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Investigating the linkage between simulated precipitation climatology and ENSO-related precipitation anomaly based on multi-model and perturbed parameter ensembles

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Abstract

It remains a challenge for climate models to correctly capture the relationship between precipitation and ENSO. This study examines the linkage between the simulated precipitation climatology and ENSO-related precipitation anomaly during boreal winter based on the multi-model ensemble from the Atmospheric Model Intercomparison Project Phase 5 (AMIP5) and perturbed parameter ensemble (PPE) with the Beijing Climate Center (BCC) atmospheric model. The AMIP5 models have large biases in simulating the tropical precipitation anomaly during El Niño, such as the shifts of the Inter-Tropical Convergence Zone (ITCZ) and South Pacific Convergence Zone (SPCZ). The inter-model differences show that the precipitation change in response to sea surface temperature (SST) change increases with enhanced precipitation climatology. The ENSO-related precipitation anomaly can also be related to the spatial distribution of the mean-state precipitation. The simulated ITCZ/SPCZ displacements are significantly correlated with the spatial precipitation-SST relationship in the mean state. Models with stronger mean-state precipitation-SST relationship also produce stronger SPCZ/ITCZ displacements. The mean-state tropical precipitation also has strong impacts on the ENSO-related precipitation anomalies over East Asia. In the BCC PPE, the connection between the mean-state precipitation and ENSO-related precipitation anomaly is overall consistent with that in AMIP5. Parameters associated with the low-cloud and deep convection processes are the most influential ones for the precipitation simulations in BCC. Compared with the version in AMIP5, the new BCC model can better simulate the precipitation climatology and the relationship between ENSO and precipitation over southern China. These results have important implications for model development and model-based climate predictions.

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References

  • Adler RF et al (2003) The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979-present). J Hydrometeorol 4:1147–1167

    Article  Google Scholar 

  • Annamalai H, Liu P (2005) Response of the Asian summer monsoon to changes in El Nino properties. Q J Roy Meteor Soc 131:805–831

    Google Scholar 

  • Bellenger H, Guilyardi E, Leloup J, Lengaigne M, Vialard J (2014) ENSO representation in climate models: from CMIP3 to CMIP5. Clim Dyn 42:1999–2018

    Google Scholar 

  • Boyle JS, Klein SA, Lucas DD, Ma HY, Tannahill J, Xie S (2015) The parametric sensitivity of CAM5’s MJO. J Geophys Res-Atmos 120:1424–1444

    Google Scholar 

  • Brown JR, Moise AF, Delage FP (2012) Changes in the South Pacific Convergence Zone in IPCC AR4 future climate projections. Clim Dyn 39:1–19

    Google Scholar 

  • Brown JR, Moise AF, Colman RA (2013) The South Pacific Convergence Zone in CMIP5 simulations of historical and future climate. Clim Dyn 41:2179–2197

    Google Scholar 

  • Brown SJ, Murphy JM, Sexton DMH, Harris GR (2014) Climate projections of future extreme events accounting for modelling uncertainties and historical simulation biases. Clim Dyn 43:2681–2705

    Google Scholar 

  • Choi KY, Vecchi GA, Wittenberg AT (2015) Nonlinear zonal wind response to ENSO in the CMIP5 models: roles of the zonal and meridional shift of the ITCZ/SPCZ and the simulated climatological precipitation. J Clim 28:8556–8573

    Google Scholar 

  • Chung CTY, Power SB (2015) Modelled rainfall response to strong El Nino sea surface temperature anomalies in the tropical pacific. J Clim 28:3133–3151

    Google Scholar 

  • Clarke A (2008) An introduction to the dynamics of El Niño and the Southern Oscillation. Academic Press 324 pp

  • Collins M, Booth BB, Bhaskaran B, Harris GR, Murphy JM, Sexton DMH, Webb MJ (2011) Climate model errors, feedbacks and forcings: a comparison of perturbed physics and multi-model ensembles. Clim Dyn 36:1737–1766

    Google Scholar 

  • Cubasch U et al (2001) Projections of future climate change, Chapter 9. In: Houghton et al. (eds) Climate change 2001: The scientific basis, third assessment report of the intergovernmental panel on climate change JT. Cambridge University Press, Cambridge, New York, pp 525–582

  • Dai N, Arkin PA (2017) Twentieth century ENSO-related precipitation mean states in twentieth century reanalysis, reconstructed precipitation and CMIP5 models. Climate Dynamics 48 (9-10):3061–3083

    Google Scholar 

  • Gilmore MS, Straka JM, Rasmussen EN (2004) Precipitation uncertainty due to variations in precipitation particle parameters within a simple microphysics scheme. Mon Weather Rev 132:2610–2627

    Google Scholar 

  • Giorgi F, Mearns LO (2002) Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “reliability ensemble averaging” (REA) method. J Clim 15:1141–1158

    Google Scholar 

  • Gong HN, Wang L, Chen W, Nath D, Huang G, Tao WC (2015) Diverse Influences of ENSO on the East Asian-Western Pacific Winter Climate Tied to Different ENSO Properties in CMIP5 Models. J Clim 28:2187–2202

    Google Scholar 

  • Grose MR et al (2014) Assessment of the CMIP5 global climate model simulations of the western tropical Pacific climate system and comparison to CMIP3. Int J Climatol 34:3382–3399

    Google Scholar 

  • Guo Z et al (2014) A sensitivity analysis of cloud properties to CLUBB parameters in the single-column Community Atmosphere Model (SCAM5). J Adv Model Earth Syst 6:829–858

    Google Scholar 

  • Guo Z et al (2015) Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM). J Adv Model Earth Syst 7:1005–1025

    Google Scholar 

  • Ham YG, Kug JS (2014) ENSO phase-locking to the boreal winter in CMIP3 and CMIP5 models. Clim Dyn 43:305–318

    Google Scholar 

  • Ham YG, Kug JS (2015) Improvement of ENSO Simulation Based on Intermodel Diversity. J Clim 28:998–1015

    Google Scholar 

  • Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90:1095

    Google Scholar 

  • He SP, Wang HJ (2013) Oscillating relationship between the East Asian winter monsoon and ENSO. J Clim 26:9819–9838

    Google Scholar 

  • Hou ZS, Huang MY, Leung LR, Lin G, Ricciuto DM (2012) Sensitivity of surface flux simulations to hydrologic parameters based on an uncertainty quantification framework applied to the Community Land Model. J Geophys Res-Atmos 117

    Google Scholar 

  • Hourdin F et al (2017) The art and science of climate model tuning. Bull Am Meteorol Soc 98:589–602

    Google Scholar 

  • 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

    Google Scholar 

  • Huang WY et al (2019) A possible mechanism for the occurrence of wintertime extreme precipitation events over South China. Clim Dyn 52:2367–2384. https://doi.org/10.1007/s00382-018-4262-8

    Article  Google Scholar 

  • Hurrell JW et al (2013) The community earth system model a framework for collaborative research. Bull Am Meteorol Soc 94:1339–1360

    Google Scholar 

  • Jackson CS, Sen MK, Huerta G, Deng Y, Bowman KP (2008) Error Reduction and convergence in climate prediction. J Clim 21:6698–6709

    Google Scholar 

  • Kang IS et al (2002) Intercomparison of the climatological variations of Asian summer monsoon precipitation simulated by 10 GCMs. Clim Dyn 19:383–395

    Google Scholar 

  • Kim ST, Cai WJ, Jin FF, Yu JY (2014) ENSO stability in coupled climate models and its association with mean state. Clim Dyn 42:3313–3321

    Google Scholar 

  • Kug J-S, Ham Y-G, Lee J-Y, Jin F-F (2012) Improved simulation of two types of El Niño in CMIP5 models. Environ Res Lett 7:034002. https://doi.org/10.1088/1748-9326/7/3/034002

    Article  Google Scholar 

  • Lee JY, Wang B (2014) Future change of global monsoon in the CMIP5. Clim Dyn 42:101–119

    Google Scholar 

  • Li G, Xie SP (2014) Tropical biases in CMIP5 multimodel ensemble: the excessive equatorial Pacific cold tongue and double ITCZ problems. J Clim 27:1765–1780

    Google Scholar 

  • Li CF et al (2016) Skillful seasonal prediction of Yangtze river valley summer rainfall. Environ Res Lett 11

    Google Scholar 

  • Li G, Xie S-P, Du Y, Luo Y (2016a) Effects of excessive equatorial cold tongue bias on the projections of tropical Pacific climate change. Part I: the warming pattern in CMIP5 multi-model ensemble. Climate Dyn 47:3817–3831

    Google Scholar 

  • Li G, Xie S-P, Du Y (2016b) A robust but spurious pattern of climate change in model projections over the tropical Indian Ocean. J Clim 29:5589–5608

    Google Scholar 

  • Li G, Xie SP, He C, Chen ZS (2017) Western Pacific emergent constraint lowers projected increase in Indian summer monsoon rainfall. Nat Clim Change 7:708

    Google Scholar 

  • 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

    Google Scholar 

  • Lintner BR, Langenbrunner B, Neelin JD, Anderson BT, Niznik MJ, Li G, Xie SP (2016) Characterizing CMIP5 model spread in simulated rainfall in the Pacific Intertropical Convergence and South Pacific Convergence Zones. J Geophys Res-Atmos 121:11590–11607

    Google Scholar 

  • Lopez A, Tebaldi C, New M, Stainforth D, Allen M, Kettleborough J (2006) Two approaches to quantifying uncertainty in global temperature changes. J Clim 19:4785–4796

    Google Scholar 

  • Lu B, Scaife AA, Dunstone N, Smith D, Ren HL, Liu Y, Eade R (2017) Skillful seasonal predictions of winter precipitation over southern China. Environ Res Lett 12

    Google Scholar 

  • Mckay MD, Beckman RJ, Conover WJ (1979) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21:239–245

    Google Scholar 

  • McPhaden MJ, Zebiak SE, Glantz MH (2006) ENSO as an integrating concept in Earth science. Science 314:1740–1745

    Google Scholar 

  • Murphy JM, Booth BB, Boulton CA, Clark RT, Harris GR, Lowe JA, Sexton DMH (2014) Transient climate changes in a perturbed parameter ensemble of emissions-driven earth system model simulations. Clim Dyn 43:2855–2885

    Google Scholar 

  • Murphy BF, Ye H, Delage F (2015) Impacts of variations in the strength and structure of El Nino events on Pacific rainfall in CMIP5 models. Clim Dyn 44:3171–3186

    Google Scholar 

  • Neelin JD, Battisti DS, Hirst AC, Jin FF, Wakata Y, Yamagata T, Zebiak SE (1998) ENSO theory. J Geophys Res-Oceans 103:14261–14290

    Google Scholar 

  • Posselt DJ, Fryxell B, Molod A, Williams B (2016) quantitative sensitivity analysis of physical parameterizations for cases of deep convection in the NASA GEOS-5. J Clim 29:455–479

    Google Scholar 

  • Qian Y et al (2015) Parametric sensitivity analysis of precipitation at global and local scales in the Community Atmosphere Model CAM5. J Adv Model Earth Syst 7:382–411

    Google Scholar 

  • Ropelewski CF, Halpert MS (1987) Global and regional scale precipitation patterns associated with the El-Nino southern oscillation. Mon Weather Rev 115:1606–1626

    Google Scholar 

  • Seager R, Harnik N, Robinson WA, Kushnir Y, Ting M, Huang HP, Velez J (2005) Mechanisms of ENSO-forcing of hemispherically symmetric precipitation variability. Q J R Meteorol Soc 131:1501–1527. https://doi.org/10.1256/qj.04.96

    Article  Google Scholar 

  • Song FF, Zhou TJ (2014a) Interannual variability of East Asian summer monsoon simulated by CMIP3 and CMIP5 AGCMs: skill dependence on Indian Ocean–western Pacific anticyclone teleconnection. J Clim 27:1679–1697. https://doi.org/10.1175/JCLI-D-13-00248.1

    Google Scholar 

  • Song FF, Zhou TJ (2014b) The climatology and interannual variability of east Asian summer monsoon in cmip5 coupled models: does air-sea coupling improve the simulations? J Clim 27:8761–8777

    Google Scholar 

  • Sperber KR, Palmer TN (1996) Interannual tropical rainfall variability in general circulation model simulations associated with the atmospheric model intercomparison project. J Clim 9:2727–2750

    Google Scholar 

  • Sperber K et al (2013) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn 41:2711–2744

    Google Scholar 

  • Stein M (1987) Large sample properties of simulations using Latin hypercube sampling. Technometrics 29:143–151

    Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of Cmip5 and the experiment design. Bull Am Meteorol Soc 93:485–498

    Google Scholar 

  • Vincent EM, Lengaigne M, Menkes CE, Jourdain NC, Marchesiello P, Madec G (2011) Interannual variability of the South Pacific Convergence Zone and implications for tropical cyclone genesis. Clim Dyn 36:1881–1896

    Google Scholar 

  • Wallace JM, Rasmusson EM, Mitchell TP, Kousky VE, Sarachik ES, von Storch H (1998) The structure and evolution of ENSO-related climate variability in the tropical Pacific: lessons from TOGA. J Geophys Res-Oceans 103:14241–14259

    Google Scholar 

  • Wang B, Zhang Q (2002) Pacific-east Asian teleconnection. Part II: how the Philippine Sea anomalous anticyclone is established during El Nino development. J Climate 15:3252–3265

    Google Scholar 

  • Wang B, Wu RG, Fu XH (2000) Pacific-East Asian teleconnection: how does ENSO affect East Asian climate? J Climate 13:1517–1536. https://doi.org/10.1175/1520-0442(2000)013<1517:Peathd>2.0.Co;2

    Article  Google Scholar 

  • Wang B, Yang J, Zhou TJ (2008) Interdecadal changes in the major modes of Asian-Australian monsoon variability: strengthening relationship with ENSO since the late 1970s. J Clim 21:1771–1789

    Google Scholar 

  • Watanabe M et al (2010) Improved climate simulation by MIROC5. Mean states, variability, and climate sensitivity. J Clim 23:6312–6335

    Google Scholar 

  • Wu RG, Wang B (2002) A contrast of the east Asian summer monsoon-ENSO relationship between 1962-77 and 1978-93. J Clim 15:3266–3279

    Google Scholar 

  • Wu TW et al (2010) The Beijing Climate Center atmospheric general circulation model: description and its performance for the present-day climate. Clim Dyn 34:123–147

    Google Scholar 

  • Wu TW et al (2019) The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6. Geosci Model Dev 12:1573–1600. https://doi.org/10.5194/gmd-12-1573-2019

    Article  Google Scholar 

  • Xie PP, Arkin PA (1997) Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Am Meteorol Soc 78:2539–2558

    Google Scholar 

  • Xie SP, Hu KM, Hafner J, Tokinaga H, Du Y, Huang G, Sampe T (2009) Indian Ocean capacitor effect on Indo-Western Pacific climate during the summer following El Nino. J Clim 22:730–747

    Google Scholar 

  • Yan HP et al (2015) A new approach to modeling aerosol effects on East Asian climate: Parametric uncertainties associated with emissions, cloud microphysics, and their interactions. J Geophys Res-Atmos 120:8905–8924

    Google Scholar 

  • Yang B, Qian Y, Lin G, Leung R, Zhang Y (2012) Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model. Atmos Chem Phys 12:2409–2427

    Google Scholar 

  • Yang B 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

    Google Scholar 

  • Yang SH, Li CF, Lu RY (2014) Predictability of winter rainfall in South China as demonstrated by the coupled models of ENSEMBLES. Adv Atmos Sci 31:779–786

    Google Scholar 

  • Yang B, Zhang YC, Qian Y, Huang AN, Yan HP (2015a) Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation. Clim Dyn 44:1661–1684

    Google Scholar 

  • Yang B, Zhang Y, Qian Y, Wu T, Huang A, Fang Y (2015b) Parametric sensitivity analysis for the Asian summer monsoon precipitation simulation in the Beijing Climate Center AGCM, Version 2.1. J Climate 28:5622–5644. https://doi.org/10.1175/JCLI-D-14-00655.1

    Article  Google Scholar 

  • Yang ZF, Huang WY, Qiu TP, He XS, Wright JS, Wang B (2018) Interannual variation and regime shift of the evaporative moisture sources for wintertime precipitation over southern China. J Geophys Res 123:13168–13185. https://doi.org/10.1029/2018JD029513

    Article  Google Scholar 

  • Yang ZF, Huang WY, He XS, Wang Y, Qiu TP, Wright JS, Wang B (2019) Synoptic conditions and moisture sources for extreme snowfall events over east China. J Geophys Res 124:601–623. https://doi.org/10.1029/2018JD029280

    Article  Google Scholar 

  • Zhang T, Sun DZ (2014) ENSO asymmetry in CMIP5 models. J Clim 27:4070–4093

    Google Scholar 

  • Zhang MH, Li SL, Lu J, Wu RG (2012) Comparison of the northwestern pacific summer climate simulated by AMIP II AGCMs. J Clim 25:6036–6056

    Google Scholar 

  • Zhang WJ et al (2016) Unraveling El Nino’s impact on the east asian monsoon and Yangtze River summer flooding. Geophys Res Lett 43:11375–11382

    Google Scholar 

  • Zhao C et al (2013) A sensitivity study of radiative fluxes at the top of atmosphere to cloud-microphysics and aerosol parameters in the community atmosphere model CAM5. Atmos Chem Phys 13:10969–10987

    Google Scholar 

  • Zhou ZQ, Xie SP, Zheng XT, Liu QY, Wang H (2014) Global warming-induced changes in El Nino teleconnections over the North Pacific and North America. J Clim 27:9050–9064. https://doi.org/10.1175/Jcli-D-14-00254.1

    Article  Google Scholar 

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Acknowledgments

We thank three anonymous reviewers for their careful reviews and constructive comments.

Funding

This study is jointly supported by the National Key R&D Program of China (Grant No. 2016YFA0602100) and the National Natural Science Foundation of China (41675101). Yun Qian in this study is supported by the U.S. Department of Energy’s Office of Science as part of the Atmospheric System Research (ASR) program. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. All the graphics in this study are created by the NCAR Command Language (NCL; doi:10.5065/D6WD3XH5).

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Authors and Affiliations

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

    Ben Yang, Yaocun Zhang & Anning Huang

  2. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

    Zhun Guo

  3. Pacific Northwest National Laboratory, Richland, WA, USA

    Yun Qian

  4. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China

    Yang Zhou

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  1. Ben Yang
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Yang, B., Zhang, Y., Guo, Z. et al. Investigating the linkage between simulated precipitation climatology and ENSO-related precipitation anomaly based on multi-model and perturbed parameter ensembles. Theor Appl Climatol 139, 533–547 (2020). https://doi.org/10.1007/s00704-019-02990-x

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