Meteorology and Atmospheric Physics

, Volume 116, Issue 1–2, pp 15–26 | Cite as

Atmospheric profiling with the UAS SUMO: a new perspective for the evaluation of fine-scale atmospheric models

  • Stephanie Mayer
  • Anne Sandvik
  • Marius O. Jonassen
  • Joachim Reuder
Original Paper

Abstract

For the first time, unmanned aerial system measurements collected by the small unmanned meteorological observer (SUMO) are used to evaluate atmospheric boundary layer (ABL) parameterization schemes embedded in the Advanced Weather Research and Forecasting model (AR-WRF). Observation sites were located in the vicinity of the almost idealized shaped mountain Hofsjökull, Central Iceland. SUMO profiles provided temperature, relative humidity and wind data to maximum heights of 3 km above ground. Two cases are investigated, one with calm wind conditions and development of a convective ABL and one with moderate winds and gravity waves over Hofsjökull. For the high-resolution simulation with AR-WRF, three two-way nested domains are chosen with a grid size of 9, 3 and 1 km. During its first meteorological test, SUMO has proved its great value for the investigation of the diurnal evolution of the ABL and the identification of mesoscale features residing above the ABL, such as subsidence.

Keywords

Unmanned aerial system ABL Fine-scale numerical simulation ABL parameterization schemes WRF Hofsjökull Central Iceland 

References

  1. Ágústsson H, Ólafsson H (2007) Simulating a severe windstorm in complex terrain. Meteorol Z 16(1):111–122CrossRefGoogle Scholar
  2. Ágústsson H, Cuxart J, Mira A, Ólafsson H (2007) Observations and simulation of katabatic flows during a heatwave in Iceland. Meteorol Z 16(1):99–110CrossRefGoogle Scholar
  3. Ahmadov R, Gerbig C, Kretschmer R, Koerner S, Neininger B, Dolman A, Sarrat C (2007) Mesoscale covariance of transport and CO2 fluxes: Evidence from observations and simulations using the WRF-VPRM coupled atmosphere–biosphere model. J Geophys Res Atmos 112(D22):14CrossRefGoogle Scholar
  4. Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46(20):3077–3107CrossRefGoogle Scholar
  5. Egger J, Bajrachaya S, Heinrich R, Kolb P, Lämmlein S, Mech M, Reuder J, Schäper W, Shakya P, Schween J, Wendt H (2002) Diurnal winds in the Himalayan Kali Gandaki Valley. Part III: remotely piloted aircraft soundings. Mon Weather Rev 130:2042–2058CrossRefGoogle Scholar
  6. Garratt J (1994) The atmospheric boundary layer. Cambridge University Press, CambridgeGoogle Scholar
  7. Hong S, Kim S (2007) Stable boundary layer mixing in a vertical diffusion scheme. The Korea Meteorological Society, Fall conference, Seoul, Korea, Oct 25–26Google Scholar
  8. Hong S, Pan H (1996) Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon Weather Rev 124(10):2322–2339CrossRefGoogle Scholar
  9. Hong S, Dudhia J, Chen S (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132(1):103–120CrossRefGoogle Scholar
  10. Hong S, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134(9):2318–2341CrossRefGoogle Scholar
  11. Holland G, Webster P, Curry J, Tyrell G, Gauntlett D, Brett G, Becker J, Hoag R, Vaglienti W (2001) The Aerosonde robotic aircraft: a new paradigm for environmental observations. Bull Am Meteorol Soc 82(5):889–901CrossRefGoogle Scholar
  12. Janjic Z (1990) The step-mountain coordinate: physical package. Mon Weather Rev 118(7):1429–1443CrossRefGoogle Scholar
  13. Janjic Z (1996) The surface layer in the NCEP eta model. 11th conference on numerical weather prediction, American Meteorological Society, pp 354–355Google Scholar
  14. Janjic Z (2002) Nonsingular implementation of the Mellor-Yamada Level 2.5 Scheme in the NCEP meso models. NCEP Office Note No. 437, 61 pGoogle Scholar
  15. Jonassen M (2008) The small unmanned meteorological observer (SUMO)—characterization and test of a new measurement system for atmospheric boundary layer research. Master’s thesis, Geophysical Institute, University of BergenGoogle Scholar
  16. Konrad T, Hill M, Rowland J, Meyer J (1970) A small, radio-controlled aircraft as a platform for meteorological sensors. Appl Phys Lab Tech Digest 10:11–19Google Scholar
  17. Ma S, Chen H, Wang G, Pan Y, Li Q (2004) A miniature robotic plane meteorological sounding system. Adv Atmos Sci 21(6):890–896CrossRefGoogle Scholar
  18. Mlawer E, Taubman S, Brown P, Iacono M, Clough S (1997) Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102(D14):16,663–16,682CrossRefGoogle Scholar
  19. Pleim J (2007) A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: model description and testing. J Appl Meteorol Climatol 46(9):1383–1395CrossRefGoogle Scholar
  20. Reuder J, Ablinger M, Águstsson H, Brisset P, Brynjólfsson S, Garhammer M, Johannesson T, Jonassen M, Kühnel R, Lämmlein S, de Lange T, Lindenberg C, Malardel S, Mayer S, Müller M, Ólafsson H, Rögnvaldsson O, Schäper W, Spengler T, Zängl G, Egger J (2009a) FLOHOF 2007: an overview of the mesoscale meteorological field campaign at Hofsjökull, Central Iceland. Meteorol Atmos Phys (this issue)Google Scholar
  21. Reuder J, Brisset P, Jonassen M, Müller M, Mayer S (2009b) The small unmanned meteorological observer SUMO: a new tool for atmospheric boundary layer research. Meteorol Z 18(2):141–147CrossRefGoogle Scholar
  22. Sandvik A, Furevik B (2002) Case study of a coastal jet at Spitsbergen—comparison of SAR and model estimated wind. Mon Weather Rev 130:1040–1051CrossRefGoogle Scholar
  23. Skamarock W, Klemp J, Dudhia J, Gill D, Barker D, Wang W, Powers J (2005) A description of the advanced research WRF version 2. NCAR Tech Notes 468+ STRGoogle Scholar
  24. Spiess T, Bange J, Buschmann M, Vörsmann P (2007) First application of the meteorological Mini-UAV M2AV. Meteorol Z 16(2):159–169CrossRefGoogle Scholar
  25. Steeneveld G, Mauritsen T, de Bruijn E, Vilà-Guerau de Arellano J, Svensson G, Holtslag A (2008) Evaluation of limited-area models for the representation of the diurnal cycle and contrasting nights in CASES-99. J Appl Meteorol Climatol 47(3):869–887CrossRefGoogle Scholar
  26. Stensrud D (2007) Parameterization schemes: keys to understanding numerical weather prediction models. Cambridge University Press, CambridgeGoogle Scholar
  27. Stull R (1988) An introduction to boundary layer meteorology. Kluwer Academic Publishers, DordrechtGoogle Scholar
  28. Teixeira J, Stevens B, Bretherton C, Cederwall R, Doyle J, Golaz J, Holtslag A, Klein S, Lundquist J, Randall D, Siebesma A, Soares P (2008) Parameterization of the atmospheric boundary layer: a view from just above the inversion. Bull Am Meteorol Soc 89(4):453–458CrossRefGoogle Scholar
  29. Troen I, Mahrt L (1986) A simple model of the atmospheric boundary layer; sensitivity to surface evaporation. Bound Layer Meteorol 37:129–148CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Stephanie Mayer
    • 1
  • Anne Sandvik
    • 2
  • Marius O. Jonassen
    • 1
  • Joachim Reuder
    • 1
  1. 1.Geophysical InstituteUniversity of BergenBergenNorway
  2. 2.Institute of Marine ResearchBergenNorway

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