水力发电学报2025，Vol.44Issue(4)：85-96,12.DOI:10.11660/slfdxb.20250409
多站点多变量天气发生器:日降水与气温随机模拟
Multisite multivariate weather generator:stochastic simulations of daily precipitation and air temperature
摘要
Abstract
Developing a stochastic hydrometeorological field with spatiotemporal correlations and a clear physical coherence is critical for hydrological simulations.This study uses a coupled model of multivariate first-order autoregressive(MAR1)model,a first-order Markov chain,and a K-nearest neighbors(KNN)to develop a multisite,multivariate weather generator that can reflect spatiotemporal dependencies,inter-variable correlations,and low-frequency interannual oscillations inherent in hydrometeorological processes.We have applied this generator to the random simulations of daily precipitation and maximum and minimum air temperatures across 12 secondary water resource divisions in the Yangtze River basin,and achieved physically meaningful meteorological fields that are characterized by temporal and spatial correlations.The model is evaluated comprehensively using several metrics,such as basic statistical characteristics,correlation features,and interannual variability.The results demonstrate the multisite,multivariate weather generator effectively reconstructs a range of characteristic indicators of the observed meteorological fields.However,it does show certain underestimated durations of the maximum drought and wet periods at a few gauge stations,and similar errors in the first-order autocorrelation coefficients for daily maximum and minimum air temperatures.The findings of this study provide valuable insights for distributed stochastic hydrological simulations.关键词
多站点多变量随机天气发生器/空间相关性/变量间相关性/年际变化特性/长江流域Key words
multisite multivariate weather generator/spatial correlation/inter-variable correlation/inter-annual variability/Yangtze River basin分类
地球科学引用本文复制引用
李新,刘玲,周义斌,陈元芳..多站点多变量天气发生器:日降水与气温随机模拟[J].水力发电学报,2025,44(4):85-96,12.基金项目
国家"十四五"重点研发项目(2023YFC3006500) （2023YFC3006500）
中央高校基本科研业务费(B240203007) （B240203007）
