Boundary-Layer Meteorology

, Volume 171, Issue 1, pp 79–99 | Cite as

An Assessment of Eddy-Covariance-Based Surface Fluxes Above an Evaporating Heated Surface Under Fair-Weather Daytime Conditions

  • Song-Lak KangEmail author
Research Article


Above an evaporating heated surface under fair-weather daytime conditions, the cospectra between the vertical velocity component, temperature, and water-vapour mixing ratio should be positive. We have applied a multi-resolution technique to a 3.64-h long, 10-Hz time series centred at midday for 16 fair-weather days at a mid-latitude site during spring to measure the averaging period τc at which the crossover from the domain of the three positive cospectra to a mixed-sign domain occurs. The τc values broadly range from 9 to 42 min, with 13 of the 16 days having values less than 30 min. When mesoscale circulations induced by surface heterogeneity are likely to be present, the vertical heat (or moisture) flux computed with the conventional averaging period of 30 min τ30 is as large (or small) as 1.09 (or 0.78) times that using τc. However, on 14 (or 13) days, the vertical heat (or moisture) fluxes using the period τc are explained by those calculated with the period τ30 within a difference range of ± 1%. The insignificant difference is due to the insensitivity of the fluxes to the averaging period at scales larger than approximately 7 min. Therefore, despite a broad range of τc values, the 30-min-averaged surface fluxes can be treated as the required turbulent fluxes. Although this finding is not robust, given that data were collected at one location over 16 days, it supports the use of 30-min-averaged surfaces fluxes, particularly for the composite midday fluxes on fair-weather days.


Averaging period Composite midday fluxes Eddy covariance Multi-resolution technique Positive cospectral domain 



This work was supported by the National Research Foundation of Korea (NRF) grand funded by the Korea government Ministry of Science and ICT (MSIT) (No. NRF-2018R1A2B6008631). The author also thanks those who collected the surface dataset at the Boulder Atmospheric Observatory (BAO) site during the XPIA field campaign.


  1. Alekseychik P, Mammarella I, Karpov D, Dengel S, Terentieva I, Sabrekov A, Glagolev M, Lapshina E (2017) Net ecosystem exchange and energy fluxes measured with the eddy covariance technique in a western Siberian bog. Atmos Chem Phys 17:9333–9345CrossRefGoogle Scholar
  2. Arya PS (1989) Introduction to micrometeorology. Academic Press, LondonGoogle Scholar
  3. Aubinet M, Vesala T, Papale D (2012) Eddy covariance: a practical guide to measurement and data analysis. Springer, New YorkCrossRefGoogle Scholar
  4. Charuchittipan D, Babel W, Mauder M, Leps JP, Foken T (2014) Extension of the averaging time in eddy-covariance measurements and its effect on the energy balance closure. Boundary-Layer Meteorol 152:303–327CrossRefGoogle Scholar
  5. de Roode SR, Duynkerke PG, Jonker HJJ (2004) Large-eddy simulation: how large is large enough? J Atmos Sci 61:403–421CrossRefGoogle Scholar
  6. Desjardins RL, Macpherson JI, Schuepp PH, Karanja F (1989) An evaluation of aircraft flux measurements of CO2, water vapor and sensible heat. Boundary-Layer Meteorol 47:55–69CrossRefGoogle Scholar
  7. Finnigan JJ, Clement R, Malhi Y, Leuning R, Cleugh HA (2003) A re-evaluation of long-term flux measurement techniques part I: averaging and coordinate rotation. Boundary-Layer Meteorol 107:1–48CrossRefGoogle Scholar
  8. Foken T, Wimmer MF, Thomas C, Liebethal C (2006) Some aspects of the energy balance closure problem. Atmos Chem Phys 6:4395–4402CrossRefGoogle Scholar
  9. Guillemet B, Isaka H, Mascart P (1983) Molecular dissipation of turbulent fluctuations in the convective mixed layer part I: height variations of dissipation rates. Boundary-Layer Meteorol 27:141–162CrossRefGoogle Scholar
  10. Hartogensis OK, De Bruin HAR (2005) Monin–Obukhov similarity functions of the structure parameter of temperature and turbulent kinetic energy dissipation rate in the stable boundary layer. Boundary-Layer Meteorol 116:253–276CrossRefGoogle Scholar
  11. Howell JF, Mahrt L (1997) Multiresolution flux decomposition. Boundary-Layer Meteorol 83:117–137CrossRefGoogle Scholar
  12. Hunt JCR, Kaimal JC, Gaynor JE (1985) Some observations of turbulence structure in stable layers. Q J R Meteorol Soc 111:793–815CrossRefGoogle Scholar
  13. Igarashi Y, Kumagai T, Yoshifuji N, Sato T, Tanaka N, Tanaka K, Suzuki M, Tantasirin C (2015) Environmental control of canopy stomatal conductance in a tropical deciduous forest in northern Thailand. Agric For Meteorol 202:1–10CrossRefGoogle Scholar
  14. Jonker HJJ, Duynkerke PG, Cuijpers JWM (1999) Mesoscale fluctuations in scalars generated by boundary layer convection. J Atmos Sci 56:801–808CrossRefGoogle Scholar
  15. Kaimal JC (1978) Horizontal velocity spectra in an unstable surface layer. J Atmos Sci 35:18–24CrossRefGoogle Scholar
  16. Kaimal JC, Businger JA (1963) A continuous wave sonic anemometer-thermometer. J Appl Meteorol 2:156–164CrossRefGoogle Scholar
  17. Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows. Oxford University Press, UKGoogle Scholar
  18. Kaimal JC, Gaynor JE (1983) The Boulder Atmospheric Observatory. J Clim Appl Meteorol 22:863–880CrossRefGoogle Scholar
  19. Kaimal JC, Gaynor G (1991) Another look at sonic thermometry. Boundary-Layer Meteorol 56:401–410CrossRefGoogle Scholar
  20. Kaimal JC, Eversole RA, Lenschow DH, Stankov BB, Kahn PH, Businger JA (1982) Spectral characteristics of the convective boundary-layer over uneven terrain. J Atmos Sci 39:1098–1114CrossRefGoogle Scholar
  21. Kang SL (2016) Regional Bowen ratio controls on afternoon moist convection: a large eddy simulation study. J Geophys Res 121:14056–14083CrossRefGoogle Scholar
  22. Kang SL, Bryan GH (2011) A large-eddy simulation study of moist convection initiation over heterogeneous surface fluxes. Mon Weather Rev 139:2901–2917CrossRefGoogle Scholar
  23. Kang SL, Ryu JH (2016) Response of moist convection to multi-scale surface flux heterogeneity. Q J R Meteorol Soc 142:2180–2193CrossRefGoogle Scholar
  24. Kang SL, Davis KJ, LeMone M (2007) Observations of the ABL structures over a heterogeneous land surface during IHOP_2002. J Hydrometeorol 8:221–244CrossRefGoogle Scholar
  25. Lareau NP, Crosman E, Whiteman CD, Horel JD, Hoch SW, Brown WOJ, Horst TW (2013) The persistent cold-air pool study. Bull Am Meteorol Soc 94:51–63CrossRefGoogle Scholar
  26. Lee X, Massman W, Law B (2006) Handbook of micrometeorology: a guide for surface flux measurement and analysis. Springer, BerlinGoogle Scholar
  27. Lundquist JK et al (2017) Assessing state-of-the-art capabilities for probing the atmospheric boundary layer: the XPIA field campaign. Bull Am Meteorol Soc 98:289–314CrossRefGoogle Scholar
  28. Ma X, Feng Q, Su Y, Yu T, Jin H (2017) Forest evapotranspiration and energy flux partitioning based on eddy covariance methods in an arid desert region of northwest China. Adv Meteorol 2017:1–10Google Scholar
  29. Mahrt L (1991) Boundary-layer moisture regimes. Q J R Meteorol Soc 117:151–176CrossRefGoogle Scholar
  30. Mahrt L (1998) Flux sampling errors for aircraft and towers. J Atmos Ocean Technol 15:416–429CrossRefGoogle Scholar
  31. Mahrt L (2010) Computing turbulent fluxes near the surface: needed improvements. Agric For Meteorol 150:501–509CrossRefGoogle Scholar
  32. Mao J et al (2018) Southeast atmosphere studies: learning from model-observation syntheses. Atmos Chem Phys 18:2615–2651CrossRefGoogle Scholar
  33. Metzger M, Holmes H (2008) Time scales in the unstable atmospheric surface layer. Boundary-Layer Meteorol 126:29–50CrossRefGoogle Scholar
  34. Moeng CH, LeMone MA, Khairoutdinov MF, Krueger SK, Bogenschutz PA, Randall DA (2009) The tropical marine boundary layer under a deep convection system: a large-eddy simulation study. J Adv Model Earth Syst 1:1–13Google Scholar
  35. Nilsso EO, Sahlee E, Rutgersson A (2014) Turbulent momentum flux characterization using extended multiresolution analysis. Q J R Meteorol Soc 140:1715–1728CrossRefGoogle Scholar
  36. Oncley SP, Businger JA, Friehe CA, Larue JC, Itsweire EC, Chang SS (1990) Surface-layer profiles and turbulence measurements over uniform land under near-neutral conditions. In: Proceedings of 9th symposium on boundary layer and turbulence, Roskilde, Denmark. American Meteorological Society, Boston, pp 237–240Google Scholar
  37. Roth M, Oke TR, Steyn DG (1989) Velocity and temperature spectra and cospectra in an unstable suburban atmosphere. Boundary-Layer Meteorol 47:309–320CrossRefGoogle Scholar
  38. Stull RB (1988) An introduction to boundary layer meteorology. Kluwer Academic Publishers, DordrechtCrossRefGoogle Scholar
  39. Vickers D, Mahrt L (1997) Quality control and flux sampling problems for tower and aircraft data. J Atmos Ocean Technol 14:512–526CrossRefGoogle Scholar
  40. Vickers D, Mahrt L (2003) The cospectral gap and turbulent flux calculations. J Atmos Ocean Technol 20(5):660–672CrossRefGoogle Scholar
  41. Weckwerth TM et al (2004) An overview of the international H2O Project (IHOP_2002) and some preliminary highlights. Bull Am Meteorol Soc 85:253–277CrossRefGoogle Scholar
  42. Wilczak JM, Parson DB, Koch SE, Moore JA, LeMone MA, Demoz BD, Flamant C, Geerts B, Wang J, Feltz WF (2001) Sonic anemometer tilt correction algorithms. Boundary-Layer Meteorol 99:127–150CrossRefGoogle Scholar
  43. Wyngaard JC, Pennell WT, Lenschow DH, LeMone MA (1978) The temperature-humidity covariance budget in the convective boundary layer. J Atmos Sci 35:47–58CrossRefGoogle Scholar
  44. Zhang Z, Tian F, Hu H, Yang P (2014) A comparison of methods for determining field evapotranspiration: photosynthesis system, sap flow, and eddy covariance. Hydrol Earth Syst Sci 18:1053–1072CrossRefGoogle Scholar
  45. Zhang H, Ahang H, Cai X, Song Y, Sun J (2016) Contribution of low-frequency motions to sensible heat fluxes over urban and suburban areas. Boundary-Layer Meteorol 161:183–201CrossRefGoogle Scholar
  46. Zhao Z, Zhiqiu G, Li Dan, Xueyan B, Chunxia L, Fei L (2013) Scalar flux-gradient relationships under unstable conditions over water in coastal regions. Boundary-Layer Meteorol 148:495–516CrossRefGoogle Scholar
  47. Zhou B, Simon JS, Chow FK (2014) The convective boundary layer in the terra incognita. J Atmos Sci 71:2545–2563CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Department of Atmospheric and Environmental SciencesGangneung-Wonju National UniversityGangneung-siRepublic of Korea

Personalised recommendations