High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS
Abstract
:1. Introduction
2. Data and Methods
2.1. MODIS Aerosol Data
- Latitude,
- Longitude,
- Land_Sea_Flag,
- Deep_Blue_Aerosol_Optical_Depth_550_Land_Best_Estimate
- Optical_Depth_Land_And_Ocean,
2.2. AERONET
2.3. Data Fusion and High-Resolution Gridding
- Ocean grids use DT AOD with quality flags 1, 2, and 3.
- Land grids use DB AOD with quality flag 2 & 3. The remaining land grids were filled with DT AODs with quality flag 3.
- Coastal grids were filled with AODs from DT with QA = 3 and (or) DB with QA = 2, and 3. If both appropriate DT and DB retrievals are available, those retrievals are averaged.
- Grids with no available valid AODs were filled with a missing value of −1.000.
2.4. Spatial and Temporal Coverage
3. Results
3.1. Validation with AERONET
3.1.1. Spatial and Temporal Collocation and Statistical Analysis
- AODAERO: Aerosol Optical Depth at 0.55 µm from AERONET
- AODMODIS: Aerosol Optical Depth at 0.55 µm from MODIS
3.1.2. Global Validation
3.1.3. Regional Validation
3.1.4. Error Dependencies
3.2. Applications Examples
3.2.1. Spatial Gradient at Local and Regional Scales
3.2.2. Long Range Dust Transport over the Atlantic Ocean
3.2.3. Long-Term Aerosol Trends
4. Data Access and Visualization
5. Discussion and Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Hsu, N.C.; Tsay, S.; King, M.D.; Member, S.; Herman, J.R. Aerosol Properties over Bright-Reflecting Source Regions. IEEE Trans. Geosci. Remote Sens. 2004, 42, 557–569. [Google Scholar] [CrossRef]
- Hsu, N.C.; Jeong, M.J.; Bettenhausen, C.; Sayer, A.M.; Hansell, R.; Seftor, C.S.; Huang, J.; Tsay, S.C. Enhanced Deep Blue aerosol retrieval algorithm: The second generation. J. Geophys. Res. Atmos. 2013, 118, 9296–9315. [Google Scholar] [CrossRef]
- Sayer, A.M.; Hsu, N.C.; Bettenhausen, C.; Jeong, M.J. Validation and uncertainty estimates for MODIS Collection 6 deep Blue aerosol data. J. Geophys. Res. Atmos. 2013, 118, 7864–7872. [Google Scholar] [CrossRef] [Green Version]
- Remer, L.A.; Kaufman, Y.J.; Tanr, D.; Mattoo, S.; Chu, D.A.; Martins, J.V.; Li, R.-R.; Ichoku, C.; Levy, R.C.; Kleidman, R.G.; et al. The MODIS aerosol algorithm, products and validation. J. Atmos. Sci. 2005, 62, 947–973. [Google Scholar] [CrossRef] [Green Version]
- Levy, R.C.; Remer, L.A.; Mattoo, S.; Vermote, E.F.; Kaufman, Y.J. Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. J. Geophys. Res. Atmos. 2007, 112, 1–21. [Google Scholar] [CrossRef] [Green Version]
- Levy, R.C.; Mattoo, S.; Munchak, L.A.; Remer, L.A.; Sayer, A.M.; Patadia, F.; Hsu, N.C. The Collection 6 MODIS aerosol products over land and ocean. Atmos. Meas. Tech. 2013, 6, 2989–3034. [Google Scholar] [CrossRef] [Green Version]
- Gupta, P.; Levy, R.C.; Mattoo, S.; Remer, L.A.; Munchak, L.A. A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm. Atmos. Meas. Tech. 2016, 9, 3293–3308. [Google Scholar] [CrossRef] [Green Version]
- Sayer, A.M.; Munchak, L.A.; Hsu, N.C.; Levy, R.C.; Bettenhausen, C.; Jeong, M. MODIS Collection 6 aerosol products: Comparison between Aqua’s e-Deep Blue, Dark Target, and merged data sets, and usage recommendations. J. Geophys. Res. Atmos. 2014, 119, 13965–13989. [Google Scholar] [CrossRef]
- Christopher, S.A.; Zhang, J. Shortwave aerosol radiative forcing from MODIS and CERES observations over the oceans. Geophys. Res. Lett. 2002, 29, 6-1–6-4. [Google Scholar] [CrossRef] [Green Version]
- Yu, H.; Dickinson, R.E.; Chin, M.; Kaufman, Y.J.; Zhou, M.; Zhou, L.; Tian, Y.; Dubovik, O.; Holben, B.N. Direct radiative effect of aerosols as determined from a combination of MODIS retrievals and GOCART simulations. J. Geophys. Res. 2004, 109, D03206. [Google Scholar] [CrossRef] [Green Version]
- Yu, H.; Kaufman, Y.J.; Chin, M.; Feingold, G.; Remer, L.A.; Anderson, T.L.; Balkanski, Y.; Bellouin, N.; Boucher, O.; Christopher, S.; et al. A review of measurement-based assessment of the aerosol direct radiative effect and forcing. Atmos. Chem. Phys. 2006, 6, 613–666. [Google Scholar] [CrossRef] [Green Version]
- Zhang, J.; Christopher, S.A.; Remer, L.A.; Kaufman, Y.J. Shortwave aerosol radiative forcing over cloud-free oceans from Terra: 2. Seasonal and global distributions. J. Geophys. Res. 2005, 110, D10S24. [Google Scholar] [CrossRef] [Green Version]
- Kaufman, Y.; Tanr, D.; Boucher, O. A satellite view of aerosols in the climate system. Nature 2002, 419, 215–223. [Google Scholar] [CrossRef] [PubMed]
- Bellouin, N.; Boucher, O.; Haywood, J.; Reddy, M.S. Global estimate of aerosol direct radiative forcing from satellite measurements. Nature 2005, 438, 1138–1141. [Google Scholar] [CrossRef]
- Kinne, S.; Lohmann, U.; Feichter, J.; Schulz, M.; Timmreck, C.; Ghan, S.; Easter, R.; Chin, M.; Ginouz, P.; Takemura, T.; et al. Monthly averages of aerosol properties: A global comparison among models, satellite data, and AERONET ground data. J. Geophys. Res. 2003, 108, 4634. [Google Scholar] [CrossRef]
- Koren, I.; Kaufman, Y.J.; Remer, L.A.; Martins, J.V. Measurement of the effect of Amazon smoke on the inhibition of cloud formation. Science 2004, 303, 1342–1345. [Google Scholar] [CrossRef] [Green Version]
- Koren, I.; Remer, L.A.; Altaratz, O.; Martins, J.V.; Davidi, A. Aerosol-induced changes of convective cloud anvils produce strong climate warming. Atmos. Chem. Physics 2010, 10, 5001–5010. [Google Scholar] [CrossRef] [Green Version]
- Kaufman, Y.J.; Remer, L.A.; Tanr, D.; Li, R.-R.; Kleidman, R.; Mattoo, S.; Levy, R.C.; Eck, T.F.; Holben, B.N.; Ichoku, C.; et al. A critical examination of the residual cloud contamination and diurnal sampling effects on MODIS estimates of aerosol over ocean. IEEE Trans. Geosci. Rem. Sens. 2005, 43, 2886–2897. [Google Scholar] [CrossRef]
- Myhre, G.; Stordal, F.; Johnsrud, M.; Kaufman, Y.J.; Rosenfeld, D.; Storelvmo, T.; Kristjansson, J.E.; Berntsen, T.K.; Myhre, A.; Isaksen, I.S.A. Aerosol-cloud interaction inferred from MODIS satellite data and global aerosol models. Atmos. Chem. Phys. 2007, 7, 3081–3101. [Google Scholar] [CrossRef] [Green Version]
- Kaufman, Y.J.; Koren, I.; Remer, L.A.; Tanr, D.; Ginoux, P.; Fan, S. Dust transport and deposition observed from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) spacecraft over the Atlantic Ocean. J. Geophys. Res. 2005, 110, D10S12. [Google Scholar] [CrossRef] [Green Version]
- Stohl, A.; Berg, T.; Burkhart, J.F.; Fjǽraa, A.M.; Forster, C.; Herber, A.; Hov, Ø.; Lunder, C.; McMillan, W.W.; Oltmans, S.; et al. Arctic smoke record air pollution levels in the European Arctic during a period of abnormal warmth, due to agricultural fires in eastern Europe. Atmos. Chem. Phys. 2007, 7, 511–534. [Google Scholar] [CrossRef] [Green Version]
- Yu, H.; Remer, L.A.; Chin, M.; Bian, H.-S.; Tan, Q.; Yuan, T.; Zhang, Y. Aerosols from Overseas Rival Domestic Emissions over North America. Science 2012, 337, 566–569. [Google Scholar] [CrossRef] [PubMed]
- Yu, H.; Tan, Q.; Chin, M.; Remer, L.A.; Kahn, R.A.; Bian, H.; Kim, D.; Zhang, Z.; Yuan, T.; Omar, A.; et al. Estimates of African Dust Deposition Along the Trans-Atlantic Transit Using the Decadelong Record of Aerosol Measurements from CALIOP, MODIS, MISR, and IASI. J. Geophys. Res. Atmos. 2019, 124, 7975–7996. [Google Scholar] [CrossRef] [PubMed]
- Wang, J.; Christopher, S.A. Intercomparison between satellite-derived aerosol optical thickness and PM2. 5 mass: Implications for air quality studies. Geophys. Res. Lett. 2003, 30, 2095. [Google Scholar] [CrossRef]
- Gupta, P.; Christopher, S.A. Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: Multiple regression approach. J. Geophys. Res. 2009, 114, D14205. [Google Scholar] [CrossRef] [Green Version]
- Van Donkelaar, A.; Martin, R.V.; Brauer, M.; Kahn, R.; Levy, R.; Verduzco, C.; Villeneuve, P.J. Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: Development and application. Environ. Health Persp. 2010, 118, 847–855. [Google Scholar] [CrossRef] [Green Version]
- Van Donkelaar, A.; Martin, R.V.; Brauer, M.; Hsu, N.C.; Kahn, R.A.; Levy, R.C.; Lyapustin, A.; Sayer, A.M.; Winker, D.M. Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors. Environ. Sci. Technol. 2016, 50, 3762–3772. [Google Scholar] [CrossRef]
- Duncan, B.N.; Prados, A.I.; Lamsal, L.N.; Liu, Y.; Streets, D.G.; Gupta, P.; Hilsenrath, E.; Kahn, R.A.; Nielsen, J.E.; Beyersdorf, A.J.; et al. Satellite data of atmospheric pollution for US air quality applications: Examples of applications, summary of data end-user resources, answers to FAQs, and common mistakes to avoid. Atmos. Environ. 2014, 94, 647–662. [Google Scholar] [CrossRef] [Green Version]
- Sogacheva, L.; Popp, T.; Sayer, A.M.; Dubovik, O.; Garay, M.J.; Heckel, A.; Hsu, N.C.; Jethva, H.; Kahn, R.A.; Kolmonen, P.; et al. Merging regional and global aerosol optical depth records from major available satellite products. Atmos. Chem. Phys. 2020, 20, 2031–2056. [Google Scholar] [CrossRef] [Green Version]
- Remer, L.A.; Mattoo, S.; Levy, R.C.; Munchak, L.A. MODIS 3 km aerosol product: Algorithm and global perspective. Atmos. Meas. Tech. 2013, 6, 1829–1844. [Google Scholar] [CrossRef] [Green Version]
- Levy, R.C.; Remer, L.A.; Kleidman, R.G.; Mattoo, S.; Ichoku, C.; Kahn, R.; Eck, T.F. Global evaluation of the Collection 5 MODIS dark-target aerosol products over land. Atmos. Chem. Phys. 2010, 10, 10399–10420. [Google Scholar] [CrossRef] [Green Version]
- Sayer, A.M.; Hsu, N.C.; Lee, J.; Kim, W.V.; Dutcher, S.T. Dutcher Validation, stability, and consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue aerosol data over land. J. Geophys. Res. Atmos. 2019, 124, 4658–4688. [Google Scholar] [CrossRef]
- Gupta, P.; Remer, L.A.; Levy, R.C.; Mattoo, S. Validation 1529 of MODIS 3 km land aerosol optical depth from NASA’s EOS Terra and Aqua missions. Atmos. Meas. Tech. 2018, 11, 3145–3159. [Google Scholar] [CrossRef] [Green Version]
- Wei, J.; Li, Z.; Peng, Y.; Sun, L. MODIS Collection 6.1 aerosol optical depth products over land and ocean: Validation and comparison. Atmos. Environ. 2019, 201, 428–440. [Google Scholar] [CrossRef]
- Sayer, A.M.; Hsu, N.C.; Bettenhausen, C.; Jeong, M.-J.; Meister, G. Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: Validation and Terra/Aqua consistency. J. Geophys. Res. Atmos. 2015, 120, 12157–12174. [Google Scholar] [CrossRef] [Green Version]
- Holben, B.N.; Eck, T.F.; Slutsker, I.; Tanre, D.; Buis, J.P.; Setzer, A.; Vermote, E.; Reagan, J.A.; Kaufman, Y.; Nakajima, T.; et al. AERONET—A federated instrument network and data archive for aerosol characterization. Remote Sens. Environ. 1998, 66, 1–16. [Google Scholar] [CrossRef]
- Eck, T.F.; Holben, B.N.; Reid, J.S.; Dubovik, O.; Smirnov, A.; O’Neill, N.T.; Slutsker, I.; Kinne, S. Wavelength dependence of the optical depth of biomass burning, urban and desert dust aerosols. J. Geophys. Res. 1999, 104, 31333–31350. [Google Scholar] [CrossRef]
- Ichoku, C.; Chu, D.A.; Mattoo, S.; Kaufman, Y.J.; Remer, L.A.; Tanr, D.; Slutsker, I.; Holben, B.N. A spatio-temporal approach for global validation and analysis of MODIS aerosol products. Geophys. Res. Lett. 2002, 29. [Google Scholar] [CrossRef] [Green Version]
- Levy, R.C.; Mattoo, S.; Sawyer, V.; Shi, Y.; Colarco, P.R.; Lyapustin, A.I.; Wang, Y.; Remer, L.A. Exploring systematic offsets between aerosol products from the two MODIS sensors. Atmos. Meas. Tech. 2018, 11, 4073–4092. [Google Scholar] [CrossRef] [Green Version]
- Gupta, P.; Christopher, S.A.; Box, M.A.; Box, G.P. Multi year satellite remote sensing of particulate matter air quality over Sydney, Australia. Int. J. Remote Sens. 2007, 28, 4483–4498. [Google Scholar] [CrossRef]
- Huff, A.K.; Kondragunta, S. Meteorologists track wildfires using satellite smoke images. Eos 2017, 98, 18–23. [Google Scholar] [CrossRef]
- Cusworth, D.H.; Mickley, L.J.; Sulprizio, M.P.; Liu, T.; Marlier, M.E.; DeFries, R.S.; Guttikunda, S.K.; Gupta, P. Quantifying the influence of agricultural fires in northwest India on urban air pollution in Delhi, India. Environ. Res. Lett. 2018, 13, 044018. [Google Scholar] [CrossRef] [Green Version]
- Wang, J.; Christopher, S.A. Christopher Mesoscale modeling of Central American smoke transport to the United States: 2. Smoke radiative impact on regional surface energy budget and boundary layer evolution. J. Geophys. Res. 2006, 111, D14S92. [Google Scholar] [CrossRef] [Green Version]
- Naeger, A.R.; Gupta, P.; Zavodsky, B.T.; McGrath, K.M. Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites. Atmos. Meas. Tech. 2016, 9, 2463–2482. [Google Scholar] [CrossRef] [Green Version]
- Flower, V.J.B.; Kahn, R.A. Interpreting the Volcanological Processes of Kamchatka, Based on Multi-Sensor Satellite Observations. Remote Sens. Environ. 2020, 237, 111585. [Google Scholar] [CrossRef]
- Streets, D.G.; Yan, F.; Chin, M.; Diehl, T.; Mahowald, N.; Schultz, M.; Wild, M.; Wu, Y.; Yu, C. Anthropogenic and natural contributions to regional trends in aerosol optical depth, 1980–2006. J. Geophys. Res. 2009, 114, D00D18. [Google Scholar] [CrossRef]
- Chin, M.; Diehl, T.; Tan, Q.; Prospero, J.M.; Kahn, R.A.; Remer, L.A.; Yu, H.; Sayer, A.M.; Bian, H.; Geogdzhayev, I.V.; et al. Multi-decadal aerosol variations from 1980 to 2009, A perspective from observations and a global model. Atmos. Chem. Phys. 2014, 14, 3657–3690. [Google Scholar] [CrossRef] [Green Version]
- Hsu, N.C.; Gautam, R.; Sayer, A.M.; Bettenhausen, C.; Li, C.; Jeong, M.J.; Tsay, S.C.; Holben, B.N. Global and regional trends of aerosol optical depth over land and ocean using SeaWiFS measurements from 1997 to 2010. Atmos. Chem. Phys. 2012, 12, 8037–8053. [Google Scholar] [CrossRef] [Green Version]
- Christopher, S.A.; Gupta, P. Global Distribution of Column Satellite Aerosol Optical Depth to Surface PM2.5 Relationships. Remote Sens. 2020, 12, 1985. [Google Scholar] [CrossRef]
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Gupta, P.; Remer, L.A.; Patadia, F.; Levy, R.C.; Christopher, S.A. High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS. Remote Sens. 2020, 12, 2847. https://doi.org/10.3390/rs12172847
Gupta P, Remer LA, Patadia F, Levy RC, Christopher SA. High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS. Remote Sensing. 2020; 12(17):2847. https://doi.org/10.3390/rs12172847
Chicago/Turabian StyleGupta, Pawan, Lorraine A. Remer, Falguni Patadia, Robert C. Levy, and Sundar A. Christopher. 2020. "High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS" Remote Sensing 12, no. 17: 2847. https://doi.org/10.3390/rs12172847