scholarly journals Climatology of the aerosol optical depth by components from the Multi-angle Imaging SpectroRadiometer (MISR) and chemistry transport models

2016 ◽  
Vol 16 (10) ◽  
pp. 6627-6640 ◽  
Author(s):  
Huikyo Lee ◽  
Olga V. Kalashnikova ◽  
Kentaroh Suzuki ◽  
Amy Braverman ◽  
Michael J. Garay ◽  
...  

Abstract. The Multi-angle Imaging SpectroRadiometer (MISR) Joint Aerosol (JOINT_AS) Level 3 product has provided a global, descriptive summary of MISR Level 2 aerosol optical depth (AOD) and aerosol type information for each month over 16+ years since March 2000. Using Version 1 of JOINT_AS, which is based on the operational (Version 22) MISR Level 2 aerosol product, this study analyzes, for the first time, characteristics of observed and simulated distributions of AOD for three broad classes of aerosols: spherical nonabsorbing, spherical absorbing, and nonspherical – near or downwind of their major source regions. The statistical moments (means, standard deviations, and skewnesses) and distributions of AOD by components derived from the JOINT_AS are compared with results from two chemistry transport models (CTMs), the Goddard Chemistry Aerosol Radiation and Transport (GOCART) and SPectral RadIatioN-TrAnSport (SPRINTARS). Overall, the AOD distributions retrieved from MISR and modeled by GOCART and SPRINTARS agree with each other in a qualitative sense. Marginal distributions of AOD for each aerosol type in both MISR and models show considerable high positive skewness, which indicates the importance of including extreme AOD events when comparing satellite retrievals with models. The MISR JOINT_AS product will greatly facilitate comparisons between satellite observations and model simulations of aerosols by type.

2015 ◽  
Vol 15 (23) ◽  
pp. 33897-33929 ◽  
Author(s):  
H. Lee ◽  
O. V. Kalashnikova ◽  
K. Suzuki ◽  
A. Braverman ◽  
M. J. Garay ◽  
...  

Abstract. The Multi-angle Imaging SpectroRadiometer (MISR) Joint Aerosol (JOINT_AS) Level 3 product provides a global, descriptive summary of MISR Level 2 aerosol optical depth (AOD) and aerosol type information for each month between March 2000 and the present. Using Version 1 of JOINT_AS, which is based on the operational (Version 22) MISR Level 2 aerosol product, this study analyzes, for the first time, characteristics of observed and simulated distributions of AOD for three broad classes of aerosols: non-absorbing, absorbing, and non-spherical – near or downwind of their major source regions. The statistical moments (means, standard deviations, and skewnesses) and distributions of AOD by components derived from the JOINT_AS are compared with results from the SPectral RadIatioN-TrAnSport (SPRINTARS) model, a chemistry transport model (CTM) with very high spatial and temporal resolution. Overall, the AOD distributions of combined MISR aerosol types show good agreement with those from SPRINTARS. Marginal distributions of AOD for each aerosol type in both MISR and SPRINTARS show considerable high positive skewness, which indicates the importance of including extreme AOD events when comparing satellite retrievals with models. The MISR JOINT_AS product will greatly facilitate comparisons between satellite observations and model simulations of aerosols by type.


2013 ◽  
Vol 13 (2) ◽  
pp. 675-692 ◽  
Author(s):  
J. A. Ruiz-Arias ◽  
J. Dudhia ◽  
C. A. Gueymard ◽  
D. Pozo-Vázquez

Abstract. The daily Level-3 MODIS aerosol optical depth (AOD) product is a global daily spatial aggregation of the Level-2 MODIS AOD (10-km spatial resolution) into a regular grid with a resolution of 1° × 1°. It offers interesting characteristics for surface solar radiation and numerical weather modeling applications. However, most of the validation efforts so far have focused on Level-2 products and only rarely on Level 3. In this contribution, we compare the Level-3 Collection 5.1 MODIS AOD dataset from the Terra satellite available since 2000 against observed daily AOD values at 550 nm from more than 500 AERONET ground stations around the globe. Overall, the mean error of the dataset is 0.03 (17%, relative to the mean ground-observed AOD), with a root mean square error of 0.14 (73%, relative to the same), but these errors are also found highly dependent on geographical region. We propose new functions for the expected error of the Level-3 AOD, as well as for both its mean error and its standard deviation. Additionally, we investigate the role of pixel count vis-à-vis the reliability of the AOD estimates, and also explore to what extent the spatial aggregation from Level 2 to Level 3 influences the total uncertainty in the Level-3 AOD. Finally, we use a radiative transfer model to investigate how the Level-3 AOD uncertainty propagates into the calculated direct normal and global horizontal irradiances.


2021 ◽  
Author(s):  
Vasilis Margaritis ◽  
Nikolaos Hatzianastassiou ◽  
Marios Bruno Korras Carraca ◽  
Maria Gavrouzou

<p>After the outbreak of SARS-CoV-2 in December 2019 and its spread worldwide in the following months and seasons, the governments around the world were forced, one by one, to impose lockdown measures in their countries during the ‘Covid Year’ of 2020, trying to slowdown or even stop the spread of the virus. These nationwide lockdowns, included measures that led to the reduction of human movement, such as transportation, in urban areas, while they also diminished the industrial activity. Since transportation and industrial activity are among the major sources of emission of anthropogenic aerosols, it is possible that a change, namely a decrease, of the atmospheric aerosol loading is observed during the year 2020. </p><p>In this study, we examine and quantify the possible effect of worldwide Covid19-related lockdowns on air quality, and more specifically on the aerosol optical depth, which is a good measure of aerosol loading. The analysis is done at global scale using Collection 6.1 Level-3 daily 1°x1° latitude-longitude gridded spectral Aerosol Optical Depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS) on AQUA satellite during the period 2003-2020. We assess the possible anomaly in AOD values during 2020 by comparing their annual, seasonal and monthly mean values with the corresponding climatological ones for the period 2003-2019. A trend analysis is also performed using time series of deseasonalized AOD anomalies during the period 2003-2020. Special emphasis is given to specific great urban areas, as well as to areas where stricter measures were taken for limiting the virus’ spread. For these areas of interest, a further analysis using higher resolution (10km x 10km) MODIS Level-2  AOD data was made in order to capture local changes in AOD that could be hindered by the coarser resolution Level-3 data. Finally, for these regions, the AOD changes estimated using MODIS Level-2 data are intercompared with the corresponding ones using data from local AERONET (AErosol RObotic NETwork) stations. Preliminary results show a clear reduction in AOD values, mainly starting from April 2020 and becoming more clear in late spring and early summer (May and June) of 2020.</p>


2020 ◽  
Vol 12 (17) ◽  
pp. 2847 ◽  
Author(s):  
Pawan Gupta ◽  
Lorraine A. Remer ◽  
Falguni Patadia ◽  
Robert C. Levy ◽  
Sundar A. Christopher

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce Level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and Level 3 data at 1 degree. The local and global applications have benefited from the coarse resolution gridded data sets (i.e., Level 3, 1 degree), as it is easier to use since data volume is low, and several online and offline tools are readily available to access and analyze the data with minimal computing resources. At the same time, researchers who require data at much finer spatial scales have to go through a challenging process of obtaining, processing, and analyzing larger volumes of data sets that require high-end computing resources and coding skills. Therefore, we created a high spatial resolution (high-resolution gridded (HRG), 0.1 × 0.1 degree) daily and monthly aerosol optical depth (AOD) product by combining two MODIS operational algorithms, namely Deep Blue (DB) and Dark Target (DT). The new HRG AODs meet the accuracy requirements of Level 2 AOD data and provide either the same or more spatial coverage on daily and monthly scales. The data sets are provided in daily and monthly files through open an Ftp server with python scripts to read and map the data. The reduced data volume with an easy to use format and tools to access the data will encourage more users to utilize the data for research and applications.


2010 ◽  
Vol 10 (12) ◽  
pp. 30731-30776 ◽  
Author(s):  
A. de Meij ◽  
A. Pozzer ◽  
J. Lelieveld

Abstract. This study evaluates global and regional aerosol optical depth (AOD) trends in view of aerosol (precursor) emission changes between 2000 and 2009. We use AOD products from MODIS, MISR and AERONET, and emission estimates from the EMEP, REAS and IPCC inventories. First we compare trends in global Level 3 AOD products of MODIS, MISR and AERONET (Level 2). We find generally negative trends over Europe and North America, whereas over South and East Asia they are mostly positive. The negative trends over parts of Europe and North-East America appear to be significant. Second, we analyze MODIS Level 2 AODs for three selected regions with good data coverage (Central Mediterranean, North-East America and East Asia) and compare with Level 3 products. This corroborates that the 2000–2009 AOD trend over the Central Mediterranean is negative and corresponds well with the MODIS Level 3 analysis. Also for North-East America the trend is generally negative and in agreement with MODIS Level 3 products. For East Asia the trends derived from Level 2 products are mostly positive and correspond with the MODIS Level 3 results. Over Europe, the trends in aerosol single scattering albedo, as derived from MISR data, appear to be positive (declining solar radiation absorption), whereas this is not the case over the USA, though these data are not yet validated. Third we compare trends in AOD with emission changes of SO2, NOx, NH3 and black carbon. We associate the downward trends in AOD over Europe and North America with decreasing emissions of SO2, NOx, and other criteria pollutants, and consequently declining aerosol concentrations. Over East Asia the MODIS Level 2 trends are generally positive, consistent with increasing pollutant emissions by fossil energy use and growing industrial and urban activities. It appears that SO2 emission changes dominate the AOD trends, although especially in Asia NOx emissions may become increasingly important. Our results suggest that solar brightening due to decreasing SO2 emissions and resulting downward AOD trends over Europe may have weakened in the 2000s compared to the 1990s.


2012 ◽  
Vol 12 (9) ◽  
pp. 23219-23260 ◽  
Author(s):  
J. A. Ruiz-Arias ◽  
J. Dudhia ◽  
C. A. Gueymard ◽  
D. Pozo-Vázquez

Abstract. The Level-3 MODIS aerosol optical depth (AOD) product offers interesting features for surface solar radiation and numerical weather modeling applications. Remarkably, the Collection 5.1 dataset extends over more than a decade, and provides daily values of AOD over a global regular grid of 1°×1° spatial resolution. However, most of the validation efforts so far have focused on Level-2 products (10-km, at original resolution) and only rarely on Level-3 (at aggregated spatial resolution of 1°×1°). In this contribution, we compare the Level-3 Collection 5.1 MODIS AOD dataset available since 2000 against observed daily AOD values at 550 nm from more than 500 AERONET ground stations around the globe. One aim of this study is to check the advisability of this MODIS dataset for surface shortwave solar radiation calculations using numerical weather models. Overall, the mean error of the dataset is 0.03 (17%, relative to the mean ground-observed AOD), with a root mean square error of 0.14 (73%, relative to the same), albeit these values are found highly dependent on geographical region. For AOD values below about 0.3 the expected error is found very similar to that of the Level-2 product. However, for larger AOD values, higher errors are found. Consequently, we propose new functions for the expected error of the Level-3 AOD, as well as for both its mean error and its standard deviation. Additionally, we investigate the role of pixel count vis-à-vis the reliability of the AOD estimates. Our results show that a higher pixel count does not necessarily turn into a more reliable AOD estimate. Therefore, we recommend to verify this assumption in the dataset at hand if the pixel count is meant to be used. We also explore to what extent the spatial aggregation from Level-2 to Level-3 influences the total uncertainty in the Level-3 AOD. In particular, we found that, roughly, half of the error might be attributable to Level-3 AOD sub-pixel variability. Finally, we use a~radiative transfer model to investigate how the Level-3 AOD uncertainty propagates into the calculated direct normal (DNI) and global horizontal (GHI) irradiances. Overall, results indicate that, for Level-3 AODs smaller than 0.5, the induced uncertainty in DNI due to the AOD uncertainty alone is below 15% on average, and below 5% for GHI (for a solar zenith angle of 30°. However, the uncertainty in AOD is highly spatially variable, and so is that in irradiance.


2010 ◽  
Vol 3 (5) ◽  
pp. 4091-4167 ◽  
Author(s):  
E. J. Hyer ◽  
J. S. Reid ◽  
J. Zhang

Abstract. MODIS Collection 5 retrieved aerosol optical depth (AOD) over land (MOD04/MYD04) was evaluated using 4 years of matching AERONET observations, to assess its suitability for aerosol data assimilation in numerical weather prediction models. Examination of errors revealed important sources of variation in random errors (e.g., atmospheric path length, scattering angle "hot spot"), and systematic biases (e.g., snow and cloud contamination, surface albedo bias). A set of quality assurance (QA) filters was developed to avoid conditions with potential for significant AOD error. An empirical correction for surface boundary condition using the MODIS 16-day albedo product captured 25% of the variability in the site mean bias at low AOD. A correction for regional microphysical bias using the AERONET fine/coarse partitioning information increased the global correlation between MODIS and AERONET from r2=0.62–0.65 to r2=0.71–0.73. Application of these filters and corrections improved the global fraction of MODIS AOD within (0.05±20%) of AERONET to 77%, up from 67% using only built-in MODIS QA. The compliant fraction in individual regions was improved by as much as 20% (South America). An aggregated Level 3 product for use in a data assimilation system is described, along with a prognostic error model to estimate uncertainties on a per-observation basis. The new filtered and corrected Level 3 product has improved performance over built-in MODIS QA with less than a 15% reduction in overall data available for data assimilation.


2012 ◽  
Vol 12 (2) ◽  
pp. 4031-4071 ◽  
Author(s):  
L. Mei ◽  
Y. Xue ◽  
G. de Leeuw ◽  
T. Holzer-Popp ◽  
J. Guang ◽  
...  

Abstract. A novel approach for the joint retrieval of aerosol optical depth (AOD) and surface reflectance, using Meteosat Second Generation – Spinning Enhanced Visible and Infrared Imagers (MSG/SEVIRI) observations in two solar channels, is presented. The retrieval is based on a time series (TS) technique, which makes use of the two visible bands at 0.6 μm and 0.8 μm in three orderly scan times (15 min interval between two scans) to retrieve the AOD over land. Using the radiative transfer equation for plane-parallel atmospheres two coupled differential equations for the upward and downward fluxes are derived. The boundary conditions for the upward and downward fluxes at the top and at the bottom of the atmosphere are used in these equations to provide an analytic solution for the surface reflectance. To derive these fluxes, the aerosol single scattering albedo (SSA) and asymmetry factor are required to provide a solution. These are provided from a set of six pre-defined aerosol types with the SSA and asymmetry factor (g). We assume one aerosol type for a grid of 1° × 1° and the surface reflectance changes little between two consequent scans. A k approximation was used in the inversion to find the best solution of atmospheric properties and surface reflectance. The algorithm makes use of numerical minimisation routines to obtain the optimal solution of atmospheric properties and surface reflectance by selection of the most suitable aerosol type from pre-defined sets. Also, it is assumed that the surface reflectance is little influenced by aerosol scattering at 1.6 μm and therefore the ratio of surface reflectances in the solar band for two consequent scans can be well-approximated by the ratio of the reflectances at 1.6 μm. A further assumption is that the surface reflectance varies only slightly over a period of 30 min. A detailed analysis of the retrieval results show that it is suitable for AOD retrieval over land. Six Aerosol Robotic Network (AERONET) sites with different surface types were used for detailed analysis and 42 other AERONET sites were used for validation. From 445 collocations representing stable and homogeneous aerosol type, we found that >75% of MSG-retrieved AOD values compared to AERONET observed values with an error envelope of ±0.05 ± 0.15τ and a high correlation (R > 0.86). The AOD datasets derived using the TS method with SEVIRI data was also compared with collocated AOD products derived from the NASA TERRA and AQUA MODIS data using the dark dense vegetation (DDV) method and the Deep Blue algorithms. Using the TS method, AOD could be retrieved for more pixels than with the NASA Deep Blue algorithm. The AOD values derived compare favourably.


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