Quantile based modeling of diurnal temperature range with the five?parameter lambda distribution

Diurnal temperature range is an important variable in climate science that can provide information regarding variability and change. Changes diurnal have implications for hydrology, human health ecology, among others. Yet, the statistical literature on modeling lacking. In this article we propose to model distribution of using five-parameter lambda (FPL) distribution. Additionally, order with explanatory variables, a distributional quantile regression combines marginal FPL Inference performed method quantiles. The models are fitted 30 years daily observations from 112 weather stations southern part Norway. flexible shows great promise as range, performs well against competing models. data geographic, orographic, climatological variables. It captures much spatial variation