DOI QR코드

DOI QR Code

Impact of Cumulus Parameterization Schemes with Different Horizontal Grid Sizes on Prediction of Heavy Rainfall

적운 모수화 방안이 고해상도 집중호우 예측에 미치는 영향

  • Lee, Jae-Bok (School of Earth and Environmental Sciences, Seoul National University) ;
  • Lee, Dong-Kyou (School of Earth and Environmental Sciences, Seoul National University)
  • 이재복 (서울대학교 지구환경과학부) ;
  • 이동규 (서울대학교 지구환경과학부)
  • Received : 2011.06.28
  • Accepted : 2011.11.14
  • Published : 2011.12.31

Abstract

This study investigates the impact of cumulus parameterization scheme (CPS) with different horizontal grid sizes on the simulation of the local heavy rainfall case over the Korean Peninsula. The Weather Research and Forecasting (WRF)-based real-time forecast system of the Joint Center for High-impact Weather and Climate Research (JHWC) is used. Three CPSs are used for sensitivity experiments: the BMJ (Betts-Miller-Janjic), GD (Grell-Devenyi ensemble), and KF (Kain-Fritsch) CPSs. The heavy rainfall case selected in this study is characterized by low-level jet and low-level transport of warm and moist air. In 27-km simulations (DM1), simulated precipitation is overestimated in the experiment with BMJ scheme, and it is underestimated with GD scheme. The experiment with KF scheme shows well-developed precipitation cells in the southern and the central region of the Korean Peninsula, which are similar to the observations. All schemes show wet bias and cold bias in the lower troposphere. The simulated rainfall in 27-km horizontal resolution has influence on rainfall forecast in 9-km horizontal resolution, so the statements on 27-km horizontal resolution can be applied to 9-km horizontal resolution. In the sensitivity experiments of CPS for DM3 (3-km resolution), the experiment with BMJ scheme shows better heavy rainfall forecast than the other experiments. The experiments with CPS in 3-km horizontal resolution improve rainfall forecasts compared to the experiments without CPS, especially in rainfall distribution. The experiments with CPS show lower LCL(Lifted Condensation Level) than those without CPS at the maximum rainfall point, and weaker vertical velocity is simulated in the experiments with CPS compared to the experiments without CPS. It means that CPS suppresses convective instability and influences mainly convective rainfall. Consequently, heavy rainfall simulation with BMJ CPS is better than the other CPSs, and even in 3-km horizontal resolution, CPS should be applied to control convective instability. This conclusion can be generalized by conducting more experiments for a variety of cases over the Korean Peninsula.

Keywords

Acknowledgement

Supported by : 한국연구재단

References

  1. Betts, A. K., 1982: Saturation point analysis of moist convective overturning. J. Atmos. Sci., 39, 1484-1505. https://doi.org/10.1175/1520-0469(1982)039<1484:SPAOMC>2.0.CO;2
  2. Betts, A. K., 1986: A new convective adjustment scheme. Part I: Observational and theoretical basis. Quart. J. Roy. Meteor. Soc., 112, 677-691.
  3. Betts, A. K. and M. J. Miller, 1986: A new convective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, ATEX and arctic air-mass data sets. Quart. J. Roy. Meteor. Soc., 112, 693-709.
  4. Black, T. L., 1994: The new NMC mesoscale Eta Model: Description and forecast examples. Wea. Forecasting, 9, 265-278. https://doi.org/10.1175/1520-0434(1994)009<0265:TNNMEM>2.0.CO;2
  5. Deng, A., N. L. Seaman, and J. S. Kain, 2003: A shallow convection parameterization for mesoscale models. Part I: Submodel description and preliminary applications. J. Atmos. Sci., 60, 34-56 https://doi.org/10.1175/1520-0469(2003)060<0034:ASCPFM>2.0.CO;2
  6. Deng, A. and D. R. Stauffer, 2006: On improving 4-km mesoscale model simulations. J. Appl. Meteor. Climatol., 45, 361-381. https://doi.org/10.1175/JAM2341.1
  7. Emanuel, K. A. and D. J. Raymond, Eds., 1983: The Representation of Cumulus Convection in Numerical Models. Meteor. Monogr., No. 46, Amer. Meteor. Soc., 246pp.
  8. Frank, W. M., 1978: The Cumulus Parameterization Problem. Mon. Wea. Rev., 111, 1859-1871.
  9. Fritsch, J. M. and C. F. Chappell, 1980: Numerical prediction of convectively driven mesoscale pressure systems. Part I: Convective parameterization. J. Atmos. Sci., 37, 1722-1732. https://doi.org/10.1175/1520-0469(1980)037<1722:NPOCDM>2.0.CO;2
  10. Grell, G. A., 1993: Prognostic evaluation of assumptions used by cumulus parameterizations. Mon. Wea. Rev., 121, 764-787. https://doi.org/10.1175/1520-0493(1993)121<0764:PEOAUB>2.0.CO;2
  11. Grell, G. A. and D. Devenyi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, 1693-1696.
  12. Hong, S.-Y. and J.-O. J. Lim, 2006: The WRF Single-Moment 6-Class Microphysics Scheme (WSM6). J. Korean Meteor. Soc., 42, 129-151.
  13. Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318-2341. https://doi.org/10.1175/MWR3199.1
  14. Janjic, Z. I., 1994: The step-mountain eta coordinate model: further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927-945. https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2
  15. Kain, J. S. and M. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47, 2784-2802. https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2
  16. Kalb, M. W., 1987: The role of convective parameterization in the simulation of a Gulf coast precipitation system. Mon. Wea. Rev., 115, 214-234. https://doi.org/10.1175/1520-0493(1987)115<0214:TROCPI>2.0.CO;2
  17. Kuo, H. L., 1974: Further studies of the parameterization of the influence of cumulus convection on large-scale flow. J. Atmos. Sci., 31, 1232-1240. https://doi.org/10.1175/1520-0469(1974)031<1232:FSOTPO>2.0.CO;2
  18. Lee, D. K. and J. G. Park, 2002: A comparison study of moist physics schemes in simulation of East Asian heavy rainfall, J. of Korean Meteo. Soc., 38, 581-592.
  19. Lean, H. W., P. A. Clark, M. Dixon, N. M. Roberts, A. Fitch, R. Forbes, and C. Halliwell, 2008: Characteristics of high resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom. Mon. Wea. Rev., 136, 3408-3424. https://doi.org/10.1175/2008MWR2332.1
  20. Molinari, J. M. and M. Dudek, 1986: Implicit versus explicit convective heating in numerical weather prediction models. Mon. Wea. Rev., 114, 326-344.
  21. Molinari, J. M. 1992: Parameterization of convective precipitation in mesoscale numerical models: A critical review. Mon. Wea. Rev., 120, 326-344. https://doi.org/10.1175/1520-0493(1992)120<0326:POCPIM>2.0.CO;2
  22. Olson, D. A., N. W. Junker, and B. Korty, 1995: Evaluation of 33 years of quantitative precipitation forecasting at the NMC. Wea. Forecasting, 10, 498-511. https://doi.org/10.1175/1520-0434(1995)010<0498:EOYOQP>2.0.CO;2
  23. Park, Y.-Y. and T.-Y. Lee 2001: Role of parameterized convection in the simulation of heavy rain over the Korean peninsula, Proceedings of International Workshop on Next Generation NWP Model, 40-46.
  24. Petch, J. C., 2006: Sensitivity studies of developing convection in a cloud-resolving model. Quart. J. Roy. Meteor. Soc., 132, 345-358. https://doi.org/10.1256/qj.05.71
  25. Snsi, S., P. Bougeault, J. che'ze, P. Cosentino, and R. Thepenier, 1996: The Vason-La-Pomaine flash flood: Mesoscale analysis and predictability issues. Wea. Forecasting, 11, 417-442. https://doi.org/10.1175/1520-0434(1996)011<0417:TVLRFF>2.0.CO;2
  26. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the Advanced Research WRF Version 2. NCAR Tech Notes-468+STR.
  27. Tao, W.-K., D. Starr, A. Hou, P. Newman, and Y. sud, 2003: A cumulus parameterization workshop. Bull. Amer. Meteor. Soc., 84, 1055-1062 https://doi.org/10.1175/BAMS-84-8-1055
  28. Wang, W. and N. L. Seaman, 1997: A comparison study of Convective Parameterization Schemes in a Mesoscale Model. Mon. Wea. Rev., 125, 252-278. https://doi.org/10.1175/1520-0493(1997)125<0252:ACSOCP>2.0.CO;2
  29. Zhang, D.-L., E.-Y. Hsie, and M. W. Moncrieff, 1988: A comparison of explicit and implicit prediction of convective and stratiform precipitating weather systems with a meso-${\beta}$-scale numerical model. Quart. J. Roy. Meteor. Soc., 114, 31-60.
  30. Zheng, Y., Q. Xu, and D. J. Stensrud, 1995: A numerical simulation of the 7 May 1985 mesoscale convective system. Mon. Wea. Rev., 123(6), 1781-1799. https://doi.org/10.1175/1520-0493(1995)123<1781:ANSOTM>2.0.CO;2