scholarly journals Implications of MODIS bowtie distortion on aerosol optical depth retrievals, and techniques for mitigation

2015 ◽  
Vol 8 (8) ◽  
pp. 8727-8752 ◽  
Author(s):  
A. M. Sayer ◽  
N. C. Hsu ◽  
C. Bettenhausen
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Geographical Location ◽  
Pixel Size ◽  
Shape Distortion ◽  
Deep Blue ◽  
L2 Processing ◽  
Simple Step ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The scan geometry of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors results in a pixel shape distortion known as the "bowtie effect". Specifically, sensor pixels near the edge of the swath are elongated along-track and across-track compared to pixels near the centre of the swath, resulting in an increase of pixel area by up to a factor of ~ 9, and additionally pixels acquired from consecutive scans overlap. The Deep Blue and Dark Target aerosol optical depth (AOD) retrieval algorithms aggregate sensor pixels and provide level 2 (L2) AOD at a nominal horizontal pixel size of 10 km, but the bowtie distortion means that they also suffer from this size increase and overlap. This means that the spatial characteristics of the data vary as a function of satellite viewing zenith angle (VZA) and, for VZA > 30°, corresponding to approximately 50 % of the data, are areally enlarged by a factor of 50 % or more compared to this nominal pixel area, and are not spatially independent of each other. This has implications for retrieval uncertainty and aggregated statistics, causing a narrowing of AOD distributions near the edge of the swath, as well as for data comparability from the application of similar algorithms to sensors without this level of bowtie distortion. Additionally, the pixel overlap is not obvious to users of the L2 aerosol products because only pixel centres, not boundaries, are provided within the L2 products. A two-step procedure is proposed to mitigate the effects of this distortion on the MODIS aerosol products. The first (simple) step involves changing the order in which pixels are aggregated in L2 processing to reflect geographical location rather than scan order, which removes the bulk of the overlap between L2 pixels, and slows the rate of growth of L2 pixel size vs. VZA. This can be achieved without significant changes to existing MODIS processing algorithms. The second step involves additionally changing the number of sensor pixels aggregated across-track as a function of VZA, which preserves L2 pixel size at around 10 km × 10 km across the whole swath, but would require algorithmic quality assurance tests to be re-evaluated. Both of these steps also improve the extent to which the pixel locations a user would infer from the L2 data products represent the actual spatial extent of the L2 pixels.

scholarly journals Implications of MODIS bow-tie distortion on aerosol optical depth retrievals, and techniques for mitigation

2015 ◽  
Vol 8 (12) ◽  
pp. 5277-5288 ◽  
Author(s):  
A. M. Sayer ◽  
N. C. Hsu ◽  
C. Bettenhausen
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Geographical Location ◽  
Pixel Size ◽  
Shape Distortion ◽  
Deep Blue ◽  
L2 Processing ◽  
Simple Step ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Bow Tie

Abstract. The scan geometry of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, combined with the Earth's curvature, results in a pixel shape distortion known as the "bow-tie effect". Specifically, sensor pixels near the edge of the swath are elongated along-track and across-track compared to pixels near the centre of the swath, resulting in an increase of pixel area by up to a factor of ∼ 9 and, additionally, the overlap of pixels acquired from consecutive scans. The Deep Blue and Dark Target aerosol optical depth (AOD) retrieval algorithms aggregate sensor pixels and provide level 2 (L2) AOD at a nominal horizontal pixel size of 10 km, but the bow-tie distortion means that they also suffer from this size increase and overlap. This means that the spatial characteristics of the data vary as a function of satellite viewing zenith angle (VZA) and, for VZA > 30°, corresponding to approximately 50 % of the data, are areally enlarged by a factor of 50 % or more compared to this nominal pixel area and are not spatially independent of each other. This has implications for retrieval uncertainty and aggregated statistics, causing a narrowing of AOD distributions near the edge of the swath, as well as for data comparability from the application of similar algorithms to sensors without this level of bow-tie distortion. Additionally, the pixel overlap is not obvious to users of the L2 aerosol products because only pixel centres, not boundaries, are provided within the L2 products. A two-step procedure is proposed to mitigate the effects of this distortion on the MODIS aerosol products. The first (simple) step involves changing the order in which pixels are aggregated in L2 processing to reflect geographical location rather than scan order, which removes the bulk of the overlap between L2 pixels and slows the rate of growth of L2 pixel size vs. VZA. This can be achieved without significant changes to existing MODIS processing algorithms. The second step involves additionally changing the number of sensor pixels aggregated across-track as a function of VZA, which preserves L2 pixel size at around 10 km × 10 km across the whole swath but would require algorithmic quality assurance tests to be re-evaluated. Both of these steps also improve the extent to which the pixel locations a user would infer from the L2 data products represent the actual spatial extent of the L2 pixels.

scholarly journals Aerosol Optical Depth from MODIS satellite data above the Pierre Auger Observatory

2019 ◽  
Vol 197 ◽  
pp. 02011
Author(s):  
Nataliia Borodai
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Satellite System ◽  
Horizontal Resolution ◽  
Pierre Auger Observatory ◽  
Fluorescence Detector ◽  
Deep Blue ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol optical depth can be retrieved from measurements performed by Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument. The MODIS satellite system includes two polar satellites, Terra and Aqua. Each of them flies over the Pierre Auger Observatory once a day, providing two measurements of aerosols per day and covering the whole area of the Observatory. MODIS aerosol data products have been generated by three dedicated algorithms over bright and dark land and over ocean surface. We choose the Deep Blue algorithm data to investigate the distribution of aerosols over the Observatory, as this algorithm is the most appropriate one for semi-arid land of the Pierre Auger Observatory. This data algorithm allows us to obtain aerosol optical depth values for the investigated region, and to build cloud-free aerosol maps with a horizontal resolution 0.1°×0.1°. Since a suffcient number of measurements was obtained only for Loma Amarilla and Coihueco fluorescence detector (FD) sites of the Pierre Auger Observatory, a more detailed analysis of aerosol distributions is provided for these sites. Aerosols over these FD sites are generally distributed in a similar way each year, but some anomalies are also observed. These anomalies in aerosol distributions appear mainly due to some transient events, such as volcanic ash clouds, fires etc. We conclude that the Deep Blue MODIS algorithm provides more realistic aerosol optical depth values than other available algorithms.

scholarly journals Comparison of aerosol optical depth from satellite (MODIS), Sun photometer and pyrheliometer ground-based measurements in Cuba

2017 ◽  
Author(s):  
Juan Carlos Antuña-Marrero ◽  
Victoria Cachorro Revilla ◽  
Frank García Parrado ◽  
Ángel de Frutos Baraja ◽  
Albeth Rodríguez Vega ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
The Sun ◽  
Deep Blue ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Sun Photometer ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Aerosol Properties ◽  
Satellite Instruments

Abstract. In the present study, we report the first comparison of the aerosol properties measured with sun photometer at Camagüey, Cuba, with the MODerate resolution Imaging Spectroradiometer (MODIS) instruments on Terra and Aqua satellites. We compared the aerosol optical depth at 550 nm (AOD) and the Ångström Exponent (AE) from the sun photometer for the period 2008 to 2014 with the same variables measured by both MODIS instruments, that are spatially and temporally coincident. The comparison includes AOD derived with both Deep Blue (DB) and Dark Target (DT) algorithms from MODIS Collection 6. The AOD derived with DT algorithm for Terra and Aqua agrees better with AOD from the sun photometer than the AOD derived with DB. Additionally there is little difference between AOD from both satellite instruments, when they are compared with sun photometer AOD, allowing to combine AOD from Terra and Aqua for more comprehensive climatological statistics. The comparison of the AE showed similar results with reports in the literature about the little skills of the current DT and DB algorithms for its retrieval. In addition, we report the comparison of the broadband AOD (BAOD) from pyrheliometer measurements located at Camagüey site and other three meteorological stations along Cuba, with AOD measurements from the sun photometer and from MODIS onboard Terra and Aqua. The comparison of the BAOD from the four sites as a whole with coincident AOD from MODIS onboard Terra and Aqua showed similar results than the ones of the comparison between the sun photometer AOD and the AOD from the two satellite instruments. In the comparison between the BAOD and the AOD at each one of the eight individual sun photometer wavelengths, the results improve in the spectral range 400 to 675 nm, with the best result at 500 nm. The BAOD typical uncertainty ranges from 0.04 to 0.06 at this band. The results from the BAOD comparisons demonstrate its reliability for characterizing AOD at sites with no sun photometer and for extending backward in time AOD estimates.

scholarly journals INTER-COMPARISON BETWEEN MODIS SATELLITE-BASED AND AERONET GROUND-BASED AEROSOL OPTICAL DEPTH PRODUCTS IN VIETNAM

2020 ◽  
Vol 58 (3A) ◽  
pp. 124
Author(s):  
DUC LUONG NGUYEN ◽  
Thi Hieu Bui ◽  
Hoang Hiep Nguyen ◽  
Quang Trung Bui ◽  
Hoang Duong Do
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Subtropical Climate ◽  
Deep Blue ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
First Time ◽  
Climatic Characteristics

Although a number of studies have extensively inter-compared the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-based aerosol optical depth (AOD) with the Aerosol Robotic Network (AERONET) ground-based AOD on both global and regional scales, almost no similar studies have been conducted for Vietnam - a humid subtropical climate region. For the first time, inter-comparison between the MODIS Terra and Aqua Collection 6.1 (C6.1) Dark Target (DT) 10 km, Deep Blue (DB) 10 km, and merged DT-DB 10 km with the AERONET AODs has been performed in different areas with different surface types and different climatic characteristics in Vietnam. Three investigated AERONET stations are Nghia Do (urban), Son La (mountainous rural), and Bac Lieu (coastal urban) with the studying periods of 2010 - 2016, 2012 - 2017, and 2010 - 2017, respectively. Our findings showed the better performances of DB algorithm than those of DT and DT-DB products in the urban area. Additionally, all MODIS AOD algorithm performed worse over the coastal area compared to those in the non-coastal areas. Generally, the ability of all the MODIS AODs to catch up the monthly-mean AERONET AODs has been expressed in this study.

scholarly journals Critical evaluation of the MODIS Deep Blue aerosol optical depth product for data assimilation over North Africa

2012 ◽  
Vol 5 (5) ◽  
pp. 7815-7865 ◽  
Author(s):  
Y. Shi ◽  
J. Zhang ◽  
J. S. Reid ◽  
E. J. Hyer ◽  
N. C. Hsu
Keyword(s):  
Quality Assurance ◽  
Data Assimilation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
North Africa ◽  
Critical Evaluation ◽  
Deep Blue ◽  
Moderate Resolution ◽  
Level 3 ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. A total of eight years of Terra (2000–2007) and Aqua (2002–2009) Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) collection 5.1 (c5.1) data were examined for their potential usage in aerosol assimilation. Uncertainties in the DB Aerosol Optical Depth (AOD) were identified and studied. Empirical corrections and quality assurance procedures were developed for North Africa and the Arabian Peninsula. After applying quality assurance and quality check procedures, the Root-Mean-Square-Error (RMSE) in the MODIS Terra and Aqua AOD are reduced by 18.1 and 18.2% to 0.16 and 0.17, respectively, with respect to AERONET data. These procedures were also applied to two months of DB collection 6 (c6) AOD data and reductions in RMSE were found, indicating that the algorithms developed for c5.1 data are applicable to c6 data to some extent. A new quality-assured DB level 3 AOD product was developed for future implementations in both aerosol data assimilation and climate related applications.

scholarly journals Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

2015 ◽  
Vol 8 (10) ◽  
pp. 4083-4110 ◽  
Author(s):  
R. C. Levy ◽  
L. A. Munchak ◽  
S. Mattoo ◽  
F. Patadia ◽  
L. A. Remer ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Quantitative Information ◽  
Environmental Data ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
Data Record ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March–April–May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

scholarly journals An Effective and Efficient Enhanced Fixed Rank Smoothing Method for the Spatiotemporal Fusion of Multiple-Satellite Aerosol Optical Depth Products

2020 ◽  
Vol 12 (7) ◽  
pp. 1102
Author(s):  
Bin Zou ◽  
Ning Liu ◽  
Wei Wang ◽  
Huihui Feng ◽  
Xiangping Liu ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Mainland China ◽  
Bayesian Maximum Entropy ◽  
Time Cost ◽  
Long Time ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Fixed Rank

Current reported spatiotemporal solutions for fusing multisensor aerosol optical depth (AOD) products used to recover gaps either suffer from unacceptable accuracy levels, i.e., fixed rank smooth (FRS), or high time costs, i.e., Bayesian maximum entropy (BME). This problem is generally more serious when dealing with multiple AOD products in a long time series or over large geographic areas. This study proposes a new, effective, and efficient enhanced FRS method (FRS-EE) to fuse satellite AOD products with uncertainty constraints. AOD products used in the fusion experiment include Moderate Resolution Imaging SpectroRadiometer (MODIS) DB/DT_DB_Combined AOD and Multiangle Imaging SpectroRadiometer (MISR) AOD across mainland China from 2016 to 2017. Results show that the average completeness of original, initial FRS fused, and FRS-EE fused AODs with uncertainty constraints are 22.80%, 95.18%, and 65.84%, respectively. Although the correlation coefficient (R = 0.77), root mean square error (RMSE = 0.30), and mean bias (Bias = 0.023) of the initial FRS fused AODs are relatively lower than those of original AODs compared to Aerosol Robotic Network (AERONET) AOD records, the accuracy of FRS-EE fused AODs, which are R = 0.88, RMSE = 0.20, and Bias = 0.022, is obviously improved. More importantly, in regions with fully missing original AODs, the accuracy of FRS-EE fused AODs is close to that of original AODs in regions with valid retrievals. Meanwhile, the time cost of FRS-EE for AOD fusion was only 2.91 h; obviously lower than the 30.46 months taken for BME.

scholarly journals Comparison of PMCAMx aerosol optical depth predictions over Europe with AERONET and MODIS measurements

2016 ◽  
Vol 9 (11) ◽  
pp. 4257-4272
Author(s):  
Antigoni Panagiotopoulou ◽  
Panagiotis Charalampidis ◽  
Christos Fountoukis ◽  
Christodoulos Pilinis ◽  
Spyros N. Pandis
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Chemical Transport Model ◽  
Secondary Aerosol ◽  
The Balkans ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
High Dust

Abstract. The ability of chemical transport model (CTM) PMCAMx to reproduce aerosol optical depth (AOD) measurements by the Aerosol Robotic Network (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) over Europe during the photochemically active period of May 2008 (EUCAARI campaign) is evaluated. Periods with high dust or sea-salt levels are excluded, so the analysis focuses on the ability of the model to simulate the mostly secondary aerosol and its interactions with water. PMCAMx reproduces the monthly mean MODIS and AERONET AOD values over the Iberian Peninsula, the British Isles, central Europe, and Russia with a fractional bias of less than 15 % and a fractional error of less than 30 %. However, the model overestimates the AOD over northern Europe, most probably due to an overestimation of organic aerosol and sulfates. At the other end, PMCAMx underestimates the monthly mean MODIS AOD over the Balkans, the Mediterranean, and the South Atlantic. These errors appear to be related to an underestimation of sulfates. Sensitivity tests indicate that the evaluation results of the monthly mean AODs are quite sensitive to the relative humidity (RH) fields used by PMCAMx, but are not sensitive to the simulated size distribution and the black carbon mixing state. The screening of the satellite retrievals for periods with high dust (or coarse particles in general) concentrations as well as the combination of the MODIS and AERONET datasets lead to more robust conclusions about the ability of the model to simulate the secondary aerosol components that dominate the AOD during this period.

Sign in / Sign up

Export Citation Format

Share Document