Performance Analysis of Temperature Models for Environmental Monitoring in Southwest Nigeria

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dc.contributor.authorWilloughby, Alexander
dc.date.accessioned2022-05-05T11:49:37Z
dc.date.available2022-05-05T11:49:37Z
dc.date.issued2019
dc.description.abstractTemperature is a major meteorological parameter driving most of the atmospheric processes vis-`a-vis climate change. Therefore, a consistent model is necessary to achieve sustainable development goal 13 (SDG 13) known as climate action. Long-term monthly averages of surface temperature obtained from six southwest states in Nigeria were subjected to five mathematical models, namely the sum of two-Gaussians, the sum of two-Lorentzians, Fourier on four harmonics, Sine wave and Fourth-order polynomial functions. Statistical tools were used to examine the accuracy and fitness of the models. The evaluation showed that the Gaussian and Lorentzian models are good fits of the observed data. Furthermore, the performance indicators such as mean bias error (MBE), root mean square error (RMSE), mean percentage error (MPE) recorded the lowest values for Fourier on the fourth harmonic model. Similarly, its correlation coe cient, R, was the highest ranging from 0.95 to 1. Consequently, the Fourier model presented the best correlation with the observed data and hence recommended for predicting the temperature at the selected locationsen_US
dc.identifier.issn2616-0714
dc.identifier.othereISSN 2616-0706
dc.identifier.urihttp://dspace.run.edu.ng:8080/jspui/handle/123456789/2667
dc.language.isoenen_US
dc.publisherNigerian Journal of Environment and Healthen_US
dc.subjectTemperature modelsen_US
dc.subjectPredictive modelsen_US
dc.subjectSurface temperatureen_US
dc.subjectStatistical testen_US
dc.subjectAnnual variationen_US
dc.titlePerformance Analysis of Temperature Models for Environmental Monitoring in Southwest Nigeriaen_US
dc.typeArticleen_US
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