Skip to main content
SpringerLink
Log in

Identifying sky conditions in Iran from MODIS Terra and Aqua cloud products

  • Published:
Chinese Geographical Science Aims and scope Submit manuscript

Abstract

Clouds can influence climate through many complex interactions within the hydrological cycle. Due to the important effects of cloud cover on climate, it is essential to study its variability over certain geographical areas. This study provides a spatial and temporal distribution of sky conditions, cloudy, partly cloudy, and clear days, in Iran. Cloud fraction parameters were calculated based on the cloud product (collection 6_L2) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on board the Terra (MOD06) and Aqua (MYD06) satellites. The cloud products were collected daily from January 1, 2003 to December 31, 2014 (12 years) with a spatial resolution of 5 km × 5 km. First, the cloud fraction data were converted into a regular geographic coordinate network over Iran. Then, the estimations from both sensors were analyzed. Results revealed that the maximum annual frequency of cloudy days occurs along the southern shores of the Caspian Sea, while the minimum annual frequency occurs in southeast Iran. On average, the annual number of cloudy and clear-sky days was 88 and 256 d from MODIS Terra, as compared to 96 and 244 d from MODIS Aqua. Generally, cloudy and partly cloudy days decrease from north to south, and MODIS Aqua overestimates the cloudy and partly cloudy days compared to MODIS Terra.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Alijani B, 1995. Climate of Iran. Tehran: Payame Noor Publications, 236.

    Google Scholar 

  • Amiri M J, Eslamian S S, 2010. Investigation of climate change in Iran. Journal of Environmental Science and Technology, 3(4): 208–216. doi: 10.3923/jest.2010.208.216

    Article  Google Scholar 

  • Bannayan A M, Mohamadian A, Alizadeh A, 2011. On climate variability in north east of Iran. J ournal of Water and Soil, 24(1): 118–131

    Google Scholar 

  • Bostan D C, Manea E F, Stefan S, 2015. Total and partial cloudiness distribution in eastern Romania. Romanian Reports in Physics, 67(3): 1117–1127

    Google Scholar 

  • Butt N, New M, Lizcano G et al., 2009. Spatial patterns and recent trends in cloud fraction and cloud-related diffuse radiation in Amazonia. Journal of Geophysical Research: Atmospheres, 114(D21): D21104. doi: 10.1029/2009JD012217

    Article  Google Scholar 

  • Calbo J, Sabburg J, 2008. Feature extraction from whole-sky ground-based images for cloud-type recognition. Journal of Atmospheric and Oceanic Technology, 25(1): 3–14. doi: 10.1175/2007JTECHA959.1

    Article  Google Scholar 

  • Chen L, Yan G J, Wang T X et al., 2012. Estimation of surface shortwave radiation components under all sky conditions: modeling and sensitivity analysis. Remote Sensing of Environment, 123: 457–469. doi: 10.1016/j.rse.2012.04.006

    Article  Google Scholar 

  • Chen T M, Guo J P, Li Z Q et al., 2016. A CloudSat perspective on the cloud climatology and its association with aerosol perturbations in the vertical over Eastern China. Journal of the Atmospheric Sciences, 73(9): 3599–3616. doi: 10.1175/JASD-15-0309.1.

    Article  Google Scholar 

  • Congren C, 2013. Spatial and Temporal Variation of Cloud Free Days in Sweden. Gothenburg: University of Gothenburg, 1–26

    Google Scholar 

  • Dai A G, Trenberth K E, Karl T R, 1999. Effects of clouds, soil moisture, precipitation, and water vapor on diurnal temperature range. Journal of Climate, 12(8): 2451–2473. doi: 10.1175/1520-0442(1999)012<2451:EOCSMP>2.0.CO;2

    Article  Google Scholar 

  • Davy R, Esau I, 2016. Differences in the efficacy of climate forcings explained by variations in atmospheric boundary layer depth. Nature Communications, 7: 11690. doi: 10.1038/ncomms11690

    Article  Google Scholar 

  • Eastman R, Warren G S, 2010. Interannual variations of arctic cloud types in relation to sea ice. Journal of Climate, 23(15): 4216–4223. doi: 10.1175/2010JCLI3492.1

    Article  Google Scholar 

  • Filipiak J, Miętus M, 2009. Spatial and temporal variability of cloudiness in Poland, 1971–2000. International Journal of Climatology, 29(9): 1294–1311. doi: 10.1002/joc.1777

    Article  Google Scholar 

  • Garcia P, Benarroch A, Riera J M, 2008. Spatial distribution of cloud cover. International Journal of Satellite Communications and Networking, 26(2): 141–155. doi: 10.1002/sat.899

    Article  Google Scholar 

  • Griggs J, Bamber J, 2008. Assessment of cloud cover characteristics in satellite datasets and reanalysis products for Greenland. Journal of Climate, 21(9): 1837–1849. doi: 10.1175/2007JCLI1570.1

    Article  Google Scholar 

  • Guo J P, Zhang X Y, Wu Y R et al., 2011. Spatio-temporal variation trends of satellite-based aerosol optical depth in China during 1980–2008. Atmospheric Environment, 45(37): 6802–6811. doi: 10.1016/j.atmosenv.2011.03.068

    Article  Google Scholar 

  • Guo J P, Deng M J, Lee S S et al., 2016a. Delaying precipitation and lightning by air pollution over the Pearl River Delta. Part I: Observational analyses. Journal of Geophysical Research: Atmospheres, 121(11): 6472–6488. doi: 10.1002/2015JD023257

    Google Scholar 

  • Guo J P, Miao Y C, Zhang Y et al., 2016b. The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data. Atmospheric Chemistry and Physics, 16(20): 13309–13319. doi: 10.5194/acp-16-13309-2016

    Article  Google Scholar 

  • Hubanks P, Platnick S, King M et al., 2015. MODIS atmosphere L3 gridded product algorithm theoretical basis document (ATBD) & users guide. ATBD reference number ATBDMOD-30, NASA. Available at: https://modis-atmos.gsfc.nasa.gov/_ docs/L3_ATBD_C6_2015_05_06.pdf. Cited 6 May 2015

    Google Scholar 

  • Javanmard S, Yatagai A, Nodzu M I et al., 2010. Comparing high-resolution gridded precipitation data with satellite rainfall estimates of TRMM_3B42 over Iran. Advances in Geosciences, 25: 119–125. doi: 10.5194/adgeo-25-119-2010

    Article  Google Scholar 

  • King N J, Bower K N, Crosier J et al, 2013. Evaluating MODIS cloud retrievals with in situ observations from VOCALS-Rex. Atmospheric Chemistry and Physics, 13(1): 191–209. doi: 10.5194/acp-13-191-2013

    Article  Google Scholar 

  • Kong H J, Kim J T, 2013. A Classification of real sky conditions for Yongin, Korea. In: Hakansson A et al. (eds). Sustainability in Energy and Buildings. Smart Innovation, Systems and Technologies, vol 22. Berlin, Heidelberg: Springer.

    Google Scholar 

  • Koren I, Dagan G, Altaratz O, 2014. From aerosol-limited to invigoration of warm convective clouds. Science, 344(6188): 1143–1146. doi: 10.1126/science.1252595

    Article  Google Scholar 

  • Kotarba A Z, 2009. A comparison of MODIS-derived cloud amount with visual surface observations. Atmospheric Research, 92(4): 522–530. doi: 10.1016/j.atmosres.2009.02.001

    Article  Google Scholar 

  • Kumar S V V A, Babu K N, Shukla A K, 2015. Comparative analysis of chlorophyll-a distribution from SEAWIFS, MODIS-AQUA, MODIS-TERRA and MERIS in the Arabian Sea. Marine Geodesy, 38(1): 40–57. doi: 10.1080/01490419.2014.914990.

    Article  Google Scholar 

  • Li Z, Cribb M C, Chang F L et al., 2004. Validation of MODISretrieved cloud fractions using whole sky imager measurements at the three ARM sites. Proceedings of the 14th ARM Science Team Meeting. Albuquerque, New Mexico: ARM.

    Google Scholar 

  • Li Z Q, Lau W K M, Ramanathan V et al., 2016. Aerosol and monsoon climate interactions over Asia. Reviews of Geophysics, 54(4): 866–929. doi: 10.1002/2015RG000500

    Article  Google Scholar 

  • Menzel W P, Frey R A, Baum B A, 2013. Cloud Top Properties and Cloud Phase Algorithm Theoretical Basis Document, Collection 006 Update. Space Science and Engineering Center, 1–70

    Google Scholar 

  • Menzel W P, Frey R A, Zhang H et al., 2008. MODIS global cloud-top pressure and amount estimation: algorithm description and results. Journal of Applied Meteorology and Climatology, 47(4): 1175–1198. doi: 10.1175/2007JAMC1705.1

    Article  Google Scholar 

  • Nakamura H, Oki M, Hayashi Y, 1985. A study on the estimation of the relative frequency of occurrences of the Clear Sky, the Intermediate Sky and the Overcast Sky in Japan. Journal of Light & Visual Environment, 9(2): 22–31. doi: 10.2150/jlve.9.2_22

    Article  Google Scholar 

  • Pincus R, Platnick S, Ackerman S A et al., 2012. Reconciling simulated and observed views of clouds: MODIS, ISCCP, and the limits of instrument simulators. Journal of Climate, 25(13): 4699–4720. doi: 10.1175/JCLI-D-11-00267.1

    Article  Google Scholar 

  • Ramanathan V, Crutzen P J, Kiehl J T et al., 2001. Aerosols, climate, and the hydrological cycle. Science, 294(5549): 2119–2124. doi: 10.1126/science.1064034

    Article  Google Scholar 

  • Schiffer R A, Rossow W B, 1983. The international satellite cloud climatology project (ISCCP): the first project of the World Climate Research Programme. Bulletin of the American Mete orological Society, 64(7): 779–784. doi: 10.1175/1520-0477(1991)072<0002:ICDP>2.0.CO;2

    Google Scholar 

  • Spena A D, D’Angiolini G, Strati C et al., 2010. First correlations for solar radiation on cloudy days in Italy. In: ASME-ATI-UIT Conference on Thermal and Environmental Issues in Energy Systems. Sorrento, Italy.

    Google Scholar 

  • Tang Q H, Leng G Y, 2013. Changes in cloud cover, precipitation, and summer temperature in North America from 1982 to 2009. Journal of Climate, 26(5): 1733–1744. doi: 10.1175/JCLI-D-12-00225.1

    Article  Google Scholar 

  • U.S. Department of Commerce/National Oceanic and Atmospheric Administration, 1995. Surface Weather Observations and Reports. Federal Meteorological Handbook No.1. OFCM U.S. Department of Commerce/NOAA, 94. Washington, D.C: U.S. Department of Commerce/National Oceanic and Atmospheric Administration.

    Google Scholar 

  • Wang F, Guo J P, Wu Y R et al., 2014. Satellite observed aerosol-induced variability in warm cloud properties under different meteorological conditions over eastern China. Atmospheric Environment, 84: 122–132. doi: 10.1016/j.atmosenv.2013.11.018

    Article  Google Scholar 

  • Wang F, Guo J P, Zhang J H et al., 2015. Multi-sensor quantification of aerosol-induced variability in warm clouds over eastern China. Atmospheric Environment, 113: 1–9. doi: 10.1016/j.atmosenv.2015.04.063

    Article  Google Scholar 

  • Warren S G, Eastman R M, Hahn C J, 2007. A survey of changes in cloud cover and cloud types over land from surface observations, 1971–96. Journal of Climate, 20(4): 717–738. doi: 10.1175/JCLI4031.1

    Article  Google Scholar 

  • Wilson A M, Jetz W, 2016. Remotely sensed high-resolution global cloud dynamics for predicting ecosystem and biodiversity distributions. PLoS Biology, 14(3): e1002415. doi: 10.1371/journal.pbio.1002415

    Article  Google Scholar 

  • Wu Jian, Liu Jia, 2013. Variations of cloud fraction over East Asia under global warming conditions in the past 20 years. Journal of Tropical Meteorology, 19(2): 171–180. doi: 1006-8775(2013)02-0171-10

    Google Scholar 

  • Wylie D, Jackson D L, Menzel W P et al., 2005. Trends in global cloud cover in two decades of HIRS observations. Journal of Climate, 18(15): 3021–3031. doi: 10.1175/JCLI3461.1

    Article  Google Scholar 

  • Xia X, 2012. Significant decreasing cloud cover during 1954–2005 due to more clear-sky days and less overcast days in China and its relation to aerosol. Annales Geophysicae, 30(3): 573–582. doi: 10.5194/angeo-30-573-2012

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, 81746-73441, Iran

    Khodakaram Hatami Bahmanbeiglou & Saeed Movahedi

Authors
  1. Khodakaram Hatami Bahmanbeiglou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Saeed Movahedi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Saeed Movahedi.

Additional information

Foundation item: Under the auspices of Faculty of Geographical Science and Planning, University of Isfahan, Doctoral Climatology Project (No. 168607/94)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hatami Bahmanbeiglou, K., Movahedi, S. Identifying sky conditions in Iran from MODIS Terra and Aqua cloud products. Chin. Geogr. Sci. 27, 800–809 (2017). https://doi.org/10.1007/s11769-017-0908-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11769-017-0908-4

Keywords

Search

Navigation