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Surface Temperature and Surface-Layer Turbulence in a Convective Boundary Layer

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Abstract

Previous laboratory and atmospheric experiments have shown that turbulence influences the surface temperature in a convective boundary layer. The main objective of this study is to examine land-atmosphere coupled heat transport mechanism for different stability conditions. High frequency infrared imagery and sonic anemometer measurements were obtained during the boundary layer late afternoon and sunset turbulence (BLLAST) experimental campaign. Temporal turbulence data in the surface-layer are then analyzed jointly with spatial surface-temperature imagery. The surface-temperature structures (identified using surface-temperature fluctuations) are strongly linked to atmospheric turbulence as manifested in several findings. The surface-temperature coherent structures move at an advection speed similar to the upper surface-layer or mixed-layer wind speed, with a decreasing trend with increase in stability. Also, with increasing instability the streamwise surface-temperature structure size decreases and the structures become more circular. The sequencing of surface- and air-temperature patterns is further examined through conditional averaging. Surface heating causes the initiation of warm ejection events followed by cold sweep events that result in surface cooling. The ejection events occur about 25 % of the time, but account for 60–70 % of the total sensible heat flux and cause fluctuations of up to 30 % in the ground heat flux. Cross-correlation analysis between air and surface temperature confirms the validity of a scalar footprint model.

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Acknowledgments

We thank (i) Daniel Alexander from University of Utah, USA; Dr. Marie Lothon, Dr. Fabienne Lohou, Solene Derrien from Laboratoire d’Aérologie, Université de Toulouse, France; Dr. Arnold Moene, Dr. Oscar Hartogensis, Anneke Van de Boer from Wageningen University, Netherlands for field assistance, data sharing and discussion; (ii) Peter Cottle and Anders Nottrott from University of California, San Diego for pre-experimental laboratory assistance and discussion about the data analysis respectively; (iii) BLLAST organizers for their hospitality during the experiment; (iv) funding from a NASA New Investigator Program award for AG and JK, and from INSU-CNRS (Institut National des Sciences de l’Univers, Centre national de la Recherche Scientifique, LEFE-IDAO program), Météo-France, Observatoire Midi-Pyrénées (University of Toulouse), EUFAR (EUropean Facility for Airborne Research) and COST ES0802 (European Cooperation in the field of Scientific and Technical) for the BLLAST field experiment.

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, University of California, 9500 Gilman Drive, EBUII–580, La Jolla, San Diego, CA, 92093-0411, USA

    Anirban Garai & Jan Kleissl

  2. Department of Mechanical Engineering, University of Utah, Salt Lake City, USA

    Eric Pardyjak

  3. Meteorology and Air Quality, Wageningen University, Wageningen, The Netherlands

    Gert-Jan Steeneveld

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  1. Anirban Garai
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  2. Eric Pardyjak
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  4. Jan Kleissl
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Correspondence to Jan Kleissl.

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Appendix

Appendix

The ogive function can be employed to estimate the sufficient averaging period for calculation of turbulent fluxes using the eddy-covariance method. Ogive \((og_{w.X} \left( {f_o } \right) )\) is a cumulative integral of the cospectrum, \(Co_{w,X}\), of a variable, \(X\), with vertical velocity, \(w\), starting with the highest frequency, \(f,\,og_{w.X} \left( {f_o } \right) =\int _\infty ^{f_0 } {Co_{w,X} \left( f \right) df}\). Ideally the ogive function increases during the integration from high frequency to small frequency, until reaching a constant value. Hence the period corresponding to the frequency at which the ogive reaches the constant value is considered to be sufficient to capture the largest turbulence scales. To improve the statistical significance and minimize the effect of diurnal cycles, twenty-six 30-min segments for each clear days corresponding to 0600–1900 UTC were used. It was found that a 5-min averaging period accounts for 90 and 85% of the maximum value of ogive for 2- and 8-m CSATs respectively for the sensible heat flux (Fig. 12) and the momentum flux (not shown). Thus an averaging period of 5-min was selected.

Fig. 12
figure 12

The normalized ogive by its maximum value for heat-flux calculation from the 2-m and 8-m CSATs for all the clear days

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Garai, A., Pardyjak, E., Steeneveld, GJ. et al. Surface Temperature and Surface-Layer Turbulence in a Convective Boundary Layer. Boundary-Layer Meteorol 148, 51–72 (2013). https://doi.org/10.1007/s10546-013-9803-4

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