Investigating the Influence of Cosmic Rays on the Climate of South-East and South-South Regions of Nigeria Using Sunshine Hours and Relative Humidity. (Published)
There is a rising concern about the agents and mechanisms of climate change. The contribution of anthropogenic greenhouse gases to global warming has long been accepted by most scientists, however, the impacts of some natural factors such as cosmic rays, sunspot and geomagnetic activities are yet to be established. This study investigated the effects of cosmic rays on the climate of south-east and south-south parts of Nigeria from 5 meteorological stations in the regions for a period of 48 years (1965-2012). Sunshine hours and relative humidity were used as weather parameters. No particular trend was found in the value of cosmic rays during the period; similarly, the sunshine hours and the relative humidity also produced very irregular patterns. A very low but positive correlation coefficient of 0.3 was found between cosmic rays and sunshine hours with almost no correlation (r = 0.1) between cosmic rays and relative humidity.
Design of a Renewable Energy Output Prediction System for 1000mw Solar-Wind Hybrid Power Plant (Published)
Problems associated with non-renewable energy sources such as fossil fuels make it necessary to move to cleaner renewable energy sources such as wind and solar. But the wind and sun are both intermittent sources of energy therefore accurate forecasts of wind and solar power are necessary to ensure the safety, stability and economy of utilizing these resources in large scale power generation. In this study, five meteorological parameters namely Temperature, Rainfall, Dew Point, Relative Humidity and Cloud Cover were collected for the year 2012 and used to predict wind and solar power output in Jos, Nigeria. The study used prediction algorithms such as Regression techniques and Artificial Neural Networks to predict the output of a 1000mW Solar-Wind Hybrid Power Plant over a period of one year. Individual prediction techniques were compared and Isotonic Regression was found to have the highest accuracy with errors of 40.5% in predicting solar power generation and 35.4% in predicting wind power generation. The relatively high levels of error are attributed to several limitations of the research work.
Current global climatic trends show a deviation from historic trends and this has necessitated this study. The paper analysed climate change trend and the perceived climatic hazards in Southeast Nigeria. Proportionate sampling technique was used to select a sample of 260 food crop farmers for the study and 232 questionnaires were returned. Secondary time series data on mean annual climate variables for a period of thirty years (1984-2014) were collected from National Root Crop Research Institute Umudike and crop output data from National Bureau of statistics. Data were analysed using descriptive statistical tools like polygon/histograms and line graphs. Also, the extent of damage by climate hazards as perceived by respondents was obtained using likert scale. The rainfall volume variation showed a very unstable pattern with high volatility over years with slightly increasing trend in the study area. Result shows that temperature is significant at 1% level of significance while rainfall volume, rainfall days, relative humidity and sunshine duration were insignificant. Rain day was characterized by unsteady rise and fall trend pattern. The trend also indicated an unsteady change in the movements of the relative humidity and sunshine levels. The result for the occurrence of climate hazards as perceived by farmers show 86.2 %, 64.68%, 63.79%, 77.82% of the respondents perceived to a great extent the impact of flooding, sea level rise, longer period of dry spell and wind storm respectively. Based on the finding, it is concluded that the damaging and devastating effects of climate change is in the increase. It is recommended therefore that adequate adaptive measures and mitigations be put in place to cushion the effect of climate change.