Estimation of Sunshine Duration using Statistical Approach:‎ Libya As A case Study

Abstract

Sunshine duration (SD) is an essential atmospheric indicator which is used in many agriculture, ‎architects and solar energy applications. In many situations where data of sunshine duration may not be ‎available due to temporal and financial constraints, developing alternative indirect methods based on ‎theoretical considerations for determining SD are essentially required. In this study, seven models were ‎developed using stepwise regression technique to estimate monthly sunshine duration for Libya. The ‎predictors which were used as inputs differ from one model to another and they included monthly ‎cloudiness index, total day length, mean relative humidity, depth of precipitation, mean maximum ‎temperature, altitude and longitude over 16 meteorological stations spread across Libya during the ‎period of 1961 – 2000 . The evaluation of the developed models was performed using a set of data of ‎four meteorological stations representing different physiogeographic and climatic zones during 2001 ‎and against Abdelwahed and Snyder (2015) equations which were developed for estimating sunshine ‎duration for Libya. The statistical parameters of evaluation criteria included mean absolute error (MAE), ‎root mean square error (RMSE), (RMSE %) and Nash and Sutcliffe Efficiency (NSE). The linear regression ‎equation relating predicted with measured data with intercept equals zero and determination coefficient ‎‎(R2) were also used for evaluation purpose. According to the performance indicators, it was detected ‎that six of the developed models were superior to the model with one parameter (cloudiness index) in ‎estimating the sunshine hours. It was also found that all the developed models have better performance ‎in estimating the sunshine duration as compared with Abdelwahed and Snyder (2015) equations. ‎However, due to its few required variables, a model with two parameters (cloudiness index and total ‎day length) is sufficient and can be used with confidence in estimating sunshine duration for Libya. ‎

Keywords: Sunshine duration, Stepwise regression, Statistical model.‎

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‎*Corresponding Author: Ahmed I. Ekhmaj. Soil and water Dep., Faculty of Agriculture, University of Tripoli, Tripoli, Libya.‎

‎ Phone. +218‎‏926577440‏‎.     Email: khmaj1@yahoo.com ‎