| Titre | A comparison of parametrizations of canopy conductance of aspen and Douglas-fir forests for class |
| Auteur | Wu, A; Black, T A; Novak, M D; Yang, P C; Verseghy, D L; Blanken, P D; Chen, W |
| Source | Atmosphere-Ocean vol. 38, no. 1, 2000 p. 81-112, https://doi.org/10.1080/07055900.2000.9649641 |
| Année | 2000 |
| Séries alt. | Ressources naturelles Canada, Contribution externe 20181875 |
| Éditeur | Informa UK Limited |
| Document | publication en série |
| Lang. | anglais |
| DOI | https://doi.org/10.1080/07055900.2000.9649641 |
| Media | papier; en ligne; numérique |
| Formats | pdf |
| Sujets | télédétection; géophysique |
| Programme | Géosciences de changements climatiques |
| Résumé | (disponible en anglais seulement)
Canopy conductance (gc) of an old boreal aspen forest and a west coast Douglas-fir forest was calculated from the inversion of the Penman-Monteith (PM) equation
with above-canopy water vapour flux measurements. Values of aspen gc agreed reasonably well with those obtained by scaling up from leafstomatal conductance measurements. Comparison of values of gc obtained from the CLASS (Canadian LAnd Surface
Scheme) parametrization with values of Douglas-fir gc in 1983 and 1984 calculated from the PM equation showed that the CLASS parametrization (based on the Jarvis-Stewart (JS) model) worked well at high soil water potential (?), but underestimated gc
at low ?. In the case of the aspen forest during a wet growing season in 1994, the CLASS parametrization underestimated gc for high values of incident photosynthetic photon flux density. The effectiveness of three parametrizations of gc, developed
using linear or non-linear least squares analysis, was evaluated for the two forests. The first (based on the JS model), related gc to the product of several independent limiting functions, the second (based on the Ball-Woo-drow-Berry (B WB) model
related gc to the product of canopy net assimilation rate and canopy surface relative humidity divided by canopy surface CO2 concentration, and the third (based on a modified form of the BWB (MBWB) model) was the same as the second except that the
relative humidity was replaced by the reciprocal of air vapour pressure deficit. For both forests, the JS parametrization gave the highest r2 and lowest root mean square (RMS) error. The RMS error of the MBWB parametrization was less than that of the
BWB parametrization because the latter underestimated gc during the morning. With the incorporation of the new JS and MBWB parametrizations into CLASS, better estimates of the latent heat flux (QE) from the aspen and Douglas-fir forests were obtained
on half-hourly and daily bases than with the original CLASS parametrization. The JS parametrization gave better estimates than the MBWB parametrization. Both models parametrized using 1994 data from the aspen forest were successfully applied to the
same stand in 1996, which also had a relatively wet growing season. Both models parametrized using data from the Douglas-fir forest were also applied to four other similar-aged Douglas-fir forests but with different values of the leaf area index.
Under conditions of minimal water stress, better estimates of QE were obtained for three of the four forests using both parametrizations. In the case of the fourth forest, none of the parametrizations gave satisfactory estimates. This was likely
because the initial conditions of soil water content and ? used in CLASS for the gravelly soil was significantly overestimated as a result of not taking the stone content into account. For conditions of high water stress, which occurred in two of the
forests, none of the parametrizations gave satisfactory estimates. However, when the ? limiting function in the JS parametrization was replaced by that developed from measurements made in the other two forests, the JS parametrization gave reasonable
estimates of QE. In the case of the MBWB parametrization, we were unable to adjust the ? limiting function due to the lack of measurements of canopy net assimilation rate at these two sites. © 2000 Taylor & Francis Group, LLC. |
| GEOSCAN ID | 312230 |
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