Skip to main content

Advertisement

Log in

Dust Detection and Aerosol Properties Over Arabian Sea Using MODIS Data

  • Original Article
  • Published:
Earth Systems and Environment Aims and scope Submit manuscript

Abstract

The present study deals with the use of Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared bands in the dust detection. Eight dust storm cases over the Arabian Sea have been selected (four TERRA and four AQUA) during the year 2002–2008. The brightness temperature (BT) difference method has been applied on MODIS thermal bands 29 (8 µm), 31 (11 µm) and 32 (12 µm) to detect dust storms over the Arabian Sea. The performance assessment of BT differences (BT29–BT31 and BT31–BT32) has shown that BT31–BT32 has performed better to BT29–BT31. We suggest that BT31–BT32 is an effective combination of MODIS bands for dust detection over oceans and sea. The maximum (Dmax) and minimum dust (Dmin) intensity locations have also been identified in all the eight dust storm cases. The aerosol properties (aerosol optical thickness, τ; asymmetry factor g and Angstrom exponent α) over Dmax and Dmin have been studied using MODIS Level 2 data. In AQUA dust storms cases τ values (Dmax) were higher than TERRA dust cases, whereas g values were nearly same. The α was always positive in case of TERRA dust cases; however in AQUA negative α was also reported. Afternoon dust storms are more intense compared to forenoon dust storms and dust particles are also coarser.

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

  • Ackerman SA (1989) Using the radiative temperature difference at 3.7 and 11 μm to tract dust outbreaks. Remote Sens Environ 27(2):129–133

    Article  Google Scholar 

  • Ackerman SA (1997) Remote sensing aerosols using satellite infrared observations. J Geophys Res Atmos 102(D14):17069–17079

    Article  Google Scholar 

  • Al-Maamary HilalMS, Hussein AK, Miqdam TC (2017) Climate change: the game changer in the Gulf Cooperation Council region. Renew Sustain Energy Rev 76:555–576

    Article  Google Scholar 

  • Babu SS, Moorthy KK, Satheesh SK (2004) Aerosol black carbon over Arabian Sea during intermonsoon and summer monsoon seasons. Geophys Res Lett 31(6):1–5

    Article  Google Scholar 

  • Baddock MC, Bullard JE, Bryant RG (2009) Dust source identification using MODIS: a comparison of techniques applied to the Lake Eyre Basin, Australia. Remote Sens Environ 113(7):1511–1528

    Article  Google Scholar 

  • Barcelona Dust Forecast Center (2015) Activity Report 2015. https://dust.aemet.es/about-us/report-2015. Accessed 12 May 2017

  • Betzer PR, Carder KL, Duce RA, Merrill JT, Tindale NW, Uematsu M, Costello DK, Young RW, Feely RA, Breland JA, Bernstein RE (1988) Long–range transport of giant mineral aerosol particles. Nature 336:568–571

    Article  Google Scholar 

  • Butt MJ, Assiri ME, Ali MA (2017) Assessment of AOD variability over Saudi Arabia using MODIS Deep Blue products. Environ Pollut 231:143–153

    Article  Google Scholar 

  • Chen YS, Sheen PC, Chen ER, Liu YK, Wu TN, Yang CY (2004) Effects of Asian dust storm events on daily mortality in Taipei, Taiwan. Environ Res 95(2):151–155. https://doi.org/10.1016/j.envres.2003.08.008

    Article  Google Scholar 

  • Chou MD, Chan PK, Wang M (2002) Aerosol radiative forcing derived from SeaWiFS-retrieved aerosol optical properties. J Atmos Sci 59(3):748–757

    Article  Google Scholar 

  • Christopher SA, Jones TA (2010) Satellite and surface-based remote sensing of Saharan dust aerosols. Remote Sens Environ 114(5):1002–1007

    Article  Google Scholar 

  • Coale KH, Johnson KS, Fitzwater SE, Gordon RM, Tanner S, Chavez FP, Ferioli L, Sakamoto C, Rogers P, Millero F, Steinberg P (1996) A massive phytoplankton bloom induced by an ecosystem-scale iron fertilization experiment in the equatorial Pacific Ocean. Nature 383(6600):495–501

    Article  Google Scholar 

  • Duan SB, Li ZL, Cheng J, Leng P (2017) Cross-satellite comparison of operational land surface temperature products derived from MODIS and ASTER data over bare soil surfaces. ISPRS J Photogramm Remote Sens 126:1–10

    Article  Google Scholar 

  • Jafari R, Malekian M (2015) Comparison and evaluation of dust detection algorithms using MODIS Aqua/Terra Level 1B data and MODIS/OMI dust products in the Middle East. Int J Remote Sens 36(2):597–617. https://doi.org/10.1080/01431161.2014.999880

    Article  Google Scholar 

  • Janugani S, Jayaram V, Cabrera SD, Rosiles JG, Gill TE, Rivera NR (2009) Directional analysis and filtering for dust storm detection in NOAA-AVHRR imagery. In: Algorithms and Technologies for multispectral, hyperspectral, and ultraspectral imagery XV 2009 Apr 27 (vol 7334, p 73341G). International Society for Optics and Photonics

  • Kaiser J (2005) Mounting evidence indicts fine-particle pollution. Science 307:1858–1861. https://doi.org/10.1126/science.307.5717.1858a

    Google Scholar 

  • Karimi N, Moridnejad A, Golian S, Vali Samani JM, Karimi D, Javadi S (2012) Comparison of dust source identification techniques over land in the Middle East region using MODIS data. Can J Remote Sens 38(5):586–599. https://doi.org/10.5589/m12-048

    Article  Google Scholar 

  • Karimi S, Niksokhan MH, Karimi S (2016) Modeling snow cover area and predicting its changes in Haraz catchment. Imaging 2(4):450–455

    Google Scholar 

  • Kaskaoutis DG, Badarinath KV, Kumar Kharol S, Rani Sharma A, Kambezidis HD (2009) Variations in the aerosol optical properties and types over the tropical urban site of Hyderabad, India. J Geophys Res Atmos 114(D22):1–20

    Article  Google Scholar 

  • Kiran VR, Talukdar S, Ratnam MV, Jayaraman A (2018) Long-term observations of black carbon aerosol over a rural location in southern peninsular India: role of dynamics and meteorology. Atmos Environ. https://doi.org/10.1016/j.atmosenv.2018.06.020

    Google Scholar 

  • Kolla V, Biscaye PE (1977) Distribution and origin of quartz in the sediments of the Indian Ocean. J Sediment Res 47(2):642–649

    Google Scholar 

  • Krishnamurthy V, Kinter JL (2003) The Indian monsoon and its relation to global climate variability. global climate. Springer, Berlin, pp 186–236

    Chapter  Google Scholar 

  • Kurosaki Y, Shinoda M, Mikami M (2011) What caused a recent increase in dust outbreaks over East Asia? Geophys Res Lett. https://doi.org/10.1029/2011gl047494

    Google Scholar 

  • LADSWEB via https://ladsweb.modaps.eosdis.nasa.gov. Accessed 12 June 2016

  • Lee YC, Yang X, Wenig M (2010) Transport of dusts from East Asian and non-East Asian sources to Hong Kong during dust storm related events 1996–2007. Atmos Environ 44(30):3728–3738. https://doi.org/10.1016/j.atmosenv.2010.03.034

    Article  Google Scholar 

  • Lee SS, Lee EH, Sohn BJ, Lee HC, Cho JH, Ryoo SB (2017) Improved dust forecast by assimilating MODIS IR-based nighttime AOT in the ADAM2 model. SOLA 13:192–198

    Article  Google Scholar 

  • Legrand M, Plana-Fattori A, N’doumé C (2001) Satellite detection of dust using the IR imagery of Meteosat: 1. Infrared difference dust index. J Geophys Res Atmos 106(16):18251–18274

    Article  Google Scholar 

  • Levy RC, Remer LA, Tanré́ D, Mattoo S, Kaufman YJ (2009) Algorithm for remote sensing of tropospheric aerosol over dark targets from MODIS: collections 005 and 051: Revision 2; Feb 2009. MODIS algorithm theoretical basis document

  • Li X, Song W (2009) Dust storm detection based on Modis data. In: International conference on geo-spatial solutions for emergency management and the 50th anniversary of the Chinese Academy of surveying and mapping 169–172

  • MCTK via https://github.com/dawhite/MCTK. Accessed 12 Jan 2017

  • Martin JH, Coale KH, Johnson KS, Fitzwater SE, Gordon RM, Tanner SJ, Hunter CN, Elrod VA, Nowicki JL, Coley TL, Barber RT (1994) Testing the iron hypothesis in ecosystems of the equatorial Pacific Ocean. Nature 371(6493):123–129

    Article  Google Scholar 

  • Middleton NJ (1986) A geography of dust storms in South-west Asia. Int J Climatol 6(2):183–196

    Article  Google Scholar 

  • Moorthy KK, Babu SS, Satheesh SK (2005) Aerosol characteristics and radiative impacts over the Arabian Sea during the intermonsoon season: results from ARMEX field campaign. J Atmos Sci 62(1):192–206

    Article  Google Scholar 

  • Munir MM, Sasmito B, Haniah H (2015) Analisis Pola Kekeringan Lahan Pertanian Di Kabupaten Kendal Dengan Menggunakan Algoritma Thermal Vegetation Index Dari Citra Satelit Modis Terra. J Geodesi Undip 4(4):174–180

    Google Scholar 

  • Norton CC, Mosher FR, Hinton B, Martin DW, Santek D, Kuhlow W (1980) A model for calculating desert aerosol turbidity over the oceans from geostationary satellite data. J Appl Meteorol 19(6):633–644

    Article  Google Scholar 

  • Operational Dust Storm Forecasting at the Met Office. Available via http://forecast.uoa.gr/Dust-wshop-pdf/Brooks.pdf. Accessed 23 Oct 2017

  • Pease PP, Tchakerian VP, Tindale NW (1998) Aerosols over the Arabian Sea: geochemistry and source areas for aeolian desert dust. J Arid Environ 39(3):477–496

    Article  Google Scholar 

  • Reed L, Nugent K (2018) The health effects of dust storms in the Southwest United States. Southwest Respir Crit Care Chronicles 6(22):42–46

    Article  Google Scholar 

  • Sateesh M, Soni VK, Raju PVS (2018) Effect of diwali firecrackers on air quality and aerosol optical properties over mega city (Delhi) in India. Earth Syst Environ. https://doi.org/10.1007/s41748-018-0054-x

    Google Scholar 

  • Satheesh SK, Moorthy KK (1998) Aerosol characteristics over coastal regions of the Arabian Sea. Oceanogr Lit Rev 3(45):466

    Google Scholar 

  • Satheesh SK, Moorthy KK, Kaufman YJ, Takemura T (2006) Aerosol optical depth, physical properties and radiative forcing over the Arabian Sea. Meteorol Atmos Phys 91(1–4):45–62

    Article  Google Scholar 

  • Shao Y (2008) Physics and modelling of wind erosion, vol 37. Springer, Berlin

    Google Scholar 

  • Shenk WE, Curran RJ (1974) The detection of dust storms over land and water with satellite visible and infrared measurements. Mon Weather Rev 102(12):830–837

    Article  Google Scholar 

  • Shi GY, Zhao SX (2003) Several scientific issues of studies on the dust storms Chin. J Atmos Sci 27(4):591–606

    Google Scholar 

  • Singh J (2016) Ranking South African provinces on the basis of MERRA 2D surface incident shortwave flux. J Energy South Afr 27(3):50–57

    Article  Google Scholar 

  • Sirocko F (1991) Deep-sea sediments of the Arabian Sea: a paleoclimatic record of the southwest-Asian summer monsoon. Geol Rundsch 80(3):557–566

    Article  Google Scholar 

  • Solmon F, Nair VS, Mallet M (2015) Increasing Arabian dust activity and the Indian summer monsoon. Atmos Chem Phys 15(14):8051–8064

    Article  Google Scholar 

  • Stocker TF et al (2013) Contribution of Working Group I to the fifth assessment report of the intergovernmental panel on climate change climate change 2013: the physical science basis. Cambridge University Press, Cambridge

    Google Scholar 

  • Taghavia F, Mohammadi H (2008) The survey of linkage between climate changes and desertification using extreme climate index software. Desert 13(1):9–17

    Google Scholar 

  • Vincent RF (2018) The effect of Arctic dust on the retrieval of satellite derived sea and ice surface temperatures. Sci Rep 8(1):9727

    Article  Google Scholar 

  • Wang T, Yan CZ, Song X, Li S (2013) Landsat images reveal trends in the aeolian desertification in a source area for sand and dust storms in China’s Alashan plateau (1975–2007). Land Degrad Dev 24(5):422–429

    Google Scholar 

  • Washington R, Todd M, Middleton NJ, Goudie AS (2003) Dust-storm source areas determined by the total ozone monitoring spectrometer and surface observations. Ann Assoc Am Geogr 93(2):297–313

    Article  Google Scholar 

  • Xie Y, Zhang W, Qu JJ (2017) Detection of Asian dust storm using MODIS measurements. Remote Sens 9(8):869

    Article  Google Scholar 

  • Yu M, Yang C (2016) Improving the non-hydrostatic numerical dust model by integrating soil moisture and greenness vegetation fraction data with different spatiotemporal resolutions. PLoS ONE 11(12):e0165616

    Article  Google Scholar 

  • Yue H, He C, Zhao Y, Ma Q, Zhang Q (2017) The brightness temperature adjusted dust index: an improved approach to detect dust storms using MODIS imagery. Int J Appl Earth Obs Geoinf 57:166–176

    Article  Google Scholar 

  • Zhang P, Lu NM, Hu XQ, Dong CH (2006) Identification and physical retrieval of dust storm using three MODIS thermal IR channels. Glob Planet Change 52(1–4):197–206

    Article  Google Scholar 

  • Zhang B, Tsunekawa A, Tsubo M (2008) Contributions of sandy lands and stony deserts to long-distance dust emission in China and Mongolia during 2000–2006. Glob Planet Change 60(3–4):487–504

    Article  Google Scholar 

  • Zhu A, Ramanathan V, Li F, Kim D (2007) Dust plumes over the Pacific, Indian, and Atlantic oceans: climatology and radiative impact. J Geophys Res: Atmospheres 112(D16):1–20

    Article  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge the Indian Institute of Remote Sensing Dehradun for conducting this research work. We express our thanks to Department of Meteorology, Stockholm University for support during the project. We also want to acknowledge NASA for MODIS data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jyotsna Singh.

Ethics declarations

Conflict of interest

The authors state that there is no conflict of interest. The authors also declare that there is no financial or personal relationship with a third party whose interests could be positively or negatively influenced by this article’s content.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, J., Noh, YJ., Agrawal, S. et al. Dust Detection and Aerosol Properties Over Arabian Sea Using MODIS Data. Earth Syst Environ 3, 139–152 (2019). https://doi.org/10.1007/s41748-018-0079-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41748-018-0079-1

Keywords

Navigation