Skip to main content
Have a personal or library account? Click to login
Atmospheric Energy Spectra in Global Kilometre-Scale Models Cover

Atmospheric Energy Spectra in Global Kilometre-Scale Models

Open Access
|Apr 2022

References

  1. Alexander, MJ. 1996. A simulated spectrum of convectively generated gravity waves: Propagation from the tropopause to the mesopause and effects on the middle atmosphere. J. Geophys. Res., 101: 15711588. DOI: 10.1029/95JD02046
  2. Baldwin, M and Co-authors. 2001. The Quasi-Biennial Oscillation. Rev. Geophys., 39(2): 179229. DOI: 10.1029/1999RG000073
  3. Beljaars, A and Wood, N. 2003. A new parametrization of turbulent orographic form drag., 427: 23. URL https://www.ecmwf.int/node/7594. DOI: 10.21957/6c5u3bbpk
  4. Beljaars, ACM, Brown, AR and Wood, N. 2004. A new parametrization of turbulent orographic form drag. Quart. J. Roy. Meteor. Soc., 130(599): 13271347. DOI: 10.1256/qj.03.73
  5. Boer, GJ and Shepherd, TG. 1983. Large-scale two-dimensional turbulence in the atmosphere. J. Atmos. Sci., 40(1): 164184. DOI: 10.1175/1520-0469(1983)040<;0164:LSTDTI>2.0.CO;2
  6. Bogenschutz, PA and Krueger, SK. 2013. A simplified PDF parameterization of subgrid-scale clouds and turbulence for cloud-resolving models. J. Adv. Model. Earth Sys., 5(2): 195211. DOI: 10.1002/jame.20018
  7. C3S. 2017. ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service Climate Data Store (CDS), Last accessed: November 2020. URL https://cds.climate.copernicus.eu/cdsapp#!/home.
  8. Caldwell, PM and Co-authors. 2021. Convection-permitting simulations with the E3SM Global Atmosphere Model. Earth and Space Sci. Open Arch., 47. DOI: 10.1002/essoar.10506530.1
  9. Chen, J-H and Lin, S-J. 2013. Seasonal predictions of tropical cyclones using a 25-km-resolution general circulation model. J. Climate, 26(2): 380398. DOI: 10.1175/JCLI-D-12-00061.1
  10. Cheng, A and Xu, K-M. 2008. Simulation of boundary-layer cumulus and stratocumulus clouds using a cloud-resolving model with low-and third-order turbulence closures. J. Meteor. Soc. Japan. Ser. II, 86A: 6786. DOI: 10.2151/jmsj.86A.67
  11. Dewan, E. 1979. Stratospheric wave spectra resembling turbulence. Science, 204: 832835. DOI: 10.1126/science.204.4395.832
  12. ECMWF. 2020. IFS Documentation CY47R1 – Part III: Dynamics and Numerical Procedures. No. 3, IFS Documentation. URL https://www.ecmwf.int/node/19747. DOI: 10.21957/u8ssd58
  13. Fjørtoft, R. 1953. On the changes in the spectral distribution of kinetic energy for twodimensional, nondivergent flow. Tellus, 5(3): 225230. DOI: 10.1111/j.2153-3490.1953.tb01051.x
  14. Garcia, RR and Boville, BA. 1994. “Downward Control” of the mean meridional circulation and temperature distribution of the polar winter stratosphere. J. Atmos. Sci., 51(15): 22382245. DOI: 10.1175/1520-0469(1994)051<;2238:COTMMC>2.0.CO;2
  15. Golaz, J-C, Larson, VE and Cotton, WR. 2002. A PDF-based model for boundary layer clouds. Part I: Method and model description. J. Atmos. Sci., 59(24): 35403551. DOI: 10.1175/1520-0469(2002)059<;3540:APBMFB>2.0.CO;2
  16. Grell, GA and Freitas, SR. 2014. A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmos. Chem. Phys., 14(10): 52335250. DOI: 10.5194/acp-14-5233-2014
  17. Han, J and Bretherton, CS. 2019. TKE-based moist eddy-diffusivity mass-flux (EDMF) parameterization for vertical turbulent mixing. Weather and Forecasting, 34(4): 869886. DOI: 10.1175/WAF-D-18-0146.1
  18. Han, J, Wang, W, Kwon, YC, Hong, S-Y, Tallapragada, V and Yang, F. 2017. Updates in the NCEP GFS cumulus convection schemes with scale and aerosol awareness. Weather and Forecasting, 32(5): 20052017. DOI: 10.1175/WAF-D-17-0046.1
  19. Harris, L, Chen, X, Putman, W, Zhou, L and Chen, J-H. 2021. A scientific description of the GFDL finite-volume cubed-sphere dynamical core. Princeton, NJ: NOAA Technical Memorandum OAR GFDL, 2021–001. DOI: 10.25923/6nhs-5897
  20. Harris, L and Co-authors. 2020. GFDL SHiELD: A unified system for weather-to-seasonal prediction. J. Adv. Mod. Earth Sys., 12(10): e2020MS002223. DOI: 10.1029/2020MS002223
  21. Hoskins, BJ and Karoly, DJ. 1981. The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci., 38: 11791196. DOI: 10.1175/1520-0469(1981)038<;1179:TSLROA>2.0.CO;2
  22. Huffman, G, Stocker, E, Bolvin, D, Nelkin, E and Tan, J. 2019. GPM IMERG final precipitation L3 half hourly 0.1 degree × 0.1 degree V06, Greenbelt, MD: Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: May 6, 2021. DOI: 10.5067/GPM/IMERG/3B-HH/06
  23. Kasahara, A. 1984. The linear response of a stratified global atmosphere to a tropical thermal forcing. J. Atmos. Sci., 41: 22172237. DOI: 10.1175/1520-0469(1984)041<;2217:TLROAS>2.0.CO;2
  24. Kasahara, A. 2020. 3D Normal Mode Functions (NMFs) of a Global Baroclinic Atmospheric Model. Modal View Of Atmospheric Variability: Applications Of Normal-Mode Function Decomposition in Weather and Climate Research, Žagar, N and Tribbia, J (eds.). 8: 162. Springer, Mathematics of Planet Earth Series. DOI: 10.1007/978-3-030-60963-4_1
  25. Kasahara, A and Puri, K. 1981. Spectral representation of three-dimensional global data by expansion in normal mode functions. Mon. Wea. Rev., 109: 3751. DOI: 10.1175/1520-0493(1981)109<;0037:SROTDG>2.0.CO;2
  26. Köhler, M, Ahlgrimm, M and Beljaars, A. 2011. Unified treatment of dry convective and stratocumulus-topped boundary layers in the ECMWF model. Quart. J. Roy. Meteor. Soc., 137(654): 4357. DOI: 10.1002/qj.713
  27. Kosovelj, K, Kucharski, F, Molteni, F and Žagar, N. 2019. Modal decomposition of the global response to tropical heating perturbations resembling MJO. J. Atmos. Sci., 76(5): 14571469. DOI: 10.1175/JAS-D-18-0203.1
  28. Koster, RD, Suarez, MJ, Ducharne, A, Stieglitz, M and Kumar, P. 2000. A catchment-based approach to modeling land surface processes in a general circulation model: 1. Model structure. J. Geophys. Res. Atmos., 105(D20): 24 809–24 822. DOI: 10.1029/2000JD900327
  29. Kubota, T and Co-authors. 2007. Global precipitation map using satellite-borne microwave radiometers by the GSMaP project: Production and validation. IEEE Transactions on Geoscience and Remote Sensing, 45(7): 22592275. DOI: 10.1109/TGRS.2007.895337
  30. Labitzke, K. 2005. On the solar cycle-QBO relationship: a summary. J. Atm. and Solar-Terrestrial Physics, 67: 4554. DOI: 10.1016/j.jastp.2004.07.016
  31. Lehmann, CI, Kim, Y-H, Preusse, P, Chun, H-Y, Ern, M and Kim, S-Y. 2012. Consistency between Fourier transform and small-volume few-wave decomposition for spectral and spatial variability of gravity waves above a typhoon. Atmos. Meas. Tech., 5(7): 16371651. DOI: 10.5194/amt-5-1637-2012
  32. Lindborg, E. 2006. The energy cascade in a strongly stratified fluid. J. FluidMech., 550: 207242. DOI: 10.1017/S0022112005008128
  33. Lindborg, E and Mohanan, AV. 2017. A two-dimensional toy model for geophysical turbulence. Phys. Fluids, 29(11): 111 114. DOI: 10.1063/1.4985990
  34. Lock, AP, Brown, AR, Bush, MR, Martin, GM and Smith, RNB. 2000. A new boundary layermixing scheme. Part I: Scheme description and single-columnmodel tests. Mon. Wea. Rev., 128(9): 31873199. DOI: 10.1175/1520-0493(2000)128<;3187:ANBLMS>2.0.CO;2
  35. Lott, F and Miller, MJ. 1997. A new subgrid-scale orographic drag parametrization: Its formulation and testing. Quart. J. Roy. Meteor. Soc., 123(537): 101127. DOI: 10.1002/qj.49712353704
  36. Louis, J-F, Tiedtke, M and Geleyn, J-F. 1982. A short history of the PBL parameterization at ECMWF. Workshop on Planetary Boundary Layer parameterization, 25–27 November 1981. Shinfield Park, Reading, ECMWF, 5979. URL https://www.ecmwf.int/node/10845.
  37. Malardel, S and Wedi, NP. 2016. How does subgrid-scale parametrization influence nonlinear spectral energy fluxes in global NWP models? J. Geophys. Res. Atmos., 121(10): 53955410. DOI: 10.1002/2015JD023970
  38. Marshall, AG and Scaife, AA. 2009. Impact of the QBO on surface winter climate. J. Geophys. Res., 114: D18110. DOI: 10.1029/2009JD011737
  39. Mauritsen, T, Svensson, G, Zilitinkevich, SS, Esau, I, Enger, L and Grisogono, B. 2007. A total turbulent energy closure model for neutrally and stably stratified atmospheric boundary layers. J. Atmos. Sci., 64(11): 41134126. DOI: 10.1175/2007JAS2294.1
  40. McFarlane, NA. 1987. The effect of orographically excited gravity wave drag on the general circulation of the lower stratosphere and troposphere. J. Atmos. Sci., 44(14): 17751800. DOI: 10.1175/1520-0469(1987)044<;1775:TEOOEG>2.0.CO;2
  41. Müller, SK, Manzini, E, Giorgetta, MA, Sato, K and Nasuno, T. 2018. Convectively generated gravity waves in high resolution models of tropical dynamics. J. Adv. Mod. Earth Sys., 10. DOI: 10.1029/2018MS001390
  42. Nastrom, GD and Gage, KS. 1985. A climatology of aircraft wavenumber spectra observed by commercial aircraft. J. Atmos. Sci., 42: 950960. DOI: 10.1175/1520-0469(1985)042<;0950:ACOAWS>2.0.CO;2
  43. Orr, A, Bechtold, P, Scinocca, J, Ern, M and Janiskova, M. 2010. Improved middle atmosphere climate and forecasts in the ECMWF model through a nonorographic gravity wave drag parameterization. J. Climate, 23(22): 59055926. DOI: 10.1175/2010JCLI3490.1
  44. Park, S and Bretherton, CS. 2009. The University of Washington shallow convection and moist turbulence schemes and their impact on climate simulations with the Community Atmosphere Model. J. Climate, 22(12): 34493469. DOI: 10.1175/2008JCLI2557.1
  45. Polichtchouk, I, Wedi, N and Kim, Y-H. 2021. Resolved gravitywaves in the tropical stratosphere: Impact of horizontal resolution and deep convection parametrization. Quart. J. Roy. Meteor. Soc. DOI: 10.1002/qj.4202
  46. Putman, WM and Lin, S-J. 2007. Finite-volume transport on various cubed-sphere grids. J. Comp. Phys., 227(1): 5578. DOI: 10.1016/j.jcp.2007.07.022
  47. Raschendorfer, M. 2001. The new turbulence parameterization of LM. COSMO News Letter No. 1, Consortium for Small-Scale Modelling, 8997. URL http://www.cosmo-model.org.
  48. Salby, ML and Garcia, RR. 1987. Transient response to localized episodic heating in the tropics. Part I: Excitation and short-time near-field behavior. J. Atmos. Sci., 44: 458498. DOI: 10.1175/1520-0469(1987)044<;0458:TRTLEH>2.0.CO;2
  49. Simmons, AJ and Burridge, DM. 1981. An energy and angular-momentum conserving vertical finite-difference scheme and hybrid vertical coordinates. Mon. Wea. Rev., 109(4): 758766. DOI: 10.1175/1520-0493(1981)109<;0758:AEAAMC>2.0.CO;2
  50. Smagorinsky, J. 1963. General circulation experiments with the primitive equations: I. The basic experiment. Mon. Wea. Rev., 91(3): 99164. DOI: 10.1175/1520-0493(1963)091<;0099:GCEWTP>2.3.CO;2
  51. Stephan, CC, Strube, C, Klocke, D, Ern, M, Hoffmann, L, Preusse, P and Schmidt, H. 2019a. Gravity waves in global high-resolution simulations with explicit and parameterized convection. J. Geophy. Res. Atmos., 124(8): 44464459. DOI: 10.1029/2018JD030073
  52. Stephan, CC, Strube, C, Klocke, D, Ern, M, Hoffmann, L, Preusse, P and Schmidt, H. 2019b. Intercomparison of gravity waves in global convection-permitting models. J. Atmos. Sci., 76(9): 27392759. DOI: 10.1175/JAS-D-19-0040.1
  53. Stevens, B and Co-authors. 2019. DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains. Prog. Earth Planet. Sci., 6(1): 61. DOI: 10.1186/s40645-019-0304-z
  54. Tanaka, H. 1985. Global energetics analysis by expansion into three-dimensional normal-mode functions during the FGGE winter. J. Meteor. Soc. Japan, 63: 180200. DOI: 10.2151/jmsj1965.63.2_180
  55. Tanaka, H and Ji, Q. 1995. Comparative energetics of FGGE re-analyses using the normal mode expansion. J. Meteor. Soc. Japan, 73: 112. DOI: 10.2151/jmsj1965.73.1_1
  56. Tanaka, H and Kimura, K. 1996. Normal-mode energetics analysis and the intercomparison for the recent ECMWF, NMC, and JMA global analyses. J. Meteor. Soc. Japan, 74: 525538. DOI: 10.2151/jmsj1965.74.4_525
  57. Tanaka, HL and Kung, EC. 1988. Normal mode energetics of the general circulation during the FGGE year. J. Atmos. Sci., 45: 37233737. DOI: 10.1175/1520-0469(1988)045<;3723:NMEOTG>2.0.CO;2
  58. Tanaka, HL, Kung, EC and Baker, W. 1986. Energetics analysis of the observed and simulated general circulation using three-dimensional normal mode expansions. Tellus A, 38: 412428. DOI: 10.3402/tellusa.v38i5.11728
  59. Taylor, MA, Guba, O, Steyer, A, Ullrich, PA, Hall, DM and Eldred, C. 2020. An energy consistent discretization of the nonhydrostatic equations in primitive variables. J. Adv. Model. Earth Syst., 12(1): e2019MS001783. DOI: 10.1029/2019MS001783
  60. Terasaki, K, Tanaka, H and Žagar, N. 2011. Energy spectra of Rossby and gravity waves. SOLA, 11: 4548. DOI: 10.2151/sola.2011-012
  61. VanZandt, TE. 1982. A universal spectrum of buoyancy waves in the atmosphere. Geophys. Res. Lett., 9(5): 575578. DOI: 10.1029/GL009i005p00575
  62. Wedi, NP and Co-authors. 2020. A baseline for global weather and climate simulations at 1 km resolution. J. Adv. Mod. Earth Sys., 12(11). DOI: 10.1029/2020MS002192
  63. Williamson, DL, Olson, JG, Hannay, C, Toniazzo, T, Taylor, M and Yudin, V. 2015. Energy considerations in the Community Atmosphere Model (CAM). J. Adv. Mod. Earth Sys., 7(3): 11781188. DOI: 10.1002/2015MS000448
  64. Xie, P, Joyce, R, Wu, S, Yoo, S-H, Yarosh, Y, Sun, F and Lin, R. 2019. NOAA CDR Program, NOAA Climate Data Record (CDR) of CPC Morphing Technique (CMORPH) High Resolution Global Precipitation Estimates, Version 1 30 min 8 km. NOAA National Centers for Environmental Information. Last accessed: May 7, 2021. DOI: 10.25921/w9va-q159
  65. Žagar, N, Jelic, D, Blaauw, M and Bechtold, P. 2017. Energy spectra and inertia-gravity waves in global analyses. J. Atmos. Sci., 74(8): 24472466. DOI: 10.1175/JAS-D-16-0341.1
  66. Žagar, N, Kasahara, A, Terasaki, K, Tribbia, J and Tanaka, H. 2015. Normal-mode function representation of global 3D datasets: open-access software for the atmospheric research community. Geosci. Model Dev., 8: 11691195. DOI: 10.5194/gmd-8-1169-2015
  67. Žagar, N, Terasaki, K and Tanaka, HL. 2012. Impact of the vertical resolution of analysis data on the estimates of large-scale inertio-gravity energy. Mon. Wea. Rev, 140(7): 22972307. DOI: 10.1175/MWR-D-11-00103.1
  68. Žagar, N, Tribbia, J, Anderson, JL and Raeder, K. 2009a. Uncertainties of estimates of inertiagravity energy in the atmosphere. Part I: Intercomparison of four analysis systems. Mon. Wea. Rev, 137(11): 38373857. DOI: 10.1175/2009MWR2815.1
  69. Žagar, N, Tribbia, J, Anderson, JL and Raeder, K. 2009b. Uncertainties of estimates of inertia–gravity energy in the atmosphere. Part II: Large-scale equatorial waves. Mon. Wea. Rev, 137(11): 38583873. DOI: 10.1175/2009MWR2816.1
  70. Zängl, G, Reinert, D, Ripodas, P and Baldauf, M. 2014. The ICON(ICOsahedralNon-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core. Quart. J. Roy. Meteor. Soc., 141: 563579. DOI: 10.1002/qj.2378
  71. Zeman, C, Wedi, NP, Dueben, PD, Ban, N and Schär, C. 2021. Model intercomparison of COSMO5.0 and IFS 45r1 at kilometer-scale grid spacing. Geosci. Mod. Dev., 14(7): 46174639. DOI: 10.5194/gmd-14-4617-2021
  72. Zhou, L, Lin, S-J, Chen, J-H, Harris, LM, Chen, X and Rees, SL. 2019. Toward convectivescale prediction within the Next Generation Global Prediction System. Bull. Amer. Meteor. Soc., 100(7): 12251243. DOI: 10.1175/BAMS-D-17-0246.1
DOI: https://doi.org/10.16993/tellusa.26 | Journal eISSN: 3035-9554
Language: English
Page range: 280 - 299
Submitted on: Dec 18, 2021
Accepted on: Apr 13, 2022
Published on: Apr 26, 2022
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2022 Claudia Christine Stephan, Julia Duras, Lucas Harris, Daniel Klocke, William M. Putman, Mark Taylor, Nils P. Wedi, Nedjeljka Žagar, Florian Ziemen, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.