An optimal model for studying UVI parameter on different regions of Iraq

The UV index is considered to be a useful medical indicator for monitoring the effect of sun radiation, as UVI is a measure for the amount of ultraviolet sunlight relevant for erythema. This study aimed to explore the behavior of the UVI parameter according to creating new optimal statistical models due to different periods of time from 1st of July 2002 to 16th June 2024 per (days, months, and years) in different regions of Iraq (Baghdad, Basra, and Mosul). As well as offering influence models either for prediction equations or to forecast estimates of UVI parameters in the next periods of preceding time series. Several suggested models were introduced for studying the influence of "obsolescence time periods," such as "linear, logarithmic, inverse, quadratic, cubic, power, compound, S-shape, logistic, growth, and exponential, which represented their outcomes of "auto-regression ANOVA". Results showed that "Inverse" auto-regressive model has recorded the best model for all of the studied religions per days, as well as UVI parameter was frequently increased in Basra region, then gradually decreased in Baghdad, and the lowest level was recorded in Mosul during the studied period, while "Quadratic" of polynomial auto-regressive model, has recorded the best model among all of the studied religions per months, as well as UVI parameter were frequently increased dramatically as temperatures rised during the months of the year,, with the same differences recorded across regions, and finally" Cubic" of polynomial auto-regressive model, has recorded the best model among all of the studied religions per years, as well as UVI parameter were frequently increased severely during the last third of the studied time series per years, with the same differences recorded across different regions. The present research might have a practical role in environmental management. Consequently, the data produced from the current research can be utilized to assess and address the environmental effects of UVI exposure, including its impacts on humans, plants, animals, and water quality.