Multi-model assessment of climate change impacts on drought characteristics

• Published in: NATURAL HAZARDS
• Main Authors: Dehghani, Adnan; Mortazavizadeh, Fatemehsadat; Dehghani, Amin; Rahmat, Muhammad Bin; Galavi, Hadi; Bolonio, David; Ng, Jing Lin; Rezaverdinejad, Vahid; Mirzaei, Majid
• Format: Article; Early Access
• Language: English
• Published: SPRINGER 2024
• Subjects: Geology; Meteorology & Atmospheric Sciences; Water Resources
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-recordWOS:001366126500001

The study of projected rainfall data across multiple future scenarios is a key factor in developing sustainable water resource management plans. This paper presents an analysis of projected rainfall series in the Sabah and Sarawak region, Malaysia, against the bias-corrected GCM simulated rainfall data. Three Shared Socioeconomic Pathways (SSP) of SSP126, SSP245, and SSP585 were used to retrieve rainfall simulations of three Global Climate Models (GCMs) of Access-CM2, HadGEM, and UKESM1. The SSPs provide different pathways through which they can affect the rainfall trend. This investigation helps to illustrate the complex interactions between socio-economic developments and climatic changes, underlining the need for adaptive strategies in regional planning. The GCM outputs were downscaled using the quantile-based bias correction method for the future projections. The annual and monthly rainfall data were divided into two periods of 2021-2055 and 2056-2090 for detailed analysis of the future rainfall in the study area. This division allows for a clearer understanding of short-term versus long-term climatic impacts. The non-parametric Mann-Kendall (MK) test and the Sen's Slope estimator were used to study the trend in the rainfall series. The rainfall data simulated using the Access-CM2 and the HadGEM showed a negative trend, while it was positive in the UKESM1 simulations. Generally, a positive trend in the projected rainfall series was observed. The rainfall series and the rainfall variability index (RVI) chart were plotted to compare the rainfall series of all the SSPs. The drought Severity-Duration-Frequency analysis for the return periods of 2-year, 5-years, 10-year, 20-year, and 50-year was also developed based on the RVI, to estimate the temporal trend of drought severity. These analyses are crucial for preparing effective drought management and mitigation strategies. Results demonstrated that as the drought duration increases its intensity and severity increases as well.