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GCMs with implicit and explicit representation of cloud microphysics for simulation of extreme precipitation frequency

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Abstract

The present study aims to develop a general circulation model (GCM) with improved simulation of heavy precipitation frequency by improving the representations of cloud and rain processes. GCMs with conventional convective parameterizations produce common bias in precipitation frequency: they overestimate light precipitation and underestimate heavy precipitation with respect to observed values. This frequency shift toward light precipitation is attributed here to a lack of consideration of cloud microphysical processes related to heavy precipitation. The budget study of cloud microphysical processes using a cloud-resolving model shows that the melting of graupel and accretion of cloud water by graupel and rain water are important processes in the generation of heavy precipitation. However, those processes are not expressed explicitly in conventional GCMs with convective parameterizations. In the present study, the cloud microphysics is modified to allow its implementation into a GCM with a horizontal resolution of 50 km. The newly developed GCM, which includes explicit cloud microphysics, produces more heavy precipitation and less light precipitation than conventional GCMs, thus simulating a precipitation frequency that is closer to the observed. This study demonstrates that the GCM requires a full representation of cloud microphysics to simulate the extreme precipitation frequency realistically. It is also shown that a coarse-resolution GCM with cloud microphysics requires an additional mixing process in the lower troposphere.

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References

  • Allan RP, Soden BJ, John VO, Ingram W, Good P (2010) Current changes in tropical precipitation. Environ Res Lett 5:1–7

    Google Scholar 

  • Bonan GB (1996) Land surface model (LSM version 1.0) for ecological, hydrological, and atmospheric studies: technical description and user’s guide. NCAR technical note NCAR/TN-417 + STR, pp 1–159

  • Boyle J, Klein SA (2010) Impact of horizontal resolution on climate model forecasts of tropical precipitation and diabatic heating for the TWP-ICE period. J Geohys Res 115:1–20

    Article  Google Scholar 

  • Chen C-T, Knutson T (2008) On the verification and comparison of extreme rainfall indices from climate models. J Clim 21:1605–1621

    Article  Google Scholar 

  • Ciesielski PE, Johnson RH, Haertel PT, Wang J (2003) Corrected TOGA COARE sounding humidity data: impact on diagnosed properties of convection and climate over the warm pool. J Clim 16:2370–2384

    Article  Google Scholar 

  • Dai A (2006) Precipitation characteristics in eighteen coupled climate models. J Clim 19:4605–4630

    Article  Google Scholar 

  • DeMott CA, Randall DA, Khairoutdinov M (2007) Convective precipitation variability as a tool for general circulation model analysis. J Clim 20:91–112

    Article  Google Scholar 

  • Durman C, Gregory J, Hassell D, Jones R, Murphy J (2001) A comparison of extreme European daily precipitation simulated by a global and a regional climate model for present and future climates. Q J R Meteorol Soc 127:1005–1015

    Article  Google Scholar 

  • Gregory D (2001) Estimation of entrainment rate in simple models of convective clouds. Q J R Meteorol Soc 127:53–72

    Article  Google Scholar 

  • Holtslag A, Boville B (1993) Local versus nonlocal boundary-layer diffusion in a global climate model. J Clim 6:1825–1842

    Article  Google Scholar 

  • Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Hong Y, Stocker EF, Wolff DB (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8:38–55

    Article  Google Scholar 

  • Iorio J, Duffy P, Govindasamy B, Thompson S, Khairoutdinov M, Randall D (2004) Effects of model resolution and subgrid-scale physics on the simulation of precipitation in the continental United States. Clim Dyn 23:243–258

    Article  Google Scholar 

  • Khairoutdinov MF, Randall DA (2003) Cloud resolving modeling of the ARM summer 1997 IOP: model formulation, results, uncertainties, and sensitivities. J Atmos Sci 60:607–625

    Article  Google Scholar 

  • Kharin VV, Zwiers FW, Zhang X, Hegerl GC (2007) Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations. J Clim 20:1419–1444

    Article  Google Scholar 

  • Kim D, Kang I-S (2012) A bulk mass flux convection scheme for climate model: description and moisture sensitivity. Clim Dyn 38:411–429

    Article  Google Scholar 

  • Kim D, Sobel AH, Maloney ED, Frierson DM, Kang I-S (2011) A systematic relationship between intraseasonal variability and mean state bias in AGCM simulations. J Clim 24:5506–5520

    Article  Google Scholar 

  • Klemp JB, Wilhelmson RB (1978) The simulation of three-dimensional convective storm dynamics. J Atmos Sci 35:1070–1096

    Article  Google Scholar 

  • Lau WKM, Wu HT, Kim KM (2013) A canonical response of precipitation characteristics to global warming from CMIP5 models. Geophys Res Lett 40:3163–3169

    Article  Google Scholar 

  • Le Treut H, Li Z-X (1991) Sensitivity of an atmospheric general circulation model to prescribed SST changes: feedback effects associated with the simulation of cloud optical properties. Clim Dyn 5:175–187

    Google Scholar 

  • Lee M-I, Kang I-S, Kim JK, Mapes BE (2001) Influence of cloud-radiation interaction on simulating tropical intraseasonal oscillation with an atmospheric general circulation model. J Geophys Res 106:14219–14233

    Article  Google Scholar 

  • Lee M-I, Kang I-S, Mapes BE (2003) Impacts of cumulus convection parameterization on aqua-planet AGCM simulations of tropical intraseasonal variability. J Meteorol Soc Jpn 81:963–992

    Article  Google Scholar 

  • Li F, Collins WD, Wehner MF, Williamson DL, Olson JG (2011a) Response of precipitation extremes to idealized global warming in an aqua-planet climate model: towards a robust projection across different horizontal resolutions. Tellus A 63:876–883

    Article  Google Scholar 

  • Li F, Collins WD, Wehner MF, Williamson DL, Olson JG, Algieri C (2011b) Impact of horizontal resolution on simulation of precipitation extremes in an aqua-planet version of community atmospheric model (CAM3). Tellus A 63:884–892

    Article  Google Scholar 

  • Li F, Rosa D, Collins WD, Wehner MF (2012) “Super-parameterization”: a better way to simulate regional extreme precipitation? J Adv Model Earth Syst 4:1–10

    Article  Google Scholar 

  • Lin Y-L, Farley RD, Orville HD (1983) Bulk parameterization of the snow field in a cloud model. J Clim Appl Meteorol 22:1065–1092

    Article  Google Scholar 

  • Lin X, Randall DA, Fowler LD (2000) Diurnal variability of the hydrologic cycle and radiative fluxes: comparisons between observations and a GCM. J Clim 13:4159–4179

    Article  Google Scholar 

  • Liu C, Ikeda K, Thompson G, Rasmussen R, Dudhia J (2011) High-resolution simulations of wintertime precipitation in the Colorado Headwaters region: sensitivity to physics parameterizations. Mon Weather Rev 139:3533–3553

    Article  Google Scholar 

  • Liu C, Allan RP, Huffman GJ (2012) Co-variation of temperature and precipitation in CMIP5 models and satellite observations. Geophys Res Lett 39:1–8

    Google Scholar 

  • Lorant V, McFarlane NA, Scinocca JF (2006) Variability of precipitation intensity: sensitivity to treatment of moist convection in an RCM and a GCM. Clim Dyn 26:183–200

    Article  Google Scholar 

  • Mapes B, Neale R (2011) Parameterizing convective organization to escape the entrainment dilemma. J Adv Model Earth Syst 3:1–20

    Article  Google Scholar 

  • Min S-K, Zhang X, Zwiers FW, Hegerl GC (2011) Human contribution to more-intense precipitation extremes. Nature 470:378–381

    Article  Google Scholar 

  • Nakajima T, Tsukamoto M, Tsushima Y, Numaguti A (1995) Modelling of the radiative processes in an AGCM. Clim Syst Dyn Model 3:104–123

    Google Scholar 

  • O’Gorman PA, Schneider T (2009) The physical basis for increases in precipitation extremes in simulations of 21st-century climate change. Proc Natl Acad Sci 106:14773–14777

    Article  Google Scholar 

  • Pan DM, Randall DD (1998) A cumulus parameterization with a prognostic closure. Q J R Meteorol Soc 124:949–981

    Google Scholar 

  • Satoh M, Tomita H, Miura H, Iga S, Nasuno T (2005) Development of a global cloud resolving model-a multi-scale structure of tropical convections. J Earth Simul 3:11–19

    Google Scholar 

  • Scinocca JF, McFarlane NA (2004) The variability of modeled tropical precipitation. J Atmos Sci 61:1993–2015

    Article  Google Scholar 

  • Scoccimarro E, Gualdi S, Zampieri M, Bellucci A, Navarra A (2013) Heavy precipitation events in a warmer climate: results from CMIP5 models. J Clim 26:7902–7911

    Article  Google Scholar 

  • Su H, Jiang JH, Vane DG, Stephens GL (2008) Observed vertical structure of tropical oceanic clouds sorted in large-scale regimes. Geophys Res Lett 35:1–6

    Google Scholar 

  • Sun Y, Solomon S, Dai A, Portmann RW (2006) How often does it rain? J Clim 19:916–934

    Article  Google Scholar 

  • Sun F, Roderick ML, Farquhar GD (2012) Changes in the variability of global land precipitation. Geophys Res Lett 39:1–6

    Google Scholar 

  • Tao W-K, Simpson J, Baker D, Braun S, Chou M-D, Ferrier B, Johnson D, Khain A, Lang S, Lynn B (2003) Microphysics, radiation and surface processes in the Goddard Cumulus Ensemble (GCE) model. Meteorol Atmos Phys 82:97–137

    Article  Google Scholar 

  • Tiedtke M (1984) Sensitivity of the time-mean large-scale flow to cumulus convection in the ECMWF model. pp 297–316

  • Tiedtke M (1989) A comprehensive mass flux scheme for cumulusparameterization in large-scale models. Mon Weather Rev 117:1779–1800

    Article  Google Scholar 

  • Tokioka T (1988) The equatorial 30–60 day oscillation and the Arakawa–Schubert penetrative cumulus parameterization. J Meteorol Soc Jpn 66:883–901

    Google Scholar 

  • Wang W, Schlesinger ME (1999) The dependence on convection parameterization of the tropical intraseasonal oscillation simulated by the UIUC 11-layer atmospheric GCM. J Clim 12:1423–1457

    Article  Google Scholar 

  • Webster PJ, Lukas R (1992) TOGA COARE: the coupled ocean-atmosphere response experiment. Bull Am Meteorol Soc 73:1377–1416

    Article  Google Scholar 

  • 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 34:241–247

    Article  Google Scholar 

  • Wilcox EM, Donner LJ (2007) The frequency of extreme rain events in satellite rain-rate estimates and an atmospheric general circulation model. J Clim 20:53–69

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MEST) (NRF-2012M1A2A2671775) and by the Brain Korea 21 Plus. Wei-Kuo Tao was supported by the NASA Precipitation Measurement Missions (PMM), the NASA Modeling, Analysis, and Prediction (MAP) Program.

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Authors and Affiliations

  1. School of Earth and Environmental Sciences, Seoul National University, Seoul, 151-747, South Korea

    In-Sik Kang

  2. International Pacific Research Center, SOEST, University of Hawaii, Honolulu, HI, 96822, USA

    Young-Min Yang

  3. Mesoscale Atmospheric Processes Laboratory, NASA/Goddard Space Flight Center, Greenbelt, MD, 20771, USA

    Wei-Kuo Tao

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  1. In-Sik Kang
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  2. Young-Min Yang
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Correspondence to In-Sik Kang.

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Kang, IS., Yang, YM. & Tao, WK. GCMs with implicit and explicit representation of cloud microphysics for simulation of extreme precipitation frequency. Clim Dyn 45, 325–335 (2015). https://doi.org/10.1007/s00382-014-2376-1

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  • DOI: https://doi.org/10.1007/s00382-014-2376-1

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