Estimating multisite precipitation by a stepwise NHMM-VAR model considering the spatiotemporal correlations of precipitation amounts

Abstract

• This study developed a stepwise NHMM-VAR multisite downscaling model. • The NHMM-VAR model performs well not only in modeling the statistical properties but also in reproducing the spatiotemporal correlations of multisite precipitation amounts. • The temporal intermittency of precipitation amounts is considered in the NHMM-VAR model. The nonhomogeneous hidden Markov model (NHMM) is a popular statistical downscaling (SD) approach that can be used for multisite precipitation estimation. However, the NHMM assumes that once the days with the occurrence of precipitation have been determined, the precipitation amounts at each station on wet days can be conditionally independently generated from a parametric family of probability distribution functions without considering impacts from the past precipitation amounts and the neighboring stations. Such assumptions may lead to underestimation of the spatiotemporal correlations (i.e., temporal autocorrelation and spatial cross-correlations) of actual multisite precipitation amounts. Thus, this study developed a stepwise downscaling method called the nonhomogeneous hidden Markov model - vector autoregressive (NHMM-VAR), in which the NHMM is used to determine the probabilities for dry days and marginal distributions of multisite daily mean precipitation amounts on wet days based on the large-scale atmospheric covariates, then a VAR(1) model is used to reproduce the spatiotemporal correlations of actual multisite daily mean precipitation amounts. A comparison experiment between the NHMM and the NHMM-VAR models is conducted against outputs from eight global climate models (GCMs) of Phase 6 of the Coupled Model Intercomparison Project (CMIP6) over the Pearl River basin (PRB) of South China. The results show that the NHMM-VAR model performs well not only in modeling the statistical properties but also in reproducing the spatiotemporal correlations of actual multisite daily mean precipitation amounts, which indicates that the VAR model does add value to the NHMM downscaling method.