Monitoring aerosols using satellite remote sensing data concurrently with ground observations in Iraq

Authors

  • Hussain Ali Ministry of Science and Technology
  • Saad Farraj Iraqi Meteorological Organization and Seismology, Baghdad-Iraq

DOI:

https://doi.org/10.24996/ijs.2012.53.Remote%20Sensing-Conf.%25g

Keywords:

dust; , aerosols, remote sensing; soils

Abstract

Dust particles from storms are one of the main atmospheric constituents that affect the air quality and the Earth’s climate system. Monitoring of these atmospheric constituents is only possible through satellite measurements because ground based measurements are very limited in space and time and these constituents get transported over long distance from their source region. Absorbing Aerosol index is a qualitative parameter however it does excellent job in classifying UV absorbing and non absorbing aerosols. In most areas, we can classify dust storms by the broad meteorological conditions that cause them. The AI is a measure of the change of spectral contrast in the near ultraviolet (with respect to a purely molecular atmosphere) brought about by the radiative transfer effects of UV-absorbing aerosols such as smoke , volcanic ash and desert dust in a Rayleigh scattering atmosphere. The AI is a very useful qualitative indicator to identify aerosol sources and transport patterns. In this paper we will examine the most common events that occur in Iraq concurrently with satellite observation. These events are dust storms caused by prefrontal and postfrontal winds that primarily occur in the winter, and summer dust storms caused by persistent northerlies. In this paper will conduct complete and thorough case studies of the meteorological conditions that led to the dust storm.

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Published

2024-04-26

Issue

Section

Remote Sensing

How to Cite

Monitoring aerosols using satellite remote sensing data concurrently with ground observations in Iraq. (2024). Iraqi Journal of Science, 53(Remote Sensing-Conf), 19-32. https://doi.org/10.24996/ijs.2012.53.Remote Sensing-Conf.%g

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