Assesment and comparison of modis aod and ae product over Ilorin Aeronet station using the statistical analysis of empirical orthogonal function (EOF)

Abstract

onboard satellite, then a second instrument was launched onboard EOS-Aqua in May 2002. Both satellites are sun-synchronous with Equatorial overpass at 10:30 AM for Terra and 1:30 PM for Aqua, local time. They measure angular dependence of radiance at multi ranging from UV to infrared. As they are able to provide spectral optical depth, and aerosol size information in the form of Angstrom exponent (Remer et al., 2005). MODIS also measures the properties of aerosols-tiny liquid or solid particles in the atmosphere. Aerosols enter the atmosphere from manmade sources like pollution and biomass burning and natural sources like dust storms, volcanic eruptions, and forest fires (Kaufman et al., 2000). Aerosol Robotic Network (AERONET) is a federated ground-based remote sensing ABSTRACT In this Paper, Empirical Orthogonal Function (EOF) was used to assess the MODIS C006 LV2 aerosol AOD and AE products, and compared the data with AERONET AOD and AE observations. The data were taken from an AERONET station at Ilorin, Nigeria which were obtained from (MAPSS) and wer data period for the two satellite data were from Dec 2004 to May 2015 It was observed from the graphical representation that the seasonal variation of AOD peaks during the dry season from Dec to Feb and reaches minimum during summer in August 2008.The comparisons showed both underestimations in MODIS AOD and considerable overestimations in the AE. On the EOF analysis it was observed that a good correlation between MODIS & AERONET AOD are observed on the correlation matrices in all the data. Lower correlation is only observed at Ilorin AERONET wavelength at 470nm (ILA470) with Ilorin 660nm (ILM660).On the total variance explained table for MODIS and AERONET AOD, it was observed that out of the 6 com with a very high percentage of 81.57% observed with a percentage of 83.95% for MODIS and AERONET AOD,and little variation was observed for MODIS and AERONET AE.

A Comparative study of Time Series, Empirical Orthogonal Transformation and Descriptive Statistical Analysis on Meteorological Parameters over Ogoja and Maiduguri

“…In Table 12, the Kaiser-Meyer-Olkin (KMO) shows that the sampling adequacy of 59.0% was obtained. ≥ (0.05) or ≥ 50% is the acceptable value and is in agreement with the study report by Aliyu et al [15]. The Bartlett's test of sphericity gives degree of freedom of 21 and it's significant at 95% confidence level.…”

“…The Empirical orthogonal transformation (EOT) has become standard statistical techniques particularly in the field of climate and meteorological research and other fields such as geophysical sciences and oceanography [15]. This method of statistical analysis is used to condense any complicated data set into a finite and small number of new variables.…”

“…This method of statistical analysis is used to condense any complicated data set into a finite and small number of new variables. It uses correlation between variable to determine a smaller number of new variables called components that can give vital information about the data [15].…”

Time Series and Empirical Orthogonal Transformation Using Meteorological Parameters across the Climatic Zones in Nigeria

“…Empirical orthogonal function (EOF) analysis or principal component analysis (PCA) have become standard statistical techniques in the geophysical sciences of meteorology and oceanography particularly in the field of climate research [5]. This method of statistical analysis is used to reduce any complicated data set into a finite and small number of new variables.…”

“…This method of statistical analysis is used to reduce any complicated data set into a finite and small number of new variables. It uses correlation between variable to determine a smaller number of new variables called components that can give vital information about the data [5].…”