Abstract
Based on IPCC mid- and high-greenhouse gas emission scenarios, we have been performed by using a CMIP5 GCM ensemble to drive the high resolution of Regional Climate Model RegCM4.4, and this study has assessed the model ability for simulating extreme precipitation indices and analyzed possible future changes in 2071–2100 under the A2 emissions scenario. Results indicate that RegCM4.4 performs well in the simulation of extreme precipitation indices and RegCM4.4 model can better reproduce the spatial distribution of extreme precipitation in Xinjiang, but this model is less effective in the Tian Shan Mountains due to topography and altitude. Prediction results show the future precipitation extreme simulation of Xinjiang indicates a tendency that the drought in Xinjiang eases relatively, showing a spatial pattern that the precipitation is gradually reduced from the northwest, the southwest to the southeast; RegCM4.4 simulation results show that indices of rainy days (RR1),number of heavy precipitation days (R10mm), maximum 5-day precipitation (RX5day), very wet day precipitation (R95p), and rainstorm rate (R95pTOT) all show an increasing trend that is more obvious in winter. In Xinjiang, the increase in extreme precipitation would not be entirely beneficial. Too much extreme precipitation will not only challenge the carrying capacity of water conservancy facilities and increase the difficulties in managing water resource, but also induce the heavy precipitation-related disasters.
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Data availability
Daily precipitation data are mainly provided by China Meteorological Administration and its Xinjiang Meteorological Information Center, and the extreme precipitation index is obtained by rclimdex software (http://cccma.seos.uvic.ca/etccdmi/). The climate model CMIP5 and RegCM4.4 data are available for free download online.
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Acknowledgements
This study is jointly financed by the Natural Science Foundation of China Guangxi (2018GXNSFAA050009) and by the major scientific and technological projects of Xinjiang Production and Construction Corps (XPCC) (2018AA004). The authors gratefully acknowledge funding for this research and would like to thank the China meteorological administration and Xinjiang meteorological information center for providing this data and the Xinjiang meteorological information center for homogenizing the meteorological data. The authors would like to express their sincere thanks to Dr. Xue feng and Dr. Shen for the help with data. At the same time, the authors are grateful to the two anonymous reviewers and the editors for their constructive comments.
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Xiang-ling, T., Xin, L. & Yanwei, Z. Estimation of future extreme precipitation changes in Xinjiang based on RegCM4.4 simulations. Nat Hazards 102, 201–218 (2020). https://doi.org/10.1007/s11069-020-03920-1
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DOI: https://doi.org/10.1007/s11069-020-03920-1