This study was designed to develop an efficient algorithm to retrieve aerosol characteristics in aerosol events, which are associated with dense concentrations of aerosols in the atmosphere, such as a dust storm or a biomass burning plume. The idea of successive scattering of light is reviewed based on the theory of radiative transfer. Then derivation of the method of successive order of scattering (MSOS) is interpreted in detail, and it is shown that MSOS is available for a simulation scheme in the dense radiation field being used to retrieve aerosol properties in the event with the high optical thickness. Finally our algorithms are practically applied for the biomass burning aerosol event over the Amazon using Aqua/MODIS data
The aerosol distribution in Asia is complicated due to the increasing emissions of sulfuric, nitric, carbonaceous and other aerosols in association with economic growth. Anthropogenic small aerosols dominate the air over urban areas because of local emissions by diesel vehicles and industries, and in addition, behavior of natural dusts significantly varies with the seasons. Thus, studying various properties of aerosols in Asian urban areas is an important subject. In this work, we classify aerosol properties with a clustering method, by utilizing the ground observations provided by multi-spectral photometers which are installed in Kinki University Campus, Higashi-Osaka, Japan. Cluster information can be used to improve estimation of relations between spectral and particle observations.
Retrieval of atmospheric aerosol characteristics from satellite data, i.e. aerosol remote sensing, is based on the light scattering theory. The aerosol properties are estimated by comparing satellite measurements with the numerical values of radiation simulations in the Earth atmosphere model. This study was designed to develop an efficient algorithm to retrieve aerosol characteristics in aerosol events, which are associated with extreme concentrations of aerosols in the atmosphere such as a yellow-sand storm. It is known that the large increase in the optical thickness of the atmosphere during aerosol events prevents the use of sun/sky photometry from the surface level. However, space-based observations are possible for monitoring the atmospheric aerosols during such events. This study focuses on new algorithms being used to detect the event core with a high optical thickness and a simulation scheme for radiative transfer in the dense radiation field being employed. Finally, the practical application of our algorithms was tested using Aqua/MODIS data for a yellow-sand storm.
It is well known that the heavy soil dust is transported from the China continent to Japan on westerly winds, especially in spring. It is also known that the increasing emissions of anthropogenic aerosols associated with continuing economic growth in Asia has caused serious air pollution over a wide range of East Asia. Accordingly the dust particles involve anthropogenic aerosols as well as soil dust. Thus aerosols in Asia are very complex due to mixing of small anthropogenic particles and large dust particles, which are called Asian dust. The satellite observation is an effective tool for global monitoring of the Asian dust. A new algorithm for detection of Asian dust from space is proposed based on multispectral satellite (Terra/Aqua/MODIS) data. The derived space-based results are validated with ground-based measurements and/or model simulations. The sun/sky photometry has been undertaken at NASA/AERONET stations at Higashi-Osaka in Japan, where the suspended particulate matter (SPM) sampling and NIES/LIDAR network equipment have been simultaneously working. In order to validate the satellite results with these surface-level data, an aerosol transportation model is available. In other words, the space-based and/or surface-based measurements are examined with the model simulations, and vice-versa.
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