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Volume 22, issue 5 | Copyright
Hydrol. Earth Syst. Sci., 22, 3087-3103, 2018
https://doi.org/10.5194/hess-22-3087-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 30 May 2018

Research article | 30 May 2018

High-resolution ensemble projections and uncertainty assessment of regional climate change over China in CORDEX East Asia

Huanghe Gu1,2, Zhongbo Yu1,2, Chuanguo Yang1,2, Qin Ju1,2, Tao Yang1,2, and Dawei Zhang3 Huanghe Gu et al.
  • 1State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China
  • 2College of Hydrology and Water Resources, Hohai University, Nanjing, China
  • 3China Institute of Water Resources and Hydropower Research, Beijing, China

Abstract. An ensemble simulation of five regional climate models (RCMs) from the coordinated regional downscaling experiment in East Asia is evaluated and used to project future regional climate change in China. The influences of model uncertainty and internal variability on projections are also identified. The RCMs simulate the historical (1980–2005) climate and future (2006–2049) climate projections under the Representative Concentration Pathway (RCP) RCP4.5 scenario. The simulations for five subregions in China, including northeastern China, northern China, southern China, northwestern China, and the Tibetan Plateau, are highlighted in this study. Results show that (1) RCMs can capture the climatology, annual cycle, and interannual variability of temperature and precipitation and that a multi-model ensemble (MME) outperforms that of an individual RCM. The added values for RCMs are confirmed by comparing the performance of RCMs and global climate models (GCMs) in reproducing annual and seasonal mean precipitation and temperature during the historical period. (2) For future (2030–2049) climate, the MME indicates consistent warming trends at around 1°C in the entire domain and projects pronounced warming in northern and western China. The annual precipitation is likely to increase in most of the simulation region, except for the Tibetan Plateau. (3) Generally, the future projected change in annual and seasonal mean temperature by RCMs is nearly consistent with the results from the driving GCM. However, changes in annual and seasonal mean precipitation exhibit significant inter-RCM differences and possess a larger magnitude and variability than the driving GCM. Even opposite signals for projected changes in average precipitation between the MME and the driving GCM are shown over southern China, northeastern China, and the Tibetan Plateau. (4) The uncertainty in projected mean temperature mainly arises from the internal variability over northern and southern China and the model uncertainty over the other three subregions. For the projected mean precipitation, the dominant uncertainty source is the internal variability over most regions, except for the Tibetan Plateau, where the model uncertainty reaches up to 60%. Moreover, the model uncertainty increases with prediction lead time across all subregions.

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An ensemble simulation of five RCMs from CORDEX in East Asia was evaluated and used for future regional climate change projection in China. In addition, the contributions of model uncertainty and internal variability are identified. We found that the multi-model ensemble outperforms the individual RCMs in historical climate simulation. The future climate projections show significant inter-RCM differences and the model uncertainty increases with prediction lead time over all subregions.
An ensemble simulation of five RCMs from CORDEX in East Asia was evaluated and used for future...
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