Anthropogenic and natural aerosols are important atmospheric constituents that significantly contribute to the Earth’s radiation budget but remain uncertainties due to the poor understanding of aerosol properties and its direct effects on scattering and absoprtion of solar radiation and the ability of aerosols to stay in atmosphere for a very short time. Different types of aerosols, representing biomass burning, urban or continental aerosols, maritime aerosols and dust particles will give different characterization and classification of aerosol properties. The data used in this study was obtained from Aerosol Robotic Network (AERONET).Two parameters were used for aerosol analysis which are Aerosol Optical Depth (AOD) at four wavelengths (440, 500, 675 and 870nm) and Angstrom exponent (α) derived from a multispectral log linear.
Difficulties on the estimating of aerosol radiative forcing is due to lack of knowledge on the microphysical and aerosol optical properties and their extreme variations of spatial distribution. In understanding the dynamics of aerosols and the associated influence on global climatic conditions one of the critical parameter used is Aerosol Optical Depth (AOD). AOD acts as a good indicator due to strong correlation between small particle concentrations and light extinction coefficients. Daily AERONET Level 2 data provides AOD at 500nm however the data is very limited to a smaller scale only. To overcome this problem, MODIS data is used to provide daily AOD at 550nm data over relatively larger spatial at 10km twice a day. The aim of this study is to retrieve AOD value from MODIS satellite data and to compare and validate the AOD value using AERONET Sunphotometer. Comparison and validation of MODIS data using different instruments are required for the long term monitoring and accuracy improvement. The usual methodology for retrieval of AOD was used which is multi regression plane technique with mean and standard deviation. However, in this study some of the improvement was done by using multi regression plane technique with relative percentage error. The interpolation technique was used to derive AOD from AERONET and the statistical parameters and correlation coefficient (R 2 ) are compared. From the result, MODIS is found to overestimate the AOD during the study period compared to AOD derived from AERONET. The correlation between extracted AOD from MODIS and AERONET using mean and standard deviation gave the R 2 at 0.9033 while R 2 for relative percentage error is 0.9422. Thus, from the comparison shows the importance of modifying the existing technique for the retrieval of AOD to reduce the error and uncertainties during the application of the parameter into radiative transfer model. Keywords-Aerosol Optical Depth (AOD), MODIS, AERONET, aerosol, multi regression plane techniqueI.
Abstract. The present study uses the Aerosol Optical Depth (AOD) retrieved from Moderate Imaging Resolution Spectroradiometer (MODIS) data for the period from January 2011 until December 2015 over an urban area in Kuching, Sarawak. The results show the minimum AOD value retrieved from MODIS is -0.06 and the maximum value is 6.0. High aerosol loading with high AOD value observed during dry seasons and low AOD monitored during wet seasons. Multi plane regression technique used to retrieve AOD from MODIS (AOD MODIS ) and different statistics parameter is proposed by using relative absolute error for accuracy assessment in spatial and temporal averaging approach. The AOD MODIS then compared with AOD derived from Aerosol Robotic Network (AERONET) Sunphotometer (AOD AERONET ) and the results shows high correlation coefficient (R 2 ) for AOD MODIS and AOD AERONET with 0.93. AOD MODIS used as an input parameters into Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model to estimate urban radiative forcing at Kuching. The observed hourly averaged for urban radiative forcing is -0.12 Wm -2 for top of atmosphere (TOA), -2.13 Wm -2 at the surface and 2.00 Wm -2 in the atmosphere. There is a moderate relationship observed between urban radiative forcing calculated using SBDART and AERONET which are 0.75 at the surface, 0.65 at TOA and 0.56 in atmosphere. Overall, variation in AOD tends to cause large bias in the estimated urban radiative forcing.
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