (INP) parameterizations, as well as influencing particle light scattering, hygroscopic growth, and reactivity, but direct observations are scarce in the Southern Ocean (SO). Two campaigns jointly conducted in austral summer 2018 provided co-located measurements of aerosol SA from particle size distributions and lidar to evaluate SA estimation methods in this region. Mie theory calculations based on measured size distributions were used to test a proposed approximation for dry aerosol SA, which relies on estimating effective scattering efficiency (Q) as a function of Ångström exponent (å). For distributions with dry å < 1, Q = 2 was found to be a good approximation within ±50%, but for distributions with dry å > 1, an assumption of Q = 3 as in some prior studies underestimates dry aerosol SA by a factor of 2 or more. We propose a new relationship between dry å and Q, which can be used for –0.2 < å < 2, and suggest å = 0.8 as the cutoff between primary and secondary marine aerosol-dominated distributions. Application of a published methodology to retrieve dry marine aerosol SA from lidar extinction profiles overestimated aerosol SA by a factor of 3–5 during these campaigns. Using Microtops aerosol optical thickness measurements, we derive alternative lidar conversion parameters from our observations, applicable to marine aerosol over the SO.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Daily Kilometer-Scale MODIS Satellite Maps of PM2.5 Describe Wintertime Episodes

The San Joaquin Valley (SJV) suffers from severe health-endangering episodes of PM2.5 aerosol loadings in wintertime; episodes last approximately 5 days and differ in geographical distribution and composition. PM2.5 stations are scattered; consequently the use of remote sensing to map variable regional patterns of these varying respirable aerosol concentrations is desirable. High-precision AOT retrievals can capture column particulate loading. However,PM2.5 mapping is challenging due to several reasons: particularly thin mixed layers (ML) and thus relatively low aerosol optical thickness (AOT) close to current measurement limits, variable and a typical composition of the aerosols, and complex surface bidirectional reflectance. However, the West does present some advantages in analysis. Air basins are isolated from long-distance transport, and experience predominant strong meteorological subsidence. Thus these Western basin regions have fewer problematic cases of overriding aerosol layers detached from the surface. To counter such local overriding, Chu et al. have described an approach for the Eastern US, and He et al have described a synoptic classification approach useful in Shanghai. The Bay Area Air Quality Management District (BAAQMD) expands our experience with the use of AOT, with lower PM2.5 and several isolated sub-basins. We have prepared daily maps of episodes in each region. We present also a sequence of increasingly detailed statistical models, AOT initially appears to contribute little information; however, inclusion of weather information reveals its utility. Lyapustin and Wang's MultiAngle Implementation of Atmospheric Correction (MAIAC) retrieval for AOT provided the most useful operational remote sensing information for these regions. It provides high (1-km) spatial resolution maps and a high percentage of availability. Empirical regression methods have found that random effects regression models (aka mixed effects models, ME) employing AOT provide good estimates of ground PM2.5 concentrations.Here, we attempt to extend these methods and evaluate the usefulness of AOT with greater physical analysis, based on DISCOVER-AQ4 experience.

Chatfield, Robert B.↗
NASA NTRS2017

CATS Near Real Time Data Products: Applications for Assimilation Into the NASA GEOS-5 AGCM

From February 2015 through October 2017, the NASA Cloud-Aerosol Transport System (CATS) backscatter lidar operated on the International Space Station (ISS) as a technology demonstration for future Earth Science Missions, providing vertical measurements of cloud and aerosols properties. Owing to its location on the ISS, a cornerstone technology demonstration of CATS was the capability to acquire, process, and disseminate near-real time (NRT) data within 6 hours of observation time. CATS NRT data has several applications, including providing notification of hazardous events for air traffic control and air quality advisories, field campaign flight planning, as well as for constraining cloud and aerosol distributions in via data assimilation in aerosol transport models. Â Recent developments in aerosol data assimilation techniques have permitted the assimilation of aerosol optical thickness (AOT), a 2-dimensional column integrated quantity that is reflective of the simulated aerosol loading in aerosol transport models. While this capability has greatly improved simulated AOT forecasts, the vertical position, a key control on aerosol transport, is often not impacted when 2-D AOT is assimilated. Here, we present preliminary efforts to assimilate CATS aerosol observations into the NASA Goddard Earth Observing System version 5 (GEOS-5) atmospheric general circulation model and assimilation system using a 1-D Variational (1-D VAR) ensemble approach, demonstrating the utility of CATS for future Earth Science Missions.

Hlavka, D. L.↗
NASA NTRS1993

Earth observing scanning polarimeter

Climate forcing by tropospheric aerosols is receiving increased attention because of the realization that the climate effects may be large, while our knowledge of global aerosol characteristics and temporal changes is very poor. Tropospheric aerosols cause a direct radiative forcing due simply to their scattering and absorption of solar radiation, as well as an indirect effect as cloud condensation nuclei which can modify the shortwave reflectivity of clouds. Sulfate aerosols tend to increase planetary albedo through both the direct and indirect effects; a cooling due to anthropogenic sulfate aerosols has been estimated of order 1 W/sq m, noting that this is similar in magnitude to the present anthropogenic greenhouse gas warming. Other aerosols, including those from biomass burning and wind-blown desert dust are also of potential climatic importance. At present, the only global monitoring of tropospheric aerosols is a NOAA operational product, aerosol optical thickness, obtained using channel-1 (0.58-0.68 mu m) radiances from the AVHRR. With this single channel radiance data, one must use an approach which is based on the inferred excess of reflected radiance owing to scattering by the aerosols over that expected from theoretical calculations. This approach is suited only for situations where the surface has a low albedo that is well known a priori. Thus, the NOAA operational product is restricted to coverage over the ocean at AVHRR scan angles well away from sun glint, and aerosol changes are subject to confusion with changes caused by either optically thin or subpixel clouds. Because optically thin aerosols have only a small effect on the radiance, accurate measurements for optical thickness less than 0.1 (which is a typical background level) are precluded. Moreover, some of the largest and most important aerosol changes are expected over land. The Earth Observing Scanning Polarimeter (EOSP) instrument, based upon design heritage and analysis techniques developed for planetary missions, will retrieve tropospheric aerosol characteristics from measurements of multispectral radiance and polarization. Moreover, the same radiance and polarization measurements will also provide very precise information on cloud properties and maps of surface characteristics for cloud-free regions. These capabilities also give EOSP the unique ability to discriminate aerosol from clouds and surface.

Travis, Larry↗
NASA NTRS1999

Vertical Distribution of Aerosol in the Troposphere

The paper addresses the issue of the vertical distribution of aerosol in the troposphere and the relation to causative mechanisms. The focus is on visible wavelength, aerosol extinction cross sections. A background on the state of knowledge will be presented, but the emphasis is on experimental results from several field programs, The GLOBE project (GLobal aerosol Backscatter Experiment) involved a series of flights by the NASA DC-8 throughout the Pacific basin region with comprehensive in situ and multi-spectral lidar aerosol distribution measurements. The data has been extensively analyzed. The results show the existence of a background mode for aerosol loading in the troposphere and a pattern of distribution for transport and boundary layer aerosol for the Pacific region. The ARM (Atmospheric Radiation Measurement) program, operates surface based monitoring sites. For several years at sites in the central great plains and northern coast of Alaska of North America and a site in the tropical western Pacific have been acquiring comprehensive radiation measurements including multispectral aerosol optical thickness and near continuous lidar profiling. Data have been analyzed for typical and special case aerosol events including smoke aerosol from biomass burning for the tropical West Pacific site. Measurements with continuous lidar and multispectral were similarly acquired from a site at Tenerife, Canary Islands during the Aerosol Characterization Experiment and include analysis of the Saharan dust layer. Various measurements will be compared and summarized.

Spinhirne, James↗
NASA NTRS2004

Comparison of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Earth Observing One (EO-1) Advanced Land Imager

We compare images from the Enhanced Thematic Mapper Plus (ETM+) sensor on Landsat-7 and the Advanced Land Imager (ALI) instrument on Earth Observing One (EO-1) over a test site in Rochester, New York. The site contains a variety of features, ranging from water of varying depths, deciduous/coniferous forest, and grass fields, to urban areas. Nearly coincident cloud-free images were collected one minute apart on 25 August 2001. We also compare images of a forest site near Howland, Maine, that were collected on 7 September, 2001. We atmospherically corrected each pair of images with the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmosphere model, using aerosol optical thickness and water vapor column density measured by in situ Cimel sun photometers within the Aerosol Robotic Network (AERONET), along with ozone density derived from the Total Ozone Mapping Spectrometer (TOMS) on the Earth Probe satellite. We present true-color composites from each instrument that show excellent qualitative agreement between the multispectral sensors, along with grey-scale images that demonstrate a significantly improved ALI panchromatic band. We quantitatively compare ALI and ETM+ reflectance spectra of a grassy field in Rochester and find < or equal to 6% differences in the visible/near infrared and approx. 2% differences in the short wave infrared. Spectral comparisons of forest sites in Rochester and Howland yield similar percentage agreement except for band 1, which has very low reflectance. Principal component analyses and comparison of normalized difference vegetation index histograms for each sensor indicate that the ALI is able to reproduce the information content in the ETM+ but with superior signal-to-noise performance due to its increased 12-bit quantization.

Pedelty, Jeffrey A.↗
NASA NTRS2012

Impacts of Cross-Platform Vicarious Calibration on the Deep Blue Aerosol Retrievals for Moderate Resolution Imaging Spectroradiometer Aboard Terra

The retrieval of aerosol properties from spaceborne sensors requires highly accurate and precise radiometric measurements, thus placing stringent requirements on sensor calibration and characterization. For the Terra/Moderate Resolution Imaging Spedroradiometer (MODIS), the characteristics of the detectors of certain bands, particularly band 8 [(B8); 412 nm], have changed significantly over time, leading to increased calibration uncertainty. In this paper, we explore a possibility of utilizing a cross-calibration method developed for characterizing the Terral MODIS detectors in the ocean bands by the National Aeronautics and Space Administration Ocean Biology Processing Group to improve aerosol retrieval over bright land surfaces. We found that the Terra/MODIS B8 reflectance corrected using the cross calibration method resulted in significant improvements for the retrieved aerosol optical thickness when compared with that from the Multi-angle Imaging Spectroradiometer, Aqua/MODIS, and the Aerosol Robotic Network. The method reported in this paper is implemented for the operational processing of the Terra/MODIS Deep Blue aerosol products.

Jeong, Myeong-Jae↗
NASA NTRS2017

Ground-Based High Spectral Resolution Lidar Observation of Aerosol Vertical Distribution in the Summertime Southeast United States

As part of the Southeast United States-based Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), and collinear with part of the Southeast Atmosphere Study, the University of Wisconsin High Spectral Resolution Lidar system was deployed to the University of Alabama from 19 June to 4 November 2013. With a collocated Aerosol Robotic Network (AERONET) sun photometer, a nearby Chemical Speciation Network (PM2.5) measurement station, and near daily ozonesonde releases for the August-September SEAC4RS campaign, the site allowed the regions first comprehensive diurnal monitoring of aerosol particle vertical structure. A 532nm lidar ratio of 55 sr provided good closure between aerosol backscatter and AERONET (aerosol optical thickness, AOT). A principle component analysis was performed to identify key modes of variability in aerosol backscatter. ''Fair weather'' days exhibited classic planetary boundary layer structure of a mixed layer accounting for approx. 50% of AOT and an entrainment zone providing another 25%. An additional 5-15% of variance is gained from the lower free troposphere from either convective detrainment or frequent intrusions of western United States biomass burning smoke. Generally, aerosol particles were contained below the 0 C level, a common level of stability in convective regimes. However, occasional strong injections of smoke to the upper troposphere were also observed, accounting for the remaining 10-15% variability in AOT. Examples of these common modes of variability in frontal and convective regimes are presented, demonstrating why AOT often has only a weak relationship to surface PM2.5 concentration.

HSRL↗
NASA NTRS2001

SIMBIOS Sun Photometer Program

Aerosol optical thickness (AOT) values determined from the satellite ocean color data provide useful information on the spatial and temporal distributions of aerosols and are by-products of the atmospheric corrections required to estimation of water-leaving radiances. The Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project is using in situ atmospheric data, primarily from sun photometers, for several purposes including: (1) validation the SeaWiFS and other ocean color mission aerosol optical products, e.g., AOT and Angstrom exponent; (2) evaluation of the aerosol models currently used for atmospheric corrections; and (3) development of vicarious sensor calibration methodologies, especially for the near-infrared bands where in situ water-leaving radiance data in the visible from sites like the Marine Optical Buoy cannot be used. The principal source of in situ aerosol observations was the Aerosol Robotic Network (AERONET).

McClain, Charles↗
NASA NTRS2012

Continental-Scale Validation of Modis-Based and LEDAPS Landsat ETM + Atmospheric Correction Methods

The potential of Landsat data processing to provide systematic continental scale products has been demonstratedby several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent freeavailability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicableto large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correctionmethods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive ProcessingSystem (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmosphericcharacterization approaches. The MODIS-based method uses the MODIS Terra derived dynamicaerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions ineach coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from eachLandsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validationresults are presented comparing ETM+ atmospherically corrected data generated using these two methodswith AERONET corrected ETM+ data for 95 10 km10 km 30 m subsets, a total of nearly 8 million 30 mpixels, located across the conterminous United States. The results indicate that the MODIS-based methodhas better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.

Atmospheric correction↗
NASA NTRS2014

Model-Based Estimation of Sampling-Caused Uncertainty in Aerosol Remote Sensing for Climate Research Applications

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiationtransport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125 deg × 1.125 deg and 2 deg × 3◦: the analysis is restricted to 60 deg S-60 deg N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.

long-term variability↗
NASA NTRS2020

Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product

We estimated the distribution of aerosol optical thickness (AOT) with a spatial resolution of 1 km over the Moscow megacity using the MAIAC aerosol product based on MODIS satellite data (Lyapustin et al., 2018) for the warm period of the year (May–September, 2001–2017). AERONET (Aerosol Robotic Network)-based validation of satellite estimates near the city centre at Moscow_MSU_MO and over the Moscow suburbs at Zvenigorod revealed that MAIAC AOT at 0.47 μm is in agreement with AERONET AOT though underestimated by 0.05–0.1 for AOT < 1 and overestimated for smoke conditions with AOT > 1. The MAIAC AOT biases were almost the same for the Moscow_MSU_MO and Zvenigorod AERONET sites, which indicated that the MAIAC algorithm effectively removed the effect of the bright urban surface in the city centre. For the ground-based measurements, the difference between annual median AOT at Moscow_MO_MSU and Zvenigorod (∆AOT) varied within -0:002 to +0:03, with statistically significant positive bias for most years, and an average ∆AOT was about 0.02. According to the MAIAC dataset, the ∆AOT varied within ±0:01 and was not statistically significant. The ∆AOT started decreasing recently due to intensive urban development of the territory around Zvenigorod and the decrease in pollutant emissions in Moscow, which is mainly caused by the environmental regulations. According to the MAIAC dataset, the most pronounced spatial AOT differences over the territory of Moscow were observed at the 5% quantile level, where they reached 0.05–0.06 over several locations and could be attributed to the stationary sources of aerosol pollution, for example, large areas of construction sites, aerosol pollution from roads and highways, or agriculture activities. The differences between the maximum and the mean AOT for different quantiles, except the 95% quantile, within the Moscow region, were about 0.02–0.04, which could be attributed to the local aerosol sources. The application of the MAIAC algorithm over the whole Moscow region has revealed a decreasing AOT trend over the centre of Moscow and an increasing trend over the “New” Moscow territory which experienced an intensive build-up and agricultural development.

urban aerosol pollution↗
NASA NTRS2003

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

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.

Remer, L. A.↗
NASA NTRS2012

Continental-scale Validation of MODIS-based and LEDAPS Landsat ETM+ Atmospheric Correction Methods

The potential of Landsat data processing to provide systematic continental scale products has been demonstrated by several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent free availability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicable to large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correction methods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmospheric characterization approaches. The MODIS-based method uses the MODIS Terra derived dynamic aerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions in each coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from each Landsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validation results are presented comparing ETM+ atmospherically corrected data generated using these two methods with AERONET corrected ETM+ data for 95 10 km×10 km 30 m subsets, a total of nearly 8 million 30 m pixels, located across the conterminous United States. The results indicate that the MODIS-based method has better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.

Landsat↗