Mass balances of Yala and Rikha Samba glaciers, Nepal, from 2000 to 2017
Bibliographic record
Abstract
Abstract. The direct or glaciological method is an integral part of international glacier monitoring strategies, and the mass balance is an essential variable to describe the climate system and model runoff. In 2011, we established two glacier mass balance programmes on Yala and Rikha Samba Glacier in the Nepal Himalaya. Here we present the methods and data that we ingested into the database of the World Glacier Monitoring Service. We present glacier length changes and the annual mass balances for the first six mass balance years for both glaciers. For Yala Glacier we additionally present the mass balance of seasonal in situ measurements and the mass balance from 2000 to 2012 analysed with the geodetic method. The annual mass balance rates of Yala Glacier from 2000 to 2012 and from 2011 to 2017 are −0.74 ± 0.53 m and −0.74 ± 0.28 m w.e. a−1, and for Rikha Samba Glacier from 2011 to 2017 −0.39 ± 0.32 m w.e. a−1. The mass loss for the period 2011 to 2017 for Yala and Rikha Samba Glacier −4.44 ± 0.69 m w.e. and −2.34 ± 0.79 m w.e., respectively. The winter balance of Yala Glacier is positive in every investigated year, but the negative summer balance determines the annual balance. The mass balance of Yala Glacier is more negative than on other glaciers in the region, mostly because of the small and low lying accumulation area. The mass balance of Rikha Samba Glacier is more positive than the other glaciers in the region, likely because of the large and high lying accumulation area. Due to the topography, the retreat rates of Rikha Samba Glacier are much higher than for Yala Glacier. From 1989 to 2013, Rikha Samba retreated 431 m (−18.0 m a−1), and from 1974 to 2016 Yala Glacier retreated 346 m (−8.2 m a−1). During the study period, a change of Yala Glacier's surface topography has been observed with glacier thinning and down wasting, which indicates the likely disappearance of Yala Glacier within this century. The datasets are freely accessible from WGMS (2020a): Fluctuations of Glaciers Database. World Glacier Monitoring Service, Zurich, Switzerland. http://dx.doi.org/10.5904/wgms-fog-2020-08.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".