Statistical Study of Solar Forcing of Total Column Ozone Variation Over Three Cities in Kenya

Carolyne M M Songa,Jared H O Ndeda,Gilbert Ouma

doi:10.5539/apr.v8n3p77

Abstract

In this study, a statistical analysis between three solar activity indices (SAI) namely; sunspot number (ssn), F10.7 index (sf) and Mg II index (mg) and total column ozone (TCO) time series over three cities in Kenya namely; Nairobi (1.17º S; 36.46º E), Kisumu (0.03º S; 34.45º E) and Mombasa (4.02º S; 39.43º E) for the period 1985 - 2011 are considered. Pearson and cross correlations, linear and multiple regression analyses are performed. All the statistical analyses are based on 95% confidence level. SAI show decreasing trend at significant levels with highest decrease in international sunspot number and least in Mg II index. TCO are highly correlated with each other at (0.936&lt; r &lt; 0.955, p &lt; 0.001). SAI are also highly correlated with each other at (0.941&lt; r &lt; 0.976, p &lt; 0.001) and are significantly positively correlated with TCO over the study period except Mg II index at Kisumu. TCO and SAI have correlations at both long and short lags. At all the cities, F10.7 index has an immediate impact and Mg II index has a delayed impact on TCO. A linear relationship exists between the two variables in all the cities. An increase in TCO of about 2 – 3 % (Nairobi), 1 – 2% (Kisumu) and 3 – 4 % (Mombasa) is attributed to solar activity indices. The multiple correlation coefficients and significant levels obtained show that 3 – 5% of the TCO at Nairobi, Kisumu and Mombasa can be predicted by the SAI.

Highlights

The Sun, undergoes changes characterized by variations in its output ranging from minutes to months and decades due to the different degrees of activity (Lockwood, 2004) and these variations reflect the inhomogeneous emission of radiation due to the presence and absence of active regions on the solar disk
The various statistical attributes of both mean monthly total column ozone (TCO) and solar activity indices (SAI) variables during the study periods are shown in Table 2 for TCO and Table 3 for SAI variables
A decreasing trend at significant levels of SAI variables is observed showing that, during the study period, SAI is decreasing with highest decrease in ssn (94% of the mean), followed by sf (34%) and least in mg (≈ 2%)

Summary

Introduction

The Sun, undergoes changes characterized by variations in its output ranging from minutes to months and decades due to the different degrees of activity (Lockwood, 2004) and these variations reflect the inhomogeneous emission of radiation due to the presence and absence of active regions on the solar disk. The variations occur because of the changing impacts of the solar features whose opposing influences depend on the wavelengths. Variations of the solar electromagnetic radiation are the cause of the radiated solar output variability both total and in various wavelengths (Spruit, 2000). The distinctive features perpetrated by these magnetic fields are displayed on different solar spheres, namely, the photosphere, chromosphere, and corona. Even though different solar layers are coupled, the variability is strongly wavelength dependent

Methods

Results

Conclusion