This paper describes a methodology for constructing and simulating from models of daily weather time series at multiple locations, incorporating potential nonstationarities and suitable for use in those studies of climate impacts and adaptation where a detailed representation of local weather is required. The approach is based on generalised linear models (GLMs) and aims to allow for realistic representations of local weather structures including spatial, temporal and inter-variable dependencies. The theory is implemented in a software tool, Rglimclim, that runs in the R programming environment; and is illustrated using a case study involving generation of daily precipitation and temperature at 26 locations in northern Iberia.

本文介绍了一种从多个位置的每日天气时间序列模型构建和模拟的方法，该方法结合了潜在的非平稳性，适用于需要详细描述当地天气的气候影响和适应研究。该方法基于广义线性模型（GLM），旨在允许对本地天气结构的真实表示，包括空间，时间和变量间的依存关系。该理论是在R编程环境中运行的软件工具Rglimclim中实现的。并通过一个案例研究进行了说明，该案例涉及在伊比利亚北部的26个地点产生的每日降水量和温度。