Skip to main content
Log in

Aerosol uncertainty assessment: an integrated approach of remote AQUA MODIS and AERONET data

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Al-Dousari AM, Al-Awadhi J, Ahmed M (2013) Dust fallout characteristics within global dust storms major trajectories. Arab J Geosci 6(10):3877–3884. https://doi.org/10.1007/s1257-012-0644-0

    Article  Google Scholar 

  • Chu DA, Kaufman YJ, Ichoku C, Remer LA, Tanr´e D, Holben BN (2002) Validation of MODIS aerosol optical depth retrieval overland. Geophys Res Lett 29. https://doi.org/10.1029/2001GL013205

  • Evan AT, Fiedler S, Zhao C, Menut L, Schepanski K, Flamant C, Doherty O (2015) Derivation of an observation-based map of North African dust emission. Aeolian Res 16:153–162

    Article  Google Scholar 

  • Fiedler S, Schepanski K, Knippertz P, Heinold B, Tegen I (2014) How important are atmospheric depressions and mobile cyclones for emitting mineral dust aerosol in North Africa. Atmos Chem Phys 14:8983–9000

    Article  Google Scholar 

  • Fraser RS (1976) Satellite measurement of mass of Sahara dust in the atmosphere. Appl Opt 15:2471–2479

    Article  Google Scholar 

  • Griggs M (1975) Measurements of atmospheric aerosol optical thickness over water using ERTS-1 data. J Air Pollut Control Assoc 25:622–626

    Article  Google Scholar 

  • Ichoku C, Allen CD, Mattoo S, Kaufman YJ, Remer LA, Tanré D, Slutsker I, Holben BN, (2002) A spatio temporal approach for global validation and analysis of MODIS aerosol products, Geophys Res Lett 29:1616

  • Kaufman YJ, Tanr’e D, Remer LA, Vermote EF, Chu A, Holben BN (1997) Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer. J Geophys Res 102(D14):17051–17067

    Article  Google Scholar 

  • Kinne S (2003) Monthly averages of aerosol properties: a global comparison among models, satellite data, and AERONET ground data. J Geophys Res 108(4634, D20). https://doi.org/10.1029/2001JD001253

  • Levy RC, Remer LA, Mattoo S, Vermote EF, Kaufman YJ (2007a) A second-generation algorithm for retrieving aerosol properties over land from MODIS spectral reflectance. J Geophys Res 112(D13211)

  • Levy RC, Remer LA, Dubovik O (2007b) Global aerosol optical properties and application to moderate resolution imaging spectroradiometer aerosol retrieval over land. J Geophys Res 112(D13210). https://doi.org/10.1029/2006JD007815

  • Levy RC, Leptoukh GG, Kahn R, Zubko V, Gopalan A, Remer LA (2009) A critical look at deriving monthly aerosol optical depth from satellite data. IEEE Trans Geosci Remote Sens 47:2942–2956

    Article  Google Scholar 

  • Li Z, Niu F, Lee KH, Xin J, Hao WM, Nordgren B, Wang Y, Wang P (2007) Validation and understanding of MODIS aerosol products using ground-based measurements from the handheld sunphotometer network in China. J Geophy Res 112(D22S07). https://doi.org/10.1029/2007JD00847

  • Mekler Y, Quenzel H, Ohring G, Marcus I (1977) Relative atmospheric aerosol content from ERTS observations. J Geophys Res 82:967–972

    Article  Google Scholar 

  • Mi W, Li Z, Xia X, Holben B, Levy R, Zhao F, Chen H, and Cribb M (2007) Evaluation of the moderate resolution imaging spectroradiometer aerosol products at two Aerosol Robotic Network stations in China. J Geophys Res 112(D22S08), doi:https://doi.org/10.1029/2007JD008474.

  • Pantillon F, Knippertz P, Marsham JH, Panitz HJ, Bischoff-Gauss I (2016) Modeling haboob dust storms in large-scale weather and climate models. J Geophys Res Atmos 121:2090–2109

    Article  Google Scholar 

  • Remer LA, Kaufman YJ, Tanr’e D, Mattoo S, Chu DA, Martins JV, Li RR, Ichoku C, Levy RC, Kleidman RG, Eck TF, Vermote E, Holben BN (2005) The MODIS aerosol algorithm, products and validation. J Atmos Sci 62:947–973

    Article  Google Scholar 

  • Remer LA, Tanre D, Kaufman YJ, Levy R, Mattoo S (2006) Algorithm for remote sensing of Tropospheric aerosol from MODIS: Collection 005, Product ID MOD04/MYD04 Ref. No. ATBD-MOD-96. Available at http://modis-atmos.gsfc.nasa.gov/_docs/MOD04:-MYD04_ATBD_C005_revl.pdf

  • Salomonsen V, Barnes W, Maymon P, Montgomery H, Ostrow H (1989) MODIS – advanced facility instrument for studies of the earth as a system. IEEE T Geosci Remote 27:145–153, 1989

    Article  Google Scholar 

  • Schepanski K, Tegen I, Macke A (2012) Comparison of satellite based observations of Saharan dust source areas. Remote Sens Environ 123:90–97

    Article  Google Scholar 

  • Shepherd G, Terradellas E, Baklanov A, Kang U, Sprigg WA, Nickovic S, Boloorani AD, Al-Dousari AM, Basart S, Benedetti A, Sealy A, Tong D, Zhang X, Sh J. Guillemot, Kebin Z, Knippertz P, Mohammed AAA ,Al-Dabbas M, Cheng L, Otani Sh, Wang F, Zhang Ch, Ryoo SB, Cha J. Global assessment of sand and dust storms. (2016). United Nations Environment Programme UNEP, Nairobi.

  • Smirnov A, Holben BN, Eck TF, Dubovik O, Slutsker I (2000) Cloud-screening andquality control algorithms for the AERONET database. Remote Sens Environ 73:337_349–337_349. https://doi.org/10.1016/S0034-4257(00)00109-7

    Article  Google Scholar 

  • Tanr’e D, Kaufman YJ, Herman M, Mattoo S (1997) Remote sensing of aerosol properties over oceans using the MODIS/EOS spectral radiances. J Geophys Res 102(D14):16971–16988

    Article  Google Scholar 

  • Tanr’e D, Remer LA, Kaufman YJ, Mattoo S, Hobbs PV, Livingston JM, Russell PB, Smirnov A (1999) Retrieval of aerosol optical thickness and size distribution over ocean from the MODIS airborne simulator during TARFOX. J Geophys Res 104(D2):2261–2278

    Article  Google Scholar 

Download references

Acknowledgments

We would like to express our special appreciation and thanks to the Deutsche Akademische Austausch dienst (DAAD) for their support. Many thanks are expressed to NASA Goddard Space Flight Center (GSFC) and Atmosphere Archive and Distribution System (LAADS) (http://ladsweb.nascom.nasa.gov) for making available the L2 MODIS AQUA C6 aerosol data. The authors are grateful to the AERONET scientific team for making data level 2 available.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Moncef Bouaziz.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bouaziz, M., Guermazi, H., Khcharem, K. et al. Aerosol uncertainty assessment: an integrated approach of remote AQUA MODIS and AERONET data. Arab J Geosci 12, 50 (2019). https://doi.org/10.1007/s12517-018-4214-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-018-4214-y

Keywords

Navigation