Testing the anelastic nonhydrostatic model EULAG as a prospective dynamical core of a numerical weather prediction model Part II: Simulations of supercell

• Autorzy: Kurowski M.J. , Rosa B. , Ziemiański M. Z.
• Języki publikacji: EN

Abstrakty

EN

The anelastic nonhydrostatic model EULAG is a candidate for the future dynamical core of a numerical weather prediction model. Achieving such an objective requires a number of experiments focused on testing correctness of the solutions and robustness of the solver. In the spirit of this idea, a set of tests related to standard atmospheric problems was performed, of which the two regarding development and evolution of a supercell were employed as benchmarks of moist dynamics of the model. Their results are discussed in this paper. Development and evolution of a stormsystem with a set of characteristic features such as stormsplitting along with the generation of horizontal vorticity and cold pool formation is investigated. In addition, the influence of domain geometry, boundary conditions and subgrid-scale mixing is examined.

Słowa kluczowe

EN

moist convection; supercell simulation; storm splitting; dynamical core; anelastic equations

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2011
• Tom: Vol. 59, no. 6
• Strony: 1267--1293
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Kurowski M.J.

autor

Rosa B.

autor

Ziemiański M. Z.

• Institute of Meteorology and Water Management, Warsaw, Poland,

Bibliografia

• Andrejczuk, M., W.W. Grabowski, S.P. Malinowski, and P.K. Smolarkiewicz (2004), Numerical simulation of cloud-clear air interfacial mixing, J. Atmos. Sci. 61, 14, 1726-1739.
• Davies, H.C. (1976), A lateral boundary formulation for multi-level prediction models, Quart. J. Roy. Met. Soc. 102, 432, 405-418.
• Grabowski, W.W., and P.K. Smolarkiewicz (2002), A multiscale anelastic model for meteorological research, Month. Weather Rev. 130, 4, 939-956.
• Klemp, J.B. (1987), Dynamics of tornadic thunderstorms, Ann. Rev. Fluid Mech. 19, 369-402.
• Klemp, J.B., and R.B. Wilhelmson (1978), The simulation of three-dimensional convective stormdynamics, J. Atmos. Sci. 35, 6, 1070-1090.
• Lipps, F.B., and R.S. Hemler (1982), A scale analysis of deep moist convection and some related numerical calculations, J. Atmos. Sci. 39, 10, 2191-2210.
• Margolin, L.G., P.K. Smolarkiewicz, and Z. Sorbjan (1999), Large-eddy simulations of convective boundary layers using nonoscillatory differencing, Physica D 133, 390-397.
• McCaul, E.W., Jr., and M.L. Weisman (2001), The sensitivity of simulated supercell structure and intensity to variations in the shapes of environmental buoyancy and shear profiles, Month.Weather Rev. 129, 4, 664-687.
• Miglietta, M.M., and R. Rotunno (2009), Numerical simulations of conditionally unstable flows over a mountain ridge, J. Atmos. Sci. 66, 7, 1865-1885.
• Morrison, H., and J. Milbrandt (2011), Comparison of two-moment bulk microphysics schemes in idealized supercell thunderstorm simulations, Month. Weather Rev. 139, 4, 1103-1130.
• Prusa, J.M., P.K. Smolarkiewicz, and A.A. Wyszogrodzki (2008), EULAG, a computational model for multiscale flows, Comput. Fluids 37, 9, 1193-1207.
• Rosa, B., M.J. Kurowski, and M.Z. Ziemianski (2011), Testing the anelastic nonhydrostatic model EULAG as a prospective dynamical core of a numerical weather prediction model. Part I: Dry benchmarks. Acta Geophys. 59, 6.
• Saito, K., J. Ishida, K. Aranami, T. Hara, T. Segawa, M. Narita, and Y. Honda (2007), Nonhydrostatic atmospheric models and operational development at JMA, J. Meteorol. Soc. Jpn 85, 271-304.
• Seifert, A., and K.D. Beheng (2006), A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 2: Maritime vs. continental deep convective storms, Meteorol. Atmos. Phys. 92, 1-2, 67-82.
• Skamarock, W.C., J.D. Doyle, P. Clark, and N. Wood (2004), A standard test set for nonhydrostatic dynamical cores of NWP models. In: 20th Conf. on Weather Analysis and Forecasting/16th Conf. on NumericalWeather Prediction, 10-15 January 2004, Seattle, USA.
• Smolarkiewicz, P.K. (2006), Multidimensional positive definite advection transport algorithm: an overview, Int. J. Numer. Meth. Fluids 50, 10, 1123-1144.
• Smolarkiewicz, P.K., and L.G. Margolin (1997), On forward-in-time differencing for fluids: an Eulerian/semi-Lagrangian nonhydrostatic model for stratified flows, Atmos. Ocean Sp. 35, 1, 127-152.
• Smolarkiewicz, P.K., and L.G. Margolin (1998), MPDATA: a finite-difference solver for geophysical flows, J. Comput. Phys. 140, 2, 459-480.
• Straka, J.M., R.B. Wilhelmson, L.J. Wicker, J.R. Anderson, and K.K. Droegemeier (1993), Numerical solutions of a non-linear density-current: A benchmark solution and comparisons, Int. J. Numer. Meth. Fluids 17, 1, 1-22.
• Takemi, T. (2010), Dependence of the precipitation intensity in mesoscale convective systems to temperature lapse rate, Atmos. Res. 96, 273-285.
• Weisman, M.L., and J.B. Klemp (1982), The dependence of numerically simulated convective storms on vertical wind shear and buoyancy, Month. Weather Rev. 110, 6, 504-520.