Heat Transfer Through Grass: A Diffusive Approach

Journal Article (2022)
Author(s)

Steven J.A. van der Linden (TU Delft - Atmospheric Remote Sensing)

M.T. Kruis

OK Hartogensis (Wageningen University & Research)

A.F. Moene (Wageningen University & Research)

F.C. Bosveld (Royal Netherlands Meteorological Institute (KNMI))

Bas J.H. Van De Wiel (TU Delft - Atmospheric Remote Sensing)

Research Group
Atmospheric Remote Sensing
Copyright
© 2022 S.J.A. van der Linden, M.T. Kruis, O.K. Hartogensis, A.F. Moene, F.C. Bosveld, B.J.H. van de Wiel
DOI related publication
https://doi.org/10.1007/s10546-022-00708-7
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 S.J.A. van der Linden, M.T. Kruis, O.K. Hartogensis, A.F. Moene, F.C. Bosveld, B.J.H. van de Wiel
Research Group
Atmospheric Remote Sensing
Issue number
2
Volume number
184
Pages (from-to)
251-276
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Abstract

Heat transport through short and closed vegetation such as grass is modelled by a simple diffusion process. The grass is treated as a homogeneous ‘sponge layer’ with uniform thermal diffusivity and conductivity, placed on top of the soil. The temperature and heat-flux dynamics in both vegetation and soil are described using harmonic analysis. All thermal properties have been determined by optimization against observations from the Haarweg climatological station in The Netherlands. Our results indicate that both phase and amplitude of soil temperatures can be accurately reproduced from the vegetation surface temperature. The diffusion approach requires no specific tuning to, for example, the daily cycle, but instead responds to all frequencies present in the input data, including quick changes in cloud cover and day– night transitions. The newly determined heat flux at the atmosphere–vegetation interface is compared with the other components of the surface energy balance at this interface. The budget is well-closed, particularly in the most challenging cases with varying cloud cover and during transition periods. We conclude that the diffusion approach (either implemented analytically or numerically) is a physically consistent alternative to more ad hoc methods, like ‘skin resistance’ approaches for vegetation and bulk correction methods for upper soil heat storage. However, more work is needed to evaluate parameter variability and robustness under different climatological conditions. From a numerical perspective, the present representation of vegetation allows for both slow and rapid feedbacks between the atmosphere and the surface. As such, it would be interesting to couple the present surface parametrization to turbulence-resolving models, such as large-eddy simulations.