Challenges in constructing a high-resolution, multi-site, and multivariate weather generator and potential solutions

A reliable simulation of the spatiotemporal characteristics of the meteorological field is of great significance for hydrological impact studies. To approach this target, a number of weather generators (WGs) have been developed over the past few decades. However, a detailed literature review shows that currently developed WGs are subject to one or several aspects of the following limitations: (1) low spatial and temporal resolutions to describe the real spatiotemporal dynamics of meteorological processes; 2) incapability to simulate a spatially coherent, temporally consistent, and physically meaningful meteorological field; and 3) inability to extend into the future in a climate change context. To tackle these problems, this study proposes some potential solutions: (1) using the multi-site multivariate WGs (MMWGs) to simulate the spatial, temporal, and inter-variable dependencies in the meteorological field; (2) coupling the MMWGs with the resampling-based algorithms to generate high-resolution spatiotemporal meteorological data; and (3) perturbing the parameters of the distribution and dependency models based on the future climate projection. A case study is carried out and shows that the proposed solutions are effective in addressing the aforementioned challenges. These findings could assist in developing high-resolution MMWGs for weather simulation and impact assessment.