Canopy architecture and turbulence structure in a coniferous forest

被引:74
作者
Marcolla, B
Pitacco, A
Cescatti, A [1 ]
机构
[1] Ctr Ecol Alpina, I-38040 Trento, Italy
[2] Univ Trent, Dept Civil & Environm Engn, Trento, Italy
[3] Univ Padua, Dept Environm Agron & Crop Prod, I-35100 Padua, Italy
关键词
canopy architecture; drag coefficient; scalar transport; turbulence statistics;
D O I
10.1023/A:1023027709805
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Synchronous sonic anemometric measurements at five heights within a mixed coniferous forest were used to test two different parameterisations of canopy architecture in the application of a second-order turbulence closure model. In the computation of the leaf drag area, the aerodynamic sheltering was replaced with an architectural sheltering, assumed to be analogous to the clumping index defined in radiative transfer theory. Consequently, the ratio of leaf area density and sheltering factor was approximated by the effective leaf area or the mean contact number, both obtained from the inversion of non-destructive optical measurements. The first parameter represents the equivalent randomly dispersed leaf area in terms of shading, the second is the average number of leaves that a straight line intercepts penetrating the canopy with a certain zenith angle. The selection of this direction was determined by the analysis of the mean angle of the wind vector during sweep events. The drag coefficient values obtained from the inversion of the momentum flux equation, using the two proposed parameterisations, are in good agreement with values found in the literature. The predicted profiles of turbulence statistics reasonably match actual measurements, especially in the case of the mean contact number parameterisation. The vertical profile of leaf drag area, obtained by forcing the turbulence model to match the observed standard deviation of vertical velocity (sigma(w)), is intermediate between the two empirical ones. Finally, the proposed canopy parameterisations were applied to a Lagrangian transport model to predict vertical profiles of air temperature, H2O and CO2 concentration.
引用
收藏
页码:39 / 59
页数:21
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