Atmospheric Kinetic Energy Spectra from Global High-Resolution Nonhydrostatic Simulations

Kinetic energy (KE) spectra derived from global high-resolution atmospheric simulations from the Model forPredictionAcrossScales(MPAS)arepresented.Thesimulationsareproducedusingquasi-uniformglobal Voronoi horizontal meshes with 3-, 7.5-, and 15-km mean cell spacings. KE spectra from the MPAS simulations compare well with observations and other simulations in the literature and possess the canonical KE spectra structure including a very-well-resolved shallow-sloped mesoscale region in the 3-km simulation. There is a peak in the vertical velocity variance at the model filter scale for all simulations, indicating the underresolved nature of updrafts even with the 3-km mesh. The KE spectra reveal that the MPAS configuration produces an effective model resolution (filter scale) of approximately 6Dx. Comparison with other published model KE spectra highlight model filtering issues, specifically insufficient filtering that can lead to spectral blocking and the production of erroneous shallow-sloped mesoscale tails in the KE spectra. The mesoscale regions in the MPAS KE spectra are produced without use of kinetic energy backscatter, in contrast to other results reported in the literature.No substantive difference is found in KE spectra computed on constant height or constant pressure surfaces. Stratified turbulence is not resolved with the vertical resolution used in this study; hence, the results do not support recent conjecture that stratified turbulence explains the mesoscale portion of the KE spectrum.

[1]  R. Frehlich,et al.  Equivalence of velocity statistics at constant pressure or constant altitude , 2010 .

[2]  G. Balmino The Spectra of the topography of the Earth, Venus and Mars , 1993 .

[3]  D. Williamson,et al.  A baroclinic instability test case for atmospheric model dynamical cores , 2006 .

[4]  M. Satoh,et al.  Characteristics of the Kinetic Energy Spectrum of NICAM Model Atmosphere , 2009 .

[5]  T. Schneider,et al.  Recovery of atmospheric flow statistics in a general circulation model without nonlinear eddy‐eddy interactions , 2007 .

[6]  E. Eliasen,et al.  On the effects of the damping mechanisms in an atmospheric general circulation model , 1989 .

[7]  E. Lindborg Can the atmospheric kinetic energy spectrum be explained by two-dimensional turbulence? , 1999, Journal of Fluid Mechanics.

[8]  G. D. Nastrom,et al.  Theoretical Interpretation of Atmospheric Wavenumber Spectra of Wind and Temperature Observed by Commercial Aircraft During GASP , 1986 .

[9]  Kevin Hamilton,et al.  Mesoscale spectrum of atmospheric motions investigated in a very fine resolution global general circulation model , 2008 .

[10]  R. Heikes,et al.  Numerical Integration of the Shallow-Water Equations on a Twisted Icosahedral Grid , 1995 .

[11]  Uang,et al.  The NCEP Climate Forecast System Reanalysis , 2010 .

[12]  K. Hamilton,et al.  Equilibrium dynamics in a forced-dissipative f-plane shallow-water system , 1994, Journal of Fluid Mechanics.

[13]  E. Becker,et al.  Indications of Stratified Turbulence in a Mechanistic GCM , 2013 .

[14]  Todd D. Ringler,et al.  A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations , 2008 .

[15]  G. Shutts A kinetic energy backscatter algorithm for use in ensemble prediction systems , 2005 .

[16]  J. Wyngaard,et al.  Resolution Requirements for the Simulation of Deep Moist Convection , 2003 .

[17]  Todd D. Ringler,et al.  A Multiscale Nonhydrostatic Atmospheric Model Using Centroidal Voronoi Tesselations and C-Grid Staggering , 2012 .

[18]  Theodore G. Shepherd,et al.  Large-Scale Two-Dimensional Turbulence in the Atmosphere , 1983 .

[19]  C. Snyder,et al.  The Mesoscale Kinetic Energy Spectrum of a Baroclinic Life Cycle , 2009 .

[20]  Joseph B. Klemp,et al.  A Terrain-Following Coordinate with Smoothed Coordinate Surfaces , 2011 .

[21]  C. Snyder,et al.  Mesoscale Energy Spectra of Moist Baroclinic Waves , 2013 .

[22]  Shian‐Jiann Lin,et al.  The remarkable predictability of inter‐annual variability of Atlantic hurricanes during the past decade , 2011 .

[23]  Energy Spectra of Rossby and Gravity Waves , 2011 .

[24]  R. Morris,et al.  Visible, near-infrared, and middle infrared spectroscopy of altered basaltic tephras: Spectral signatures of phyllosilicates, sulfates, and other aqueous alteration products with application to the mineralogy of the Columbia Hills of Gusev Crater, Mars , 2008 .

[25]  William C. Skamarock,et al.  Conservative Transport Schemes for Spherical Geodesic Grids: High-Order Flux Operators for ODE-Based Time Integration , 2011 .

[26]  G. D. Nastrom,et al.  A Climatology of Atmospheric Wavenumber Spectra of Wind and Temperature Observed by Commercial Aircraft , 1985 .

[27]  W. Skamarock,et al.  The resolution dependence of explicitly modeled convective systems , 1997 .

[28]  W. Skamarock Evaluating Mesoscale NWP Models Using Kinetic Energy Spectra , 2004 .

[29]  Jimy Dudhia,et al.  An Upper Gravity-Wave Absorbing Layer for NWP Applications , 2008 .

[30]  D. Schertzer,et al.  Reinterpreting aircraft measurements in anisotropic scaling turbulence , 2009 .

[31]  G. Powers,et al.  A Description of the Advanced Research WRF Version 3 , 2008 .

[32]  E. Lindborg,et al.  The energy cascade in a strongly stratified fluid , 2006, Journal of Fluid Mechanics.

[33]  Craig S. Long,et al.  The NCEP climate forecast system reanalysis. Bull Am Meteorol Soc , 2010 .

[34]  Masaki Satoh,et al.  Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations , 2008, J. Comput. Phys..

[35]  Pierre Augier,et al.  A New Formulation of the Spectral Energy Budget of the Atmosphere, with Application to Two High-Resolution General Circulation Models , 2013 .

[36]  T. Shepherd,et al.  The Troposphere-to-Stratosphere Transition in Kinetic Energy Spectra and Nonlinear Spectral Fluxes as Seen in ECMWF Analyses , 2013 .