The MODIS Aerosol Algorithm, Products, and Validation

A new method of satellite-based haze aerosol monitoring over the North China Plain and a comparison with MODIS Collection 6 aerosol products

Abstract. Satellite-derived aerosol products provide long-term and large-scale observations for analysing aerosol distributions and variations, climate-scale aerosol simulations, and aerosol–climate interactions. Therefore, a better understanding of the consistencies and differences among multiple aerosol products is important. The objective of this study is to compare 11 global monthly aerosol optical depth (AOD) products, which are the European Space Agency Climate Change Initiative (ESA-CCI) Advanced Along-Track Scanning Radiometer (AATSR), Advanced Very High Resolution Radiometer (AVHRR), Multi-angle Imaging SpectroRadiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Visible Infrared Imaging Radiometer (VIIRS), and POLarization and Directionality of the Earth's Reflectance (POLDER) products. AErosol RObotic NEtwork (AERONET) Version 3 Level 2.0 monthly measurements at 308 sites around the world are selected for comparison. Our results illustrate that the spatial distributions and temporal variations of most aerosol products are highly consistent globally but exhibit certain differences on regional and site scales. In general, the AATSR Dual View (ADV) and SeaWiFS products show the lowest spatial coverage with numerous missing values, while the MODIS products can cover most areas (average of 87 %) of the world. The best performance is observed in September–October–November (SON) and the worst is in June–July–August (JJA). All the products perform unsatisfactorily over northern Africa and Middle East, southern and eastern Asia, and their coastal areas due to the influence from surface brightness and human activities. In general, the MODIS products show the best agreement with the AERONET-based AOD values on different spatial scales among all the products. Furthermore, all aerosol products can capture the correct aerosol trends at most cases, especially in areas where aerosols change significantly. The MODIS products perform best in capturing the global temporal variations in aerosols. These results provide a reference for users to select appropriate aerosol products for their particular studies.

Assessing spatiotemporal variations of AOD in Japan based on Himawari-8 L3 V31 aerosol products: Validations and applications

The moderate resolution imaging spectroradiometer (MODIS) is one of the widely used sensors to address environmental and climate change subjects with a daily global coverage. MODIS Collection 6 aerosol products at 10-km resolution are used in this study to monitor aerosol variability and assess its uncertainty using ground-based measurements. The aerosol optical depth (AOD) is retrieved by different algorithms based on the pixel surface, determining between land and ocean. Using data collected from Sidi Salem Aerosol Robotic Network (AERONET) station, we computed the accuracy for aerosol optical depth (AOD) retrieved from MODIS aboard the AQUA satellite using two validation methods. The results show a good agreement between MODIS and AERONET data for the study period using both the algorithms. We obtained high values of the correlation coefficient. These findings indicate that MODIS data perform well over Ben Salem AERONET station and are recommended for air quality monitoring over Tunisia. The conducted validation throughout the AERONET leads to a degree of confidence that allows a deep investigation of the AOD spatial variability over Tunisia. Then, MODIS data shows high performance with good certainty to identify the principal dust sources and typical transport paths occurring on the study region.

We present the first extended validation of a new synergy global aerosol product (SY_2_AOD) which is based on synergistic use of data from the Ocean and Land Color Instrument (OLCI), and the Sea and Land Surface Temperature Radiometer (SLSTR) sensors onboard the Copernicus Sentinel-3A (S3A) and Sentinel-3B (S3B) satellites. Several approaches, including statistical analysis, time series analysis, comparison with similar aerosol products from the other spaceborne sensor Moderate Resolution Imaging Spectroradiometer (MODIS), were used for validation end evaluation of S3A and S3B SY_2 aerosol products, including Aerosol Optical Depth (AOD) provided at different wavelengths, AOD pixel level uncertainties, fine mode AOD and Angström exponent. Over ocean, the performance of SY_2 retrieved AOD is good: for S3A and S3B respectively, correlation coefficients with the Maritime Aerosol Network (MAN) component of the AErosol RObotic NETwork (AERONET) are 0.88 and 0.85; 88.6 % and 89.5 % of pixels fit into MODIS error envelope of ±0.05±0.2*AOD. Over land correlation coefficients with AERONET AOD are 0.60 and 0.63 for S3A and S3B respectively; 51.4 % and 57.9 % of pixels fit into MODIS error envelope. Reduced performance over land is expected since the surface reflectance and angular distribution of scattering is higher and more difficult to predict over land than over ocean. The results are affected by a large number of outliers. Evaluation of the per-retrieval uncertainty indicated good correlation with measured error distributions. The retrieval of Angstrom exponent, related to aerosol size distribution, shows good spatial correlation with expected sources but generally overestimates AE for cases where AERONET Angstrom is low, resulting in overall high bias. Differences between the annual and seasonal AOD values from SY_2 and MODIS Dark Target and Deep blue products are within 0.02 for the study area. The agreement is better over ocean. Over bright land surface (Saharan desert) the difference between two products is highest (up to 0.11), and the sign of the difference varies over time and space. For both S3A and S3B AOD products, validation statistics are often slightly better in the Southern hemisphere. In general, the performance of S3B is slightly better.

Satellite aerosol remote sensing entered a new era with the deployment of advanced satellite imaging instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra and Aqua satellites. These new instruments provide the opportunity to learn more about aerosol properties than was possible using the simpler NOAA Advanced Very High Resolution Radiometer (AVHRR), which has been used to retrieve aerosol optical thickness for more than 20 years. Combining historical AVHRR and the more advanced MODIS aerosol retrievals to form a long‐term aerosol data record is critical for studying aerosol climate forcing. To achieve this objective, it is necessary to build a connection and establish consistency between the two retrievals through a careful evaluation of the two retrieval methods applied to the same data. As a first step in this effort, this paper exploits the potential of the Clouds and the Earth's Radiant Energy System (CERES) Single‐Scanner Footprint (SSF) data set that includes aerosol products derived from Terra MODIS data at the same locations using both the multichannel MODIS and the two‐channel AVHRR aerosol retrieval algorithms. The analysis examines the differences in the results seen over oceans on a global scale. It was found in a global mean sense that advancement in the aerosol retrieval over ocean from the MODIS algorithm relative to the AVHRR method is realized mostly in the improvement of the aerosol size parameter (ASP) rather than in the aerosol optical thickness (AOT). However, regional differences were observed in both AOT and ASP retrieved from the MODIS and AVHRR algorithms. These are examined further in the second part of this two‐part paper. Cloud contamination and surface roughness appear to affect both aerosol retrievals, effects that need further investigation.

This paper is devoted to analysis of aerosol distribution and variability over East Asia based on PARASOL/POLDER‐3 aerosol products over land. We first compared POLDER‐3 Aerosol Optical Depth (AOD) with fine mode AOD (particles radius ≤ 0.30 μm) computed from AERONET (Aerosol Robotic Network) inversions over 14 sites. The rather good correlation (R ≈ 0.92) observed over land demonstrates the remarkable sensitivity of POLDER‐3 retrievals to the smaller fraction of fine particles, mostly originating from anthropogenic sources. We analyzed the characteristics and seasonal variation of aerosol distribution over East Asia by considering 4 years of POLDER‐3 Level 2 data (March 2005 to February 2009). Our study shows that the spatial distribution of fine‐mode aerosols over East Asia, as retrieved from POLDER‐3, is highly associated with human activities. Our work also evidenced a strong variability of seasonal fine‐mode AOD patterns with geographical locations. Finally, the interannual variation during 2003–2009 periods of summer fine‐mode AOD over North China, in particular the Beijing City region, was analyzed for the contribution to evaluating the regional impact of emission reduction enforced in Beijing during the 2008 Olympic Summer Games. We found that the summer average of fine‐mode AOD exhibited relatively higher values in 2003, 2007, and 2008. The interannual variation patterns of monthly averaged AOD (June to August) shows that June generally exhibits the strongest variation and varies similarly to July, but differs from August. As a reference point, measured total AOD and fine‐mode AOD computed from AERONET inversions in summer are also discussed for the Beijing City region.

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 with the AERONET-retrieved microphysical and optical properties. For the Version 1 SOAR aerosol product, the dust optical models representative for Capo Verde site are 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 three 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 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; i.e., 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.

Abstract. The Earth Explorer mission Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) will not only provide profile information on aerosols but also deliver a horizontal context to it through measurements by its Multi-Spectral Imager (MSI). The columnar aerosol product relying on these passive signals is called M-AOT (MSI-Aerosol Optical Thickness). Its main parameters are aerosol optical thickness (AOT) at 670 nm over ocean and valid land pixels and at 865 nm over ocean. Here, the algorithm and assumptions behind it are presented. Further, first examples of product parameters are given based on applying the algorithm to simulated EarthCARE test data and Moderate Resolution Imaging Spectroradiometer (MODIS) Level-1 data. Comparisons to input fields used for simulations, to the official MODIS aerosol product, to AErosol RObotic NETwork (AERONET) and to Maritime Aerosol Network (MAN) show an overall reasonable agreement. Over ocean, correlations are 0.98 (simulated scenes), 0.96 (compared to MYD04) and 0.9 (compared to MAN). Over land, correlations are 0.62 (simulated scenes), 0.87 (compared to MYD04) and 0.77 (compared to AERONET). A concluding discussion will focus on future improvements that are necessary and envisioned to enhance the product.

Aerosol monitoring from space has been performed at mesoscale, for over two decades. Latest satellite aerosol products offer global daily coverage and a typical spatial resolution of 10 km × 10 km. A new synergy algorithm has been recently developed, to retrieve aerosol properties in higher spatial resolution, which may improve the study of aerosols at local scale, increasing the potential of Earth Observation to support local level air quality studies. The algorithm combines both spectral and angular information provided by MERIS and AATSR sensors, respectively. In the present study, the MERIS/AATSR synergy algorithm is validated by comparing the retrieved Aerosol Optical Thickness (AOT) with the respective AOT values observed at AERONET stations located in urban regions globally. AATSR, MERIS and AERONET data for the period August–September 2011 were analyzed. Comparisons with the respective AOT spatial distributions retrieved from MODIS aerosol product were also performed for the broader area of Athens. Results indicate that the retrieved AOT is in good agreement with the corresponding station measurements.KeywordsAerosol Robotic Network (AERONET)Moderate Resolution Imaging Spectroradiometer (MODIS)AERONET ObservationsAerosol RetrievalAdvanced Along-Track Scanning Radiometer (AATSR)These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Satellite aerosol optical depth (AOD) is widely used to estimate particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) mass concentrations. Polar orbiting satellite retrieval 1–2 times each day is frequently affected by cloud, snow cover or misclassification of heavy pollution. Novel methods are therefore required to improve AOD sampling. Sunphotometer provides much more AODs than satellite at a fixed point. Furthermore, much of the aerosol pollution is regional. Both factors indicate that sunphotometer has great potential for PM2.5 concentration estimation. The spatial representativeness of the Aerosol Robotic Network (AERONET) AOD at Beijing site is investigated by linear regression analysis of 13-year daily paired AODs at each grid from Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and Beijing AERONET. The result suggests a good correlation for the whole Beijing Administrative region, with regional mean correlation coefficient exceeding 0.73. Pixel AODs are then estimated from AERONET AOD using linear equations, which are verified to have the same accuracy as that of MODIS AOD. Either AOD from MODIS retrieval or estimation from AERONET AOD in the absence of MODIS pixel AOD is finally used to predict PM2.5 concentration. Daily AOD sampling in average is enhanced by 59% in winter when MODIS AODs are very limited. More importantly, synergy of AERONET and MODIS AOD is able to improve the estimation of regional mean PM2.5 concentrations, which indicates this method would play a significant role in monitoring regional aerosol pollution.

Improved aerosol retrieval algorithm using Landsat images and its application for PM10 monitoring over urban areas

<strong class="journal-contentHeaderColor">Abstract.</strong> The Earth Explorer mission Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) will not only provide profile information on aerosols but will also deliver a horizontal context to it through measurements by its Multi-Spectral Imager (MSI). The columnar aerosol product relying on these passive signals is called M-AOT. Its main parameters are aerosol optical thickness (AOT) at 670 nm over ocean and, where possible land, and at 865 nm over ocean. Here, the algorithm and assumptions behind it are presented. Further, first examples of product parameters are given based on applying the algorithm to simulated EarthCARE test data and Moderate Resolution Imaging Spectroradiometer (MODIS) Level-1 data. Comparisons to input fields used for simulations, to the official MODIS aerosol product, AErosol RObotic NETwork (AERONET) and to Maritime Aerosol Network (MAN) show an overall reasonable agreement. Over ocean correlations are 0.98 (simulated scenes), 0.96 (compared to MYD04) and 0.9 (compared to MAN). Over land correlations are 0.62 (simulated scenes), 0.87 (compared to MYD04) and 0.77 (compared to AERONET). A concluding discussion will focus on future improvements necessary and envisioned to enhance the product.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Earth Explorer mission Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) will not only provide profile information on aerosols but will also deliver a horizontal context to it through measurements by its Multi-Spectral Imager (MSI). The columnar aerosol product relying on these passive signals is called M-AOT. Its main parameters are aerosol optical thickness (AOT) at 670 nm over ocean and, where possible land, and at 865 nm over ocean. Here, the algorithm and assumptions behind it are presented. Further, first examples of product parameters are given based on applying the algorithm to simulated EarthCARE test data and Moderate Resolution Imaging Spectroradiometer (MODIS) Level-1 data. Comparisons to input fields used for simulations, to the official MODIS aerosol product, AErosol RObotic NETwork (AERONET) and to Maritime Aerosol Network (MAN) show an overall reasonable agreement. Over ocean correlations are 0.98 (simulated scenes), 0.96 (compared to MYD04) and 0.9 (compared to MAN). Over land correlations are 0.62 (simulated scenes), 0.87 (compared to MYD04) and 0.77 (compared to AERONET). A concluding discussion will focus on future improvements necessary and envisioned to enhance the product.

This paper presents the validation results of Aerosol Optical Depth (AOD) retrieved from the Spinning Enhanced Visible Infrared Radiometer (SEVIRI) data using the near-real-time algorithm further developed in the frame of the Satellite-based Monitoring Initiative for Regional Air quality (SAMIRA) project. The SEVIRI AOD was compared against multiple data sources: six stations of the Aerosol Robotic Network (AERONET) in Romania and Poland, three stations of the Aerosol Research Network in Poland (Poland–AOD) and Moderate Resolution Imaging Spectroradiometer (MODIS) data overlapping Romania, Czech Republic and Poland. The correlation values between a four-month dataset (June–September 2014) from SEVIRI and the closest temporally available data for both ground-based and satellite products were identified. The comparison of the SEVIRI AOD with the AERONET AOD observations generally shows a good correlation (r = 0.48–0.83). The mean bias is 0.10–0.14 and the root mean square error RMSE is between 0.11 and 0.15 for all six stations cases. For the comparison with Poland–AOD correlation values are 0.55 to 0.71. The mean bias is 0.04–0.13 and RMSE is between 0.10 and 0.14. As for the intercomparison to MODIS AOD, correlations values were generally lower (r = 0.33–0.39). Biases of −0.06 to 0.24 and RMSE of 0.04 to 0.28 were in good agreement with the ground–stations retrievals. The validation of SEVIRI AOD with AERONET results in the best correlations followed by the Poland–AOD network and MODIS retrievals. The average uncertainty estimates are evaluated resulting in most of the AOD values falling above the expected error range. A revised uncertainty estimate is proposed by including the observed bias form the AERONET validation efforts.