• Annan, J. D., D. J. Lunt, J. C. Hargreaves, and P. J. Valdes, 2005: Parameter estimation in an atmospheric GCM using the ensemble Kalman filter. Nonlinear Processes Geophys., 12, 363371, doi:10.5194/npg-12-363-2005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bao, X., and F. Zhang, 2013: Evaluation of NCEP–CFSR, NCEP–NCAR, ERA-Interim, and ERA-40 reanalysis datasets against independent sounding observations over the Tibetan Plateau. J. Climate, 26, 206214, doi:10.1175/JCLI-D-12-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barnett, T. P., J. C. Adam, and D. P. Lettenmaier, 2005: Potential impacts of a warming climate on water availability in snow-dominated regions. Nature, 438, 303309, doi:10.1038/nature04141.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Betts, A. K., M. Köhler, and Y. Zhang, 2009: Comparison of river basin hydrometeorology in ERA‐Interim and ERA‐40 reanalyses with observations. J. Geophys. Res., 114, doi:10.1029/2008JD010761.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, H., S. Shi, and J. Zhou, 2011: Evaluation of recent 50 years extreme climate events over China simulated by Beijing Climate Center (BCC) climate model. Trans. Atmos. Sci., 34, 513528.

    • Search Google Scholar
    • Export Citation
  • Chen, H., J. Sun, X. Chen, and W. Zhou, 2012: CGCM projections of heavy rainfall events in China. Int. J. Climatol., 32, 441450, doi:10.1002/joc.2278.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, L., and O. W. Frauenfeld, 2014: Surface air temperature changes over the twentieth and twenty-first centuries in China simulated by 20 CMIP5 models. J. Climate, 27, 39203937, doi:10.1175/JCLI-D-13-00465.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, W., L. H. Kang, and D. Wang, 2006: The coupling relationship between summer rainfall in China and global sea surface temperature. Climatic Environ. Res., 11, 259269.

    • Search Google Scholar
    • Export Citation
  • Cubasch, U., and Coauthors, 2001: Projections of future climate change. Climate Change 2001: The Scientific Basis, J. T. Houghton et al., Eds., Cambridge University Press, 526–582.

  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Y., G. Ren, Z. Zhao, Y. Xu, Y. Luo, Q. Li, and J. Zhang, 2007: Detection, causes and projection of climate change over China: An overview of recent progress. Adv. Atmos. Sci., 24, 954971, doi:10.1007/s00376-007-0954-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gao, J., V. Masson-Delmotte, T. Yao, L. Tian, C. Risi, and G. Hoffmann, 2011: Precipitation water stable isotopes in the south Tibetan Plateau: Observations and modeling. J. Climate, 24, 31613178, doi:10.1175/2010JCLI3736.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gao, X., Z. Zhao, and G. Filippo, 2002: Changes of extreme events in regional climate simulations over East Asia. Adv. Atmos. Sci., 19, 927942, doi:10.1007/s00376-002-0056-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gong, H., L. Wang, W. Chen, R. Wu, K. Wei, and X. Cui, 2014: The climatology and interannual variability of the East Asian winter monsoon in CMIP5 models. J. Climate, 27, 16591678, doi:10.1175/JCLI-D-13-00039.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gong, H., L. Wang, W. Chen, D. Nath, G. Huang, and W. Tao, 2015: Diverse influences of ENSO on the East Asian–western Pacific winter climate tied to different ENSO properties in CMIP5 models. J. Climate, 28, 21872202, doi:10.1175/JCLI-D-14-00405.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gu, H., G. Wang, Z. Yu, and R. Mei, 2012: Assessing future climate changes and extreme indicators in East and South Asia using the RegCM4 regional climate model. Climatic Change, 114, 301317, doi:10.1007/s10584-012-0411-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gu, H., Z. Yu, J. Wang, G. Wang, Q. Ju, C. Yang, and C. Fan, 2014: Climate change hotspots identification in China through the CMIP5 global climate model ensemble. Adv. Meteor., 2014, 963196, doi:10.1155/2014/963196.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gu, H., Z. Yu, J. Wang, G. Wang, T. Yang, Q. Ju, and C. Fan, 2015: Assessing CMIP5 general circulation model simulations of precipitation and temperature over China. Int. J. Climatol., 35, 24312440, doi:10.1002/joc.4152.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gu, W., C. Li, X. Wang, W. Zhou, and W. Li, 2009: Linkage between mei-yu precipitation and North Atlantic SST on the decadal timescale. Adv. Atmos. Sci., 26, 101108, doi:10.1007/s00376-009-0101-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guo, Y., W.-J. Dong, F.-M. Ren, Z.-C. Zhao, and J.-B. Huang, 2013: Surface air temperature simulations over China with CMIP5 and CMIP3. Adv. Climate Change Res., 4, 145152, doi:10.3724/SP.J.1248.2013.145.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hodges, K. I., R. W. Lee, and L. Bengtsson, 2011: A comparison of extratropical cyclones in recent reanalyses ERA-Interim, NASA MERRA, NCEP CFSR, and JRA-25. J. Climate, 24, 48884906, doi:10.1175/2011JCLI4097.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, Z.-Z., S. Yang, and R. Wu, 2003: Long‐term climate variations in China and global warming signals. J. Geophys. Res., 108, 4614, doi:10.1029/2003JD003651.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, R., J. Chen, L. Wang, and Z. Lin, 2012: Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system. Adv. Atmos. Sci., 29, 910942, doi:10.1007/s00376-012-2015-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ji, Z., and S. Kang, 2013: Double-nested dynamical downscaling experiments over the Tibetan Plateau and their projection of climate change under two RCP scenarios. J. Atmos. Sci., 70, 12781290, doi:10.1175/JAS-D-12-0155.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ji, Z., and S. Kang, 2015: Evaluation of extreme climate events using a regional climate model for China. Int. J. Climatol., 35, 888902, doi:10.1002/joc.4024.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, D.-B., H. J. Wang, and X. M. Lang, 2004: Multimodel ensemble prediction for climate change trend of China under SRES A2 scenario. Chin. J. Geophys., 47, 878886, doi:10.1002/cjg2.564.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, D.-B., Z. Tian, and X. Lang, 2015: Reliability of climate models for China through the IPCC Third to Fifth Assessment Reports. Int. J. Climatol., 36, 11141133, doi:10.1002/joc.4406.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, Z., J. Song, L. Li, W. Chen, Z. Wang, and J. Wang, 2012: Extreme climate events in China: IPCC-AR4 model evaluation and projection. Climatic Change, 110, 385401, doi:10.1007/s10584-011-0090-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klein, S. A., and D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 15871606, doi:10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuo, Y. H., L. Cheng, and R. A. Anthes, 1986: Mesoscale analyses of the Sichuan flood catastrophe, 11–15 July 1981. Mon. Wea. Rev., 114, 19842003, doi:10.1175/1520-0493(1986)114<1984:MAOTSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, J., T. Ding, X. Jia, and X. Zhao, 2015: Analysis on the extreme heat wave over China around Yangtze River region in the summer of 2013 and its main contributing factors. Adv. Meteor., 2015, 706713, doi:10.1155/2015/706713.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Q., W. Dong, W. Li, X. Gao, P. Jones, J. Kennedy, and D. Parker, 2010: Assessment of the uncertainties in temperature change in China during the last century. Chin. Sci. Bull., 55, 19741982, doi:10.1007/s11434-010-3209-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., and H. Gu, 2006: Relationship between middle stratiform clouds and large scale circulation over eastern China. Geophys. Res. Lett., 33, L09706, doi:10.1029/2005GL025615.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., R. Yu, Y. Xu, and T. Zhou, 2005: AREM simulations of cloud features over eastern China in February 2001. Adv. Atmos. Sci., 22, 260270, doi:10.1007/BF02918515.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., S. P. Harrison, P. Zhao, and J. Ju, 2009: Simulations of the impacts of dynamic vegetation on interannual and interdecadal variability of Asian summer monsoon with modern and mid-Holocene orbital forcings. Global Planet. Change, 66, 235252, doi:10.1016/j.gloplacha.2008.12.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., Z. Xiao, J. Ju, and G. Hu, 2010: The variations of dominant convection modes over Asia, Indian Ocean, and western Pacific Ocean during the summers of 1997–2004. Adv. Atmos. Sci., 27, 901920, doi:10.1007/s00376-009-9072-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ma, T., Z. Wu, and Z. Jiang, 2012: How does coldwave frequency in China respond to a warming climate? Climate Dyn., 39, 24872496, doi:10.1007/s00382-012-1354-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mao, J., X. Shi, L. Ma, D. P. Kaiser, Q. Li, and P. E. Thornton, 2010: Assessment of reanalysis daily extreme temperatures with China’s homogenized historical dataset during 1979–2001 using probability density functions. J. Climate, 23, 66056623, doi:10.1175/2010JCLI3581.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meinshausen, M., and Coauthors, 2011: The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change, 109, 213241, doi:10.1007/s10584-011-0156-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mooney, P. A., F. J. Mulligan, and R. Fealy, 2011: Comparison of ERA‐40, ERA‐Interim and NCEP/NCAR reanalysis data with observed surface air temperatures over Ireland. Int. J. Climatol., 31, 545557, doi:10.1002/joc.2098.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moss, R. H., and Coauthors, 2010: The next generation of scenarios for climate change research and assessment. Nature, 463, 747756, doi:10.1038/nature08823.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Patz, J. A., D. Campbell-Lendrum, T. Holloway, and J. A. Foley, 2005: Impact of regional climate change on human health. Nature, 438, 310317, doi:10.1038/nature04188.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Perkins, S. E., A. J. Pitman, N. J. Holbrook, and J. McAneney, 2007: Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions. J. Climate, 20, 43564376, doi:10.1175/JCLI4253.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiao, X., D. Jaffe, Y. Tang, M. Bresnahan, and J. Song, 2015: Evaluation of air quality in Chengdu, Sichuan basin, China: Are China’s air quality standards sufficient yet? Environ. Monit. Assess., 187, 250, doi:10.1007/s10661-015-4500-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ren, G. Y., M. Z. Xu, Z. Y. Chu, J. Guo, Q. X. Li, X. N. Liu, and Y. Wang, 2005: Changes of surface air temperature in China during 1951–2004. Climatic Environ. Res., 10, 717727.

    • Search Google Scholar
    • Export Citation
  • Sanford, T., P. C. Frumhoff, A. Luers, and J. Gulledge, 2014: The climate policy narrative for a dangerously warming world. Nat. Climate Change, 4, 164166, doi:10.1038/nclimate2148.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Simmons, A. J., S. Uppala, D. Dee, and S. Kobayashi, 2007: ERA-Interim: New ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter, No. 110, ECMWF, Reading, United Kingdom, 25–35.

  • Song, F., and T. Zhou, 2014: The climatology and interannual variability of East Asian summer monsoon in CMIP5 coupled models: Does air–sea coupling improve the simulations? J. Climate, 27, 87618777, doi:10.1175/JCLI-D-14-00396.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Su, F., X. Duan, D. Chen, Z. Hao, and L. Cuo, 2013: Evaluation of the global climate models in the CMIP5 over the Tibetan Plateau. J. Climate, 26, 31873208, doi:10.1175/JCLI-D-12-00321.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, J., H. Wang, W. Yuan, and H. Chen, 2010: Spatial‐temporal features of intense snowfall events in China and their possible change. J. Geophys. Res., 115, D16110, doi:10.1029/2009JD013541.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, Q., C. Miao, and Q. Duan, 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, 48064824, doi:10.1002/2014JD022994.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, doi:10.1175/BAMS-D-11-00094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, G., 2005: Agricultural drought in a future climate: Results from 15 global climate models participating in the IPCC 4th assessment. Climate Dyn., 25, 739753, doi:10.1007/s00382-005-0057-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, H. J., and Coauthors, 2012: Extreme climate in China: Facts, simulation and projection. Meteor. Z., 21, 279304, doi:10.1127/0941-2948/2012/0330.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, L., and W. Chen, 2014: A CMIP5 multimodel projection of future temperature, precipitation, and climatological drought in China. Int. J. Climatol., 34, 20592078, doi:10.1002/joc.3822.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wei, K., and W. Chen, 2011: An abrupt increase in the summer high temperature extreme days across China in the mid-1990s. Adv. Atmos. Sci., 28, 10231029, doi:10.1007/s00376-010-0080-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, B., and T. Zhou, 2016: Relationships between ENSO and the East Asian–western North Pacific monsoon: Observations versus 18 CMIP5 models. Climate Dyn., 46, 729743, doi:10.1007/s00382-015-2609-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, C., and G. Huang, 2016: Projection of climate extremes in the Zhujiang River basin using a regional climate model. Int. J. Climatol., 36, 11841196, doi:10.1002/joc.4412.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, C. H., 2007: A multi-model research on the detection and prediction of climate change in China (in Chinese). M.S. thesis, Nanjing University of Information Science and Technology, 98 pp.

  • Xu, C. H., and Y. Xu, 2012: The projection of temperature and precipitation over China under RCP scenarios using a CMIP5 multi-model ensemble. Atmos. Ocean. Sci. Lett., 5, 527533.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, C. H., X. Y. Shen, and Y. Xu, 2007: An analysis of climate change in East Asia by using the IPCC AR4 simulations. Adv. Climate Change Res., 3, 287292.

    • Search Google Scholar
    • Export Citation
  • Xu, J., Y. Shi, X. Gao, and F. Giorgi, 2013: Projected changes in climate extremes over China in the 21st century from a high resolution regional climate model (RegCM3). Chin. Sci. Bull., 58, 14431452, doi:10.1007/s11434-012-5548-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, Y., C. Xu, X. Gao, and Y. Luo, 2009: Projected changes in temperature and precipitation extremes over the Yangtze River basin of China in the 21st century. Quat. Int., 208, 4452, doi:10.1016/j.quaint.2008.12.020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yao, R., Q. Luo, Z. Luo, L. Jiang, and Y. Yang, 2015: An integrated study of urban microclimates in Chongqing, China: Historical weather data, transverse measurement and numerical simulation. Sustainable Cities Soc., 14, 187199, doi:10.1016/j.scs.2014.09.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yin, M., C. Wen, and F. Ruiquan, 2012: Interannual and interdecadal variations of precipitation over eastern China during meiyu season and their relationships with the atmospheric circulation and SST (in Chinese). Chin. J. Atmos. Sci., 36, 397410.

    • Search Google Scholar
    • Export Citation
  • Yu, R., B. Wang, and T. Zhou, 2004: Climate effects of the deep continental stratus clouds generated by the Tibetan Plateau. J. Climate, 17, 27022713, doi:10.1175/1520-0442(2004)017<2702:CEOTDC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, R., 2015: Changes in East Asian summer monsoon and summer rainfall over eastern China during recent decades. Sci. Bull., 60, 12221224, doi:10.1007/s11434-015-0824-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, W., Q. Lu, Z. Gao, and J. Peng, 2008: Response of remotely sensed normalized difference water deviation index to the 2006 drought of eastern Sichuan basin. Sci. China, 51D, 748758, doi:10.1007/s11430-008-0037-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, Y., 2012: Projections of 2.0°C warming over the globe and China under RCP4.5. Atmos. Ocean. Sci. Lett., 5, 514520.

  • Zhou, B., Q. H. Wen, Y. Xu, L. Song, and X. Zhang, 2014: Projected changes in temperature and precipitation extremes in China by the CMIP5 multimodel ensembles. J. Climate, 27, 65916611, doi:10.1175/JCLI-D-13-00761.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, B., Y. Xu, J. Wu, S. Dong, and Y. Shi, 2016: Changes in temperature and precipitation extreme indices over China: Analysis of a high‐resolution grid dataset. Int. J. Climatol., 36, 10511066, doi:10.1002/joc.4400.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, T., and Z. Li, 2002: Simulation of the East Asian summer monsoon using a variable resolution atmospheric GCM. Climate Dyn., 19, 167180, doi:10.1007/s00382-001-0214-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, T., and R. Yu, 2006: Twentieth-century surface air temperature over China and the globe simulated by coupled climate models. J. Climate, 19, 58435858, doi:10.1175/JCLI3952.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, W., C. Li, and J. C. L. Chan, 2006: The interdecadal variations of the summer monsoon rainfall over South China. Meteor. Atmos. Phys., 93, 165175, doi:10.1007/s00703-006-0184-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 374 374 28
PDF Downloads 70 70 15

An Assessment of Recent and Future Temperature Change over the Sichuan Basin, China, Using CMIP5 Climate Models

View More View Less
  • 1 British Antarctic Survey, and Centre for Atmospheric Sciences, University of Cambridge, Cambridge, United Kingdom
  • 2 Centre for Atmospheric Sciences, University of Cambridge, Cambridge, United Kingdom
  • 3 British Antarctic Survey, Cambridge, United Kingdom
  • 4 Department of Architecture, University of Cambridge, Cambridge, United Kingdom
© Get Permissions
Restricted access

Abstract

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.

Denotes content that is immediately available upon publication as open access.

This article is licensed under a Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/).

© 2017 American Meteorological Society.

Corresponding author: Daniel Bannister, danban70@bas.ac.uk

Abstract

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.

Denotes content that is immediately available upon publication as open access.

This article is licensed under a Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/).

© 2017 American Meteorological Society.

Corresponding author: Daniel Bannister, danban70@bas.ac.uk
Save