Skip to main content
Log in

Investigation of the atmospheric surface layer using a novel high-resolution sensor array

  • Research Article
  • Published:
Experiments in Fluids Aims and scope Submit manuscript

Abstract

Representing land-atmosphere exchange processes as lower boundary conditions remains a challenge in numerical weather predictions. One important reason is the lack of understanding of heterogeneities in topography, land cover, stability, and their effects on all aspects of the flow field and scalar transport. Well-resolved flow measurements can shed light on these near-surface processes, yielding improved modeling approaches. Yet, it is precisely the heterogeneous characteristics in question—along with the large separation of scales—that make field measurements notoriously challenging. To address some of the difficulties encountered in probing the atmospheric surface layer, a unique and economically scalable field measurement platform was designed around the nanoscale thermal anemometry probe technology, which has previously been used successfully at high Reynolds numbers in laboratory settings. The small size of the nanoscale sensors not only provides a high spatial resolution but also allows for velocity and temperature measurements with the same constant current operating circuit. This operating mode is more economical and straightforward to construct than conventional constant temperature anemometry systems, providing a scalable platform for multi-point measurements. The measurement platform was deployed at the Surface Layer Turbulence and Environmental Science Test site in Utah’s West Desert as part of the Idealised horizontal Planar Array study for Quantifying Surface heterogeneity. Streamwise velocity and temperature data were acquired within the first meter above ground with good agreement in spectral behavior to well-known scaling laws in wall-bounded flows.

Graphic Abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  • Arwatz G, Fan Y, Bahri C, Hultmark M (2015) Development and characterization of a nano-scale temperature sensor (T-NSTAP) for turbulent temperature measurements. Meas Sci Technol 26(3):035103

    Article  Google Scholar 

  • Ashok A, Bailey SCC, Hultmark M, Smits AJ (2012) Hot-wire spatial resolution effects in measurements of grid-generated turbulence. Exp fluids 53(6):1713–1722

    Article  Google Scholar 

  • Avissar R, Schmidt T (1998) An evaluation of the scale at which ground-surface heat flux patchiness affects the convective boundary layer using large-eddy simulations. J Atmos Sci 55(16):2666–2689

    Article  Google Scholar 

  • Bailey SCC, Kunkel GJ, Hultmark M, Vallikivi M, Hill JP, Meyer KA, Tsay C, Arnold CB, Smits AJ (2010) Turbulence measurements using a nanoscale thermal anemometry probe. J Fluid Mech 663:160–179

    Article  MATH  Google Scholar 

  • Banerjee T, Katul GG (2013) Logarithmic scaling in the longitudinal velocity variance explained by a spectral budget. Phys Fluids 25(12):125106

    Article  Google Scholar 

  • Banerjee T, Katul GG, Salesky ST, Chamecki M (2015) Revisiting the formulations for the longitudinal velocity variance in the unstable atmospheric surface layer. Quart J R Meteorol Soc 141(690):1699–1711

    Article  Google Scholar 

  • Bodenschatz E, Bewley GP, Nobach H, Sinhuber M, Xu H (2014) Variable density turbulence tunnel facility. Rev Sci Instrum 85(9):093908

    Article  Google Scholar 

  • Bruun HH (1996) Hot-wire anemometry: principles and signal analysis. IOP Publishing, Bristol

    Google Scholar 

  • Byers CP, Fu MK, Fan Y, Hultmark M (2018) Development of instrumentation for measurements of two components of velocity with a single sensing element. Meas Sci Technol 29(2):025304

    Article  Google Scholar 

  • Calaf M, Hultmark M, Oldroyd HJ, Simeonov V, Parlange MB (2013) Coherent structures and the \(k^{-1}\) spectral behaviour. Phys Fluids 25(12):125107

    Article  Google Scholar 

  • Chow FK, Weigel AP, Street RL, Rotach MW, Xue M (2006) High-resolution large-eddy simulations of flow in a steep Alpine valley. J Appl Meteorol Climatol 45(1):63–86

    Article  Google Scholar 

  • Comte-Bellot G (1976) Hot-wire anemometry. Annu Rev Fluid Mech 8(1):209–231

    Article  Google Scholar 

  • Desai AR, Davis KJ, Senff CJ, Ismail S, Browell EV, Stauffer DR, Reen BP (2006) A case study on the effects of heterogeneous soil moisture on mesoscale boundary-layer structure in the southern Great Plains, USA. Bound Layer Meteorol 119(2):195–238

    Article  Google Scholar 

  • Dryden HL, Kuethe AM (1929) The measurement of fluctuations of air speed by the hot-wire anemometer. US Government Printing Office

  • ECMWF SP, (2014) IFS documentation CY40R1 part IV: Physical processes. ECMWF, Reading, UK, pp 111–113

  • Emes MJ, Arjomandi M, Kelso RM, Ghanadi F (2019) Turbulence length scales in a low-roughness near-neutral atmospheric surface layer. J Turbul 20(9):545–562

    Article  MathSciNet  Google Scholar 

  • Fan Y, Arwatz G, Van Buren TW, Hoffman DE, Hultmark M (2015) Nanoscale sensing devices for turbulence measurements. Exp Fluids 56(7):138

    Article  Google Scholar 

  • Hultmark M, Smits AJ (2010) Temperature corrections for constant temperature and constant current hot-wire anemometers. Meas Sci Technol 21(10):105404

    Article  Google Scholar 

  • Hultmark M, Vallikivi M, Bailey SCC, Smits AJ (2013) Logarithmic scaling of turbulence in smooth-and rough-wall pipe flow. J Fluid Mech 728:376–395

    Article  MATH  Google Scholar 

  • Hutchins N, Chauhan K, Marusic I, Monty J, Klewicki J (2012) Towards reconciling the large-scale structure of turbulent boundary layers in the atmosphere and laboratory. Bound Layer Meteorol 145(2):273–306

    Article  Google Scholar 

  • Jensen DD, Nadeau DF, Hoch SW, Pardyjak ER (2016) Observations of near-surface heat-flux and temperature profiles through the early evening transition over contrasting surfaces. Bound Layer Meteorol 159(3):567–587

    Article  Google Scholar 

  • Kader BA, Yaglom AM (1991) Spectra and correlation functions of surface layer atmospheric turbulence in unstable thermal stratification. In: Turbulence and Coherent Structures. Fluid Mechanics and Its Applications, vol 2. Springer, Dordrecht

  • Kaimal JCJ (1973) Turbulenece spectra, length scales and structure parameters in the stable surface layer. Bound Layer Meteorol 4(1–4):289–309

    Article  Google Scholar 

  • Kaimal JCJ, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Quart J R Meteorol Soc 98(417):563–589

    Article  Google Scholar 

  • Kannuluik WG, Carman EH (1951) The temperature dependence of the thermal conductivity of air. Aust J Chem 4(3):305–314

    Article  Google Scholar 

  • Katul GG, Chu CR, Parlange MB, Albertson JD, Ortenburger TA (1995a) Low-wavenumber spectral characteristics of velocity and temperature in the atmospheric surface layer. J Geophys Res Atmos 100(D7):14243–14255

    Article  Google Scholar 

  • Katul GG, Goltz SM, Hsieh CI, Cheng Y, Mowry F, Sigmon J (1995b) Estimation of surface heat and momentum fluxes using the flux-variance method above uniform and non-uniform terrain. Bound Layer Meteorol 74(3):237–260

    Article  Google Scholar 

  • Katul GG, Porporato A, Nikora V (2012) Existence of \(k^{-1}\) power-law scaling in the equilibrium regions of wall-bounded turbulence explained by Heisenberg’s eddy viscosity. Phys Rev E 86(6):066311

    Article  Google Scholar 

  • Kit E, Cherkassky A, Sant T, Fernando HJS (2010) In situ calibration of hot-film probes using a collocated sonic anemometer: Implementation of a neural network. J Atmos Ocean Technol 27(1):23–41

    Article  Google Scholar 

  • Klewicki JC, Foss JF, Wallace JM (1998) High Reynolds number [\(R_\theta = \text{O} (10^6)\)] boundary layer turbulence in the atmospheric surface layer above western Utah’s salt flats. In: Flow at Ultra-High Reynolds and Rayleigh Numbers. Springer, New York

  • Kunkel GJ, Marusic I (2006) Study of the near-wall-turbulent region of the high-Reynolds-number boundary layer using an atmospheric flow. J Fluid Mech 548:375–402

    Article  Google Scholar 

  • Li D, Katul GG, Bou-Zeid E (2015) Turbulent energy spectra and cospectra of momentum and heat fluxes in the stable atmospheric surface layer. Bound Layer Meteorol 157(1):1–21

    Article  Google Scholar 

  • Li D, Katul GG, Gentine P (2016) The \(k^{-1}\) scaling of air temperature spectra in atmospheric surface layer flows. Quart J R Meteorol Soc 142(694):496–505

    Article  Google Scholar 

  • Ligrani PM, Moffat RJ (1986) Structure of transitionally rough and fully rough turbulent boundary layers. J Fluid Mech 162:69–98

    Article  MathSciNet  Google Scholar 

  • Marusic I, Kunkel GJ (2003) Streamwise turbulence intensity formulation for flat-plate boundary layers. Phys Fluids 15(8):2461–2464

    Article  MATH  Google Scholar 

  • Marusic I, Monty JP, Hultmark M, Smits AJ (2013) On the logarithmic region in wall turbulence. J Fluid Mech 716:R3

    Article  MathSciNet  MATH  Google Scholar 

  • Metzger MM (2003) Scalar dispersion in high Reynolds number turbulent boundary layers. PhD thesis, University of Utah

  • Metzger MM, Klewicki JC (2001) A comparative study of near-wall turbulence in high and low Reynolds number boundary layers. Phys Fluids 13(3):692–701

    Article  MATH  Google Scholar 

  • Metzger MM, McKeon BJ, Holmes H (2007) The near-neutral atmospheric surface layer: turbulence and non-stationarity. Philos Trans R Soc A Math Phys Eng Sci 365(1852):859–876

    Article  MATH  Google Scholar 

  • Mironov DV, Sullivan PP (2016) Second-moment budgets and mixing intensity in the stably stratified atmospheric boundary layer over thermally heterogeneous surfaces. J Atmos Sci 73(1):449–464

    Article  Google Scholar 

  • Morrison JF, Jiang W, McKeon BJ, Smits AJ (2002) Reynolds number dependence of streamwise velocity spectra in turbulent pipe flow. Phys Rev Lett 88(21):214501

    Article  Google Scholar 

  • Morrison T, Calaf M, Higgins C, Drake SA, Perelet A, Pardyjak E (2021) The impact of surface temperature heterogeneity on near-surface heat transport, Boundary-Layer Meteor. accepted 

  • Nickels TB, Marusic I, Hafez S, Chong MS (2005) Evidence of the \(k_1^{-1}\) law in a high-Reynolds-number turbulent boundary layer. Phys Rev Lett 95(7):074501

    Article  Google Scholar 

  • Ookouchi Y, Segal M, Kessler RC, Pielke RA (1984) Evaluation of soil moisture effects on the generation and modification of mesoscale circulations. Mon Weather Rev 112(11):2281–2292

    Article  Google Scholar 

  • Perry AE, Abell CJ (1975) Scaling laws for pipe-flow turbulence. J Fluid Mech 67(2):257–271

    Article  Google Scholar 

  • Perry AE, Abell CJ (1977) Asymptotic similarity of turbulence structures in smooth-and rough-walled pipes. J Fluid Mech 79(4):785–799

    Article  Google Scholar 

  • Perry AE, Li JD (1990) Experimental support for the attached-eddy hypothesis in zero-pressure-gradient turbulent boundary layers. J Fluid Mech 218:405–438

    Article  Google Scholar 

  • Perry AE, Henbest S, Chong MS (1986) A theoretical and experimental study of wall turbulence. J Fluid Mech 165:163–199

    Article  MathSciNet  MATH  Google Scholar 

  • Perry AE, Marusic I, Li JD (1994) Wall turbulence closure based on classical similarity laws and the attached eddy hypothesis. Phy Fluids 6(2):1024–1035

    Article  MATH  Google Scholar 

  • Pope SB (2001) Turbulent flows. IOP Publishing, Bristol

    MATH  Google Scholar 

  • Rosenberg BJ, Hultmark M, Vallikivi M, Bailey SCC, Smits AJ (2013) Turbulence spectra in smooth-and rough-wall pipe flow at extreme Reynolds numbers. J Fluid Mech 731:46–63

    Article  MATH  Google Scholar 

  • Samie M, Marusic I, Hutchins N, Fu MK, Fan Y, Hultmark M, Smits AJ (2018) Fully resolved measurements of turbulent boundary layer flows up to \(Re_\tau =\) 20000. J Fluid Mech 851:391–415

    Article  MathSciNet  MATH  Google Scholar 

  • Schlichting H (1968) Boundary layer theory, vol 960. Springer, Berlin

    MATH  Google Scholar 

  • Seuffert G, Gross P, Simmer C, Wood EF (2002) The influence of hydrologic modeling on the predicted local weather: Two-way coupling of a mesoscale weather prediction model and a land surface hydrologic model. J Hydrometeorol 3(5):505–523

    Article  Google Scholar 

  • Sinhuber M, Bodenschatz E, Bewley GP (2015) Decay of turbulence at high R eynolds numbers. Phys Revi Lett 114(3):034501

    Article  Google Scholar 

  • Smits AJ, McKeon BJ, Marusic I (2011) High-Reynolds number wall turbulence. Annu Rev Fluid Mech 43:418–428

    Article  MATH  Google Scholar 

  • Stensrud DJ (2009) Parameterization schemes: keys to understanding numerical weather prediction models. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Stull RB (2012) An introduction to boundary layer meteorology, vol 13. Springer Science & Business Media, Berlin

    MATH  Google Scholar 

  • Tchen CM (1953) On the spectrum of energy in turbulent shear flow. J Res Natl Bur Stand 50(1):51–62

    Article  MATH  Google Scholar 

  • Tchen CM (1954) Transport processes as foundations of the Heisenberg and Obukhoff theories of turbulence. Phys Rev 93(1):4

    Article  MathSciNet  MATH  Google Scholar 

  • Tropea C, Yarin AL (2007) Springer handbook of experimental fluid mechanics. Springer Science & Business Media, Berlin

    Book  Google Scholar 

  • Vallikivi M, Smits AJ (2014) Fabrication and characterization of a novel nanoscale thermal anemometry probe. J Microelectromechanical syst 23(4):899–907

    Article  Google Scholar 

  • Vallikivi M, Ganapathisubramani B, Smits AJ (2015) Spectral scaling in boundary layers and pipes at very high Reynolds numbers. J Fluid Mech 771:303–326

    Article  Google Scholar 

  • Wamser C, Peters G, Lykossov VN (1997) The frequency response of sonic anemometers. Bound Layer Meteorol 84(2):231–246

    Article  Google Scholar 

  • Wyngaard JC (1992) Atmospheric turbulence. Annu Rev Fluid Mech 24(1):205–234

    Article  MATH  Google Scholar 

  • Wyngaard JC, Coté OR (1972) Cospectral similarity in the atmospheric surface layer. Quart J R Meteorol Soc 98(417):590–603

    Article  Google Scholar 

  • Yavuzkurt S (1984) A guide to uncertainty analysis of hot-wire data. J Fluids Eng 106(2):181–186

Download references

Acknowledgements

This work was supported by the NSF AGS-1649049 (Program manager: Dr. JS). KYH and CEB were supported by the Department of Defense (DoD) through the National Defense Science and Engineering Graduate Fellowship (NDSEG) Program. The authors would like to thank Prof. Clayton Byers and Agastya Parikh for their assistance with the CCA circuit design, Alexander Piqué for providing support in the field, and Princeton University’s clean room staff for their assistance in manufacturing the sensors.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Y. Huang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, K.Y., Brunner, C.E., Fu, M.K. et al. Investigation of the atmospheric surface layer using a novel high-resolution sensor array. Exp Fluids 62, 76 (2021). https://doi.org/10.1007/s00348-021-03173-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00348-021-03173-z

Navigation