Estimating sub‐canopy shortwave irradiance to melting snow on forested slopes
Bibliographic record
Abstract
Abstract Estimates of shortwave irradiance energy beneath needle‐leaf forests over complex terrain are needed to drive energy balance snowmelt models and to evaluate the potential hydrological impacts of forest‐cover change in mountain regions. This paper outlines and evaluates a physically‐based model designed to estimate sub‐canopy shortwave irradiance to snowcover under needle‐leaf forest‐cover with respect to surface slope and azimuth. Transmission of above‐canopy irradiance was estimated using forest‐surveys and hemispherical photographs to determine the fractions of forest‐cover occupied by non‐transmitting trunks, partially‐transmitting crowns and fully‐transmitting gaps with respect to above‐canopy diffuse and direct beam shortwave irradiance. Simulations were conducted for continuous, uniform lodgepole pine forests on level site and a north facing slope and a discontinuous, non‐uniform forest on a southeast facing slope during snowmelt at the Marmot Creek Research Basin, Alberta, Canada. Mean observed daily transmissivity values of irradiance were 0·09 at the north‐facing forest, 0·21 at the level forest and 0·36 at the southeast‐facing forest. Modelled and observed results indicate that potential snowmelt energy from sub‐canopy shortwave irradiance is likely to exhibit the greatest variation with change in cloudiness and forest‐cover density under south‐facing forests and the least variation under north‐facing forests. Comparisons of simulations to observations indicate that the model can explain much of the difference in daily shortwave transmission amongst sites, performing relatively poorest at the north‐facing forest where fluxes were small and relatively best at the south‐east facing forest where fluxes were large. However, simulation errors in terms of absolute irradiance were greatest at the southeast‐facing forest, having a root mean square error (RMSE) 0·64 MJ m −2 d −1 compared to 0·44 MJ m −2 d −1 at the level forest and 0·27 MJ m −2 d −1 at the north‐facing forest. Copyright © 2007 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".