Prediction Of Clearness Index For Some Nigerian Stations Using Temperature Data

Global solar radiation and mean temperature data for five Nigeria stations have been used to fit the Angstrom model for the clearness index (KT =H/Ho), the mean temperature (Tmean) and maximum temperature (Tmax). The tests of performance of the model for the five stations have been done in terms of the widely used statistical indicators, Mean Bias Error (MBE) and Root Mean Square Error (RMSE). It was found from statistical model performance indicators that the models provided reasonably high degree of precision in the prediction of average monthly global solar radiation on horizontal surfaces. Keywords: Clearness index, Global solar radiation, and Temperature. Journal of Science and Technology (Ghana) Vol. 28 (2) 2008: pp. 94-10

Statistical study of variation of diffuse solar radiation over Nigeria

Multiple regression models have been developed to study the variation of diffuse solar radiation over Nigeria using monthly mean data of clearness index, relative sunshine duration, average temperature and cloud cover. The data for eight stations representing the weather conditions of Nigeria and covering a period 16 years were analyzed, and the statistical accuracy of the regression equations were evaluated by root mean square error, stand-ard error, mean bias error, t-statistic, correlation coefficient and coefficient of determination. The regression prod-uced good correlation between the dependent variable of fraction of diffuse solar radiation and the independent variables of clearness index, relative sunshine duration, cloud cover and average temperature. The multiple regre-ssion equations reflected the spatial variability with the latitudes, and can be used for prediction of diffuse solar radiation in Nigeria. A temporal and spatial diffuse solar radiation contour map was developed using Surfer 10 Golden graphic software.Keywords: Multiple regression, Diffuse solar radiation, Clearness index, Cloud cover, Correlation coefficien

ESTIMATING GEOMAGNETICALLY INDUCED CURRENTS AT SUBAURORAL AND LOW LATITUDES TO ASSESS THEIR EFFECTS ON POWER SYSTEMS

ABSTRACT During large magnetic storm the geomagnetically induced current has a negative impact on ground conducting technology systems. The time derivative of the horizontal component of the geomagnetic field (dH/dt) is greater than 30nT/min for induced currents causing undesirable consequence in power grids. Multiple regression analyses were developed to predict the level of geomagnetic disturbance using time derivatives of the horizontal geomagnetic field, east and north components of the geoelectric field, auroral electrojet and disturbance storm times from 1994-2007 at low and subauroral latitudes. The statistical test RMSE (Root Mean Square Error) and MBE (Mean Bias Error) were employed to evaluate the accuracy of the geomagnetic disturbance. Different variables have been used to develop different types of models. Values of the correlation coefficient and the coefficient of determination were high, which indicates that the results are good. The equations produced the best correlations at subauroral and low latitudes, and the best correlation was obtained with low values of RMSE and MBE

Modelling of geomagnetically induced currents during geomagnetic storms using geoelectric fields and auroral electrojet indices

The effects of space weather on ground based technology mostly occur due to the varying geomagnetic field during geomagnetic storms, producing geomagnetically induced current (GIC). Space weather storms involve intense and rapidly varying electric currents in the ionosphere, which create geoelectric and geomagnetic fields at the Earth's surface. In this study we have investigated some intense geomagnetic storms: September 18th, 2000; March 31th, 2001; October 21st, 2001; November 6th and 24th, 2001; October 29th and 31st, 2003 and November 9th, 2004. The electric field for each day has been computed using ground conductivity and geomagnetic recordings. The conductivity models are determined by least square fit between the observed and predicted GIC values. Our results show that GIC are strongly correlated with the geoelectric field, and also with eastward and westward auroral electrojet indices and time derivatives of the horizontal geomagnetic field. Root mean square error statistical test has been employed to evaluate the accuracy of the models used. ©2012 IACS