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Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

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Abstract

The uncertainty of global summer precipitation simulated by the 23 CMIP5 CGCMs and the possible impacts of model resolutions are investigated in this study. Large uncertainties exist over the tropical and subtropical regions, which can be mainly attributed to convective precipitation simulation. High-resolution models (HRMs) and low-resolution models (LRMs) are further investigated to demonstrate their different contributions to the uncertainties of the ensemble mean. It shows that the high-resolution model ensemble means (HMME) and low-resolution model ensemble mean (LMME) mitigate the biases between the MME and observation over most continents and oceans, respectively. The HMME simulates more precipitation than the LMME over most oceans, but less precipitation over some continents. The dominant precipitation category in the HRMs (LRMs) is the heavy precipitation (moderate precipitation) over the tropic regions. The combinations of convective and stratiform precipitation are also quite different: the HMME has much higher ratio of stratiform precipitation while the LMME has more convective precipitation. Finally, differences in precipitation between the HMME and LMME can be traced to their differences in the SST simulations via the local and remote air-sea interaction.

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References

  • Abe M, Shiogama H, Hargreaves JC et al (2009) Correlation between inter-model similarities in spatial pattern for present and projected future mean climate. Sola 5:133-136. doi:10.2151/sola.2009-034

    Article  Google Scholar 

  • Back LE, Bretherton CS (2009) On the relationship between SST gradients, boundary layer winds, and convergence over the tropical oceans. J Clim 22:4182-4196. doi:10.1175/2009JCLI2392.1

    Article  Google Scholar 

  • Bacmeister JT, Wehner MF, Neale RB et al (2014) Exploratory high-resolution climate simulations using the community atmosphere model (CAM). J Clim 27:3073-3099. doi:10.1175/JCLI-D-13-00387.1

    Article  Google Scholar 

  • Blázquez J, Nuñez MN (2012) Analysis of uncertainties in future climate projections for South America: comparison of WCRP-CMIP3 and WCRP-CMIP5 models. Clim Dyn 41:1039-1056. doi:10.1007/s00382-012-1489-7

    Article  Google Scholar 

  • Chan SC, Kendon EJ, Fowler HJ et al (2012) Does increasing the spatial resolution of a regional climate model improve the simulated daily precipitation? Clim Dyn 41:1475-1495. doi:10.1007/s00382-012-1568-9

    Article  Google Scholar 

  • Chen J, Bordoni S (2014) Intermodel spread of East Asian summer monsoon simulations in CMIP5. Geophys Res Lett 41:1-8. doi:10.1002/2013GL058981

    Article  Google Scholar 

  • Christensen, J. H., et al., 2007: Regional climate projections. In: Climate Change 2007: The Physical Scientific Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M. and Miller, H. L. (eds). Cambridge University Press

  • 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, 525-582

  • Dai A (2006) Precipitation characteristics in eighteen coupled climate models. J Clim 19:4605-4630. doi:10.1175/JCLI3884.1

    Article  Google Scholar 

  • Dai A, Fyfe JC, Xie S-P, Dai X (2015) Decadal modulation of global surface temperature by internal climate variability. Nat Clim Chang. doi: 10.1038/nclimate2605

  • Demory M-E, Vidale PL, Roberts MJ, et al. (2013) The role of horizontal resolution in simulating drivers of the global hydrological cycle. Clim Dyn. doi: 10.1007/s00382-013-1924-4

  • Deser C, Phillips A, Bourdette V, Teng H (2010) Uncertainty in climate change projections: the role of internal variability. Clim Dyn 38:527-546. doi:10.1007/s00382-010-0977-x

    Article  Google Scholar 

  • Dimri A (2004) Impact of horizontal model resolution and orography on the simulation of a western disturbance and its associated precipitation. Meteorol Appl 11:115-127. doi:10.1017/S1350482704001227

    Article  Google Scholar 

  • Fu X, Yang B, Bao Q, Wang B (2008) Sea surface temperature feedback extends the predictability of tropical Intraseasonal oscillation. Mon Weather Rev 136:577-597. doi:10.1175/2007MWR2172.1

    Article  Google Scholar 

  • Gao Y, Fu JS, Drake JB et al (2012) Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system. Environ Res Lett 7:44025. doi:10.1088/1748-9326/7/4/044025

    Article  Google Scholar 

  • Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Q J R Meteorol Soc 106:447-462

    Article  Google Scholar 

  • Giorgi F, Marinucci MR (1996) An investigation of the sensitivity of the simulated precipitation to model resolution and its implications for climate studies.pdf. Mon Weather Rev 148-166.

  • Gomes JL, Chou SC (2010) Dependence of partitioning of model implicit and explicit precipitation on horizontal resolution. Meteorog Atmos Phys 106:1-18. doi:10.1007/s00703-009-0050-7

    Article  Google Scholar 

  • Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90:1095-1107. doi:10.1175/2009BAMS2607.1

    Article  Google Scholar 

  • Hawkins E, Sutton R (2011) The potential to narrow uncertainty in projections of regional precipitation change. Clim Dyn 37:407-418. doi:10.1007/s00382-010-0810-6

    Article  Google Scholar 

  • He C, Zhou T (2014) Responses of the western North Pacific subtropical high to global warming under RCP4.5 and RCP8.5 scenarios projected by 33 CMIP5 models: the dominance of tropical Indian Ocean—tropical western Pacific SST gradient. J Clim. doi: 10.1175/JCLI-D-13-00494.1

  • Hirota N, Takayabu YN (2013) Reproducibility of precipitation distribution over the tropical oceans in CMIP5 multi-climate models compared to CMIP3. Clim Dyn. doi: 10.1007/s00382-013-1839-0

  • Hu Y, Guo M, Li Z et al (2012) Evaluation of summer climate simulations over east Asia by a variable resolution model LMDZ. J Meteorol Sci (in Chinese) 32:482-491

    Google Scholar 

  • Huang P, Xie S-P (2015) Mechanisms of change in ENSO-induced tropical Pacific rainfall variability in a warming climate. Nat Geosci. doi: 10.1038/ngeo2571

  • Huang D, Zhu J, Zhang Y, Huang A (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

    Article  Google Scholar 

  • Huang D-Q, Zhu J, Zhang Y-C, et al. (2015) Assessment of summer monsoon precipitation derived from five reanalysis datasets over East Asia. Q J R Meteorol Soc. doi: 10.1002/qj.2634

  • Huffman GJ, Adler RF, Arkin P, Chang A, Ferraro R, Gruber A, Janowiak J, Mcnab A, Rudolf B, Schneider U (1997) The global precipitation climatology project ( GPCP ) combined precipitation dataset. Bull Am Meteorol Soc 78(1):5-20

    Article  Google Scholar 

  • Jung T, Gulev SK, Rudeva I, Soloviov V (2006) Sensitivity of extratropical cyclone characteristics to horizontal resolution in the ECMWF model. Q J R Meteorol Soc 132:1839-1857. doi:10.1256/qj.05.212

    Article  Google Scholar 

  • Kan M, Huang A, Zhao Y, et al. (2015) Evaluation of the summer precipitation over China simulated by BCC_CSM model with different horizontal resolutions during the recent half century. J Geophys Res Atmos. doi: 10.1002/2015JD023131

  • Kimoto M (2005) Simulated change of the east Asian circulation under global warming scenario. Geophys Res Lett 32:L16701. doi:10.1029/2005GL023383

    Article  Google Scholar 

  • Knutti R, Sedláček J (2012) Robustness and uncertainties in the new CMIP5 climate model projections. Nat Clim Chang 3:369-373. doi:10.1038/nclimate1716

    Article  Google Scholar 

  • Lambert SJ, Boer GJ (2001) CMIP1 evaluation and intercomparison of coupled climate models. Clim Dyn 17:83-106

    Article  Google Scholar 

  • Lau WK-M, Wu H-T, Kim K-M (2013) A canonical response of precipitation characteristics to global warming from CMIP5 models. Geophys Res Lett 40:3163-3169. doi:10.1002/grl.50420

    Article  Google Scholar 

  • Li G, Xie S-P (2014) Tropical biases in CMIP5 multimodel ensemble: the excessive equatorial Pacific cold tongue and double ITCZ problems. J Clim 27:1765-1780. doi:10.1175/JCLI-D-13-00337.1

    Article  Google Scholar 

  • Li B, Zhou T (2010) Projected climate change over China under SRES A1B scenario: multi-model ensemble and uncertainties. Adv Clim Chang Res Chinese 6:270-276

    Google Scholar 

  • Li F, Collins WD, Wehner MF et al (2011) Impact of horizontal resolution on simulation of precipitation extremes in an aqua-planet version of community atmospheric model (CAM3). Tellus A 63A:884-892. doi:10.1111/j.1600-0870.2011.00544.x

    Article  Google Scholar 

  • Li J, Yu R, Yuan W, et al. (2015) Precipitation over East Asia simulated by NCAR CAM5 at different horizontal resolutions. J Adv Model Earth Syst. doi: 10.1002/ 2014MS000414

  • Lindzen RS, Nigam S (1987) On the role of sea surface temperature gradients in forcing low-level winds and convergence in the tropics. J Atmos Sci 44:2418-2436. doi:10.1175/1520-0469

    Article  Google Scholar 

  • Liu J, Zhou T, Man W (2013) Simulation study on the anomalous East Asian summer monsoon in 1998 using a variable-grid atmospheric general circulation model. Chinese J Geophys (in Chinese) 56:12-26. doi:10.6038/cjg20130102

    Google Scholar 

  • Lu R, Lu S (2014) Local and remote factors affecting the SST-precipitation relationship over the western North Pacific during Summer. J Clim. doi: 10.1175/JCLI-D-13-00510.1

  • Meehl G and Coauthors, 2007: Global climate projections. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 747-845

  • Meehl G, Covey C, McAvaney B et al (2005) Overview of the coupled model intercomparison project. Bull Am Meteorol Soc 86:89-93. doi:10.1175/BAMS-86-1-89

    Article  Google Scholar 

  • Monselesan DP, Kane TJO, Risbey JS (2015) Internal climate memory in observations and models. Geophys Res Lett. doi: 10.1002/2014GL062765

  • Oueslati B, Bellon G (2013) Tropical precipitation regimes and mechanisms of regime transitions: contrasting two aquaplanet general circulation models. Clim Dyn 40:2345-2358. doi:10.1007/s00382-012-1344-x

    Article  Google Scholar 

  • Oueslati B, Bellon G (2015) The double ITCZ bias in CMIP5 models: interaction between SST, large - scale circulation and precipitation. Clim Dyn. doi: 10.1007/s00382-015-2468-6

  • Pope VD, Stratton RA (2002) The processes governing horizontal resolution sensitivity in a climate model. Clim Dyn 19:211-236. doi:10.1007/s00382-001-0222-8

    Article  Google Scholar 

  • Rajendran K, Kitoh A, Srinivasan J et al (2012) Monsoon circulation interaction with Western Ghats orography under changing climate. Theor Appl Climatol 110:555-571. doi:10.1007/s00704-012-0690-2

    Article  Google Scholar 

  • Rajendran K, Sajani S, Jayasankar CB, Kitoh A (2013) How dependent is climate change projection of Indian summer monsoon rainfall and extreme events on model resolution ? Curr Sci 104:1409-1418

    Google Scholar 

  • Rayner NA, Parker DE, Horton EB et al (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108:4407. doi:10.1029/2002JD002670

    Article  Google Scholar 

  • Reichler T, Kim J (2008) How well do coupled models simulate today’s climate? Bull Am Meteorol Soc 89:303-311. doi:10.1175/BAMS-89-3-303

    Article  Google Scholar 

  • Sabin PT, Krishnan R, Ghattas J et al (2013) High resolution simulation of the South Asian monsoon using a variable resolution global climate model. Clim Dyn 41:173-194. doi:10.1007/s00382-012-1658-8

    Article  Google Scholar 

  • Shashikanth K, Salvi K, Ghosh S, Rajendran K (2014) Do CMIP5 simulations of Indian summer monsoon rainfall differ from those of CMIP3? Atmos Sci Lett 15:79-85. doi:10.1002/asl2.466

    Article  Google Scholar 

  • Song H, Lin W, Lin Y et al (2013) Evaluation of precipitation simulated by seven SCMs against the ARM observations at the SGP site. J Clim 26:5467-5492. doi:10.1175/JCLI-D-12-00263.1

    Article  Google Scholar 

  • Sperber KR, Annamalai H, Kitoh A et al (2013) The Asian summer monsoon:an intercomparison of CMIP5 vs. CMIP3 simulations of the late twentieth century. Clim Dyn 41:2711-2744. doi:10.1007/s00382-012-1607-6

    Article  Google Scholar 

  • Su F, Duan X, Chen D et al (2013) Evaluation of the global climate models in the CMIP5 over the Tibetan Plateau. J Clim 26:3187-3208. doi:10.1175/JCLI-D-12-00321.1

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl G a. (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485-498. doi: 10.1175/BAMS-D-11-00094.1

  • Trenberth K, Shea D (2005) Relationships between precipitation and surface temperature. Geophys Res Lett. doi: 10.1029/2005GL022760

  • Vial J, Dufresne J-L, Bony S (2013) On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Clim Dyn. doi: 10.1007/s00382-013-1725-9

  • Wang B, Ding Q (2008) Global monsoon: dominant mode of annual variation in the tropics. Dyn Atmos Ocean 44:165-183. doi:10.1016/j.dynatmoce.2007.05.002

    Article  Google Scholar 

  • Wen M, Yang S, Vintzileos A et al (2012) Impacts of model resolutions and initial conditions on predictions of the Asian summer monsoon by the NCEP climate forecast system. Weather Forecast 27:629-646. doi:10.1175/WAF-D-11-00128.1

    Article  Google Scholar 

  • Wu R, Kirtman BP, Pegion K (2006) Local air-sea relationship in observations and model simulations. J Clim 19:4914-4932. doi:10.1175/JCLI3904.1

    Article  Google Scholar 

  • Wu B, Li T, Zhou T (2010) Relative contributions of the Indian Ocean and local SST anomalies to the maintenance of the western North Pacific anomalous anticyclone during the el Niño decaying summer*. J Clim 23:2974-2986. doi:10.1175/2010JCLI3300.1

    Article  Google Scholar 

  • Xie S, Zhang M, Branson M et al (2005) Simulations of midlatitude frontal clouds by single-column and cloud-resolving models during the atmospheric radiation measurement march 2000 cloud intensive operational period. J Geophys Res 110:D15S03. doi:10.1029/2004JD005119

    Article  Google Scholar 

  • Xu J, Shi Y, Gao X, Giorgi F (2012) Projected changes in climate extremes over China in the 21st century from a high resolution regional climate model (RegCM3). Chinese Sci Bull. doi: 10.1007/s11434-012-5548-6

  • Yang B, Qian Y, Lin G et al (2013) Uncertainty quantification and parameter tuning in the CAM5 Zhang-McFarlane convection scheme and impact of improved convection on the global circulation and climate. J Geophys Res Atmos 118:395-415. doi:10.1029/2012JD018213

    Article  Google Scholar 

  • Zhang M, Song H (2006) Evidence of deceleration of atmospheric vertical overturning circulation over the tropical Pacific. Geophys Res Lett 33:L12701. doi:10.1029/2006GL025942

    Article  Google Scholar 

  • Zhang Y, Chen H, Yu R (2014) Simulations of stratus clouds over eastern China in CAM5: sensitivity to horizontal resolution. J Clim. doi: 10.1175/JCLI-D-13-00732.1

  • Zhou T-J, Yu R (2005) Atmospheric water vapor transport associated with typical anomalous summer rainfall patterns in China. J Geophys Res 110:D08104. doi:10.1029/2004JD005413

    Google Scholar 

  • Zhou T, Yu R (2006) Twentieth-century surface air temperature over China and the globe simulated by. J Clim 19:5843-5858

    Article  Google Scholar 

  • Zhou T, Yu R, Zhang J et al (2009) Why the western Pacific subtropical high has extended westward since the late 1970s. J Clim 22:2199-2215. doi:10.1175/2008JCLI2527.1

    Article  Google Scholar 

  • Zhou L, Tam C, Zhou W, Chan JCL (2010) Influence of South China Sea SST and the ENSO on winter rainfall over South China. Adv Atmos Sci 27:832-844. doi:10.1007/s00376

    Article  Google Scholar 

  • Zhu J, Zhang Y, Huang D (2009) Analysis of changes in different-class precipitation over Eastern China under global warming. Plateau Meteorol (in Chinese) 28:889-896

    Google Scholar 

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Acknowledgments

This study is jointly sponsored by the National Key Research and Development Program of China (Grant Nos. 2016YFA0602104, 2016YFA0600701, and 2016YFA0600504), the National Natural Science Foundation of China (Grant No. 41575071) and the Jiangsu Collaborative Innovation Center for Climate Change. We acknowledge the climate modeling groups (listed in Table 1) for making their model outputs available, and the World Climate Research Program’s (WCRP’s) Working Group on Coupled Modeling (WGCM) which coordinates the CMIP5 project.

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Authors and Affiliations

  1. CMA-NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China

    Danqing Huang, Peiwen Yan, Yaocun Zhang & Xueyuan Kuang

  2. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China

    Jian Zhu

  3. I.M. System Group, INC., 3206 Tower Oaks Blvd. Suite 300, Rockville, MD, 20850, USA

    Jing Cheng

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  1. Danqing Huang
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Correspondence to Danqing Huang.

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Huang, D., Yan, P., Zhu, J. et al. Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models. Theor Appl Climatol 132, 55–69 (2018). https://doi.org/10.1007/s00704-017-2078-9

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