Near‐surface climate in the boreal forest
Bibliographic record
Abstract
This paper addresses processes that affect near‐surface climate over the boreal forest, using data from the Boreal Ecosystem‐Atmosphere Study (BOREAS) northern study area just west of Thompson, Manitoba. The boreal forest is marked by a very large seasonal cycle with below‐freezing temperatures for half the year. The freezing and thawing of the soil plays an important role in the climate at high latitudes. It moderates winter temperatures (together with the insulating snow cover), because during the freeze process, the effective heat capacity of the soil is greatly increased, and it introduces a significant lag into the climate system. Perhaps the most important consequence is that water is unavailable for evaporation and photosynthesis until snow melts and the ground thaws, which occurs late in spring. As a result, in April and in early May, relative humidity (RH) is a minimum, the surface sensible heat flux is large, and the daytime boundary layer (BL) is very deep, because of this unavailability of water. The situation reverses in the fall, when the ground is warmer than the cooling atmosphere, and mean RH is high and BL depths low. This asymmetry between spring and fall can be seen in both seasonal and diurnal cycles. The forest is heterogeneous, and there is a marked difference in summer in daytime evaporative fraction between the conifers and the deciduous forest and fens. However, above the forest the daytime BL has a strong homogenizing effect, and it is the dominant coniferous forest that controls the mean BL depth. The impact of recent rainfall, stored on the canopy, in the surface moss layer, and in the top soil layer can be readily seen in summer. BL depths rise on succeeding days without rain. A comparison of the fen and young jack pine sites shows the important role of the stomatal control by conifers on transpiration. Since evaporation goes down at high net radiation and low RH for conifer sites, it is clear that the low RH and high BL depth over the forest are a direct consequence of stomatal control. At night, however, temperature, relative humidity, and CO2 are quite heterogeneous under the stable BL. We show that uncoupling of the stable BL at night inside the forest canopy occurs at low wind speeds and high outgoing net radiation and can lead to a 5K cooling within the canopy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".