Aerosol Optical Thickness Retrieval Algorithm Research Articles

Simulated reflectance above snow constrained by airborne measurements of solar radiation: implications for the snow grain morphology in the Arctic

Abstract. Accurate knowledge of the reflectance from snow/ice-covered surfaces is of fundamental importance for the retrieval of snow parameters and atmospheric constituents from space-based and airborne observations. In this paper, we simulate the reflectance in a snow–atmosphere system, using the phenomenological radiative transfer model SCIATRAN, and compare the results with that of airborne measurements. To minimize the differences between measurements and simulation, we determine and employ the key atmospheric and surface parameters, such as snow grain morphologies (or habits). First, we report on a sensitivity study. This addresses the requirement for adequate a priori knowledge about snow models and ancillary information about the atmosphere. For this aim, we use the well-validated phenomenological radiative transfer model, SCIATRAN. Second, we present and apply a two-stage snow grain morphology (i.e., size and shape of ice crystals in the snow) retrieval algorithm. We then describe the use of this new retrieval for estimating the most representative snow model, using different types of snow morphologies, for the airborne observation conditions performed by NASA's Cloud Absorption Radiometer (CAR). Third, we present a comprehensive comparison of the simulated reflectance (using retrieved snow grain size and shape and independent atmospheric data) with that from airborne CAR measurements in the visible (0.670 µm) and near infrared (NIR; 0.870 and 1.6 µm) wavelength range. The results of this comparison are used to assess the quality and accuracy of the radiative transfer model in the simulation of the reflectance in a coupled snow–atmosphere system. Assuming that the snow layer consists of ice crystals with aggregates of eight column ice habit and having an effective radius of ∼99 µm, we find that, for a surface covered by old snow, the Pearson correlation coefficient, R, between measurements and simulations is 0.98 (R2∼0.96). For freshly fallen snow, assuming that the snow layer consists of the aggregate of five plates ice habit with an effective radius of ∼83 µm and having surface inhomogeneity, the correlation is ∼0.97 (R2∼0.94) in the infrared and 0.88 (R2∼0.77) in the visible wavelengths. The largest differences between simulated and measured values are observed in the glint area (i.e., in the angular regions of specular and near-specular reflection), with relative azimuth angles <±40∘ in the forward-scattering direction. The absolute difference between the modeled results and measurements in off-glint regions, with a viewing zenith angle of less than 50∘, is generally small ∼±0.025 and does not exceed ±0.05. These results will help to improve the calculation of snow surface reflectance and relevant assumptions in the snow–atmosphere system algorithms (e.g., aerosol optical thickness retrieval algorithms in the polar regions).

Understanding MODIS dark-target collection 5 and 6 aerosol data over China: Effect of surface type, aerosol loading and aerosol absorption

For regions where limited in-situ observations are available for use as a reference, such as in China, the understanding of how changes in the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol retrieval algorithm impact the data quality is limited. In this paper, the MODIS-Aqua Aerosol Optical Thickness (AOT) Collection 5 (C5) and 6 (C6) Dark-Target (DT) products are evaluated by comparison with similar products from the China Aerosol Remote Sensing NETwork (CARSNET) and the Aerosol Robotic Network (AERONET) in China for the year 2008. The validation data are analyzed for key factors affecting the results of the MODIS-DT aerosol retrieval algorithm, including surface type, aerosol loading and aerosol absorption. The impacts of the change from the C5 to the C6 versions of the MODIS AOT retrieval algorithm are discussed in detail. The main findings are: (1) The agreement from retrieval aspects between both MODIS C5/C6 and CARSNET-AERONET for most AOT values over distinct regions indicates that the conclusions obtained from C5 hold for C6; (2) MODIS-DT has an extended coverage (more retrievals) with good quality due to the change of upstream data (calibration, cloud masking, etc); (3) About 64% of the MODISDT C6 AOT data over China fall within the (±0.15 AOT ± 0.05) error envelope; (4) positive AOT differences between C6 and C5 over relatively dark surfaces and negative differences over relatively bright surfaces due to the change of surface parameterization have been observed; (5) the AOT difference between MODIS and CARSNET-AERONET relating to AOT loading is not significant, especially for large AOT; (6) MODIS-DT performs well for absorbing aerosol over relatively bright surfaces.

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

AbstractThe 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.

Assessment of two aerosol optical thickness retrieval algorithms applied to MODIS Aqua and Terra measurements in Europe

Abstract. The aim of the present study is to validate AOT (aerosol optical thickness) and Ångström exponent (α), obtained from MODIS (MODerate resolution Imaging Spectroradiometer) Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground) with the SAER (Satellite AErosol Retrieval) algorithm and with MODIS Collection 5 (c005) standard product retrievals (10 km horizontal resolution), against AERONET (AErosol RObotic NETwork) sun photometer observations over land surfaces in Europe. An inter-comparison of AOT at 0.469 nm obtained with the two algorithms has also been performed. The time periods investigated were chosen to enable a validation of the findings of the two algorithms for a maximal possible variation in sun elevation. The satellite retrievals were also performed with a significant variation in the satellite-viewing geometry, since Aqua and Terra passed the investigation area twice a day for several of the cases analyzed. The validation with AERONET shows that the AOT at 0.469 and 0.555 nm obtained with MODIS c005 is within the expected uncertainty of one standard deviation of the MODIS c005 retrievals (ΔAOT = ± 0.05 ± 0.15 · AOT). The AOT at 0.443 nm retrieved with SAER, but with a much finer spatial resolution, also agreed reasonably well with AERONET measurements. The majority of the SAER AOT values are within the MODIS c005 expected uncertainty range, although somewhat larger average absolute deviation occurs compared to the results obtained with the MODIS c005 algorithm. The discrepancy between AOT from SAER and AERONET is, however, substantially larger for the wavelength 488 nm. This means that the values are, to a larger extent, outside of the expected MODIS uncertainty range. In addition, both satellite retrieval algorithms are unable to estimate α accurately, although the MODIS c005 algorithm performs better. Based on the inter-comparison of the SAER and MODIS c005 algorithms, it was found that SAER on the whole is able to obtain results within the expected uncertainty range of MODIS Aqua and Terra observations.

Speeding up the aerosol optical thickness retrieval using analytical solutions of radiative transfer theory

Abstract. We present here the aerosol retrieval technique FAR that uses radiative transfer computations in the process of retrieval rather than look-up tables (LUT). This approach provides operational satellite data processing due to the use of the accurate and extremely fast radiative transfer code RAY previously developed by authors along with approximate analytical solutions of the radiative transfer theory. The model of the stratified atmosphere is taken as two coupled layers. Both layers include aerosol scattering and absorption, molecular scattering and gas absorption. The atmosphere parameters are assumed to change from pixel to pixel in the lower atmosphere layer, but the upper stratified layer of the atmosphere over 2–3 km is supposed to be horizontally homogenous for the frame under retrieval. The model of the land spectral albedo is taken as a weighted sum of two a priory chosen basic spectra. The aerosol optical thickness (AOT), Angström exponent and the weight in the land spectral albedo are optimized in the iteration process using the least-squares technique with fast computations of the derivatives of radiative characteristics with respect to retrieved values. The aerosol model and, hence, the aerosol phase function and single scattering albedo, is predefined and does not change in the iteration process. The presented version of FAR is adjusted to process the MERIS data. But it is important that the developed technique can be adapted for processing data of various satellite instruments (including any spectral multi-angle polarization-sensitive sensors). The use of approximate analytical radiative transfer solutions considerably speeds up data processing but may lead to about 15–20% increase of AOT retrieval errors. This approach is advantageous when just the satellite data processing time rather than high accuracy of the AOT retrieval is crucial. A good example is monitoring the trans-boundary transfer of aerosol impurities, particularly in the case of emergencies such as volcano eruptions, or various industrial disasters. Beside, two important problems that determine the accuracy of the AOT retrieval are considered. The first one is the effect of the preliminary choice of the aerosol model, particularly for the retrieval from satellite instruments providing only spectral data (MERIS, MODIS). The second problem is the influence of clouds in adjacent pixels. As for our knowledge, this problem has not been given the required attention up to now and it should be properly accounted for in the AOT retrieval algorithms.

A new method to retrieve aerosol optical thickness from satellite images on a parallel system

A wide variety of algorithms have been developed to monitor aerosol burden from satellite images. Still, few solutions currently allow for real-time and efficient retrieval of aerosol optical thickness (AOT), mainly due to the extremely large volume of computation necessary for the numeric solution of atmospheric radiative transfer equations. Taking into account the efforts to exploit the SYNergy of Terra and Aqua Modis (SYNTAM, an AOT retrieval algorithm), we present in this paper a novel method to retrieve AOT from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images, in which the strategy of block partition and collective communication was taken, thereby maximizing load balance and reducing the overhead time during inter-processor communication. Experiments were carried out to retrieve AOT at 0.44, 0.55, and 0.67 μm of MODIS/Terra and MODIS/Aqua data, using the parallel SYNTAM algorithm in the IBM System Cluster 1600 deployed at China Meteorological Administration (CMA). Results showed that parallel implementation can greatly reduce computation time, and thus ensure high parallel efficiency. AOT derived by parallel algorithm was validated against measurements from ground-based sun-photometers; in all cases, the relative error range was within 20%, which demonstrated that the parallel algorithm was suitable for applications such as air quality monitoring and climate modeling.

Validation of MODIS aerosol observations over the Netherlands with GLOBE student measurements

We have established a network of secondary schools in the Netherlands with students routinely measuring aerosol optical thickness (AOT) at two wavelengths with hand‐held Sun photometers. Students have performed more than 400 measurements between January 2002 and October 2005 over more than 12 locations within the Netherlands as a contribution to Global Learning and Observations to Benefit the Environment (GLOBE). We have developed an improved AOT retrieval algorithm that accounts for the effective wavelength of the broad‐band GLOBE detectors and for the spatiotemporal variation of ozone. Results from a theoretical error analysis indicate that GLOBE measurements achieve a precision better than 0.02 AOT for both channels. Comparisons with professional instruments generally give high correlations and low scatter and bias. From these tests, we conclude that student data are scientifically valid and may be used to validate MODIS AOT retrievals over the Netherlands. We find that over land, MODIS AOT is biased by +0.03 (470 nm) and −0.01 AOT (660 nm). Over coastal areas, MODIS overestimates AOT by 0.10 (470 nm) and 0.08 AOT (660 nm). Seasonally averaged MODIS observations over northwestern Europe show relatively highest AOT values over the region of Flanders and the Netherlands, with a seasonal cycle peaking in spring/summer. Our study shows the potential of secondary school‐based networks in addition to existing, professional networks that have much less spatial coverage.

Correlating MODIS aerosol optical thickness data with ground-based PM 2.5 observations across Texas for use in a real-time air quality prediction system

Investigations have been conducted at the Center for Space Research (CSR) into approaches to correlate MODIS aerosol optical thickness (AOT) values with ground-based, PM 2.5 observations made at continuous air monitoring station locations operated by the Texas Commission on Environmental Quality (TCEQ). These correlations are needed to more fully utilize real-time MODIS AOT analyses generated at CSR in operational air quality forecasts issued by TCEQ using a trajectory-based forecast model developed by NASA. Initial analyses of two data sets collected during 3 months in 2003 and all of 2004 showed linear correlations in the 0.4–0.5 range in the data collected over Texas. Stronger correlations (exceeding 0.9) were obtained by averaging these same data over longer timescales but this approach is considered unsuitable for use in issuing air quality forecasts. Peculiarities in the MODIS AOT analyses, referred to as hot spots, were recognized while attempting to improve these correlations. It is demonstrated that hot spots are possible when pixels that contain surface water are not detected and removed from the AOT retrieval algorithms. An approach to reduce the frequency of hot spots in AOT analyses over Texas is demonstrated by tuning thresholds used to detect inland water surfaces and remove pixels that contain them from the analysis. Finally, the potential impact of hot spots on MODIS AOT-PM 2.5 correlations is examined through the analysis of a third data set that contained sufficient levels of aerosols to mask inland water surfaces from the AOT algorithms. In this case, significantly stronger correlations, that exceed the 0.9 value considered suitable for use in a real-time air quality prediction system, were observed between the MODIS AOT observations and ground-based PM 2.5 measurements.

Development of a Global Validation Package for Satellite Oceanic Aerosol Optical Thickness Retrieval Based on AERONET Observations and Its Application to NOAA/NESDIS Operational Aerosol Retrievals

In this paper, a global validation package for satellite aerosol optical thickness retrieval using the Aerosol Robotic Network (AERONET) observations as ground truth is described. To standardize the validation procedure, the optimum time–space match-up window, the ensemble statistical analysis method, the best selection of AERONET channels, and the numerical scheme used to interpolate/extrapolate these observations to satellite channels have been identified through sensitivity studies. The package is shown to be a unique tool for more objective validation and intercomparison of satellite aerosol retrievals, helping to satisfy an increasingly important requirement of the satellite aerosol remote sensing community. Results of applying the package to the second-generation operational aerosol observational data (AEROBS) from the NOAA-14 Advanced Very High Resolution Radiometer (AVHRR) in 1998 and to the same year aerosol observation data [Clouds and the Earth's Radiant Energy System-Single Scanner Foodprint version 4 (CERES-SSF4)] from the Tropical Rainfall Measuring Mission (TRMM) Visible Infrared Scanner (VIRS) are presented as examples of global validation. The usefulness of the package for identifying improvements to the aerosol optical thickness τ retrieval algorithm is also demonstrated. The principal causes of systematic errors in the current National Oceanic and Atmospheric Administration (NOAA)/National Environmental Satellite, Data, and Information Service (NESDIS) operational aerosol optical thickness retrieval algorithm have been identified and can be reduced significantly, if the correction and adjustment suggested from the global validation are adopted. Random error in the τ retrieval is identified to be a major source of error on deriving the effective Ångström wavelength exponent α and may be associated with regional differences in aerosol particles, which are not accounted for in the current second-generation operational algorithm. Adjustments to the nonaerosol and aerosol radiative transfer model parameters that reduce systematic errors in τ retrievals are suggested for consideration in the next-generation algorithm. Basic features that should be included in the next-generation algorithm to reduce random error in τ retrievals and the resulting error in the effective Ångström wavelength exponent have also been discussed. Compared to the AERONET observation, the NOAA-14 AVHRR (AEROBS) τ values for mean conditions are biased high by 0.05 and 0.08, with random errors of 0.08 and 0.05, at 0.63 and 0.83 μm, respectively. Correspondingly, the TRMM VIRS (CERES-SSF4) values for mean conditions are biased high by 0.06 and 0.02, with random errors of 0.06 and 0.04 at 0.63 and 1.61 μm, respectively. After corrections and adjustments to the retrieval algorithm, the biases in both channels of AVHRR and VIRS are reduced significantly to values close to zero, although random error is almost unchanged. The α exponent derived directly from the aerosol optical thicknesses (τs) has been shown to be poorly correlated both before and after adjustments, indicating that random error in the τ measurement (possibly related to aerosol model parameter variations or cloud–surface reflectance contamination) needs to be reduced.

RETRIEVAL OF AEROSOL OPTICAL THICKNESS BY MEANS OF THE LEAST-MEDIAN-SQUARES ROBUST ALGORITHM

Atmospheric aerosols play an active role in the atmospheric radiative energy transfer by interacting with the solar energy through light scattering and/or absorption. Such an interaction has the potential to counter balance or enhance the warming caused by the greenhouse gases (e.g. carbon dioxide, water vapor, and methane). The interactions would depend on a variety of factors such as the microphysics and chemistry of aerosol particles, and the environmental conditions. To model the energy transfer processes accurately, several aerosol parameters such as aerosol optical thickness (AOT), single scattering albedo, scattering phase function, refractive index, and chemical composition of aerosols have to be known. In this report, a robust method for aerosol optical thickness is presented. The method is based on the least median squares (LMS) regression technique. The LMS-based technique is fundamentally different from the traditional least-squares (LS) technique commonly used today to retrieve AOT. The LMS technique was found to resist influential outliers and sustain the impacts of outliers much better than the LS in our application. The outlier-resistance property is an important design consideration for an automatic AOT retrieval algorithm. We demonstrated the strength of the new technique by using the shortwave irradiance measurements taken by one of the Multi-filter Rotating Shadow-band Radiometers installed at the Southern Great Plains in Oklahoma, U.S.A., one of the three sites operated by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program. The data cover a time period from September 1995 to May 1997. The LMS-retrieved mean top-of-atmosphere solar irradiance values (i.e. I 0) were stable based on the one-tailed Student’s t tests. It was also found that the difference between the 75th and 25th percentiles (a non-parametric robust estimate of variation) of I 0 over the 2-year period was 0.2 for the 499-nm channel, and 0.05 for the 860-nm channel. The monthly averaged AOT values over the 2-year period were from 0.05 to 0.30 for the 499-nm channel and from 0.03 to 0.15 for the 860-nm channels. AOT values peaked between May and September and reached minima in between November and January. The synoptic flow from the North might have contributed to the low level of AOT values during the wintertime, while the southerly flow, traversing through more industrial areas before reaching the site, could have contributed to the influx of particles during the summertime.