scholarly journals An analysis of the Collection 5 MODIS over-ocean aerosol optical depth product for its implication in aerosol assimilation

2010 ◽  
Vol 10 (8) ◽  
pp. 20239-20265 ◽  
Author(s):  
Y. Shi ◽  
J. Zhang ◽  
J. S. Reid ◽  
B. Holben ◽  
E. J. Hyer ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Data Assimilation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Characteristics ◽  
Water Aerosol ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Level 3 ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. As an update to our previous use of the Collection 4 Moderate Resolution Imaging Spectroradiometer (MODIS) over-water aerosol optical depth (AOD, symbol as τ data, we examined ten years of Terra and eight years of Aqua data Collection 5 data for its potential usage in aerosol data assimilation. Uncertainties in the over-water MODIS AOD were studied as functions of observing conditions, such as surface characteristics, aerosol optical properties, and cloud artifacts. Empirical corrections and quality assurance procedures were developed and compared to Collection 4 data. After applying quality assurance and empirical correction procedures, the Root-Mean-Square-Error (RMSE) in the MODIS Terra and Aqua AOD are reduced by 30% and 10–20%, respectively. Ten years of Terra and eight years of Aqua quality-assured level 3 MODIS over-water aerosol products were produced. The newly developed MODIS over-water aerosol products will be used in operational aerosol data assimilation and aerosol climatology studies, and will also be useful to other researchers who are using the MODIS satellite products in their projects.

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 An analysis of the collection 5 MODIS over-ocean aerosol optical depth product for its implication in aerosol assimilation

2011 ◽  
Vol 11 (2) ◽  
pp. 557-565 ◽  
Author(s):  
Y. Shi ◽  
J. Zhang ◽  
J. S. Reid ◽  
B. Holben ◽  
E. J. Hyer ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Characteristics ◽  
Mean Square ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Level 3 ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Empirical Corrections

Abstract. As an update to our previous use of the collection 4 Moderate Resolution Imaging Spectroradiometer (MODIS) over-ocean aerosol optical depth (AOD) data, we examined ten years of Terra and eight years of Aqua collection 5 data for its potential usage in aerosol assimilation. Uncertainties in the over-ocean MODIS AOD were studied as functions of observing conditions, such as surface characteristics, aerosol optical properties, and cloud artifacts. Empirical corrections and quality assurance procedures were developed and compared to collection 4 data. After applying these procedures, the Root-Mean-Square-Error (RMSE) in the MODIS Terra and Aqua AOD are reduced by 30% and 10–20%, respectively, with respect to AERONET data. Ten years of Terra and eight years of Aqua quality-assured level 3 MODIS over-ocean aerosol products were produced. The newly developed MODIS over-ocean aerosol products will be used in operational aerosol assimilation and aerosol climatology studies, as well as other research based on MODIS products.

scholarly journals An over-land aerosol optical depth data set for data assimilation by filtering, correction, and aggregation of MODIS Collection 5 optical depth retrievals

2010 ◽  
Vol 3 (5) ◽  
pp. 4091-4167 ◽  
Author(s):  
E. J. Hyer ◽  
J. S. Reid ◽  
J. Zhang
Keyword(s):  
Data Assimilation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Prediction Models ◽  
Hot Spot ◽  
Weather Prediction ◽  
Surface Boundary ◽  
Data Set ◽  
Modis Aod ◽  
Level 3

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.

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.

scholarly journals Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements

2020 ◽  
Vol 12 (14) ◽  
pp. 2330
Author(s):  
Yan Tong ◽  
Lian Feng ◽  
Kun Sun ◽  
Jing Tang
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Radiative Forcing ◽  
Large Scale ◽  
Data Availability ◽  
Temporal Scales ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Assessments of long-term changes of air quality and global radiative forcing at a large scale heavily rely on satellite aerosol optical depth (AOD) datasets, particularly their temporal binning products. Although some attempts focusing on the validation of long-term satellite AOD have been conducted, there is still a lack of comprehensive quantification and understanding of the representativeness of satellite AOD at different temporal binning scales. Here, we evaluated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products at various temporal scales by comparing the MODIS AOD datasets from both the Terra and Aqua satellites with the entire global AErosol RObotic NETwork (AERONET) observation archive between 2000 and 2017. The uncertainty levels of the MODIS hourly and daily AOD products were similarly high, indicating that MODIS AOD retrievals could be used to represent daily aerosol conditions. The MODIS data showed the reduced quality when integrated from the daily to monthly scale, where the relative mean bias (RMB) changed from 1.09 to 1.21 for MODIS Terra and from 1.04 to 1.17 for MODIS Aqua, respectively. The limitation of valid data availability within a month appeared to be the primary reason for the increased uncertainties in the monthly binning products, and the monthly data associated uncertainties could be reduced when the number of valid AOD retrievals reached 15 times in one month. At all three temporal scales, the uncertainty levels of satellite AOD products decreased with increasing AOD values. The results of this study could provide crucial information for satellite AOD users to better understand the reliability of different temporal AOD binning products and associated uncertainties in their derived long-term trends.

scholarly journals MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water

2017 ◽  
Author(s):  
Yi WANG ◽  
Jun Wang ◽  
Robert C Levy ◽  
Xiaoguang Xu ◽  
Jeffrey S Reid
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Coastal Water ◽  
Visible Spectrum ◽  
Single Scattering ◽  
Retrieval Algorithm ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Large Water

We present a new approach to retrieve Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) over the turbid coastal water. This approach supplements the operational Dark Target (DT) aerosol retrieval algorithm that currently don’t conduct any AOD retrieval in the regions with large water-leaving radiances in the visible spectrum. Over the global coastal water regions in all cloud-free conditions, this unavailability of AOD retrievals due to the inherent limitation in existing DT algorithm is ~20%. Here, we refine the MODIS DT algorithm by considering that water-leaving radiance at 2.1 μm is negligible regardless of water turbidity. This refinement, with the assumption that the aerosol single scattering properties over coastal turbid water are similar to that over the adjacent open-ocean pixels, yields ~18% more of MODIS-AERONET collocated pairs for six AEROENT stations in the coastal water regions. Furthermore, comparison with these AERONET observations show that the new AOD retrievals are in either equivalent or better accuracy than those retrieved by the MODIS operational algorithm (over coastal land and non-turbid coastal water). Combining the new retrievals with the existing MODIS operational retrievals not only yield an overall improvement of AOD over those coastal water regions, but also successfully extend the spatial and temporal coverage of MODIS AOD retrievals over the coastal regions where 60% of human population resides, and thereby, aerosol impacts on regional air quality and climate are expected to be significant.

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 An over-land aerosol optical depth data set for data assimilation by filtering, correction, and aggregation of MODIS Collection 5 optical depth retrievals

2011 ◽  
Vol 4 (3) ◽  
pp. 379-408 ◽  
Author(s):  
E. J. Hyer ◽  
J. S. Reid ◽  
J. Zhang
Keyword(s):  
Data Assimilation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Prediction Models ◽  
Hot Spot ◽  
Weather Prediction ◽  
Surface Boundary ◽  
Data Set ◽  
Modis Aod ◽  
Level 3

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.

scholarly journals Relationship Between MODIS-based Aerosol Optical Depth and PM10 over Sumatra to Overcome the Limitations of Air Quality Monitoring Data Availability

2018 ◽  
Vol 34 (4) ◽  
pp. 2163-2169 ◽  
Author(s):  
Syafrijon Syafrijon ◽  
Marzuki Marzuki ◽  
Emriadi Emriadi ◽  
Ridho Pratama
Keyword(s):  
Air Quality ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Forest Fire ◽  
Correlation Coefficients ◽  
Data Availability ◽  
Near Surface ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

The present study uses the aerosol optical depth (AOD) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite as a proxy to estimate the surface particulate matter (PM) concentrations over Sumatra. The daily average PM10 data collected during 2015 from three air quality stations across Sumatra, i.e., Kototabang, Jambi and Pekanbaru, were analyzed. The 2015 Indonesian forest fire significantly increased the PM10 concentrations and MODIS AOD values. The ratios of the mean PM10 concentrations and AOD values during the peak forest fire period to those during the period of normal conditions varied from 6 to 9. MODIS AOD may be a good indicator of the near-surface PM10 concentrations over Sumatra, as the correlation coefficients of the linear regressions were 0.86 (Kototabang), 0.80 (Jambi), and 0.81 (Pekanbaru). The linear regression functions of PM10 and satellite-observed AOD can be used to estimate the surface PM10 concentrations, and the correlation coefficient is 0.84.

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

2013 ◽  
Vol 6 (4) ◽  
pp. 949-969 ◽  
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 ◽  
Noise Floor ◽  
Deep Blue ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Using Data

Abstract. Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) collection 5.1 (c5.1) aerosol optical depth (AOD) data were analyzed and evaluated for the first time from an independent research group using eight years of Terra (2000–2007) and Aqua (2002–2009). Uncertainties in the DB AOD were identified and studied, and our results show that the performance of DB c5.1 is strongly dependent on surface albedo and aerosol microphysics. Using data with only "very good" quality assurance, the root-mean-square error (RMSE) of the DB Terra (Aqua) AOD is 0.24 (0.19) when validated against AERONET. Expanding upon the uncertainty analysis, the potential of applying the DB products for aerosol assimilation was explored. Empirical corrections and quality assurance procedures were developed for North Africa and the Arabian Peninsula to create a data assimilation (DA)-quality DB product. After applying those procedures, the RMSE is reduced by 18.1% (18.2%) for Terra (Aqua) DB data. Prognostic error models of 0.069 + 0.175 × AODTerra_DB with no noise floor and 0.048 + 0.182 × AODAqua_DB with a noise floor of 0.104 were found for DA-quality Terra and Aqua DB data, respectively. 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.

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