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Inconsistent Global Kinetic Energy Spectra in Reanalyses and Models

Inconsistent Global Kinetic Energy Spectra in Reanalyses and Models AbstractGlobal upper-tropospheric kinetic energy (KE) spectra in several global atmospheric circulation datasets are examined. The datasets considered include ERA-Interim, JRA-55, and ERA5 and two versions of NOAA GFS analyses at horizontal resolutions ranging from 0.7° to 0.12°. The mesoscale portions of the spectra are found to be highly inconsistent. This is shown to be mainly due to inconsistencies in the scale-dependent numerical damping and in the large contributions to the global mesoscale KE from the KE in convective regions and near orography. The spectra also generally have a steeper mesoscale slope than the −5/3 slope of the observational Nastrom–Gage spectrum pursued at many modeling centers. The sensitivity of the slope in global models to 1) stochastically perturbing diabatic tendencies and 2) decreasing the horizontal hyperviscosity coefficient is explored in large ensembles of 10-day forecasts made with the NCEP GFS (0.7° grid) model. Both changes lead to larger mesoscale KE and a flatter spectral slope. The effect is stronger in the modified hyperviscosity experiment. These results show that (i) despite assimilating vastly more observations than used in the original Nastrom–Gage studies, current high-resolution global analyses still do not converge to a single “true” global mesoscale KE spectrum, and (ii) model KE spectra can be made flatter not just by increasing model resolution but also by perturbing model physics and decreasing horizontal diffusion. Such sensitivities and lack of consensus on the spectral slope also raise the possibility that the true global mesoscale spectral slope may not be a precisely −5/3 slope. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Atmospheric Sciences American Meteorological Society

Inconsistent Global Kinetic Energy Spectra in Reanalyses and Models

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0469
eISSN
1520-0469
DOI
10.1175/JAS-D-20-0294.1
Publisher site
See Article on Publisher Site

Abstract

AbstractGlobal upper-tropospheric kinetic energy (KE) spectra in several global atmospheric circulation datasets are examined. The datasets considered include ERA-Interim, JRA-55, and ERA5 and two versions of NOAA GFS analyses at horizontal resolutions ranging from 0.7° to 0.12°. The mesoscale portions of the spectra are found to be highly inconsistent. This is shown to be mainly due to inconsistencies in the scale-dependent numerical damping and in the large contributions to the global mesoscale KE from the KE in convective regions and near orography. The spectra also generally have a steeper mesoscale slope than the −5/3 slope of the observational Nastrom–Gage spectrum pursued at many modeling centers. The sensitivity of the slope in global models to 1) stochastically perturbing diabatic tendencies and 2) decreasing the horizontal hyperviscosity coefficient is explored in large ensembles of 10-day forecasts made with the NCEP GFS (0.7° grid) model. Both changes lead to larger mesoscale KE and a flatter spectral slope. The effect is stronger in the modified hyperviscosity experiment. These results show that (i) despite assimilating vastly more observations than used in the original Nastrom–Gage studies, current high-resolution global analyses still do not converge to a single “true” global mesoscale KE spectrum, and (ii) model KE spectra can be made flatter not just by increasing model resolution but also by perturbing model physics and decreasing horizontal diffusion. Such sensitivities and lack of consensus on the spectral slope also raise the possibility that the true global mesoscale spectral slope may not be a precisely −5/3 slope.

Journal

Journal of the Atmospheric Sciences – American Meteorological Society

Published: Aug 29, 2021

References

  • A spectral stochastic kinetic energy backscatter scheme and its impact on flow-dependent predictability in the ECMWF Ensemble Prediction System
    Berner, J.; Shutts, G.; Leutbecher, M.; Palmer, T.
  • Systematic model error: The impact of increased horizontal resolution versus improved stochastic and deterministic parameterizations
    Berner, J.; Jung, T.; Palmer, T. N.
  • Increasing the skill of probabilistic forecasts: Understanding performance improvements from model-error representations
    Berner, J.; Fossell, K. R.; Ha, S.-Y.; Hacker, J. P.; Snyder, C.
  • Data assimilation using incremental analysis updates
    Bloom, S. C.; Takacs, L. L.; da Silva, A. M.; Ledvina, D.
  • Four-dimensional ensemble-variational data assimilation for global deterministic weather prediction
    Buehner, M.; Morneau, J.; Charette, C.
  • Use and impact of automated aircraft data in a global 4DVar data assimilation system
    Cardinali, C.; Isaksen, L.; Andersson, E.
  • Horizontal wavenumber spectra of winds, temperature, and trace gases during the Pacific Exploratory Missions: 1. Climatology
    Cho, J. Y. N.
  • Horizontal wavenumber spectra of winds, temperature, and trace gases during the Pacific Exploratory Missions: 2. Gravity waves, quasi-two-dimensional turbulence, and vortical modes
    Cho, J. Y. N.; Newell, R.; Barrick, J. D.
  • The ERA-Interim reanalysis: Configuration and performance of the data assimilation system
    Dee, D. P.
  • Advancing science and services during the 2015/16 El Niño: The NOAA El Niño Rapid Response field campaign
    Dole, R. M.
  • Global simulations of the atmosphere at 1.45 km grid-spacing with the Integrated Forecasting System
    Dueben, P. D.; Wedi, N.; Saarinen, S.; Zeman, C.
  • Uncertainty in the representation of orography in weather and climate models and implications
    Elvidge, A. D.
  • Climatology of velocity and temperature turbulence statistics determined from rawinsonde and ACARS/AMDAR data
    Frehlich, R.; Sharman, R.
  • Mesoscale spectrum of atmospheric motions investigated in a very fine resolution global general circulation model
    Hamilton, K.; Takahashi, Y. O.; Ohfuchi, W.
  • The JRA-55 Reanalysis: Representation of atmospheric circulation and climate variability
    Harada, Y.
  • The ERA5 global reanalysis
    Hersbach, H.
  • The verification of objective analyses: Diagnostics of analysis system performance
    Hollingsworth, A.; Lonnberg, P.
  • Diabatic digital-filtering initialization: Application to the HIRLAM model
    Huang, X.-Y.; Lynch, P.
  • Insights into atmospheric predictability through global convection-permitting model simulations
    Judt, F.
  • Energy cascade processes in rotating stratified turbulence with application to the atmospheric mesoscale
    Kitamura, Y.; Matsuda, Y.
  • An OSSE-based evaluation of hybrid variational–ensemble data assimilation for the NCEP GFS. Part II: 4DEnVar and hybrid variants
    Kleist, D. T.; Ide, K.
  • The JRA-55 Reanalysis: General specifications and basic characteristics
    Kobayashi, S.
  • Inertial ranges in two-dimensional turbulence
    Kraichnan, R. H.
  • Implementation of new diffusion/filtering operators in the CAM-FV dynamical core
    Lauritzen, P. H.; Mirin, A. A.; Truesdale, J.; Raeder, K.; Anderson, J. L.; Bacmeister, J.; Neale, R. B.
  • A four-dimensional incremental analysis update for the ensemble Kalman filter
    Lei, L.; Whitaker, J. S.
  • Stochastic representations of model uncertainties at ECMWF: State of the art and future vision
    Leutbecher, M.
  • Weakly and strongly nonlinear mesoscale dynamics close to the tropopause?
    Li, Q.; Lindborg, E.
  • Numerical simulation studies of two-dimensional turbulence. II. Stability and predictability studies
    Lilly, D. K.
  • Stratified turbulence and the mesoscale variability of the atmosphere
    Lilly, D. K.
  • Can the atmospheric kinetic energy spectrum be explained by two-dimensional turbulence?
    Lindborg, E.
  • Climatology and interannual variability of dynamic variables in multiple reanalyses evaluated by the SPARC Reanalysis Intercomparison Project (S-RIP)
    Long, C. S.; Fujiwara, M.; Davis, S.; Mitchell, D. M.; Wright, C. J.
  • The predictability of a flow which possesses many scales of motion
    Lorenz, E. N.
  • Initialization of the HIRLAM model using a digital filter
    Lynch, P.; Huang, X.-Y.
  • A climatology of atmospheric wavenumber spectra of wind and temperature observed by commercial aircraft
    Nastrom, G. D.; Gage, K. S.
  • Kinetic energy spectrum of large- and mesoscale atmospheric processes
    Nastrom, G. D.; Gage, K. S.; Jasperson, W. H.
  • Recovery of atmospheric flow statistics in a general circulation model without nonlinear eddy-eddy interactions
    O’Gorman, P. A.; Schneider, T.
  • On the impact and benefits of AMDAR observations in operational forecasting—Part I: A review of the impact of automated aircraft wind and temperature reports
    Petersen, R. A.
  • Impact of a stochastic kinetic energy backscatter scheme across time-scales and resolutions
    Sanchez, C.; Williams, K. D.; Shutts, G.; Collins, M.
  • Impacts of orography on large-scale atmospheric circulation
    Sandu, I.
  • A kinetic energy backscatter algorithm for use in ensemble prediction systems
    Shutts, G.
  • Evaluating mesoscale NWP models using kinetic energy spectra
    Skamarock, W. C.
  • Atmospheric kinetic energy spectra from global high-resolution nonhydrostatic simulations
    Skamarock, W. C.; Park, S.-H.; Klemp, J. B.; Snyder, C.
  • What is the impact of additional tropical observations on a modern data assimilation system?
    Slivinski, L. C.; Compo, G. P.; Whitaker, J. S.; Sardeshmukh, P. D.; Wang, J.-W. A.; Friedman, K.; McColl, C.
  • Comments on “The k−3 and k−5/3 energy spectrum of atmospheric turbulence: Quasigeostrophic two-level model simulation
    Smith, K. S.
  • The stability of incremental analysis update
    Takacs, L. L.; Suárez, M. J.; Todling, R.
  • Characteristics of the kinetic energy spectrum of NICAM model atmosphere
    Terasaki, K.; Tanaka, H.
  • A moist aquaplanet variant of the Held-Suarez test for atmospheric model dynamical core
    Thatcher, D. R.; Jablonowski, C.
  • A stochastic convective approach to account for model uncertainty due to unresolved humidity variability
    Tompkins, A. M.; Berner, J.
  • Reply
    Tung, K. K.
  • The k−3 and k−5/3 energy spectrum of atmospheric turbulence: Quasigeostrophic two-level model simulation
    Tung, K. K.; Orlando, W. W.
  • Sensitivities of the NCEP Global Forecast System
    Wang, J.-W. A.; Sardeshmukh, P. D.; Compo, G. P.; Whitaker, J. S.; Slivinski, L. C.; McColl, C. M.; Pegion, P. J.
  • Effects of moist convection on mesoscale predictability
    Zhang, F.; Snyder, C.; Rotunno, R.
  • Mesoscale predictability of moist baroclinic waves: Convection-permitting experiments and multistage error growth dynamics
    Zhang, F.; Bei, N.; Rotunno, R.; Snyder, C.; Epifanio, C. C.