The influence of DEM resolution on simulated solar radiation‐induced glacier melt
Bibliographic record
Abstract
Abstract The influence of digital elevation model (DEM) resolution to modelled glacier melt during peak melt production was evaluated by performing a clear sky GIS radiation simulation over the Peyto Glacier in the Canadian Rockies. DEMs were generated at eight resolutions ranging from 1 m to 1000 m grid spacing from airborne lidar data. When applied to the planar area (PA) of the terrain, it was found that total melt increased with DEM resolution ( r 2 = 0·63) by 4% over 3 orders of magnitude. This systematic scaling‐effect was mitigated at the basin scale, however, when the DEM slope variant area (SVA) was used to account for the increased divergence from PA as resolution increases. However, even after the inclusion of SVA in glacier surface melt simulations, localized melt variations with scale were still evident in the ablation and accumulation zone observations. In the ablation zone, there was a systematic increase in simulated melt (∼4%) as resolution decreased from 1 m to 1000 m ( r 2 = 0·89), with the opposite effect in the accumulation zone ( r 2 = 0·81). DEM resolution also affected the diurnal melt cycle, such that for the entire glacier there was a tendency for a morning over‐estimation and afternoon underestimation of melt rate with decreasing resolution. For the accumulation zone, there was an increased melt rate at low resolutions occurring in the afternoon, while in the ablation zone there was a tendency for increasing melt rates with decreasing resolution throughout the day. These localized spatio‐temporal variations in simulated melt are largely due to the lowering of ridges and raising of valley floors that occur as resolution decreases. This scale dependence in the representation of terrain morphology directly controls the pattern and relative proportion of direct beam shadowing over actively melting surfaces and thereby has a systematic influence on the grid cell‐level hydrological balance. It is recommended that GIS‐based glacier melt modelling routines take into account the slope area of grid cells, while noting that the choice of DEM scale can have a discernible and systematic influence on modelled runoff magnitude. It is important to note that while higher grid resolutions mitigate the effect of terrain smoothing on spatio‐temporal melt patterns, lower resolutions actually mitigate the systematic error associated with assuming all surface areas are planar. Copyright © 2010 John Wiley & Sons, Ltd and Her Majesty the Queen in right of Canada.
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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 | 0.000 |
| 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) | 0.000 | 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".