Browsing by Author "Sharafa, S. B."

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    Analysis of Kano Meteorological Data using Time Series Analysis and Empirical Orthogonal Functions
    (FACULTY OF SCIENCE, KANO UNIVERSITY OF SCIENCE AND TECHNOLOGY, WUDIL, 2020) Aliyu, R.; Tijjani, B. I.; Gana, U. M.; Bala, S.; Sharafa, S. B.; Uba, S.; Auwalu, S.; Yerima, S. U.; Abdulkarim, U. Y.; Idris, M.
    In this work, two different statistical techniques were used to analyses the meteorological data of Kano State. The meteorological parameters utilized are daily Solar Radiations, Sunshine Hours, wind speed, Maximum and Minimum Temperatures, Rainfall, Cloud Cover, and Relative Humidity, data spanning for thirty-one years (1980 to 2010). The statistical analysis involves the use of time series analysis and empirical orthogonal functions. In the time series analysis (TS) all the parameters are assumed independent. The second is the Empirical Orthogonal Transformation (EOF) in which the data were analyzed using unrotated and orthogonal transformations and six components were extracted. From component matrices, it is discovered that there are two distinct season as Rainy and Dry seasons. The rainy season has two components comprising heavy rain and light rain, while the dry season comprises of three different types of seasons. The period of heavy rain is around 3.3 months and period of light rain is 1.6 month. These gives a total of 4.9 months for rainy season and 7.1 months for dry season. The values of the eigen values are consistent with what is observed in real-time of seven (7.1) months of dry season and (4.7) months of rainy season. Now combining the two results, it can be said that the TS analysis show that all the parameters have seasonal variation, and the EOF now described the two seasons quantitatively
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    The application of Angstrom Exponent and measures of shapes in the classifications of aerosol size distributions
    (FACULTY OF SCIENCE, KANO UNIVERSITY OF SCIENCE AND TECHNOLOGY, WUDIL, 2020) Aliyu, R.; Tijjani, B. I.; Gana, U. M.; Bala, S.; Sharafa, S. B.; Uba, S.; Auwalu, S.; Yerima, S. U.; Abdulkarim, U. Y.; Muhammad, A.; Idris, M.
    In this work, Ansgrom exponent (a) and curvature (a2), skewness and kurtosis are used to give a clear particles size distribution. This is because some researchers reported the existence of negative curvatures for fine mode aerosols and near zero or positive curvatures are characteristic of size distributions with a dominant coarse-mode or bimodal distribution with coarse-mode aerosols having a significant relative magnitude. The aerosol types used in this work are Sahara and Urban aerosols that are extracted from Optical Properties of Aerosols and Clouds (OPAC4.0). From the results, it is discovered that a and skewness can be used to determine the main dominance particles size distributionin terms of number. The kurtosis can be used to determine the dominant particles in terms of volume. The a2 signifies whether the particle distribution is either monomodal or bimodal. It shows that when a2 is negative, it signifies monomodal distribution while when a2 is positive it signifies bimodal type of size distribution.