Advertisement

Boundary-Layer Meteorology

, Volume 155, Issue 2, pp 189–208 | Cite as

Methods for Evaluating the Temperature Structure-Function Parameter Using Unmanned Aerial Systems and Large-Eddy Simulation

  • Charlotte E. Wainwright
  • Timothy A. Bonin
  • Phillip B. Chilson
  • Jeremy A. Gibbs
  • Evgeni Fedorovich
  • Robert D. Palmer
Article

Abstract

Small-scale turbulent fluctuations of temperature are known to affect the propagation of both electromagnetic and acoustic waves. Within the inertial-subrange scale, where the turbulence is locally homogeneous and isotropic, these temperature perturbations can be described, in a statistical sense, using the structure-function parameter for temperature, \(C_{T}^2\). Here we investigate different methods of evaluating \(C_{T}^2\), using data from a numerical large-eddy simulation together with atmospheric observations collected by an unmanned aerial system and a sodar. An example case using data from a late afternoon unmanned aerial system flight on April 24 2013 and corresponding large-eddy simulation data is presented and discussed.

Keywords

Large-eddy simulation Sodar Structure-function parameter  Unmanned aerial system 

Notes

Acknowledgments

The National Science Foundation (NSF) is acknowledged for the support of the reported study through the Grant ATM-1016153. The authors acknowledge the three anonymous reviewers whose suggestions substantially improved the manuscript.

References

  1. Asimakopoulos DN, Cole RS, Caughey SJ, Crease BA (1976) A quantitative comparison between acoustic sounder returns and the direct measurement of atmospheric temperature fluctuations. Boundary-Layer Meteorol 19:137–147Google Scholar
  2. Balsley BB (2008) The cires tethered lifting sysytem: a survey of the system, past results, and future capabilities. Acta Geophys 56(1):21–57CrossRefGoogle Scholar
  3. Bonin TA, Chilson PB, Zielke B, Fedorovich E (2012) Observations of early evening boundary layer transitions using a small unmanned aerial system. Boundary-Layer Meteorol 2:1–14. doi: 10.1007/s10546-012-9760-3 Google Scholar
  4. Bonin TA, Chilson PB, Zielke BS, Klein PM, Leeman JR (2013) Comparison and application of wind retrieval algorithms for small unmanned aerial systems. Geosci Instrum Method Data Syst 2:177–187CrossRefGoogle Scholar
  5. Bonin TA, Goines D, Scott A, Wainwright CE, Gibbs JA, Chilson PB (2015) Measuring structure function parameters with a small unmanned aerial system. Boundary-Layer Meteorol, (in press)Google Scholar
  6. Cheinet S, Cumin P (2011) Local structure parameters of temperature and humidity in the entrainment-drying convective boundary layer: a large-eddy simulation analysis. J Appl Meteorol Climatol 50(2):472–481CrossRefGoogle Scholar
  7. Cheinet S, Siebesma AP (2009) Variability of local structure parameters in the convective boundary layer. J Atmos Sci 66(4):1002–1017CrossRefGoogle Scholar
  8. Deardorff JW (1980) Stratocumulus-capped mixed layer derived from a three-dimensional model. Boundary-Layer Meteorol 18:495–527CrossRefGoogle Scholar
  9. Fedorovich E, Nieuwstadt FTM, Kaiser R (2001) Numerical and laboratory study of horizontally evolving convective boundary layer. Part I: transition regimes and development of the mixed layer. J Atmos Sci 58:70–86CrossRefGoogle Scholar
  10. Fedorovich E, Conzemius R, Esau I, Chow FK, Lewellen D, Moeng CH, Pino D, Sullivan P, de Arellano JVG (2004a) Entrainment into sheared convective boundary layers as predicted by different large eddy simulation codes. In: Preprints, 16th Symposium on boundary layers and turbulence. American Meteorological Society, 9–13 August, Portland, Maine, USA, pp CD-ROM, P4.7Google Scholar
  11. Fedorovich E, Conzemius R, Mironov D (2004b) Convective entrainment into a shear-free, linearly stratified atmosphere: bulk models reevaluated through large eddy simulations. J Atmos Sci 61:281–295CrossRefGoogle Scholar
  12. Frehlich R (1992) Laser scintillation measurements of the temperature spectrum in the atmospheric surface layer. J Atmos Sci 49(16):1494–1509CrossRefGoogle Scholar
  13. Gibbs J, Fedorovich E (2014) Comparison of convective boundary layer velocity spectra retrieved from large eddy simulation and weather research and forecasting model data. J Appl Meteorol Climatol 53(2):377–394CrossRefGoogle Scholar
  14. Gibbs JA, Fedorovich E, van Eijk AMJ (2011) Evaluating weather research and forecasting (WRF) model predictions of turbulent flow parameters in a dry convective boundary layer. J Appl Meteorol Climatol 50(12):2429–2444CrossRefGoogle Scholar
  15. Gur’yanov AE, Kallistratova MA, Martvel FE, Pequr MS, Petenko IV, Time NS (1987) Comparision of sodar and microfluctuation measurements of the temperature structure parameter in mountainous terrain. Atmos Ocean Phys 23(9):685–691Google Scholar
  16. Gur’yanov AE, Kallistratova MA, Kutyrev AS, Petenko IV, Shcheglov PV, Tokovinin AA (1992) The contribution of the lower atmospheric layers to the seeing at some mountain observatories. Astron Astrophys 262:373–381Google Scholar
  17. Holland GJ, adn JA, Curry PJW, 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 82:889–901CrossRefGoogle Scholar
  18. ISO9613-1 S Geneva (1993) Acoustics—attenuation of sound during propagation outdoors—part 1: calculation of the absorption of sound by the atmosphere. ISO9613-1:1993(E)Google Scholar
  19. Kaimal JC, Businger JA (1963) A continuous wave sonic anemometer-thermometer. J Appl Meteorol 2:156–164CrossRefGoogle Scholar
  20. Kumar MS, Anandan VK, Kesarkar A, Narasimha PN (2011) Doppler sodar observations of the temperature structure parameter during moonsoon season over a tropical rural station, Gadanki. J Earth Syst Sci 120(1):65–72CrossRefGoogle Scholar
  21. Kunkel KE, Walters DL, Ely GA (1981) Behavior of the temperature structure parameter in a desert basin. J Appl Meteorol 20(2):130–136CrossRefGoogle Scholar
  22. Little CG (1969) Acoustic methods for the remote probing of the lower atmosphere. Proc IEEE 57:571–578CrossRefGoogle Scholar
  23. Maronga B, Moene AF, van Dinther D, Raasch S, Bosveld FC, Gioli B (2013) Derivation of structure parameters of temperature and humidity in the convective boundary layer from large eddy simulations and implications for the interpretation of scintillometer observations. Boundary-Layer Meteorol 148(1):1–30CrossRefGoogle Scholar
  24. Mesinger F, DiMego G, Kalnay E, Mitchell K, Shafran PC, Ebisuzaki W, Woollen J, Jović D, Rogers E, Berbery EH, Ek MB, Fan Y, Grumbine R, Higgins W, Li H, Lin Y, Manikin G, Parrish D, Shi W (2006) North american regional reanalysis. Bull Am Meteorol Soc 87(3):343–360CrossRefGoogle Scholar
  25. Muschinski A, Sullivan PP, Wuertz DB, Hill RJ, Cohn SA, Lenschow DH, Doviak RJ (1999) First synthesis of wind-profiler signals on the basis of large-eddy simulation data. Radio Sci 34(6):1437–1459Google Scholar
  26. Neff WD (1975) Quantitative evaluation of acoustic echoes from the planetary boundary layer. J Atmos Sci 36:1820–1821Google Scholar
  27. Peltier LJ, Wyngaard JC (1995) Structure-function parameters in the convective boundary layer from large-eddy simulation. J Atmos Sci 52(21):3641–3660CrossRefGoogle Scholar
  28. Petenko I, Argentini S, Pietroni S, Viola A, Mastrantonio G, Casasanta G, Arisitidi E, Bouchez G, Agabi A, Bondoux E (2014a) Observations of optically active turbulence in the planetary boundary layer by sodar at the Concordia astronomical observatory, Dome C. Antarctica. Astron Astrophys 568:A44CrossRefGoogle Scholar
  29. Petenko I, Mastrantonio G, Viola A, Argentini S, Pietroni I (2014b) Some statistics of the temperature structure parameter in the convective boundary layer observed by sodar. Boundary-Layer Meteorol 150(2):215–233CrossRefGoogle Scholar
  30. Readings CJ, Butler HE (1972) The measurement of atmospheric turbulence from a captive balloon. Meteorol Mag 101:286–298Google Scholar
  31. Scipión DE, Chilson PB, Fedorovich E, Palmer RD (2008) Evaluation of an LES-based wind profiler simulator for observations of a daytime atmospheric convective boundary layer. J Atmos Ocean Technol 25:1423–1436CrossRefGoogle Scholar
  32. Shuqing M, Hongbin C, Gai W, Yi P, Qiang L (2004) A miniature robotic plane meteorological sounding system. Adv Atmos Sci 21(6):890–896CrossRefGoogle Scholar
  33. Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Wang W, Powers JG (2008) A description of the advanced research WRF version 3. Tech. Rep, NCAR, USAGoogle Scholar
  34. Spiess T, Bange J, Buschmann M, Vörsmann P (2007) First application of the meteorological Mini-UAV ‘M2AV’. Meteorol Z 16:159–169CrossRefGoogle Scholar
  35. Tatarskii VI (1961) Wave propagation in a turbulent medium. McGraw-Hill, New York 285 ppGoogle Scholar
  36. Tatarskii VI (1971) The effects of the turbulent atmosphere on wave propagation. Kefer Press, Jerusalem 472 ppGoogle Scholar
  37. Taylor GI (1938) The spectrum of turbulence. Proc R Soc Ser A 164:476–490CrossRefGoogle Scholar
  38. Thomson D, Coulter R, Warhaft Z (1978) Simulataneous measurements of turbulence in the lower atmosphere using sodar and aircraft. J Appl Meteorol 17:723–734CrossRefGoogle Scholar
  39. Travouillon T, Ashley MCB, Burton MG, Storey JWV, Loewenstein RF (2003) Atmospheric turbulence at the South Pole and its implications for astronomy. Astron Astrophys 400:1163–1172CrossRefGoogle Scholar
  40. Tunick A (2005) Toward increasing the accuracy and realism of future optical turbulence calculations. Meteorol Atmos Phys 90:159–164CrossRefGoogle Scholar
  41. van den Kroonenberg A, Martin T, Buschmann M, Bange J, Vörsmann P (2008) Measuring the wind vector using the Autonomous Mini Aerial Vehicle M2AV. J Atmos Ocean Technol 25:1969–1982CrossRefGoogle Scholar
  42. van den Kroonenberg AC, Martin S, Beyrich F, Bange J (2012) Spatially-averaged temperature structure parameter over a heterogeneous surface measured by an Unmanned Aerial Vehicle. Boundary-Layer Meteorol 142:55–77CrossRefGoogle Scholar
  43. Weill A, Klapisz C, Strauss B, Baudin F, Jaupart C, Grunderbeeck PV, Goutorbe JP (1980) Measuring heat flux and structure functions of temperature fluctuations with an acoustic doppler sodar. J Appl Meteorol 19:199–205CrossRefGoogle Scholar
  44. Wilson C, Fedorovich E (2012) Direct evaluation of refractive-index structure functions from large-eddy simulation output for atmospheric convective boundary layers. Acta Geophys 60(5):1474–1492CrossRefGoogle Scholar
  45. Wood CR, Kouznetsov RD, Gierens R, Nordbo A, Järvi L, Kallistratova MA, Kukkonen J (2013) On the temperature structure parameter and sensible heat flux over Helsinki from sonic anemometry and scintillometry. J Atmos Oceanic Technol 30(8):1604–1615CrossRefGoogle Scholar
  46. Wyngaard JC, Izumi YSA, Collins J (1971) Behavior of the refractive-index-structure parameter near the ground. J Opt Soc Am 61(12):1646–1650CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Charlotte E. Wainwright
    • 1
  • Timothy A. Bonin
    • 2
  • Phillip B. Chilson
    • 1
  • Jeremy A. Gibbs
    • 2
  • Evgeni Fedorovich
    • 2
  • Robert D. Palmer
    • 1
  1. 1.Advanced Radar Research Center and School of MeteorologyUniversity of OklahomaNormanUSA
  2. 2.School of MeteorologyUniversity of OklahomaNormanUSA

Personalised recommendations