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Boundary-Layer Meteorology

, Volume 140, Issue 2, pp 177–206 | Cite as

Evaluation of the Diurnal Cycle in the Atmospheric Boundary Layer Over Land as Represented by a Variety of Single-Column Models: The Second GABLS Experiment

  • G. Svensson
  • A. A. M. Holtslag
  • V. Kumar
  • T. Mauritsen
  • G. J. Steeneveld
  • W. M. Angevine
  • E. Bazile
  • A. Beljaars
  • E. I. F. de Bruijn
  • A. Cheng
  • L. Conangla
  • J. Cuxart
  • M. Ek
  • M. J. Falk
  • F. Freedman
  • H. Kitagawa
  • V. E. Larson
  • A. Lock
  • J. Mailhot
  • V. Masson
  • S. Park
  • J. Pleim
  • S. Söderberg
  • W. Weng
  • M. Zampieri
Open Access
Article

Abstract

We present the main results from the second model intercomparison within the GEWEX (Global Energy and Water cycle EXperiment) Atmospheric Boundary Layer Study (GABLS). The target is to examine the diurnal cycle over land in today’s numerical weather prediction and climate models for operational and research purposes. The set-up of the case is based on observations taken during the Cooperative Atmosphere-Surface Exchange Study-1999 (CASES-99), which was held in Kansas, USA in the early autumn with a strong diurnal cycle with no clouds present. The models are forced with a constant geostrophic wind, prescribed surface temperature and large-scale divergence. Results from 30 different model simulations and one large-eddy simulation (LES) are analyzed and compared with observations. Even though the surface temperature is prescribed, the models give variable near-surface air temperatures. This, in turn, gives rise to differences in low-level stability affecting the turbulence and the turbulent heat fluxes. The increase in modelled upward sensible heat flux during the morning transition is typically too weak and the growth of the convective boundary layer before noon is too slow. This is related to weak modelled near-surface winds during the morning hours. The agreement between the models, the LES and observations is the best during the late afternoon. From this intercomparison study, we find that modelling the diurnal cycle is still a big challenge. For the convective part of the diurnal cycle, some of the first-order schemes perform somewhat better while the turbulent kinetic energy (TKE) schemes tend to be slightly better during nighttime conditions. Finer vertical resolution tends to improve results to some extent, but is certainly not the solution to all the deficiencies identified.

Keywords

Diurnal cycle GABLS Model intercomparison Single-column models Turbulence parametrizations 

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • G. Svensson
    • 1
  • A. A. M. Holtslag
    • 2
  • V. Kumar
    • 3
  • T. Mauritsen
    • 4
  • G. J. Steeneveld
    • 2
  • W. M. Angevine
    • 5
    • 6
  • E. Bazile
    • 7
  • A. Beljaars
    • 8
  • E. I. F. de Bruijn
    • 9
  • A. Cheng
    • 10
    • 11
  • L. Conangla
    • 12
  • J. Cuxart
    • 13
  • M. Ek
    • 14
  • M. J. Falk
    • 15
  • F. Freedman
    • 16
  • H. Kitagawa
    • 17
  • V. E. Larson
    • 15
  • A. Lock
    • 18
  • J. Mailhot
    • 19
  • V. Masson
    • 7
  • S. Park
    • 20
  • J. Pleim
    • 21
  • S. Söderberg
    • 22
  • W. Weng
    • 23
  • M. Zampieri
    • 24
  1. 1.Department of MeteorologyStockholm UniversityStockholmSweden
  2. 2.Meteorology and Air Quality SectionWageningen UniversityWageningenThe Netherlands
  3. 3.Department of Geography and Environmental EngineeringJohns Hopkins UniversityBaltimoreUSA
  4. 4.Max Planck Institute for MeteorologyHamburgGermany
  5. 5.CIRES, University of ColoradoBoulderUSA
  6. 6.NOAA ESRLBoulderUSA
  7. 7.CNRM (National Centre for Meteorological Research)–GAME, Météo-France/CNRSToulouseFrance
  8. 8.European Centre for Medium-Range Weather ForecastReadingUK
  9. 9.KNMI, Royal Netherlands Meteorological InstituteDe BiltThe Netherlands
  10. 10.Science Systems and Applications, Inc.HamptonUSA
  11. 11.Langley Research Center, NASAHamptonUSA
  12. 12.Departament de Física AplicadaUniversitat Politècnica de CatalunyaManresaSpain
  13. 13.Departament de Física, Grup de MeteorologiaUniversitat de les Illes BalearsCiutat de MallorcaSpain
  14. 14.NOAA Science Center, National Centers for Environmental Prediction/Environmental Modeling CenterCamp SpringsUSA
  15. 15.Department of Mathematical SciencesUniversity of WisconsinMilwaukeeUSA
  16. 16.San Jose State UniversitySan JoseUSA
  17. 17.Japan Meteorological AgencyTokyoJapan
  18. 18.Met OfficeExeterUK
  19. 19.Meteorological Research Division, Environment CanadaDorvalCanada
  20. 20.Climate and Global Dynamics DivisionNational Center for Atmospheric ResearchBoulderUSA
  21. 21.U.S. Environmental Protection AgencyResearch Triangle ParkUSA
  22. 22.WeatherTech ScandinaviaUppsalaSweden
  23. 23.York UniversityTorontoCanada
  24. 24.ISAC-CNRBolognaItaly

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