The performance of multisource renewable energy system depends strongly on the meteorological parameters pertinent to the energy generating systems. Therefore, a method of modelling and forecasting meteorological and system parameters is necessary for efficient operation of the renewable energy power management system. Bahrain's first hybrid renewable energy system utilizes two renewable energy sources, namely solar irradiance through a 4.0 kW(p) PV (photovoltaic) panel and wind through a 1.7 kW(p) wind turbine. The focus of the present work is to investigate the proficiency of the Box Jenkins based modelling approach in analysing and forecasting the daily averages of wind speed, solar irradiance, ambient air temperature, and the PV module temperature. Different non-seasonal ARIMA (Autoregressive Integrated Moving Average) models have been constructed. ARIMA(1,0,0), ARIMA(1,0,0), ARIMA(0,1,2), and ARIMA(0,1,1) have been found adequate in capturing the auto-correlative structure of the daily averages of wind speed, solar irradiance, ambient air temperature, and PV module temperature, respectively. In addition, a functional relationship that correlates the diurnal PV module temperature to the ambient air temperature and solar irradiance have been developed. Residual and forecasting analyses have been used to ensure the adequacy of the identified models. (C) 2016 Elsevier Ltd. All rights reserved.