Radiative forcing determination depending on MISR data and Fu-Liou Model

Authors

  • Islam Maher Amin  Egyptian Meteorological Authority, Ministry of Aviation Kobry El Qoba El-Kalefa Al-mamoon st.,Cairo, Egypt
  • T. A. Sayad  Al-Azhar University, Faculty of Science, Astronomy and Meteorology Department, Cairo, Egypt
  • A. S. Zakey  Egyptian Meteorological Authority, Ministry of Aviation Kobry El Qoba El-Kalefa Al-mamoon st.,Cairo, Egypt
  • F. Elhossiny  Al-Azhar University, Faculty of Science, Astronomy and Meteorology Department, Cairo, Egypt

Keywords:

Aerosol Optical Depth, Aerosol Robotic network, Angstrom, Earth’s energy budget and Radiative Forcing.

Abstract

Atmospheric aerosols particles exert significant direct radiative forcing and this plays an important rule of climate and climate change. Aerosols particles can affect the radiation budget and the temperature by changing the energy balance and distribution of solar and terrestrial radiation in the atmosphere. This paper discusses aerosols distribution over Middle East and North Africa and their influences on Radiative Forcing (RF) which consequently affect the radiation budget and try to find out an alternative method to obtain data of AOD else that obtained from Aeronet with acceptable error. These data can be used as input for RTM model (Fu-Liou) to determine RF. Thus RF can be calculated anywhere over the study area and not only at Aeronet stations. For this purpose Aerosol properties data from several Aeronet stations and corresponding data from MISR satellite in the focused region for long term have been retrieved and analyzed to verify MISR data; then data of Aeronet used to feed Fu-Liou model to simulate irradiances in the shortwave range under cloud-free conditions. Radiative Forcing estimated from Fu-Liou model have been compared with daily RF data of year 2015 over Egypt from Aeronet. As well as, average seasonal RF outputs from Fu-Liou model over North Africa and Middle East have been compared with the Aeronet RF at the surface and top of atmosphere for the different four seasons. The results illustrated that data from MISR satellite is coincide with Aeronat data with acceptable error while the average error of RF values from the Fu-Liou model and Aeront at wavelength 550nm is 10 % on surface and 7 % at top of atmosphere relative to Aeront when the prevailing type of aerosols is dust. While this ratio, increases to be from 14 to 19% on surface and from 17 to 22% at top of atmosphere for the different cases of aerosol types. This study is considered as an important attempt to find out method to determine RF at any where over the focused area and not only at Aeronet stations also this paper addressed the percentage of different types of aerosols during different situations and it documented the horizontal distribution of aerosols optical properties and its radiative forcing over the selected region.

References

x

  1. Abdelkader, M., Metzger, S., Mamouri, R. E., Astitha, M., Barrie, L., Levin, Z., and Lelieveld, J.  2015: Dust-air pollution dynamics over the eastern Mediterranean, Atmos. Chem. Phys., 15, 9173- 9189, doi:10.5194/acp-15-9173-2015,.
  2. Ackerman, A. S., O. B. Toon, D. E. Stevens, A. J. Heymsfield, V. Ramanathan, and E. J. Welton (2000): Reduction of tropical cloudiness by soot, Science, 288, 1042 - 1047.
  3. Alpert, P., Y. J. Kaufman, Y. Shay-El, D. Tanre´, A. da Silva, S. Schubert, and J. H. Joseph (1998): Quantification of dust-forced heating of the lower troposphere, Nature, 395, 367 - 370.
  4. Astitha, M., Lelieveld, J., Abdel Kader, M., Pozzer, A., and de Meij, A. (2012): Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties, Atmos. Chem. Phys., 12, 11057-11083, doi:10.5194/acp-12-11057-2012,
  5. Bauer, E. Bierwirth, M. Esselborn, A. Petzold, A. Macke, T. Trautmann, M. Wendisch 2011
  6. Airborne spectral radiation measurements to derive solar radiative forcing of Saharan dust mixed with biomass burning smoke particles
  7. Tellus, 63B, pp. 742-750
  8. Charlson.RJ, Schwartz Hales.J.M Cess,RD.Coakley Jr,JA. Hansen, .J.E.Hofman.DJ.1992.Climate forcing anthropogenic aerosols, science 255,423-430
  9. De Meij, A., Pozzer, A., and Lelieveld, J.: Trend analysis in aerosol optical depths and pollutant emission estimates between 2000 and 2009, Atmos. Environ., 51, 75-85, 2012.
  10. Dubovik, O., B. N. Holben, T. F. Eck, A. Smirnov, Y. J. Kaufman, M. D. King, D. Tanre, and I. Slutsker (2002a), Variability of absorption and optical properties of key aerosol types observed in worldwide locations, J. Atmos. Sci., 59, 590 - 608, doi:10.1175/1520-0469 (2002) 0:VOAAOP,2.0.CO;2.
  11. Holben, B. N., T. F. Eck, I. Slutsker, D. Tanré, J. P. Buis, A. Setzer, E. Vermote, J. A. Reagan, Y. J. Kaufman, T. Nakajima, F. Lavenu, I. Jankowiak, A. Smirnov (1998): AERONET - A federated instrument network and data archive for aerosol characterization, Rem. Sens. Env., 66(1), 1-16.
  12. Hsu, N. C., Gautam, R., Sayer, A. M., Bettenhausen, C., Li, C., Jeong, M. J., Tsay, S.-C., and 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., 12, 8037-8053, doi:10.5194/acp-12-8037-2012, 2012.
  13. Kalenderski, S., Stenchikov, G., and Zhao, C. (2013): Modeling a typical winter-time dust event over the Arabian Peninsula and the Red Sea, Atmos. Chem. Phys., 13, 1999-2014, doi:10.5194/acp-13- 1999-2013,
  14. Lacis.A.A and V. Oinas, (1991): A description of the correlated k distribution method for modeling nongray gaseous absorption, thermal emission, and multiple scattering in vertically inhomogeneous atmospheres. J. Geophys. Res., 96, 9027-9063.
  15. Mishra.A, K. Klingmueller, E. Fredj, J. Lelieveld, Y.Rudich, I. Koren (2014): Radiative signature of absorbing aerosol over the eastern Mediterranean basin Atmos. Chem. Phys., 14 , pp. 7213-7231
  16. Osipov, S., Stenchikov, G., Brindley, H., and Banks, J. (2015): Diurnal cycle of the dust instantaneous direct radiative forcing over the Arabian Peninsula, Atmos. Chem. Phys., 15, 9537-9553, doi:10.5194/acp-15-9537-2015.
  17. Pozzer, A., de Meij, A., Yoon, J., Tost, H., Georgoulias, A. K., and Astitha, M.  (2015): AOD trends during 2001-2010 from observations and model simulations, Atmos. Chem. Phys., 15, 5521-5535, doi:10.5194/acp-15-5521-2015,.
  18. Prospero, J.M., (1999): Long-term measurements of the transport of African mineral dust to the Southeastern United States: Implications for regional air quality. Journal of Geophysical Research 104(D13):15,917-15,927.
  19. Wilson, R., and J. Spengler (Eds.) (1996): Particles in Our Air: Concen- trations and Health Effects, 254 pp., Harvard Univ. Press, Cambridge, Mass.
  20. Zakey, A. S., F. Solmon, , and F. Giorgi, (2006): Implementation and testingof a desert dust module in a regional climate model, Atmos.Chem. Phys., 6, 4687-4704, doi:10.5194/acp-6-4687,
  21. Zakey, A. S., F. Giorgi, , and X. Bi, (2008): Modeling of sea salt in a regional climate model: Fluxes and radiative forcing, J. Geophys. Res., 113, D14221, doi:10.1029/2007JD009209,.
  22. Zhang, L., Q. B. Li, Y. Gu, K. N. Liou, and B. Meland 2013: Dust vertical profile impact on global radiative forcing estimation using a coupled chemical-transport-radiative-transfer model. Atmos. Chem. Phys., 13, 7097-7114.

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Published

2017-10-31

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Section

Research Articles

How to Cite

[1]
Islam Maher Amin, T. A. Sayad, A. S. Zakey, F. Elhossiny, " Radiative forcing determination depending on MISR data and Fu-Liou Model, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 6, pp.363-377, September-October-2017.