Boundary-Layer Meteorology

, Volume 151, Issue 2, pp 195–219 | Cite as

Evaluation of Two Energy Balance Closure Parametrizations

  • Fabian Eder
  • Frederik De Roo
  • Katrin Kohnert
  • Raymond L. Desjardins
  • Hans Peter Schmid
  • Matthias Mauder
Article

Abstract

A general lack of energy balance closure indicates that tower-based eddy-covariance (EC) measurements underestimate turbulent heat fluxes, which calls for robust correction schemes. Two parametrization approaches that can be found in the literature were tested using data from the Canadian Twin Otter research aircraft and from tower-based measurements of the German Terrestrial Environmental Observatories (TERENO) programme. Our analysis shows that the approach of Huang et al. (Boundary-Layer Meteorol 127:273–292, 2008), based on large-eddy simulation, is not applicable to typical near-surface flux measurements because it was developed for heights above the surface layer and over homogeneous terrain. The biggest shortcoming of this parametrization is that the grid resolution of the model was too coarse so that the surface layer, where EC measurements are usually made, is not properly resolved. The empirical approach of Panin and Bernhofer (Izvestiya Atmos Oceanic Phys 44:701–716, 2008) considers landscape-level roughness heterogeneities that induce secondary circulations and at least gives a qualitative estimate of the energy balance closure. However, it does not consider any feature of landscape-scale heterogeneity other than surface roughness, such as surface temperature, surface moisture or topography. The failures of both approaches might indicate that the influence of mesoscale structures is not a sufficient explanation for the energy balance closure problem. However, our analysis of different wind-direction sectors shows that the upwind landscape-scale heterogeneity indeed influences the energy balance closure determined from tower flux data. We also analyzed the aircraft measurements with respect to the partitioning of the “missing energy” between sensible and latent heat fluxes and we could confirm the assumption of scalar similarity only for Bowen ratios \(\approx \)1.

Keywords

Airborne measurements Eddy covariance Energy balance closure Surface heterogeneity TERENO programme 

References

  1. Aubinet M, Grelle A, Ibrom A, Rannik Ü, Moncrieff J, Foken T, Kowalski AS, Martin PH, Berbigier P, Bernhofer C, Clement R, Elbers J, Granier A, Grünwald T, Morgenstern K, Pilegaard K, Rebmann C, Snijders W, Valentini R, Vesala T (2000) Estimates of the annual net carbon and water exchange of forests: the EUROFLUX methodology. Adv Ecol Res 30:113–175CrossRefGoogle Scholar
  2. Aubinet M, Heinesch B, Yernaux M (2003) Horizontal and vertical CO\(_{2}\) advection in a sloping forest. Boundary-Layer Meteorol 108:397–417CrossRefGoogle Scholar
  3. Baidya Roy S, Weaver CP, Nolan DS, Avissar R (2003) A preferred scale for landscape forced mesoscale circulations? J Geophys Res 108:8854CrossRefGoogle Scholar
  4. Barr AG, Griffis TJ, Black TA, Lee X, Staebler RM, Fuentes JD, Chen Z, Morgenstern K (2002) Comparing the carbon budgets of boreal and temperate deciduous forest stands. Can J For Res 32:813–822CrossRefGoogle Scholar
  5. Barr AG, Morgenstern K, Black TA, McCaughey JH, Nesic Z (2006) Surface energy balance closure by the eddy-covariance method above three boreal forest stands and implications for the measurement of the CO2 flux. Agric For Meteorol 140:322–337CrossRefGoogle Scholar
  6. Barr AG, van der Kamp G, Black TA, McCaughey JH, Nesic Z (2012) Energy balance closure at the BERMS flux towers in relation to the water balance of the White Gull Creek watershed 1999–2009. Agric For Meteorol 153:3–13CrossRefGoogle Scholar
  7. Betts AK, Desjardins RL, MacPherson JI (1992) Budget analysis of the boundary layer grid flights during FIFE 1987. J Geophys Res 97:18533–18546CrossRefGoogle Scholar
  8. Bou-Zeid E, Parlange MB, Meneveau C (2007) On the parameterization of surface roughness at regional scales. J Atmos Sci 64:216–227CrossRefGoogle Scholar
  9. Dalu GA, Pielke RA, Baldi M, Zeng X (1996) Heat and momentum fluxes induced by thermal inhomogeneities with and without large-scale flow. J Atmos Sci 53:3286–3302CrossRefGoogle Scholar
  10. De Jong JJ, De Vries AC, Klaasen W (1999) Influence of obstacles on the aerodynamic roughness of the Netherlands. Boundary-Layer Meteorol 91:51–64CrossRefGoogle Scholar
  11. Deardorff JW (1972) Numerical investigation of neutral and unstable planetary boundary layers. J Atmos Sci 29:91–115CrossRefGoogle Scholar
  12. Desjardins RL (1985) Carbon dioxide budget of maize. Agric For Meteorol 36:29–41CrossRefGoogle Scholar
  13. Desjardins RL, Schuepp PH, MacPherson JI, Buckley DJ (1992) Spatial and temporal variations of the fluxes of carbon dioxide and sensible and latent heat over the FIFE site. J Geophys Res 97:18467–18475CrossRefGoogle Scholar
  14. Dobosy RJ, Crawford TL, MacPherson JI, Desjardins RL, Kelly RD, Oncley SP, Lenschow DH (1997) Intercomparison among four flux aircraft at BOREAS in 1994. J Geophys Res 102:29101–29111CrossRefGoogle Scholar
  15. Emeis S, Jahn C, Münkel C, Münsterer C, Schäfer K (2007) Multiple atmospheric layering and mixing-layer height in the Inn valley observed by remote sensing. Meteorol Z 16:415–424CrossRefGoogle Scholar
  16. Emeis S, Schäfer K, Münkel C (2008) Surface-based remote sensing of the mixing-layer height—a review. Meteorol Z 17:621–630CrossRefGoogle Scholar
  17. 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
  18. Foken T (2008) The energy balance closure problem: an overview. Ecol Appl 18:1351–1367CrossRefGoogle Scholar
  19. Foken T, Mauder M, Liebethal C, Wimmer F, Beyrich F, Leps JP, Raasch S, DeBruin H, Meijninger W, Bange J (2010) Energy balance closure for the LITFASS-2003 experiment. Theor Appl Climatol 101:149–160CrossRefGoogle Scholar
  20. Foken T, Leuning R, Oncley SR, Mauder M, Aubinet M (2012) Corrections and data quality control. In: Aubinet M, Vesala T, Papale D (eds) Eddy covariance: a practical guide to measurement and data analysis. Springer, Dordrecht, pp 85–131CrossRefGoogle Scholar
  21. Frank JM, Massman WJ, Ewers BE (2013) Underestimates of sensible heat flux due to vertical velocity measurement errors in non-orthogonal sonic anemometers. Agric For Meteorol 171–172:72–81CrossRefGoogle Scholar
  22. Grossmann A, Morlet J (1984) Decomposition of hardy functions into square integrable wavelets of constant shape. SIAM J Math Anal 15:723–736CrossRefGoogle Scholar
  23. Grossmann A, Kronland-Martinet R, Morlet J (1989) Reading and understanding continous wavelet transforms. In: Combes JM, Grossmann A, Tchamitchian P (eds) Wavelets: time-frequency methods and phase space. Springer, New York, pp 2–20CrossRefGoogle Scholar
  24. Hall FG, Knapp DE, Huemmrich KF (1997) Physically based classification and satellite mapping of biophysical characteristics in the southern boreal forest. J Geophys Res 102:29567–29580CrossRefGoogle Scholar
  25. Hendricks-Franssen HJ, Stöckli R, Lehner I, Rotenberg E, Seneviratne SI (2010) Energy balance closure of eddy-covariance data: a multisite analysis for European FLUXNET stations. Agric For Meteorol 150:1553–1567CrossRefGoogle Scholar
  26. Heusinkveld BG, Jacobs AFG, Holtslag AAM, Berkowicz SM (2004) Surface energy balance closure in an arid region: role of soil heat flux. Agric For Meteorol 122:21–37CrossRefGoogle Scholar
  27. Hiyama T, Strunin MA, Tanaka H, Ohta T (2007) The development of local circulations around the Lena River and their effect on tower-observed energy imbalance. Hydrol Proc 21:2038–2048CrossRefGoogle Scholar
  28. Huang J, Lee X, Patton E (2008) A modelling study of flux imbalance and the influence of entrainment in the convective boundary layer. Boundary-Layer Meteorol 127:273–292CrossRefGoogle Scholar
  29. Hudgins LE, Mayer ME, Friehe CA (1993) Fourier and wavelet analysis of atmospheric turbulence. In: Meyers E, Roques S (eds) Progress in wavelet analysis and applications. Editions Frontiers, Gif-sur-Yvette, pp 491–498Google Scholar
  30. Inagaki A, Letzel MO, Raasch S, Kanda M (2006) Impact of surface heterogeneity on energy imbalance: a study using LES. J Meteorol Soc Jpn 84:187–198CrossRefGoogle Scholar
  31. Ingwersen J, Steffens K, Högy P, Warrach-Sagi K, Zhunusbayeva D, Poltoradnev M, Gäbler R, Wizemann HD, Fangmeier A, Wulfmeyer V, Streck T (2011) Comparison of Noah simulations with eddy covariance and soil water measurements at a winter wheat stand. Agric For Meteorol 151:345–355CrossRefGoogle Scholar
  32. Kanda M, Inagaki A, Letzel MO, Raasch S, Watanabe T (2004) LES Study of the energy imbalance problem with eddy covariance fluxes. Boundary-Layer Meteorol 110:381–404CrossRefGoogle Scholar
  33. Kochendorfer J, Meyers TP, Frank J, Massman WJ, Heuer MW (2012) How well can we measure the vertical wind speed? Implications for fluxes of energy and mass. Boundary-Layer Meteorol 145:383–398CrossRefGoogle Scholar
  34. Kronland-Martinet R, Morlet J, Grossmann A (1987) Analysis of sound patterns through wavelet transforms. Int J Pattern Recogn 1:273–302CrossRefGoogle Scholar
  35. Lamaud E, Irvine M (2006) Temperature-humidity dissimilarity and heat-to-water-vapour transport efficiency above and within a pine forest canopy: the role of the Bowen ratio. Boundary-Layer Meteorol 120:87–109CrossRefGoogle Scholar
  36. Lee X, Black TA (1993) Atmospheric turbulence within and above a douglas-fir stand. Part II: eddy fluxes of sensible heat and water vapour. Boundary-Layer Meteorol 64:369–389CrossRefGoogle Scholar
  37. Lenschow DH, Stankov BB (1986) Length scales in the convective boundary layer. J Atmos Sci 43:1198–1209CrossRefGoogle Scholar
  38. Leuning R, van Gorsel E, Massman WJ, Isaac PR (2012) Reflections on the surface energy imbalance problem. Agric For Meteorol 156:65–74CrossRefGoogle Scholar
  39. Liebethal C, Huwe B, Foken T (2005) Sensivity analysis for two ground heat flux calculation approaches. Agric For Meteorol 132:253–262CrossRefGoogle Scholar
  40. Lothon M, Couvreux F, Donier S, Guichard F, Lacarrère P, Lenschow D, Noilhan J, Saïd F (2007) Impact of coherent eddies on airborne measurements of vertical turbulent fluxes. Boundary-Layer Meteorol 124:425–447CrossRefGoogle Scholar
  41. MacPherson JI (1996) NRC Twin Otter operations in BOREAS, (1994) Rep LTR-FR-129. Natl Res Counc Can. Inst for Aerosp Res, Ottawa, 32 ppGoogle Scholar
  42. Mahrt L (1998) Flux sampling errors for aircraft and towers. J Atmos Oceanic Technol 15:416–429CrossRefGoogle Scholar
  43. Mahrt L (2000) Surface heterogeneity and vertical structure of the boundary layer. Boundary-Layer Meteorol 96:33–62CrossRefGoogle Scholar
  44. Maronga B, Raasch S (2013) Large-eddy simulations of surface heterogeneity effects on the convective boundary layer during the LITFASS-2003 experiment. Boundary-Layer Meteorol 146:17–44CrossRefGoogle Scholar
  45. Mauder M (2013) A comment on “How well can we measure the vertical wind speed? Implications for fluxes of energy and mass”, by Kochendorfer, et al. Boundary-Layer Meteorol 47:329–335CrossRefGoogle Scholar
  46. Mauder M, Foken T (2011) Documentation and instruction manual of the Eddy-Covariance software package TK3. Arbeitsergebnisse/Universität Bayreuth, Abteilung Mikrometeorologie - 46. ISSN:1614–8916, 60 ppGoogle Scholar
  47. Mauder M, Liebethal C, Goeckede M, Leps JP, Beyrich F, Foken T (2006) Processing and quality control of flux data during LITFASS-2003. Boundary-Layer Meteorol 121:67–88CrossRefGoogle Scholar
  48. Mauder M, Jegede OO, Okogbue EC, Wimmer F, Foken T (2007a) Surface energy balance measurements at a tropical site in West Africa during the transition from dry to wet season. Theor Appl Climatol 89:171–183CrossRefGoogle Scholar
  49. Mauder M, Desjardins RL, MacPherson I (2007b) Scale analysis of airborne flux measurements over heterogeneous terrain in a boreal ecosystem. J Geophys Res 112:D13112CrossRefGoogle Scholar
  50. Mauder M, Oncley S, Vogt R, Weidinger T, Ribeiro L, Bernhofer C, Foken T, Kohsiek W, DeBruin H, Liu H (2007c) The energy balance experiment EBEX-2000. Part II: intercomparison of eddy-covariance sensors and post-field data processing methods. Boundary-Layer Meteorol 123:29–54CrossRefGoogle Scholar
  51. Mauder M, Desjardins RL, Pattey E, Worth D (2010) An attempt to close the daytime surface energy balance using spatially-averaged flux measurements. Boundary-Layer Meteorol 136:175–191CrossRefGoogle Scholar
  52. Mauder M, Cuntz M, Drüe C, Graf A, Rebmann C, Schmid HP, Schmidt M, Steinbrecher R (2013) A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements. Agric For Meteorol 169:122–135CrossRefGoogle Scholar
  53. Moene AF, Schüttemeyer D (2008) The effect of surface heterogeneity on the temperature–humidity correlation and the relative transport efficiency. Boundary-Layer Meteorol 129:99–113CrossRefGoogle Scholar
  54. Moeng CH, Sullivan PP (1994) A comparison of shear- and buoyancy-driven planetary boundary layer flows. J Atmos Sci 51:999–1022CrossRefGoogle Scholar
  55. Oncley S, Foken T, Vogt R, Kohsiek W, DeBruin H, Bernhofer C, Christen A, van Gorsel E, Grantz D, Feigenwinter C, Lehner I, Liebethal C, Liu H, Mauder M, Pitacco A, Ribeiro L, Weidinger T (2007) The energy balance experiment EBEX-2000. Part I: overview and energy balance. Boundary-Layer Meteorol 123:1–28CrossRefGoogle Scholar
  56. Panin GN, Bernhofer Ch (2008) Parametrization of turbulent fluxes over inhomogeneous landscapes. Izvestiya Atmos Oceanic Phys 44:701–716CrossRefGoogle Scholar
  57. Panin GN, Tetzlaff G, Raabe A (1998) Inhomogeneity of the land surface and problems in the parameterization of surface fluxes in natural conditions. Theor Appl Climatol 60:163–178CrossRefGoogle Scholar
  58. Patton EG, Sullivan PP, Moeng CH (2005) The influence of idealized heterogeneity on wet and dry planetary boundary layers coupled to the land surface. J Atmos Sci 62:2078–2097CrossRefGoogle Scholar
  59. Pearson RJ, Oncley SP, Delany AC (1998) A scalar similarity study based on surface layer ozone measurements over cotton during the California Ozone Deposition Experiment. J Geophys Res 103:18919–18926CrossRefGoogle Scholar
  60. Raasch S, Harbusch G (2001) An analysis of secondary circulations and their effects caused by small-scale surface inhomogeneities using large-eddy simulation. Boundary-Layer Meteorol 101:31–59CrossRefGoogle Scholar
  61. Ruppert J, Thomas C, Foken T (2006) Scalar similarity for relaxed eddy accumulation methods. Boundary-Layer Meteorol 120:39–63CrossRefGoogle Scholar
  62. Schmidt H, Schumann U (1989) Coherent structure of the convective boundary layer derived from large-eddy simulations. J Fluid Mech 200:511–562CrossRefGoogle Scholar
  63. Segal M, Arritt RW (1992) Nonclassical mesoscale circulations caused by surface sensible heat-flux gradients. Bull Am Meteorol Soc 73:1593–1604CrossRefGoogle Scholar
  64. Segal M, Avissar R, McCumber MC, Pielke RA (1988) Evaluation of vegetation effects on the generation and modification of mesoscale circulations. J Atmos Sci 45:2268–2293CrossRefGoogle Scholar
  65. Sellers PJ, Hall FG, Kelly RD, Black A, Baldocchi D, Berry J, Ryan M, Ranson KJ, Crill PM, Lettenmaier DP, Margolis H, Cihlar J, Newcomer J, Fitzjarrald D, Jarvis PG, Gower ST, Halliwell D, Williams D, Goodison B, Wickland DE, Guertin FE (1997) BOREAS in 1997: Experiment overview, scientific results, and future directions. J Geophys Res 102:28731–28769CrossRefGoogle Scholar
  66. Shen S, Leclerc MY (1995) How large must surface inhomogeneities be before they influence the convective boundary layer structure? A case study. Q J R Meteorol Soc 121:1209–1228CrossRefGoogle Scholar
  67. Smith SD (1988) Coefficients for sea-surface wind-stress, heat flux and wind profiles as a function of wind-speed and temperature. J Geophys Res 93:15467–15472CrossRefGoogle Scholar
  68. Steinfeld G, Letzel M, Raasch S, Kanda M, Inagaki A (2007) Spatial representativeness of single tower measurements and the imbalance problem with eddy-covariance fluxes: results of a large-eddy simulation study. Boundary-Layer Meteorol 123:77–98CrossRefGoogle Scholar
  69. Stoy PC, Katul GG, Siqueira MBS, Juang JY, Novick KA, McCarthy HR, Oishi AC, Uebelherr JM, Kim HS, Oren RAM (2006) Separating the effects of climate and vegetation on evapotranspiration along a successional chronosequence in the southeastern US. Glob Change Biol 12:2115–2135CrossRefGoogle Scholar
  70. Stoy PC, Mauder M, Foken T, Marcolla B, Boegh E, Ibrom A, Arain MA, Arneth A, Aurela M, Bernhofer C, Cescatti A, Dellwik E, Duce P, Gianelle D, van Gorsel E, Kiely G, Knohl A, Margolis H, McCaughey H, Merbold L, Montagnani L, Papale D, Reichstein M, Saunders M, Serrano-Ortiz P, Sottocornola M, Spano D, Vaccari F, Varlagin A (2013) A data-driven analysis of energy balance closure across FLUXNET research sites: the role of landscape scale heterogeneity. Agric For Meteorol 171–172:137–152CrossRefGoogle Scholar
  71. Strunin MA, Hiyama T (2005) Spectral structure of small-scale turbulent and mesoscale fluxes in the atmospheric boundary layer over a thermally inhomogeneous land surface. Boundary-Layer Meteorol 117:479–510CrossRefGoogle Scholar
  72. Stull RB (1988) An introduction to boundary layer meteorology. Kluwer, Dordrecht 666 ppCrossRefGoogle Scholar
  73. Sun J, Lenschow DH, Mahrt L, Crawford TL, Davis KJ, Oncley SP, MacPherson IJ, Wang Q, Dobosy RJ, Desjardins RL (1997) Lake-induced atmospheric circulations during BOREAS. J Geophys Res 102:29155–29166CrossRefGoogle Scholar
  74. Taylor PA (1987) Comments and further analysis on effective roughness lengths for use in numerical three-dimensional models. Boundary-Layer Meteorol 39:403–418CrossRefGoogle Scholar
  75. Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteorol Soc 79:61–78CrossRefGoogle Scholar
  76. Twine TE, Kustas WP, Norman JM, Cook DR, Houser PR, Meyers TP, Prueger JH, Starks PJ, Wesley ML (2000) Correcting eddy-covariance flux underestimates over a grassland. Agric For Meteorol 103:279–300CrossRefGoogle Scholar
  77. Vickers D, Mahrt L (2003) The cospectral gap and turbulent flux calculations. J Atmos Oceanic Technol 20:660–672CrossRefGoogle Scholar
  78. von Randow C, Sá LDA, Gannabathula PSSD, Manzi AO, Arlino PRA, Kruijt B (2002) Scale variability of atmospheric surface layer fluxes of energy and carbon over a tropical rain forest in southwest Amazonia 1. Diurnal conditions. J Geophys Res 107:8062CrossRefGoogle Scholar
  79. Wieringa J (1993) Representative roughness parameters for homogeneous terrain. Boundary-Layer Meteorol 63:323–363CrossRefGoogle Scholar
  80. Wilczak JL, Cancillo ML, King CW (1997) A wind profiler climatology of boundary layer structure above the boreal forest. J Geophys Res 102:29083–29100CrossRefGoogle Scholar
  81. Williams AG, Kraus H, Hacker JM (1996) Transport processes in the tropical warm pool boundary layer. Part I: spectral composition of fluxes. J Atmos Sci 53:1187–1202CrossRefGoogle Scholar
  82. Wilson K, Goldstein A, Falge E, Aubinet M, Baldocchi D, Berbigier P, Bernhofer C, Ceulemans R, Dolman H, Field C, Grelle A, Ibrom A, Law BE, Kowalski A, Meyers T, Moncrieff J, Monson R, Oechel W, Tenhunen J, Valentini R, Verma S (2002) Energy balance closure at FLUXNET sites. Agric For Meteorol 113:223–243CrossRefGoogle Scholar
  83. Zacharias S, Bogena H, Samaniego L, Mauder M, Fuß R, Pütz T, Frenzel M, Schwank M, Baessler C, Butterbach-Bahl K, Bens O, Borg E, Brauer A, Dietrich P, Hajnsek I, Helle G, Kiese R, Kunstmann H, Klotz S, Munch JC, Papen H, Priesack E, Schmid HP, Steinbrecher R, Rosenbaum U, Teutsch G, Vereecken H (2011) A network of terrestrial environmental observatories in Germany. Vadose Zone J 10:955–973CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Fabian Eder
    • 1
  • Frederik De Roo
    • 1
  • Katrin Kohnert
    • 1
    • 2
    • 3
  • Raymond L. Desjardins
    • 4
  • Hans Peter Schmid
    • 1
  • Matthias Mauder
    • 1
  1. 1.Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU)Karlsruhe Institute of Technology (KIT)Garmisch-PartenkirchenGermany
  2. 2.Department of MicrometeorologyUniversity of BayreuthBayreuthGermany
  3. 3.Helmholtz Centre PotsdamGFZ German Research Centre for GeosciencesPotsdamGermany
  4. 4.Agriculture and Agri-Food CanadaOttawaCanada

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