Radiative impact of boreal smoke in the Arctic: Observed and modeled
Notice bibliographique
Résumé
The Arctic climate is modulated, in part, by the presence of aerosols that affect the horizontal and vertical distribution of radiant energy passing through the atmosphere. Aerosols affect the surface‐atmosphere radiation balance directly through interactions with solar and terrestrial radiation and indirectly through interactions with cloud particles. During summer 2004 forest fires destroyed vast areas of boreal forest in Alaska and western Canada, releasing smoke into the atmosphere. Smoke aerosol passing over instrumented field sites near Barrow, Alaska, was monitored to determine its physical and optical properties and its impact on the surface radiation budget. Empirical determinations of the direct aerosol radiative forcing (DARF) by the smoke were used to corroborate simulations made using the Moderate Resolution Transmittance radiative transfer model, MODTRAN™5. DARF is defined as the change in net shortwave irradiance per unit of aerosol optical depth (AOD). DARF, varying with solar angle and surface type, was evaluated at the surface, at the top of the atmosphere (TOA), and within the intervening layers of the atmosphere. The TOA results are compared with fluxes derived from coincident satellite retrievals made using the Clouds and the Earth's Radiant Energy System (CERES) radiance data. Smoke tends to reduce the net shortwave irradiance at the surface while increasing it within layers in which it resides. Over the Arctic tundra during summer, a layer of smoke having AOD = 0.5 at 500 nm produces a diurnally averaged DARF of about −40 W m−2 at the surface and −20 W m−2 at TOA, while the layer itself tends to warm at a rate of ≈1 K d−1. The tendency of smoke to cool the surface while heating the layer above may lead to increased atmospheric stability and suppress cloud formation. Radiative forcing at the top of the atmosphere is especially sensitive to small changes in surface albedo, evidenced in both the model results and satellite retrievals. TOA net shortwave flux decreases when smoke is present over dark surfaces and tends to increase if the underlying surface is bright. For example, at solar noon during midsummer at Barrow, a layer of smoke having AOD(500) = 0.5 will reduce the net shortwave flux at TOA by ≈30 W m−2 over the ocean while at the same time increasing it by 20 W m−2 over an adjacent area of melting sea ice. For smoke aerosol, the sensitivity of DARF to changing surface albedo (assuming a solar zenith angle of 50°) is about +15 W m−2 AOD−1 for every increase in surface albedo of 0.10. Throughout the Arctic summer, surface and TOA cooling and a tendency toward warming in the intervening atmospheric layers are the dominant radiative impacts of boreal smoke over the ocean and tundra areas, but the radiative forcing at TOA is positive over regions covered by ice or snow. Enhanced differential cooling/heating of ocean, ice, and snow due to the presence of smoke in the atmosphere may affect regional circulation patterns by perturbing diabatic processes. Should the frequency and intensity of boreal fires increase in the future because of global warming, the more persistent presence of smoke in the atmosphere may be manifest as a negative feedback at the surface. In addition, there will likely be indirect radiative impacts of the smoke as it influences cloudiness, which in turn further modulates the Arctic radiation budget.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».