Validation of the RACMO2.3 surface mass-balance model over northwest Devon Ice Cap, Nunavut
Bibliographic record
Abstract
The RACMO2.3 regional climate model has been validated against in-situ mass-balance measurements along the northwest Devon ice cap transect (herein after referred to as Devon(NW)) at annual, pentadal, and decadal time scales over the period spanning 2006 to 2015. Results show close agreement between Summer Balance measurements at the pentadal and decadal time scales, with a bias towards suppressed melt by ~200 mm w.e. in the RACMO2.3 data averaged over the entire transect (ie. 100 - 1800 m a.s.l.), and maximum biases to ~600 mm w.e. between 400 and 900 m a.s.l. Comparisons at the annual scale indicate greatest discrepancies for 2010 for which RACMO2.3 was up to 80 cm w.e. less negative than the in-situ values. Winter Balance in the RACMO2.3 data showed an inverse elevational trend relative to the in-situ values with an overall bias towards greater accumulation by ~120 mm w.e. along the entire transect. At the basin-wide scale, RACMO2.3 under (over) estimates of summer (winter) balance values combine to result in basin-wide estimates of net balance for the Devon (NW) basin to be 37% less negative than the in-situ measurements over the 2006-2015 period. Reasonable agreement with in-situ derived Summer Balance values indicates RACMO2.3 can provide estimates of seasonal freshwater flux to oceans close to and within error of the measurements. However, significant biases in the RACMO2.3 Net Annual Balance modeled values must be accounted for when estimating annual or multi-annual contributions to global sea-level rise from glaciers and ice caps in the Canadian high Arctic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".