Estimating daily global solar radiation by day of the year in six cities located in the Yucatán Peninsula, Mexico

Abstract

HighlightsDay of the year-based (DYB) models were used to predict daily solar radiation.Day of the year is the sole input to the DYB models assessed.A new Gaussian day of the year-based model is proposed.The proposed model estimates daily solar radiation with acceptable accuracy. 2 ABSTRACTPrediction of daily global solar radiation by using day of the year is particularly attractive because this parameter is not dependent on the input of meteorological parameters. In this study, four existing day of the year-based (DYB) models were evaluated and a new empirical DYB model was developed for estimating daily global solar radiation on a horizontal surface for six automatic weather stations of Yucatán Peninsula, Mexico. The performance of the models was assessed with root mean squared error (RMSE), mean bias error (MBE), mean percentage error (MPE), mean absolute percentage error (MAPE), mean absolute bias error (MABE) and coefficient of determination (R 2 ). The results show that the new proposed Gaussian DYB model estimates daily solar radiation better than other DYB models.Furthermore, a seasonal analysis shows that the model has good performance in all seasons, including in the rainy season. The results also suggest that the new model can be useful for highly variable climate conditions.

Impacts of climate change on characteristics of daily‐scale rainfall events based on nine selected GCMs under four CMIP5 RCP scenarios in Qu River basin, east China

“…To evaluate the effectiveness of the bias correction method and obtain information on the differences between observed and simulated rainfall before and after bias correction, we measure the differences between the observed and (corrected) simulated empirical CDFs by using the mean absolute percentage error (MAPE) indicator (Quej et al ., ; Shamshirband et al ., ) as Equation , where n = 99 is the number of 1% quantile intervals between the 1 and 99% quantiles of rainfall, and O i and S i are the i th percentiles of the observed and simulated distribution, respectively.…”

Dimming in Iran since the 2000s and the potential underlying causes

“…(Kun et al, 2006;Wild et al, 2015a;Dagon and Schrag, 2016;Huber et al, 2016). Therefore, it is considered as one of the most important inputs of hydrological, irrigation scheduling and crop growth models (Aladenola and Madramootoo, 2014;Jahani et al, 2016;Jahani et al, 2017;Quej et al, 2017;Wang et al, 2017). Furthermore, R s is also a renewable clean source of energy, which has received increasing attention recently, because it can be exploited without bearing any harm to nature and is also an alternative for fossil fuels (Viorel, 2008;Zekai, 2008;Demirhan and Atilgan, 2015;Wild et al, 2015a;Wild et al, 2015b;El Mghouchi et al, 2016).…”

Approximation of Empirical and ANN Based Solar Radiation Models for Four Smart Cities in Tamil Nadu with Most Prompting Input Parameters

“…Therefore itis essential to assessment solar radiation models based on commonlyavailablemeteorologicaldatasuchastemperature, sunshine radiation and relative humidity and so on.Selection of input parameter is the first step to develop models for estimation of daily global solar radiation. The prediction model has developed based on sunshine duration and clearnessindex [1].Predictingthedailyglobalsolarradiation bydayoftheyearinsixcitiesusingcurvefittinganalysisand regressioncoefficienthasbeenevaluatedfordifferentmodels [2]. Prediction of direct normal radiation and global solar radiation using neural network is proposed in [3].The network configuration to select the number of hidden neuron andtransferfunctionofdifferentmodelshasbseenevaluated.…”