Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/147843
Title: STATISTICAL MODELLING AND ANALYSIS FOR REGIONAL CLIMATE CHANGE
Authors: LI XIN
ORCID iD:   orcid.org/0000-0001-7205-7506
Keywords: Weather Generator, Statistical Downscaling, Rainfall Disaggregation, Wet and Dry Spells, Rainfall Extremes, Singapore
Issue Date: 22-May-2018
Citation: LI XIN (2018-05-22). STATISTICAL MODELLING AND ANALYSIS FOR REGIONAL CLIMATE CHANGE. ScholarBank@NUS Repository.
Abstract: General circulation models (GCMs) are often used to inform climate change information, however, due to their coarse spatial resolutions, downscaling approaches are often relied to transit the coarser-scale GCM outputs to higher resolutions. Multivariate multisite weather generators (MMWGs) are appealing tools, as they allow for simulations of multiple realizations of climate change scenarios consistent with local-scale weather characteristics as well as large-scale climate change signal informed by GCMs. This thesis developed a new MMWG which integrates a single WG with a post-processing technique to rebuild the observed inter-site, inter-variable correlations, and temporal structures in the simulations. The proposed MMWG was then adapted and extended to a multivariate multisite statistical downscaling (MMSD) approach for regional climate change study. Along with these statistical modeling approaches, observational investigation of the climate change signal in the gauge-based precipitation observations was also carried out. The proposed approaches could add value to modeling of regional climate change.
URI: http://scholarbank.nus.edu.sg/handle/10635/147843
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