Climate Dynamics

, Volume 50, Issue 11–12, pp 4037–4060 | Cite as

High-resolution projections of mean and extreme precipitations over China through PRECIS under RCPs

  • Jinxin Zhu
  • Gordon Huang
  • Xiuquan Wang
  • Guanhui Cheng
  • Yinghui Wu
Article

Abstract

The impact of global warming on the characteristics of mean and extreme precipitations over China is investigated by using the Providing REgional Climate Impacts for Studies (PRECIS) model. The PRECIS model was driven by the Hadley Centre Global Environment Model version 2 with Earth System components and coupling (HadGEM2-ES). The results of both models are analyzed in terms of mean precipitation and indices of precipitation extremes (R95p, R99p, SDII, WDF, and CWD) over China at the resolution of 25 km under the Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5) scenarios for the baseline period (1976–2005) and two future periods (2036–2065 and 2070–2099). With improved resolution, the PRECIS model is able to better represent the fine-scale physical process than HadGEM2-ES. It can provide reliable spatial patterns of precipitation and its related extremes with high correlations to observations. Moreover, there is a notable improvement in temporal patterns simulation through the PRECIS model. The PRECIS model better reproduces the regional annual cycle and frequencies of daily precipitation intensity than its driving GCM. Under RCP4.5 and RCP8.5, both the HadGEM2-ES and the precis project increasing annual precipitation over the entire country for two future periods. Precipitation increase in winter is greater than the increase in summer. The results suggest that increased radiative forcing from RCP4.5 to RCP8.5 would further intensify the magnitude of projected precipitation changes by both PRECIS and HadGEM2-ES. For example, some parts of south China with decreased precipitation under RCP4.5 would expect even less precipitation under RCP8.5; regions (northwest, northcentral and northeast China) with increased precipitation under RCP4.5 would expect more precipitation under RCP8.5. Apart from the projected increase in annual total precipitation, the results also suggest that there will be an increase in the days with precipitation higher than 15 mm and a decrease in the days with precipitation less than 5 mm. Under both RCPs, there would be an increasing trend in the magnitude of changes in precipitation extremes indices (R95p, R99p, and SDII) over China, while an opposite trend is projected for CWD and no apparent trend is projected for WDF from 2036–2065 to 2070–2099. Increased extreme precipitation amounts accompanied with decreased frequencies of extreme precipitation suggest that the future daily extreme precipitation intensity is likely to become large in northeast China and south China.

Keywords

Precipitation and extremes Dynamical downscaling PRECIS China RCP4.5 and RCP8.5 

References

  1. Bao J, Feng J, Wang Y (2015) Dynamical downscaling simulation and future projection of precipitation over China. J Geophys Res Atmos 120:8227–8243. doi: 10.1002/2015JD023275 CrossRefGoogle Scholar
  2. Bucchignani E, Montesarchio M, Cattaneo L, Manzi MP, Mercogliano P (2014), Regional climate modeling over China with COSMO-CLM: performance assessment and climate projections. J Geophys Res Atmos 119:12151–12170. doi: 10.1002/2014JD022219 CrossRefGoogle Scholar
  3. Chen L, Frauenfeld OW (2014) A comprehensive evaluation of precipitation simulations over China based on CMIP5 multimodel ensemble projections. J Geophys Res Atmos 119:5767–5786. doi: 10.1002/2013JD021190 CrossRefGoogle Scholar
  4. Chen H, Sun J (2009) How the “best” models project the future precipitation change in China. Adv Atmos Sci 26(4):773–782. doi: 10.1007/s00376-009-8211-7 CrossRefGoogle Scholar
  5. Chou C, Lan C (2012) Changes in the annual range of precipitation under global warming. J Clim 25:222–235. doi: 10.1175/JCLI-D-11-00097.1 CrossRefGoogle Scholar
  6. Christensen JH et al (2007) Regional climate projections, in climate change 2007: the physical science basis. In: Solomon S et al (eds) Contribution of working group i to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 847–940Google Scholar
  7. Colette A, Vautard R, Vrac M (2012) Regional climate downscaling with prior statistical correction of the global climate forcing. Geophys Res Lett 39:L13707. doi: 10.1029/2012GL052258 CrossRefGoogle Scholar
  8. Collins WJ, Bellouin N, Doutriaux-Boucher M, Gedney N, Hinton T, Jones CD, Liddicoat S, Martin G, O’Connor F, Rae J, Senior C, Totterdell I, Woodward S, Reichler T, Kim J (2008), Evaluation of the HadGEM2 model. Met Office Hadley Centre Technical Note no. HCTN 74, available from Met Office, FitzRoy Road, Exeter EX1 3 PB. http://www.metoffice.gov.uk/publications/HCTN/index.html. Accessed 24 Oct 2016
  9. Dong L, Zhou T, Chen X (2014) Changes of Pacific decadal variability in the twentieth century driven by internal variability, greenhouse gases, and aerosols. Geophys Res Lett 41:8570–8577. doi: 10.1002/2014GL062269 CrossRefGoogle Scholar
  10. Dunne JP et al (2012) GFDL’s ESM2 global coupled climate–carbon Earth system models. Part I: Physical formulation and baseline simulation characteristics. J Clim 25:6646–6665. doi: 10.1175/JCLI-D-11-00560.1 CrossRefGoogle Scholar
  11. Ehret U, Zehe E, Wulfmeyer V, Warrach-Sagi K, Liebert J (2012) HESS Opinions “Should we apply bias correction to global and regional climate model data? Hydrol Earth Syst Sci 16:3391–3404. doi: 10.5194/hess-16-3391-2012 CrossRefGoogle Scholar
  12. Feng L, Zhou T, Wu B, Li T, Luo J (2011) Projection of future precipitation changes over China with a high-resolution global atmospheric model. Adv Atmos Sci 28(2):464–476. doi: 10.1007/s00376-010-0016-1 CrossRefGoogle Scholar
  13. Feng J, Wang Y, Ma Z, Liu Y (2012) Simulating the regional impacts of urbanization and anthropogenic heat release on climate across China. J Clim 25(20):7187–7203. doi: 10.1175/JCLI-D-11-00333.1 CrossRefGoogle Scholar
  14. Flato G et al (2013) Evaluation of climate models. In: Stocker TF et al (eds) Climate change 2013: the physical science basis. contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 741–866Google Scholar
  15. Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Klein Tank AMG, Peterson T (2002) Observed coherent changes in climatic extremes during the second half of the twentieth Century. Clim Res 19:193–212CrossRefGoogle Scholar
  16. Gao X, Zhao Z, Ding Y, Huang R, Giorgi F (2001) Climate change due to greenhouse effects in China as simulated by a regional climate model. Adv Atmos Sci 18:1224–1230. doi: 10.1007/s00376-001-0036-y CrossRefGoogle Scholar
  17. Gao X, Shi Y, Song R, Giorgi F, Wang Y, Zhang D (2008) Reduction of future monsoon precipitation over China: comparison between a high-resolution RCM simulation and the driving GCM. Meteorol Atmos Phys 100:73–86. doi: 10.1007/s00703-008-0296-5 CrossRefGoogle Scholar
  18. Gao X, Shi Y, Giorgi F (2011) A high resolution simulation of climate change over China. Sci China Earth Sci 54(3):462–472. doi: 10.1007/s11430-010-4035-7 CrossRefGoogle Scholar
  19. Gao X, Shi Y, Zhang D, Wu J, Giorgi F, Ji Z, Wang Y (2012) Uncertainties in monsoon precipitation projections over China: results from two high-resolution RCM simulations. Clim Res 52:213–226. doi: 10.3354/cr01084 CrossRefGoogle Scholar
  20. Gao X-J, Wang M-L, Giorgi F (2013) Climate change over China in the 21st century as simulated by BCC_CSM1.1-RegCM4.0. Atmos Ocean Sci Lett 6(5):381–386. doi:  10.3878/j.issn.1674-2834.13.0029 CrossRefGoogle Scholar
  21. Giorgi F (2006) Regional climate modeling: status and perspectives. J Phys IV 139:101–118. doi: 10.1051/jp4:2006139008 Google Scholar
  22. Giorgi F, Mearns LO (1991) Approaches to the simulation of regional climate change: A review. Rev Geophys 29:191–216. doi: 10.1029/90RG02636 CrossRefGoogle Scholar
  23. Giorgi F, Jones J, Asrar GR (2009) Addressing climate information needs at the regional level: the CORDEX framework. WMO Bull 58(3):175–183Google Scholar
  24. Gong H, Wang L, Chen W, Wu R, Wei K, Cui X (2014) The climatology and interannual variability of the East Asian winter monsoon in CMIP5 models. J Clim 27(4):1659–1678. doi: 10.1175/JCLI-D-13-00039.1 CrossRefGoogle Scholar
  25. Guo J, Huang G, Wang X, Li Y, Lin Q (2017) Investigating future precipitation changes over China through a high-resolution regional climate model ensemble. Earth’s Future 5:285–303. doi: 10.1002/2016EF000433 CrossRefGoogle Scholar
  26. Hartmann DL et al (2013) Observations: atmosphere and surface, in climate change 2013: the physical science basis. In: Stocker TF et al (eds) Contribution of working group i to the fifth assessment report of the intergovernmental panel on climate change. Cambridge Univ. Press, Cambridge, pp 159–254Google Scholar
  27. Held IM, Soden BJ (2006) Robust responses of the hydrological cycle to global warming. J Clim 19:5686–5699. doi: 10.1175/JCLI3990.1 CrossRefGoogle Scholar
  28. Hewitson B, Janetos AC, Carter TR, Giorgi F, Jones RG, Kwon W-T, Mearns LO, Schipper ELF, van Aalst M (2014), Regional context, in climate change 2014: impacts, adaptation, and vulnerability. Part B: regional aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change, In: Barros VR et al (eds) Climate change 2014: impacts, adaptation, and vulnerability. Cambridge University Press, Cambridge, pp 1133–1197Google Scholar
  29. Hirakuchi H, Giorgi F (1995), Multi-year present day and 2x CO2 simulations of monsoon-dominated climate over eastern Asia and Japan with a regional climate model nested in a general circulation model. J Geophys Res. 100:21105–21,125. doi: 10.1029/95JD01885 CrossRefGoogle Scholar
  30. Hori ME, Ueda H (2006) Impact of global warming on the East Asian winter monsoon as revealed by nine coupled atmosphere–ocean GCMs. Geophys Res Lett 33:L03713. doi: 10.1029/2005GL024961 Google Scholar
  31. Huang DQ, Zhu J, Zhang YC, Huang AN (2013) Uncertainties on the simulated summer precipitation over eastern China from the CMIP5 models. J Geophys Res Atmos 118:9035–9047. doi: 10.1002/jgrd.50695 CrossRefGoogle Scholar
  32. Ji Z, Kang S (2015) Evaluation of extreme climate events using a regional climate model for China. Int J Climatol 35:888–902. doi: 10.1002/joc.4024 CrossRefGoogle Scholar
  33. Jiang L, Yan Y, Hararuk O, Mikle N, Xia J, Shi Z, Tjiputra J, Wu T, Luo Y (2015) Scale-dependent performance of CMIP5 earth system models in simulating terrestrial vegetation carbon. J Clim 28:5217–5232. doi:  10.1175/JCLI-D-14-00270.1 CrossRefGoogle Scholar
  34. Jones RG, Noguer M, Hassell DC, Hudson D, Wilson SS, Jenkins GJ, Mitchell JFB (2004) Generating high resolution climate change scenarios using PRECIS. Met Office Hadley Centre, Exeter (40 pp, April 2004)Google Scholar
  35. Karl TR, Knight RW, Plummer N (1995) Trends in high-frequency climate variability in the twentieth century. Nature 377:217–220. doi: 10.1038/377217a0 CrossRefGoogle Scholar
  36. Kitoh A, Hirokazu E (2016), Changes in precipitation extremes projected by a 20-km mesh global atmospheric model. Weather Clim Extremes. doi: 10.1016/.j.wace.2015.09.001 Google Scholar
  37. Kitoh A, Endo H, Krishna Kumar K, Cavalcanti IFA, Goswami P, Zhou T (2013) Monsoons in a changing world: a regional perspective in a global context. J Geophys Res Atmos 118:3053–3065. doi: 10.1002/jgrd.50258 CrossRefGoogle Scholar
  38. Lee JW, Hong SY, Chang EC, Suh MS, Kang HS (2014) Assessment of future climate change over East Asia due to the RCP scenarios downscaled by GRIMs-RMP. Clim Dyn 42(3–4):733–747. doi: 10.1007/s00382-013-1841-6 CrossRefGoogle Scholar
  39. Lenderink G, Meijgaard E (2009) Reply to: unexpected rise in extreme precipitation caused by a shift in rain type? Nat Geosci 2:373. doi: 10.1038/ngeo524 CrossRefGoogle Scholar
  40. Li C, Yanai M (1996) The onset and interannual variability of the Asian summer monsoon in relation to land-sea thermal contrast. J Clim 9:358–375. doi: 10.1175/1520-0442(1996)009<0358:TOAIVO>2.0.CO;2 CrossRefGoogle Scholar
  41. Li S, Lu J, Huang G, Hu K (2008) Tropical Indian Ocean basin warming and East Asian summer monsoon: a multiple AGCM study. J Clim 21:6080–6088. doi:  10.1175/2008JCLI2433.1 CrossRefGoogle Scholar
  42. Li H, Feng L, Zhou T (2011a) Multi-model projection of July–August climate extreme changes over China under CO2 doubling. Part I: Precipitation. Adv Atmos Sci 28(2):433–447. doi: 10.1007/s00376-010-0013-4 CrossRefGoogle Scholar
  43. Li HM, Feng L, Zhou TJ (2011b) Multi-model projection of July–August climate extreme changes over China under CO2 doubling. Part II: Temperature. Adv Atmos Sci 28(2):448–463. doi:  10.1007/s00376-010-0052-x CrossRefGoogle Scholar
  44. Li Z, Lau WK-M, Ramanathan V, Wu G, Ding Y, Manoj MG, Liu J, Qian Y, Li J, Zhou T, Fan J, Rosenfeld D, Ming Y, Wang Y, Huang J, Wang B, Xu X, Lee S-S, Cribb M, Zhang F, Yang X, Zhao C, Takemura T, Wang K, Xia X, Yin Y, Zhang H, Guo J, Zhai PM, Sugimoto N, Babu SS, Brasseur GP (2017) Aerosol and monsoon climate interactions over Asia. Rev Geophys 54:866–929. doi: 10.1002/2015RG00050 CrossRefGoogle Scholar
  45. Liang XZ, Kunkel KE, Meehl GA, Jones RG, Wang JX (2008) Regional climate models downscaling analysis of general circulation models present climate biases propagation into future change projections. Geophys Res Lett 35:L08709. doi: 10.1029/2007GL032849 CrossRefGoogle Scholar
  46. Liu S, Gao W, Liang XZ (2013) A regional climate model downscaling projection of China future climate change. Clim Dyn 41(7–8):1871–1884. doi: 10.1007/s00382-012-1632-5 CrossRefGoogle Scholar
  47. Luo L, Tang W, Lin Z et al (2013) Evaluation of summer temperature and precipitation predictions from NCEP CFSv2 retrospective forecast over China. Clim Dyn 41:2213–2230. doi: 10.1007/s00382-013-1927-1 CrossRefGoogle Scholar
  48. Ma S, Zhou T, Dai A, Han Z (2015) Observed changes in the distributions of daily precipitation frequency and amount over China from 1960 to 2013. J Clim 28:6960–6978. doi:  10.1175/JCLI-D-15-0011.1 CrossRefGoogle Scholar
  49. Ma S, Zhou T, Stone DA, Polson D, Dai A, Stott PA, von Storch H, Qian Y, Burke C, Wu P, Zou L, Ciavarella A (2017) Detectable anthropogenic shift toward heavy precipitation over Eastern China. J Clim 30:1381–1396. doi:  10.1175/JCLI-D-16-0311.1 CrossRefGoogle Scholar
  50. MACA (2017) MACA Downscaling of CMIP5 GCMs, multivariate adaptive constructed analogs (MACA) datasets. http://maca.northwestknowledge.net/GCMs.php. Accessed 14 May 2017
  51. Martin GM, Bellouin N, Collins WJ et al (2011) The HadGEM2 family of met office unified model climate configurations. Geosci Model Dev 4(3):723–757. doi: 10.5194/gmd-4-723-2011 CrossRefGoogle Scholar
  52. Meehl GA et al (2007) Global climate projections. in climate change 2007: the physical science basis. In: Solomon S et al (eds) Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 747–845Google Scholar
  53. Moss RH et al (2010) The next generation of scenarios for climate change research and assessment. Nature 463(7282):747–756. doi: 10.1038/nature08823 CrossRefGoogle Scholar
  54. Mulcahy JP, Walters DN, Bellouin N, Milton SF (2014) Impacts of increasing the aerosol complexity in the met office global numerical weather prediction model. Atmos Chem Phys 14:4749–4778. doi: 10.5194/acp-14-4749-2014 CrossRefGoogle Scholar
  55. Piao S, Ciais P, Huang Y et al (2010) The impacts of climate change on water resources and agriculture in China. Nature 467:43–51. doi: 10.1038/nature09364 CrossRefGoogle Scholar
  56. Racherla PN, Shindell DT, Faluvegi GS (2012) The added value to global model projections of climate change by dynamical downscaling: a case study over the continental US using the GISS-ModelE2 and WRF models. J Geophys Res 117:D20118. doi: 10.1029/2012JD018091 CrossRefGoogle Scholar
  57. Rupp DE, Abatzoglou JT, Hegewisch KC, Mote PW (2013), Evaluation of CMIP5 20th century climate simulations for the Pacific Northwest USA., J Geophys Res Atmos 118:10884–10906. doi: 10.1002/jgrd.50843 CrossRefGoogle Scholar
  58. Sato T, Xue Y (2013) Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability. Clim Dyn 41:2411–2426. doi: 10.1007/s00382-012-1616-5 CrossRefGoogle Scholar
  59. Seager R et al (2007) Model projections of an imminent transition to a more arid climate in southwestern North America. Science 316(5828):1181–1184. doi: 10.1126/science.1139601 CrossRefGoogle Scholar
  60. Sperber KR, Annamalai H, Kang IS, Kitoh A, Moise A, Turner A, Wang B, Zhou T (2013) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn 41(9–10):2711–2744. doi: 10.1007/s00382-012-1607-6 CrossRefGoogle Scholar
  61. Sun J, Ao J (2013) Changes in precipitation and extreme precipitation in a warming environment in China. J China Sci Bull 58:1395. doi: 10.1007/s11434-012-5542-z CrossRefGoogle Scholar
  62. Sun Y, Solomon S, Dai A, Portmann RW (2007) How often will it rain? J Clim 20:4801–4818. doi: 10.1175/JCLI4263.1 CrossRefGoogle Scholar
  63. Sun Q, Miao C, Duan Q (2015) Comparative analysis of CMIP3 and CMIP5 global climate models for simulating the daily mean, maximum, and minimum temperatures and daily precipitation over China. J Geophys Res Atmos 120:4806–4824. doi:  10.1002/2014JD022994 CrossRefGoogle Scholar
  64. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106:7183–7192. doi: 10.1029/2000JD900719 CrossRefGoogle Scholar
  65. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. doi: 10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  66. Trenberth KE, Shea DJ (2005) Relationships between precipitation and surface temperature. Geophys Res Lett 32:L14703. doi: 10.1029/2005GL022760 CrossRefGoogle Scholar
  67. Ueda H, Iwai A, Kuwano K, Hori ME (2006) Impact of anthropogenic forcing on the Asian summer monsoon as simulated by eight GCMs. Geophys Res Lett 33:L06703. doi: 10.1029/2005GL025336 CrossRefGoogle Scholar
  68. Van Vuuren DP et al (2011) The representative concentration pathways: An overview. Clim Change 109:5–31. doi: 10.1007/s10584-011-0148-z CrossRefGoogle Scholar
  69. Vautard R, Yiou P, D’Andrea F, de Noblet N, Viovy N, Cassou C, Polcher J, Ciais P, Kageyama M, Fan Y (2007), Summertime European heat and drought waves induced by wintertime Mediterranean rainfall deficit. Geophys Res Lett 34:L07711. doi: 10.1029/2006GL028001 CrossRefGoogle Scholar
  70. Wang HJ, He SP (2012) Weakening relationship between East Asian winter monsoon and ENSO after mid-1970s. China Sci Bull 57:3535–3540. doi: 10.1007/s11434-012-5285-x CrossRefGoogle Scholar
  71. Wang XQ, Huang GH, Lin QG, Nie XH, Cheng GH, Fan YR, Li Z, Yao Y, Suo MQ (2013) A stepwise cluster analysis approach for downscaled climate projection—a Canadian case study. Environ Model Softw 49:141–151. doi:  10.1016/j.envsoft.2013.08.006 CrossRefGoogle Scholar
  72. Wang XQ, Huang GH, Liu JL (2014) Projected increases in near-surface air temperature over Ontario, Canada: a regional climate modeling approach. Clim Dyn. doi:  10.1007/s00382-014-2387-y Google Scholar
  73. Wang XQ, Huang GH, Lin Q, Nie X, Liu JL (2015) High-resolution temperature and precipitation projections over Ontario, Canada: a coupled dynamical-statistical approach. QJR Meteorol Soc 141:1137–1146. doi: 10.1002/qj.2421 CrossRefGoogle Scholar
  74. Wang X, Huang G, Liu J (2016), Twenty-first century probabilistic projections of precipitation over Ontario, Canada through a regional climate model ensemble. Clim Dyn 46:3979. doi: 10.1007/s00382-015-2816-6 CrossRefGoogle Scholar
  75. Wehner MF, Smith RL, Bala G, Duffy P (2010) The effect of horizontal resolution on simulation of very extreme US precipitation events in a global atmosphere model. Clim Dyn 34(2–3):241–247. doi: 10.1007/s00382-009-0656-y CrossRefGoogle Scholar
  76. White CJ, McInnes KL, Cechet RP, Corney SP, Grose MR, Holz GK, Katzfey JJ, Bindoff NL (2013) On regional dynamical downscaling for the assessment and projection of temperature and precipitation extremes across Tasmania. Aust Clim Dyn 41(11–12):3145–3165. doi: 10.1007/s00382-013-1718-8 CrossRefGoogle Scholar
  77. Wilson W, Hassell D, Hein D, Wang C, Tucker S, Jones R, Taylor R (2015), Technical manual for PRECIS: the met office hadley centre regional climate modelling system version 2.0.0. http://www.metoffice.gov.uk/precis. Accessed 11 Sept 2016
  78. Wood AW, Lettenmaier DP, Palmer RN (1997) Assessing climate change implications for water resources planning. Clim Change 37(1):203–228CrossRefGoogle Scholar
  79. Wu G, Liu Y, He B, Bao Q, Duan A, Jin F-F (2012), Thermal controls on the Asian summer monsoon. Sci Rep 2:404. doi: 10.1038/srep00404 CrossRefGoogle Scholar
  80. Xu C-H, Xu Y (2012) The projection of temperature and precipitation over China under RCP scenarios using a CMIP5 multi-model ensemble, Atmos. Ocean Sci Lett 5:527–533Google Scholar
  81. Xu Y, Zhang Y, Lin E, Lin W, Dong W, Jones R, Hassell D, Wilson S (2006) Analyses on the climate change responses over China under SRES B2 scenario using PRECIS. Chin Sci Bull 51:2260–2267. doi: 10.1007/s11434-006-2099-8 CrossRefGoogle Scholar
  82. Xu Y, Gao XJ, Shen Y, Xu CH, Shi Y, Giorgi F (2009) A daily temperature dataset over China and its application in validating a RCM simulation. Adv Atmos Sci 26(4):763–772. doi: 10.1007/s00376-009-9029-z CrossRefGoogle Scholar
  83. Xu J, Shi Y, Gao X, Giorgi F (2013) Projected changes in climate extremes over China in the 21st century from a high resolution regional climate model (RegCM3). Chin Sci Bull 58:12, 1443–1452. doi: 10.1007/s11434-012-5548-6 CrossRefGoogle Scholar
  84. Xue Y, Janjic Z, Dudhia J, Vasic R, Sales FD (2014), A review on regional dynamical downscaling in inter-seasonal to seasonal simulation/prediction and major factors that affect downscaling ability. Atmos Res 147–148:68–85.doi:  10.1016/j.atmosres.2014.05.001 CrossRefGoogle Scholar
  85. Yan D, Werners SE, Ludwig F, Huang HQ (2015) Hydrological response to climate change: the pearl river, China under different RCP scenarios. J Hydrol 4(B):228–245.  10.1016/j.ejrh.2015.06.006 Google Scholar
  86. Yatagai A, Kamiguchi K, Arakawa O, Hamada A, Yasutomi N, Kitoh A (2012) APHRODITE: constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull Am Meteorol Soc. doi: 10.1175/BAMS-D-11-00122.1 Google Scholar
  87. Yu E-T, Wang H-J, Sun J-Q (2010) A quick report on a dynamical downscaling simulation over China using the nested model. Atmos Ocean Sci Lett 3:325–329CrossRefGoogle Scholar
  88. Yuan X, Liang X-Z, Wood EF (2012) WRF ensemble downscaling seasonal forecasts of China winter precipitation during 1982–2008 Clim Dyn 39(7–8):2041–2058. doi: 10.1007/s00382-011-1241-8 CrossRefGoogle Scholar
  89. Zhang H, Fraedrich K, Blender R, Zhu X (2013) Precipitation extremes in CMIP5 simulations on different time scales. J Hydrometeor 14:923–928. doi:  10.1175/JHM-D-12-0181.1 CrossRefGoogle Scholar
  90. Zhang X, Liu H, Zhang M (2015) Double ITCZ in coupled ocean–atmosphere models: from CMIP3 to CMIP5. Geophys Res Lett 42:8651–8659. doi: 10.1002/2015GL065973 CrossRefGoogle Scholar
  91. Zheng Z, Gao J, Ma Z, Wang Z, Yang X, Luo X, Jacquet T, Fu G (2016) Urban flooding in China: main causes and policy recommendations. Hydrol Process 30:1149–1152. doi:  10.1002/hyp.10717 CrossRefGoogle Scholar
  92. Zhou LT (2011) Impact of East Asian winter monsoon on rainfall over southeastern China and its dynamical process. Int J Climatol 31:677–686. doi: 10.1002/joc.2101 CrossRefGoogle Scholar
  93. Zhou B et al (2011) The great 2008 Chinese ice storm: its socioeconomic-ecological impact and sustainability lessons learned. Bull Am Meteorol Soc 92(1):47–60. doi:  10.1175/2010BAMS2857.1 CrossRefGoogle Scholar
  94. Zhou T, Song F, Lin R, Chen X, Chen X (2013) The 2012 North China floods: explaining an extreme rainfall event in the context of along-term drying tendency [in“Explaining Extreme Events of 2012 from a Climate Perspective”]. Bull Am Meteorol Soc 94(9):S49-S51Google Scholar
  95. Zhou B, Wen QH, Xu Y, Song L, Zhang X (2014) Projected changes in temperature and precipitation extremes in China by the CMIP5 multi-model ensembles. J Clim 27:6591–6611. doi:  10.1175/JCLI-D-13-00761.1 CrossRefGoogle Scholar
  96. Zou L, Zhou T (2013) Near future (2016–2040) summer precipitation changes over China as projected by a regional climate model (RCM) under the RCP8.5 emissions scenario: comparison between RCM downscaling and the driving GCM. Adv Atmos Sci 30(3):806–818. doi: 10.1007/s00376-013-2209-x CrossRefGoogle Scholar
  97. Zou L, Zhou T, Peng D (2016) Dynamical downscaling of historical climate over CORDEX East Asia domain: a comparison of regional ocean–atmosphere coupled model to stand-alone RCM simulations. J Geophys Res Atmos 121:1442–1458. doi: 10.1002/2015JD023912 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Jinxin Zhu
    • 1
  • Gordon Huang
    • 1
  • Xiuquan Wang
    • 1
  • Guanhui Cheng
    • 1
  • Yinghui Wu
    • 1
  1. 1.Institute for Energy, Environment and Sustainability ResearchUniversity of ReginaReginaCanada

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