Testing and development of the Canadian land surface scheme (class) for forests, agricultural crops and bare soils
Notice bibliographique
Résumé
CLASS (Canadian Land Surface Scheme) is the land surface model currently used in the Canadian general circulation model. It features a single vegetation layer, three soil layers (and a snow layer when necessary) and physically-based calculations of the energy and water exchange between the atmosphere and land surface. This research focused on the validation of CLASS and the improvement of relevant parameterizations. CLASS was tested using continuous half-hourly energy balance and soil water content (θ) data collected during much of 1994 and from spring 1996 to the end of 1998 from a boreal aspen forest and during short summer periods over past 20 years from six west coast Douglas-fir forests, two agricultural crops and two bare soils. Tests identified the following deficiencies in CLASS : (1) evaporation from the soil surface was significantly overestimated, (2) transpiration from the aspen forest was underestimated under conditions of high solar irradiance, (3) winter albedo was too high, and (4) surface runoff after snowmelt was excessive. Two semi-empirical soil evaporation relationships (the α and β methods) were compared with Philip's relationship using measurements of evaporation from a bare loam/silt-loam soil. The latter, although physically-based, performed poorly when used with a thick surface soil layer as in CLASS. The β method performed significantly better than the a method. Parameterizations of canopy conductance (g[sub c]) based on the Jarvis- Stewart (JS) (also used in CLASS), the Ball-Woodrow-Berry (BWB) and a modified form of the BWB parameterization (MBWB) were evaluated for the aspen forest and a Douglas-fir forest. A new JS parameterization gave the best estimates of g[sub c], while the MBWB parameterization performed better than the BWB parameterization. The new JS and MBWB parameterizations worked well for five Douglas-fir forests of similar age with different leaf area indices under conditions of high θ but worked poorly for conditions of low θ because the response of Douglas-fir g[sub c] to soil water stress differed considerably from site to site. Adjusting the winter albedo for the aspen forest from 0.5 to the more realistic value of 0.25 significantly improved the calculation of winter net radiation, predicted the occurrence of snowmelt only 5-10 days later than observations and significantly reduced the overestimation of surface runoff following snowmelt. The near-field effect on flux calculations was examined using two approaches: (1) the near-field resistance was places in series with the aerodynamic resistance in CLASS, and (2) the performance of a Lagrangian two-layer canopy model was compared with a Ktheory two-layer canopy model and a /f-theory single-layer canopy model. The first approach was tested using data from a Douglas-fir forest, the aspen forest and an agricultural crop. The second approach was tested using data from the aspen forest because it had a thick understory canopy. Results from both approaches confirmed that the difference between simulations from AT-theory and the Lagrangian evaporation models was small due to the strong control by stomatal conductance. Furthermore, the two-layer canopy models were inferior to the single-layer canopy model in the calculation of the sensible and latent heat fluxes above the forest.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».