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NASA NTRS1991

Stratospheric aerosol optical depth observed by the Stratospheric Aerosol and Gas Experiment. II - Decay of the El Chichon and Ruiz volcanic perturbations

The decay of the El Chichon perturbation to the optical depth of stratospheric aerosols at 1.02 micron, 0.525 micron, and 0.453 micron is calculated from the Stratospheric Aerosol and Gas Experiment II (SAGE II) data set for the period December 1984 to December 1988. It is found that the perturbed optical depths at middle and higher latitudes of both hemispheres exhibited an exponential decay superimposed by a seasonal oscillation with a maximum and a minimum occurring in local winter and local summer, respectively. Microphysical processes and variation of the tropopause height alone cannot explain this seasonal change of optical depth. The magnitudes of the exponential component at higher latitudes were, in general, larger than those at lower latitudes. For optical depths in tropical regions, the seasonal oscillations were small and were disturbed by the eruption of Nevado del Ruiz on November 13, 1985. The increase in the ratio of optical depth at 0.525 micron to that at 1.02 micron from about 2.0 at the beginning of 1985 to about 3.5 at the end of 1988 indicates the average size of aerosol particles in the stratosphere is diminishing since the eruption of El Chichon. The 1/e folding time for El Chichon decay derived from the SAGE II data set is in reasonably good agreement with those derived by other methods.

Yue, G. K.↗
NASA NTRS2014

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

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.

aerosol optical depth↗
NASA NTRS1994

Aerosol Optical Depth Determinations for BOREAS

Automated tracking sun photometers were deployed by NASA/Ames Research Center aboard the NASA C-130 aircraft and at a ground site for all three Intensive Field Campaigns (IFCs) of the Boreal Ecosystem-Atmosphere Study (BOREAS) in central Saskatchewan, Canada during the summer of 1994. The sun photometer data were used to derive aerosol optical depths for the total atmospheric column above each instrument. The airborne tracking sun photometer obtained data in both the southern and northern study areas at the surface prior to takeoff, along low altitude runs near the ground tracking sun photometer, during ascents to 6-8 km msl, along remote sensing flightlines at altitude, during descents to the surface, and at the surface after landing. The ground sun photometer obtained data from the shore of Candle Lake in the southern area for all cloud-free times. During the first IFC in May-June ascents and descents of the airborne tracking sun photometer indicated the aerosol optical depths decreased steadily from the surface to 3.5 kni where they leveled out at approximately 0.05 (at 525 nm), well below levels caused by the eruption of Mt. Pinatubo. On a very clear day, May 31st, surface optical depths measured by either the airborne or ground sun photometers approached those levels (0.06-0.08 at 525 nm), but surface optical depths were often several times higher. On June 4th they increased from 0.12 in the morning to 0.20 in the afternoon with some evidence of brief episodes of pollen bursts. During the second IFC surface aerosol optical depths were variable in the extreme due to smoke from western forest fires. On July 20th the aerosol optical depth at 525 nm decreased from 0.5 in the morning to 0.2 in the afternoon; they decreased still further the next day to 0.05 and remained consistently low throughout the day to provide excellent conditions for several remote sensing missions flown that day. Smoke was heavy for the early morning of July 24th but cleared partially by 10:30 local time and cleared fully by 11:30. Heavy smoke characterized the rest of the IFC in both study areas.

Wrigley, R. C.↗
NASA NTRS1994

Characteristic aerosol optical depths during the Harmattan season on sub-Sahara Africa

Aerosol optical depths were derived from sun photometer measurements in three narrow bands centered at 500, 675 and 875 nm, taken at Ilorin, Nigeria, located in sub-Saharan Africa. Selected results will be presented on the diurnal, seasonal, and interannual variability of spectral aerosol optical depth for two Harmattan seasons, during 1987-1989. At 500 nm values between 0.9-1.6 were quite common while the averages were between 1-1.2.

Pinker, Rachel T.↗
NASA NTRS1985

Variations in stratospheric aerosol optical depth during northern warmings

In this paper, the properties of the stratospheric aerosol optical depth (above 50 mbar) have been studied by using aerosol extinction profiles (at 1 micron) derived from the Stratospheric Aerosol Measurement and Stratospheric Aerosol and Gas Experiment (SAGE) during warming periods in the Northern Hemisphere. It is shown that, during the disturbed periods in winter, low values of aerosol optical depth (less than 0.0002) are found within the low-pressure system(s) (at the 30-mbar pressure surface), while high values are found outside. Similar characteristics are found to exist for the simultaneously observed SAGE O3 and NO2 columnar density distributions. Strong longitudinal gradients are shown with the low values within and wherever the vortex exists. This characteristic is maintained during and after the circumpolar vortex is disturbed, even after breakdown, indicating an isolation of the material within the vortex.

Wang, P.-H.↗
NASA NTRS2016

Reducing Multisensor Satellite Monthly Mean Aerosol Optical Depth Uncertainty: 1. Objective Assessment of Current AERONET Locations

Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.

aerosol optical depth↗
NASA NTRS2012

Evaluating Nighttime CALIOP 0.532 micron Aerosol Optical Depth and Extinction Coefficient Retrievals

NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 micron aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1 deg X 1 deg resolution versus corresponding/co-incident 0.550 micron AOD derived using the US Navy Aerosol Analysis and Prediction System (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. In the absence of sunlight, since passive radiometric AOD retrievals rely overwhelmingly on scattered radiances, the model represents one of the few practical global estimates available from which to attempt such a validation. Daytime comparisons, though, provide useful context. Regional-mean CALIOP vertical profiles of night/day 0.532 micron extinction coefficient are compared with 0.523/0.532 micron ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalised 1 deg. X 1 deg. bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalised bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach +/- 20 %. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalised bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day.

aerosol optical depth↗
NASA NTRS2001

Characterizing the Spatial and Temporal Distribution of Aerosol Optical Thickness Over the Atlantic Basin Utilizing GOES-8 Multispectral Data

In recent years, modeling and analysis efforts have suggested that the direct and indirect radiative effects of both anthropogenic and natural aerosols play a major role in the radiative balance of the earth and are an important factor in climate change calculations. The direct effects of aerosols on radiation and indirect effects on cloud properties are not well understood at this time. In order to improve the characterization of aerosols within climate models it is important to accurately parameterize aerosol forcing mechanisms at the local, regional, and global scales. This includes gaining information on the spatial and temporal distribution of aerosols, transport regimes and mechanisms, aerosol optical thickness, and size distributions. Although there is an expanding global network of ground measurements of aerosol optical thickness and size distribution at specific locations, satellite data must be utilized to characterize the spatial and temporal extent of aerosols and transport regimes on regional and global scales. This study was part of a collaborative effort to characterize aerosol radiative forcing over the Atlantic basin associated with the following three major aerosol components in this region: urban/sulfate, Saharan dust, and biomass burning. In-situ ground measurements obtained by a network of sun photometers during the Smoke Clouds and Radiation Experiment in Brazil (SCAR-B) and the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) were utilized to develop, calibrate, and validate a Geostationary Operational Environmental Satellite (GOES)-8 aerosol optical thickness (AOT) product. Regional implementation of the GOES-8 AOT product was used to augment point source measurements to gain a better understanding of the spatial and temporal distributions of Atlantic basin aerosols during SCAR-B and TARFOX.

Fox, Robert↗
NASA NTRSDate not supplied

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Greg Schuster↗
NASA NTRSDate not supplied

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Elisabeth Andrews↗
NASA NTRSDate not supplied

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Greg Schuster↗
NASA NTRS1991

Temporal and spatial variability of aerosol optical depth in the Sahel region in relation to vegetation remote sensing

In order to monitor the aerosol characteristics needed for atmospheric correction of remotely sensed data, a network of sun photometers was established in the Sahel region of Senegal, Mali, and Niger. Data analysis suggests that there is a high spatial variability of the aerosol optical thickness tau(a) in the western Sahel region. At a 67 percent confidence level the instantaneous values of tau(a) can be extrapolated approximately 270-400 km with an error tolerance of 50 percent. Spatial variability in the dry season is found to be of a similar magnitude. The ranges of variations in the NDVI in the Sahel region are shown to be approximately 0.02 and 0.01, respectively, due to commonly observed fluctuations in the aerosol optical thickness and aerosol size distribution.

Holben, B. N.↗
NASA NTRS2018

Optimal Estimation-Based Algorithm to Retrieve Aerosol Optical Properties for GEMS Measurements Over Asia

The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled to be in orbit in 2019 onboard the GEO-KOMPSAT 2B satellite and will continuously monitor air quality over Asia. The GEMS will make measurements in the UV spectrum (300-500 nm) with 0.6 nm resolution. In this study, an algorithm is developed to retrieve aerosol optical properties from UV-visible measurements for the future satellite instrument and is tested using 3 years of existing OMI L1B data. This algorithm provides aerosol optical depth (AOD), single scattering albedo (SSA) and aerosol layer height (ALH) using an optimized estimation method. The retrieved AOD shows good correlation with Aerosol Robotic Network (AERONET) AOD with correlation coefficients of 0.83, 0.73 and 0.80 for heavy-absorbing fine (HAF) particles, dust and non-absorbing (NA) particles, respectively. However, regression tests indicate underestimation and overestimation of HAF and NA AOD, respectively. In comparison with AOD from the OMI/Aura Near-UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13 km x 24 km V003 (OMAERUV) algorithm, the retrieved AOD has a correlation coefficient of 0.86 and linear regression equation, AOD(sub GEMS) = 1.18AOD(sub OMAERUV) + 0.09. An uncertainty test based on a reference method, which estimates retrieval error by applying the algorithm to simulated radiance data, revealed that assumptions in the spectral dependency of aerosol absorptivity in the UV cause significant errors in aerosol property retrieval, particularly the SSA retrieval. Consequently, retrieved SSAs did not show good correlation with AERONET values. The ALH results were qualitatively compared with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products and were found to be well correlated for highly absorbing aerosols. The difference between the attenuated-backscatter-weighted height from CALIOP and retrieved ALH were mostly closed to zero when the retrieved AOD is higher than 0.8 and SSA is lower than 0.93. Although retrieval accuracy was not significantly improved, the simultaneous consistent retrieval of AOD, SSA and ALH alone demonstrates the value of this stand-alone algorithm, given their nature for error using other methods. The use of these properties as input parameters for the air mass factor calculation is expected to improve the retrieval of other trace gases over Asia.

Geostationary Environment Monitoring Spectrometer ↗
NASA NTRS2004

3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

Wen, Guo-Yong↗
NASA NTRS2010

Simulations of the Aerosol Index and the Absorption Aerosol Optical Depth and Comparisons with OMI Retrievals During ARCTAS-2008 Campaign

We have computed the Aerosol Index (AI) at 354 nm, useful for observing the presence of absorbing aerosols in the atmosphere, from aerosol simulations conducted with the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) module running online the GEOS-5 Atmospheric GCM. The model simulates five aerosol types: dust, sea salt, black carbon, organic carbon and sulfate aerosol and can be run in replay or data assimilation modes. In the assimilation mode, information's provided by the space-based MODIS and MISR sensors constrains the model aerosol state. Aerosol optical properties are then derived from the simulated mass concentration and the Al is determined at the OMI footprint using the radiative transfer code VLIDORT. In parallel, model derived Absorption Aerosol Optical Depth (AAOD) is compared with OMI retrievals. We have focused our study during ARCTAS (June - July 2008), a period with a good sampling of dust and biomass burning events. Our ultimate goal is to use OMI measurements as independent validation for our MODIS/MISR assimilation. Towards this goal we document the limitation of OMI aerosol absorption measurements on a global scale, in particular sensitivity to aerosol vertical profile and cloud contamination effects, deriving the appropriate averaging kernels. More specifically, model simulated (full) column integrated AAOD is compared with model derived Al, this way identifying those regions and conditions under which OMI cannot detect absorbing aerosols. Making use of ATrain cloud measurements from MODIS, C1oudSat and CALIPSO we also investigate the global impact on clouds on OMI derived Al, and the extent to which GEOS-5 clouds can offer a first order representation of these effects.

Source record↗
NASA NTRS2016

Aerosol Optical Depth Distribution in Extratropical Cyclones over the Northern Hemisphere Oceans

Using Moderate Resolution Imaging Spectroradiometer and an extratropical cyclone database,the climatological distribution of aerosol optical depth (AOD) in extratropical cyclones is explored based solely on observations. Cyclone-centered composites of aerosol optical depth are constructed for the Northern Hemisphere mid-latitude ocean regions, and their seasonal variations are examined. These composites are found to be qualitatively stable when the impact of clouds and surface insolation or brightness is tested. The larger AODs occur in spring and summer and are preferentially found in the warm frontal and in the post-cold frontal regions in all seasons. The fine mode aerosols dominate the cold sector AODs, but the coarse mode aerosols display large AODs in the warm sector. These differences between the aerosol modes are related to the varying source regions of the aerosols and could potentially have different impacts on cloud and precipitation within the cyclones.

MODIS↗
NASA NTRS2018

Correcting for Trace Gas Absorption When Retrieving Aerosol Optical Depth from Satellite Observations of Reflected Shortwave Radiation

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 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 Moderate Resolution Imaging Spectroradiometer (MODIS, onboard Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, onboard 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 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 up to 0.07. As recent studies are attempting to create a long-term data record by joining multiple satellite datasets, including MODIS and VIIRS, the consistency of gas correction becomes even more crucial.

Satellite Remote Sensing↗
NASA NTRS2014

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Air pollution↗