Skip to main content
Log in

Surface Thermal Heterogeneities and the Atmospheric Boundary Layer: The Relevance of Dispersive Fluxes

  • Research Article
  • Published:
Boundary-Layer Meteorology Aims and scope Submit manuscript

Abstract

While the increasing availability of computational power is enabling finer grid resolutions in numerical-weather-prediction models, representing land–atmosphere exchange processes remains challenging. This partially results from the fact that land-surface heterogeneity exists at all spatial scales, and its variability does not necessarily ‘average’ out with decreasing size. The work presented here uses large-eddy simulations and the concept of dispersive fluxes to quantify the effects of a surface that is thermally inhomogeneous (with scales that are approximately 10% of the height of the atmospheric boundary layer), but uniformly rough. These near-canonical cases describe inhomogeneous scalar transport over a broad range of unstable atmospheric flows. Results illustrate the existence of a regime where the mean flow is mostly driven by the surface thermal heterogeneities. In this regime, the contribution of the dispersive fluxes can account for more than 40% of the total sensible heat flux at 100 m above the ground and about 5–10% near the surface. This result is independent of the spatial distribution of the thermal heterogeneities and weakly dependent on the averaging time used to define the dispersive fluxes. Additionally, an alternative regime exists where the effects of the surface thermal heterogeneities are quickly blended and the dispersive fluxes match those obtained over an equivalent homogeneous surface. Results further illustrate the existence of a new cospectral scaling for the dispersive sensible heat fluxes that differs from the traditional turbulence cospectral scaling. We believe that these results might elucidate pathways for developing new parametrizations for the non-canonical atmospheric surface layer.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Albertson JD, Parlange MB (1999) Natural integration of scalar fluxes from complex terrain. Adv Water Resour 23:239–252

    Google Scholar 

  • Ament F, Simmer C (2006) Improved representation of land-surface heterogeneity in a non-hydrostatic numerical weather prediction model. Boundary-Layer Meteorol 121(1):153–174

    Google Scholar 

  • Arola A (1999) Parameterization of turbulent and mesoscale fluxes for heterogeneous surfaces. J Atmos Sci 56(4):584–598

    Google Scholar 

  • Avissar R (1991) A statistical-dynamical approach to parameterize subgrid-scale land-surface heterogeneity in climate models. Surv Geophys 12(1–3):155–178

    Google Scholar 

  • Avissar R (1992) Conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. J Geophys Res 97(D3):2729–2742

    Google Scholar 

  • Avissar R, Pielke RA (1989) A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology. Mon Weather Rev 117(10):2113–2136

    Google Scholar 

  • Bailey BN, Stoll R (2013) Turbulence in sparse, organized vegetative canopies: A large-eddy simulation study. Boundary-Layer Meteorol 147(3):369–400

    Google Scholar 

  • Basu S, Lacser A (2017) A cautionary note on the use of Monin-Obukhov similarity theory in very high-resolution large-eddy simulations. Boundary-Layer Meteorol 163(2):351–355

    Google Scholar 

  • Beare RJ (2014) A length scale defining partially-resolved boundary-layer turbulence simulations. Boundary-Layer Meteorol 151(1):39–55

    Google Scholar 

  • Beljaars ACM, Holtslag AAM (1991) Flux parameterization over land surfaces for atmospheric models. J Appl Meteorol 30(3):327–341

    Google Scholar 

  • Bennett LJ, Weckwerth TM, Blyth AM, Geerts B, Miao Q, Richardson YP (2010) Observations of the evolution of the nocturnal and convective boundary layers and the structure of open-celled convection on 14 June 2002. Mon Weather Rev 138(7):2589–2607

    Google Scholar 

  • Blyth EM (1995) Using a simple SVAT scheme to describe the effect of scale on aggregation. Boundary-Layer Meteorol 72(3):267–285

    Google Scholar 

  • Blyth EM, Dolman AJ, Wood N (1993) Effective resistance to sensible- and latent- heat flux in heterogeneous terrain. Q J R Meteorol Soc 119(511):423–442

    Google Scholar 

  • Bou-Zeid E, Meneveau C, Parlange MB (2004) Large-eddy simulation of neutral atmospheric boundary layer flow over heterogeneous surfaces: Blending height and effective surface roughness. Water Resour Res 40(2):1–18

    Google Scholar 

  • Bou-Zeid E, Meneveau C, Parlange MB (2005) A scale-dependent Lagrangian dynamic model for large eddy simulation of complex turbulent flows. Phys Fluids 17(2):025105

    Google Scholar 

  • Brutsaert W (1982) Evaporation into the atmosphere. Springer, Dordrecht

    Google Scholar 

  • Brutsaert W (2005) Hydrology. Cambridge University Press, Cambridge

    Google Scholar 

  • Calaf M, Meneveau C, Meyers J (2010) Large eddy simulation study of fully developed wind-turbine array boundary layers. Phys Fluids (1994-present) 22(1):015110

    Google Scholar 

  • Calaf M, Meneveau C, Parlange MB (2011) Large Eddy Simulation study of a fully developed thermal wind-turbine array boundary layer. In: Kuerten H, Geurts B, Armenio V, Fröhlich J (eds) Direct and large-eddy simulation VIII, ERCOFTAC Series, vol 15. Springer, Dordrecht

    Google Scholar 

  • 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(3):303–327

    Google Scholar 

  • Cheng H, Castro IP (2002) Near wall flow over urban-like roughness. Boundary-Layer Meteorol 104(2):229–259

    Google Scholar 

  • Claussen M (1990) Area-averaging of surface fluxes in a neutrally stratified, horizontally inhomogeneous atmospheric boundary layer. Atmos Environ Part A Gen Top 24(6):1349–1360

    Google Scholar 

  • Claussen M (1991) Estimation of areally-averaged surface fluxes. Boundary-Layer Meteorol 54(4):387–410

    Google Scholar 

  • De Roo F, Mauder M (2018) The influence of idealized surface heterogeneity on virtual turbulent flux measurements. Atmos Chem Phys 18(7):5059–5074

    Google Scholar 

  • Eder F, Schmidt M, Damian T, Träumner K, Mauder M (2015) Mesoscale eddies affect near-surface turbulent exchange: Evidence from lidar and tower measurements. J Appl Meteorol Clim 54(1):189–206

    Google Scholar 

  • Finnigan JJ (1985) Turbulent transport in flexible plant canopies. The forest–atmosphere interaction. Springer, Dordrecht, pp 443–480

    Google Scholar 

  • Finnigan JJ (2000) Turbulence in plant canopies. Ann Rev Fluid Mech 32(1):519–571

    Google Scholar 

  • Foken T (2006) 50 years of the Monin–Obukhov similarity theory. Boundary-Layer Meteorol 119(3):431–447

    Google Scholar 

  • Foken T (2008) The energy balance closure problem: an overview. Ecol Appl 18(6):1351–1367

    Google Scholar 

  • Giometto MG, Christen A, Meneveau C, Fang J, Krafczyk M, Parlange MB (2016) Spatial characteristics of roughness sublayer mean flow and turbulence over a realistic urban surface. Boundary-Layer Meteorol 160(3):425–452

    Google Scholar 

  • Hultmark M, Calaf M, Parlange MB (2013) A new wall shear stress model for atmospheric boundary layer simulations. J Atmos Sci 70(11):3460–3470

    Google Scholar 

  • 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(1):187–198

    Google Scholar 

  • Jacob C, Anderson W (2017) Conditionally averaged large-scale motions in the neutral atmospheric boundary layer: Insights for aeolian processes. Boundary-Layer Meteorol 162(1):21–41

    Google Scholar 

  • Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows: their structure and measurement, 1st edn. Oxford University Press, Oxford

    Google Scholar 

  • 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(3):381–404

    Google Scholar 

  • von Kármán T (1931) Mechanical similitude and turbulence. Nachrichten von der Gesellschaft der Wissenschaften zu Gottingen - Fachgruppe I (Mathematik) 5:1–19

    Google Scholar 

  • Konrad TG (1970) The dynamics of the convective process in clear air as seen by radar. J Atmos Sci 27:1138–1147

    Google Scholar 

  • Kravchenko A, Moin P (1997) On the effect of numerical errors in large eddy simulations of turbulent flows. J Comput Phys 131(2):310–322

    Google Scholar 

  • Li D, Bou-Zeid E (2013) Synergistic interactions between urban heat islands and heat waves: the impact in cities is larger than the sum of its parts. J Appl Meteorol Clim 52(9):2051–2064

    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. Boundary-Layer Meteorol 157(1):1–21

    Google Scholar 

  • Lilly D (1967) Representation of small scale turbulence in numerical simulation experiments. In: Proceedings of the IBM scientific computing symposium on environmental sciences (December), pp195–210

  • Margairaz F, Giometto MG, Parlange MB, Calaf M (2018) Comparison of dealiasing schemes in large-eddy simulation of neutrally stratified atmospheric flows. Geosci Model Dev 11(10):4069–4084

    Google Scholar 

  • Martilli A, Santiago JL (2007) CFD simulation of airflow over a regular array of cubes. Part II: analysis of spatial average properties. Boundary-Layer Meteorol 122(3):635–654

    Google Scholar 

  • Mason PJ (1988) The formation of areally-averaged roughness lengths. Q J R Meteorol Soc 114(480):399–420

    Google Scholar 

  • Mauder M, Desjardins RL, Pattey E, Gao Z, van Haarlem R (2008) Measurement of the sensible eddy heat flux based on spatial averaging of continuous ground-based observations. Boundary-Layer Meteorol 128(1):151–172

    Google Scholar 

  • Mignot E, Barthelemy E, Hurther D (2009) Double-averaging analysis and local flow characterization of near-bed turbulence in gravel-bed channel flows. J Fluid Mech 618:279–303

    Google Scholar 

  • Moeng C, Sullivan PP (2015) Large-eddy simulation. In: Encyclopedia of Atmospheric Sciences, Elsevier, pp 232–240

  • Moltchanov S, Bohbot-Raviv Y, Duman T, Shavit U (2015) Canopy edge flow: a momentum balance analysis. Water Resour Res 51(4):2081–2095

    Google Scholar 

  • Monin A, Obukhov A (1954) Basic laws of turbulent mixing in the surface layer of the atmosphere. Contrib Geophys Inst Acad Sci USSR 24(151):163–187

    Google Scholar 

  • Morrison TJ, Calaf M, Fernando HJS, Price TA, Pardyjak ER (2017) A methodology for computing spatially and temporally varying surface sensible heat flux from thermal imagery. Q J R Meteorol Soc 143(707):2616–2624

    Google Scholar 

  • Munters W, Meneveau C, Meyers J (2016) Shifted periodic boundary conditions for simulations of wall-bounded turbulent flows. Phys Fluids 28(2):025112

    Google Scholar 

  • 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(7):2078–2097

    Google Scholar 

  • Poggi D, Katul GG (2008) The effect of canopy roughness density on the constitutive components of the dispersive stresses. Exp Fluids 45(1):111–121

    Google Scholar 

  • Poggi D, Katul GG, Albertson JD (2004) A note on the contribution of dispersive fluxes to momentum transfer within canopies. Boundary-Layer Meteorol 111(3):615–621

    Google Scholar 

  • Pope SB (2000) Turbulent flows. Cambridge University Press, Cambridge

    Google Scholar 

  • Prandtl L (1932) Zur Turbulenten Strömung in Rohren und langs Glätten. Ergebnisse der Aerodynamischen Versuchsanstalt zu Göttingen B 4:18–29

    Google Scholar 

  • Raupach MR (1994) Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index. Boundary-Layer Meteorol 71(1–2):211–216

    Google Scholar 

  • Raupach MR, Shaw RH (1982) Averaging procedures for flow within vegetation canopies. Boundary-Layer Meteorol 22(1):79–90

    Google Scholar 

  • Raupach MR, Thom AS (1981) Turbulence in and above plant canopies. Annu Rev Fluid Mech 13(1):97–129

    Google Scholar 

  • Raupach MR, Coppin PA, Legg BJ (1986) Experiments on scalar dispersion within a model plant canopy part I: The turbulence structure. Boundary-Layer Meteorol 35(1–2):21–52

    Google Scholar 

  • Salesky ST, Anderson W (2018) Buoyancy effects on large-scale motions in convective atmospheric boundary layers: Implications for modulation of near-wall processes. J Fluid Mech 856:135–168

    Google Scholar 

  • Salesky ST, Chamecki M, Bou-Zeid E (2017) On the nature of the transition between roll and cellular organization in the convective boundary layer. Boundary-Layer Meteorol 163(1):41–68

    Google Scholar 

  • Smagorinsky J (1963) General circulation experiments with primirive equations. Mon Weather Rev 91(3):99–164

    Google Scholar 

  • Stoll R, Porté-Agel F (2006) Dynamic subgrid-scale models for momentum and scalar fluxes in large-eddy simulations of neutrally stratified atmospheric boundary layers over heterogeneous terrain. Water Resour Res 42(1):1–18

    Google Scholar 

  • Stoll R, Porté-Agel F (2009) Surface heterogeneity effects on regional-scale fluxes in stable boundary layers: surface temperature transitions. J Atmos Sci 66(2):412–431

    Google Scholar 

  • 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 171–172:137–152

    Google Scholar 

  • Stull RB (1988) An Introduction to boundary layer meteorology. Springer, Dordrecht

    Google Scholar 

  • Taylor PA (1987) Comments and further analysis on effective roughness lengths for use in numerical three-dimensional models. Boundary-Layer Meteorol 39(4):403–418

    Google Scholar 

  • Weckwerth TM, Horst TW, Wilson JW (1999) An observational study of the evolution of horizontal convective rolls. Mon Weather Rev 127(9):2160–2179

    Google Scholar 

  • Wieringa J (1986) Roughness-dependent geographical interpolation of surface wind speed averages. Q J R Meteorol Soc 112(473):867–889

    Google Scholar 

  • Wilson NR, Shaw RH (1977) A higher order closure model for canopy flow. J Appl Meteorol 16(11):1197–1205

    Google Scholar 

  • Wood N, Mason PJ (1991) The influence of static stability on the effective roughness lengths for momentum and heat transfer. Q J R Meteorol Soc 117(501):1025–1056

    Google Scholar 

  • Wyngaard JC (2004) Toward numerical modeling in the “terra-incognita”. J Atmos Sci 61(14):1816–1826

    Google Scholar 

  • Wyngaard JC (2010) Turbulence in the atmosphere. Cambridge University Press, Cambridge

    Google Scholar 

  • Xie ZT, Coceal O, Castro IP (2008) Large-eddy simulation of flows over random urban-like obstacles. Boundary-Layer Meteorol 129(1):1–23

    Google Scholar 

  • Zhou Y, Li D, Liu H, Li X (2018) Diurnal variations of the flux imbalance over homogeneous and heterogeneous landscapes. Boundary-Layer Meteorol 168(3):417–442

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank Prof. Katul (Duke University) for fruitful discussions and Prof. Anderson (UT Dallas) for the suggestion to consider using the spectrogram representation. This project has been developed with the support of the U.S. National Science Foundation Grant Number PDM-1649067. Marc Calaf also acknowledges the Mechanical Engineering Department at the University of Utah for start-up funds, and the Center for High Computing Performance (CHPC) at the University of Utah for computing hours. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant Number ACI-1548562. The authors declare no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marc Calaf.

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

Margairaz, F., Pardyjak, E.R. & Calaf, M. Surface Thermal Heterogeneities and the Atmospheric Boundary Layer: The Relevance of Dispersive Fluxes. Boundary-Layer Meteorol 175, 369–395 (2020). https://doi.org/10.1007/s10546-020-00509-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10546-020-00509-w

Keywords

Navigation