Start Submission Become a Reviewer

Reading: Role of convective parameterization in simulations of a convection band at grey-zone resolut...

Download

A- A+
Alt. Display

Original Research Papers

Role of convective parameterization in simulations of a convection band at grey-zone resolutions

Authors:

Xing Yu ,

Laboratory for Atmospheric Modeling Research, Department of Atmospheric Sciences, Yonsei University, Seodaemoon-ku, 120-749 Seoul, KR
X close

Tae-Young Lee

Laboratory for Atmospheric Modeling Research, Department of Atmospheric Sciences, Yonsei University, Seodaemoon-ku, 120-749 Seoul, KR
X close

Abstract

In this study, we investigate the role of convective parameterization (CP) in simulations of a convection band over the mid-Korean Peninsula at grey-zone resolutions, at which convection is partially resolved, partially subgrid. An approach similar to that used in ‘observing system simulation experiment’ is adopted. Simulations with a 500-m grid size serve as benchmark simulations. The impacts of resolution and convective parameterization at grey-zone resolutions (i.e. 3, 6 and 9 km) are then investigated. Results indicate that a grid size of 3 km is sufficient to resolve the convection band and CP for this size grid is not necessary. With 6 and 9 km grids, explicit simulations or those based on a Kain—Fritsch CP scheme do not simulate the atmospheric structure surrounding the band accurately.

A major problem with CP is excessive triggering of parameterized convection. False triggers of CP in the band adjacent area suppress evolution of the resolved convection band through excessive stabilization of inflow air. We obtain significant improvements by using a modified trigger function, resulting in reduction of the area of parameterized convection, which in turn leads to stronger development of a resolved convection band. Furthermore, our approach reduces bias in the domain-averaged vertical thermodynamic structure.

How to Cite: Yu, X. and Lee, T.-Y., 2010. Role of convective parameterization in simulations of a convection band at grey-zone resolutions. Tellus A: Dynamic Meteorology and Oceanography, 62(5), pp.617–632. DOI: http://doi.org/10.1111/j.1600-0870.2010.00470.x
3
Views
1
Downloads
45
Citations
  Published on 01 Jan 2010
 Accepted on 25 May 2010            Submitted on 7 Dec 2009

References

  1. Adlerman , E. J. and Droegemeier , K. K . 2002 . The sensitivity of numerically simulated cyclic mesocyclogenesis to variations in model physical and computational parameters. Mon . Wea. Re v . 130 , 2671 – 2691 .  

  2. Aralcawa , A . 2004 . The cumulus parameterization problem: past, present, and future . J. Climate 17 , 2493 – 2525 .  

  3. Aralcawa , A. and Chen , J. M . 1987 . Closure assumptions in the cumulus parameterization problem. In: Short and Medium Range Numerical Weather Prediction (ed. T. Matsuno ). Jpn Meteor Soc., 107 – 131 .  

  4. Bryan , G. H. , Wyngaard , J. C. and Fritsch , J. M . 2003 . Resolution requirements for the simulation of deep moist convection. Mon . Wea. Re v . 131 , 2394 – 2416 .  

  5. Craig , G. C. and Dörnbrack , A . 2008 . Entrainment in cumulus clouds: what resolution is cloud-resolving?. J. Atmos. Sc i . 65 , 3978 – 3988 .  

  6. Deng , A. and Stauffer , D. R . 2006 . On improving 4-km mesoscale model simulations . J. Appl. Meteor. Climatol . 45 , 361 – 381 .  

  7. Dudhia , J . 1993 . A nonhydrostatic version of the Penn State-NCAR Mesoscale Model: validation tests and simulation of an Atlantic cyclone and cold front. Mon . Wea. Re v . 121 , 1493 – 1513 .  

  8. Fritsch , J. M. and Chappell , C. E 1980 . Numerical prediction of convectively driven mesoscale pressure systems. Part I: Convective parameterization. J. Atmos. Sc i . 37 , 1722 – 1733 .  

  9. Gerard , L . 2007 . An integrated package for subgrid convection, clouds and precipitation compatible with mesogamma scales . Quart. J. Roy. Meteor Soc . 133 , 711 – 730 .  

  10. Gerard , L. and Geleyn , J.-F . 2005 . Evolution of a subgrid deep convection parameterization in a limited area model with increasing resolution . Quart. J. Roy. Meteor. Soc . 131 , 2293 – 2312 .  

  11. Grell , G. , Dudhia , J. and Stauffer , D . 1994 . A description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5). NCAR Technical Note NCAR/TN-398±STR, 138 pp .  

  12. Hammarstrand , U . 1998 . Questions involving the use of traditional convection parameterization in NVVP models with higher resolution . Tellus 50A , 265 – 282 .  

  13. Kain , J. S . 2004 . The Kain-Fritsch convective parameterization: an update . J. Appl. Meteor 43 , 170 – 181 .  

  14. Kain , J. S. and Fritsch , J. M . 1990 . A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sc i . 47 , 2784 – 2802 .  

  15. Kain , J. S. and Fritsch , J. M . 1993 . Convective parameterization for mesoscale models: the Kain-Fritsch scheme. In: The Representation of Cumulus Convection in Numerical Models, Meteor Monogr , No. 46, Amer. Meteor Soc. , 165 – 170 .  

  16. Kain , J. S. , Weiss , S. J. , Bright , D. R. , Levit , J. J. , Carbin , G. W. and co-authors . 2008 . Some practical considerations regarding horizontal resolution in the first generation of operational convection-allowing NWP. Wea. Forecasting 23 , 931 – 952 .  

  17. Kalnay , E. , Kanamitsu , M. , Kistler , R. , Collins , W. , Deaven , D. and co-authors . 1996 . The NCEP/NCAR 40-Year Reanalysis Project. Bull. Am. Meteor Soc . 77 , 437 – 471 .  

  18. Kotroni , V. and Lagouvardos , K . 2004 . Evaluation of MM5 high-resolution real-time forecasts over the urban area of Athens, Greece . J. Appl. Meteor 43 , 1666 – 1678 .  

  19. Kuell , V. , Gassmann , A. and Bott , A . 2007 . Towards a new hybrid cumulus parameterization schemes for use in non-hydrostatic weather prediction models . Quart. J. R. Meteor. Soc . 133 , 479 – 490 .  

  20. Lau , K. M. , Ding , Y. , Wang , J. T. , Johnson , R. , Keenan , T. and co-authors . 2000. A report of the field operations and early results of the South China Sea Monsoon Experiment (SCSMEX) . Bull. Am. Meteor. Soc . 81 , 1261 – 1270 .  

  21. Lean , H. W. , Clark , P. A. , Dixon , M. , Roberts , N. M. , Fitch , A. and co-authors . 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 .  

  22. Liu , C. , Liu , Y. and Xu , H . 2006 . A physics-based diffusion scheme for numerical models. Geophys. Res. Lett . 33 , https://doi.org/10.1029/2006GL025781 .  

  23. Ma , L.-M. and Tan , Z.-M . 2009 . Improving the behavior of the cumulus parameterization for tropical cyclone prediction: Convection trigger . Atmos. Res . 92 , 190 – 211 .  

  24. Molinari , J. M. and Dudek , M . 1992 . Parameterization of convective precipitation in mesoscale numerical models: a critical review. Mon . Wea. Re v . 120 , 326 – 344 .  

  25. Niemelä , S. and Fortelius , C . 2005 . Applicability of large-scale convection and condensation parameterization to meso-y -scale HIRLAM: a case study of a convective event. Mon . Wea. Re v . 133 , 2422 – 2435 .  

  26. Noda , A. and Niino , H . 2003 . Critical grid size for simulating convective storms: a case study of the Del City supercell storm. Geophys. Res. Lett . 30 , https://doi.org/10.1029/2003GL017498 .  

  27. Petch , J. C. , Brown , A. R. and Gray , M. E. B . 2002 . The impact of horizontal resolution on the simulations of convective development overland . Quart. J. R. Meteor Soc . 128 , 2031 – 2044 .  

  28. Reisner , J. , Rasmussen , R. J. and Bruintjes , R. T . 1998 . Explicit fore-casting of supercooled liquid water in winter storms using the MM5 Mesoscale Model . Quart. J. R. Meteor. Soc . 124B , 1071 – 1107 .  

  29. Roberts , N. M. and Lean , H. W . 2008 . Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon . Wea. Re v . 136 , 78 – 97 .  

  30. Saito , K. , Ishida , J.-I. , Aranami , K. , Hara , T. , Segawa , T. and co-authors . 2007 . Nonhydrostatic atmospheric models and operational development at .IMA. J. Meteor Soc. Jpn . 85B , 271 – 304 .  

  31. Schwartz , C. S. , Kain , J. S. , Weiss , S. J. , Xue , M. , Bright , D. R. and co-authors. 2009. Next-day convection-allowing WRF model guidance: a second look at 2-km versus 4-km grid spacing. Mon. Wea. Rev . 137 , 3351 – 3372 .  

  32. Steppeler , J. , Hess , R. , Schattler , U. and Bonaventura , L . 2003 . Review of numerical methods for nonhydrostatic weather prediction models . Meteorol. Atmos. Phys . 82 , 287 – 301 .  

  33. Sun , J. and Lee , T. Y . 2002 . A numerical study of an intensive quasi-stationary convection band over the Korean Peninsula . J. Meteor Soc. Jpn . 80 ( 5 ), 1221 – 1245 .  

  34. Thompson , G. , Rasmussen , R. M. and Manning , K . 2004 . Explicit fore-casts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Mon . Wea. Re v . 132 , 519 – 542 .  

  35. Weisman , M. L. , Slcamarock , W. C. and Klemp , J. B . 1997 . The resolution dependence of explicitly modeled convective systems. Mon . Wea. Re v . 125 , 527 – 548 .  

  36. Weisman , M. L. , Davis , C. , Wang , W. , Wanning , K. W. and Klemp , J. B . 2008 . Experiences with 0-36-h experiments convective forecasts with the WRF-ARW model . Wea. Forecasting 23 , 407 – 437 .  

  37. Zhang , D.-L. and Anthes , R. A . 1982 . A high-resolution model of the planetary boundary layer-sensitivity tests and comparisons with SESAME-79 data . J. Appl. Meteor 21 , 1594 – 1609 .  

comments powered by Disqus