Improved weather generator algorithm for multisite simulation of precipitation and temperature

TL;DR

This paper introduces KnnCAD Version 4, a nonparametric multisite weather generator that preserves temporal correlations and enhances extreme value simulation without relying on distributional assumptions.

Contribution

The paper presents an improved multisite weather generator algorithm that incorporates block resampling and perturbation techniques for better simulation of temperature and precipitation data.

Findings

Effectively simulates historical climate characteristics

Preserves temporal correlation in temperature data

Does not assume specific spatial or probability distributions

Abstract

The KnnCAD Version 4 weather generator algorithm for nonparametric, multisite simulations of temperature and precipitation data is presented. The K-nearest neighbour weather generator essentially reshuffles the historical data, with replacement. In KnnCAD Version 4, a block resampling scheme is introduced to preserve the temporal correlation structure in temperature data. Perturbation of the reshuffled variable data is also added to enhance the generation of extreme values. A case study of the Upper Thames River Basin in Ontario, Canada is performed and the model is shown to simulate effectively the historical characteristics at the site. The KnnCAD Version 4 approach offers a major advantage over parametric and semi-parametric weather generators as it can be applied to multiple sites for simulation of temperatures and precipitation amounts without making assumptions regarding the spatial correlations and the probability distributions for each variable.