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High-Resolution Simulations for Vietnam - Methodology and Evaluation of Current Climate
Jack Katzfey,Kim Nguyen,John McGregor,Peter Hoffmann,Suppiah Ramasamy,Hiep Van Nguyen,Mai Van Khiem,Thang Van Nguyen,Kien Ba Truong,Thang Van Vu,Hien Thuan Nguyen,Tran Thuc,Doan Ha Phong,Bang Thanh Ng 한국기상학회 2016 Asia-Pacific Journal of Atmospheric Sciences Vol.52 No.2
To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (−60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.
Tang, Jianping,Li, Qian,Wang, Shuyu,Lee, Dong‐,Kyou,Hui, Pinhong,Niu, Xiaorui,Gutowski Jr., William J.,Dairaku, Koji,McGregor, John,Katzfey, Jack,Gao, Xuejie,Wu, Jia,Hong, Song‐,You,Wang, Wiley 2016 International journal of climatology Vol.36 No.13
<P><B>ABSTRACT</B></P><P>Under the Asia‐Pacific Network for Global Change (APN) project ‘Building Asian Climate Change Scenarios by Multi‐Regional Climate Models Ensemble’ (RMIP III, Regional Model Intercomparision Project), the simulation results of eight regional climate models (RCMs) and two fine‐resolution global climate models are validated for reproducibility of the current surface air temperature climatology (1981–2000), and are used to generate surface air future temperature projections (2041–2060) over the CORDEX‐EA (A Coordinated Regional climate Downscaling Experiment‐East Asia) domain. Four ensemble methods, namely, the equal weighting, the weighted mean, the reliability ensemble averaging, and the performance‐based ensemble averaging, are employed to generate the multi‐model projection of regional climate change over the region. The results show that the regional temperature ensembles of the present climate obtained from all four methods can outperform a single RCM result in aspects of the spatial distribution as well as the seasonal variation over East Asia. The four ensemble methods are then used to project the regional temperature climatology under the IPCC emission scenario of A1B for 2041–2060. Compared with the control climate of 1981–2000, the annual mean temperature of the future climate (2041–2060) increases 1–2 °C in low latitude areas and 2–3 °C in middle–high latitude areas over Asia.</P>
Li, Qian,Wang, Shuyu,Lee, Dong‐,Kyou,Tang, Jianping,Niu, Xiaorui,Hui, Pinhong,Gutowski Jr., William J.,Dairaku, Koji,McGregor, John L.,Katzfey, Jack,Gao, Xuejie,Wu, Jia,Hong, Song‐,You,Wan Wiley 2016 International journal of climatology Vol.36 No.13
<P><B>ABSTRACT</B></P><P>Under the framework of an project ‘Building Asian Climate Change Scenarios by Multi‐Regional Climate Models Ensemble’, the ability of eight regional climate models and two fine‐resolution global climate models to reproduce late 20th century (1981–2000) precipitation climatology is assessed. Future precipitation change (2041–2060) under the A1B scenario is also quantified by applying four different ensemble methods: equal weighting, weighted mean (WM), reliability ensemble averaging (REA) and performance‐based ensemble averaging, after applying fourfold cross‐validation using observation and multi‐model‐simulated precipitation. The results indicate that the ensemble of simulated precipitation outperforms any single RCM in many aspects. Among the four ensemble approaches, the WM and REA methods show better skill in improving the simulation results, and are used for ensemble prediction of regional climate in Asia. Under the A1B scenario, the WM method estimates future precipitation change of approximately 0.2 mm day<SUP>−1</SUP> with less precipitation in northern and western China and northern India, and more precipitation in most other areas in Asia. The future annual precipitation will decrease by 0.1‐0.5 mm day<SUP>−1</SUP> in northern India, Pakistan and the central area of southern China. No significant change is found over eastern Kazakhstan, Mongolia, north‐central and western China.</P>