Abstract
Future projections of anthropogenic climate change play a pivotal role in devising viable countermeasures to address climate-related risks. This study strove to construct future daily rainfall and maximum and minimum temperature scenarios in Vu Gia Thu Bon river basin by employing the Statistical DownScaling Model (SDSM). The model performance was evaluated by utilizing a Taylor diagram with dimensioned and dimensionless statistics. During validation, all model-performance measures show good ability in simulating extreme temperatures and reasonable ability for rainfall. Subsequently, a set of predictors derived from HadCM3 and CanESM2 was selected to generate ensembles of each climatic variables up to the end of 21st century. The generated outcomes exhibit a consistent increase in both extreme temperatures under all emission scenarios. The greatest changes in maximum and minimum temperature were predicted to increase by 2.67–3.9 °C and 1.24–1.96 °C between the 2080s and reference period for the worst-case scenarios. Conversely, there are several discrepancies in the projections of rainfall under different emission scenarios as well as among considered stations. The predicted outcomes indicate a significant decrease in rainfall by approximately 11.57%–17.68% at most stations by 2099. Moreover, all ensemble means were subjected to the overall and partial trend analysis by applying the Innovative-Şen trend analysis method. The results exhibit similar trend patterns, thereby indicating high stability and applicability of the SDSM. Generally, it is expected that these findings will contribute numerous valuable foundations to establish a framework for the assessment of climate change impacts at the river basin scale.
Highlights
There is high confidence that human activities are the main causes of the global warming of 1 ◦ C [0.8–1.2 ◦ C] above the pre-industrial levels, and this figure is likely to reach 1.5 ◦ C between2030 and 2052 [1]
During the 2080s, the worst-case scenarios (i.e., HadCM3 A2 and CanESM2 RCP8.5) are responsible for the greatest increase in Tmax and Tmin by 2.67–3.90 ◦ C and 1.24–1.96 ◦ C, which are significantly higher than the figures for the remaining scenarios varying approximately from 1.01–2.65 ◦ C and 0.38–1.01 ◦ C, respectively
The main aim of this study was to construct daily rainfall, maximum and minimum temperatures for the near, middle, and far-future periods over the Vu Gia Thu Bon (VGTB) river basin by employing Statistical DownScaling Model (SDSM) tool and a set of general circulation models (GCMs)-derived predictors retrieved from HadCM3 (A2 and B2) and CanESM2 (RCP2.6, 4.5, and 8.5)
Summary
There is high confidence that human activities are the main causes of the global warming of 1 ◦ C [0.8–1.2 ◦ C] above the pre-industrial levels, and this figure is likely to reach 1.5 ◦ C between2030 and 2052 [1]. There is high confidence that human activities are the main causes of the global warming of 1 ◦ C [0.8–1.2 ◦ C] above the pre-industrial levels, and this figure is likely to reach 1.5 ◦ C between. Based on a comparison between 1.5◦ C and 4◦ C warming, it is evident that the global average chance of major heatwave, agricultural drought, and 50-year return period river flood. Utilized various indicators representing heat extremes, water resources, river and coastal flooding, droughts, agriculture, and energy use to estimate the potential impacts of climate change under different levels of climate forcings and socio-economic scenarios. This study indicated that precipitation extremes in China are likely to be more severe, and highlighted the usefulness of employing large ensemble high-resolution climate simulations to address future uncertainties
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