Diurnal temperature range is an important variable in climate science that can provide information regarding climate variability and climate change. Changes in diurnal temperature range can have implications for human health, ecology and hydrology, among others. Yet, the statistical literature on modelling diurnal temperature range is lacking. This paper proposes to model the distribution of diurnal temperature range using the five-parameter lambda distribution (FPLD). Additionally, in order to model diurnal temperature range with explanatory variables, we propose a distributional quantile regression model that combines quantile regression with marginal modelling using the FPLD. Inference is performed using the method of quantiles. The models are fitted to 30 years of daily observations of diurnal temperature range from 112 weather stations in the southern part of Norway. The flexible FPLD shows great promise as a model for diurnal temperature range, and performs well against competing models. The regression model is fitted to diurnal temperature range data using geographic, orographic and climatological explanatory variables. It performs well and captures much of the spatial variation in the distribution of diurnal temperature range in Norway.
翻译：日光温度范围是气候科学的一个重要变量,可以提供有关气候多变性和气候变化的信息。日光温度范围的变化可能会对人类健康、生态和水文学等产生影响。然而,缺乏关于二极温范围建模的统计文献。本文件建议使用五分数的羊羔分布(FPLD)来模拟二极温范围的分布。此外,为了用解释变量来模拟二极温范围,我们建议一种分布式孔径回归模型,将孔径回归与使用FPLD的边际建模结合起来。使用量衡算法进行推断。这些模型安装了30年,每天对挪威南部112个气象站的二极温范围进行观测。灵活的FPLD显示了极光温度范围模型的巨大前景,并与相互竞争的模型相匹配。回归模型与使用地理、地理或气候和气候解释变量的二极温范围数据相结合。它很好地测量和捕捉到挪威平离子温度范围分布的空间变化。
相关内容
微信扫码咨询专知VIP会员