The impact of coniferous forest temperature on incoming longwave radiation to melting snow
Bibliographic record
Abstract
Abstract Measurements were conducted in coniferous forests of differing density, insolation and latitude to test whether air temperatures are suitable surrogates for canopy temperature in estimating sub‐canopy longwave irradiance to snow. Air temperature generally was a good representation of canopy radiative temperature under conditions of low insolation. However during high insolation, needle and branch temperatures were well estimated by air temperature only in relatively dense canopies and exceeded air temperatures elsewhere. Tree trunks exceeded air temperatures in all canopies during high insolation, with the relatively hottest trunks associated with direct interception of sunlight, sparse canopy cover and dead trees. The exitance of longwave radiation from these relatively warm canopies exceeded that calculated assuming canopy temperature was equal to air temperature. This enhancement was strongly related to the extinction of shortwave radiation by the canopy. Estimates of sub‐canopy longwave irradiance using either two‐energy source or two thermal regime approaches to evaluate the contribution of canopy longwave exitance performed better than did estimates that used only air temperature and sky view. However, there was little evidence that such corrections are necessary under cloudy or low solar insolation conditions. The longwave enhancement effect due to shortwave extinction was important to sub‐canopy longwave irradiance to snow during clear, sunlit conditions. Longwave enhancement increased with increasing solar elevation angle and decreasing air temperature. Its relative importance to longwave irradiance to snow was insensitive to canopy density. As errors from ignoring enhanced longwave contributions from the canopy accumulate over the winter season, it is important for snow energy balance computations to include the enhancement in order to better calculate snow internal energy and therefore the timing and magnitude of snowmelt and sublimation. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".