Evaluation of local climate variability in the Peruvian Andes: an analysis of high-resolution observations and regional trends
Bibliographic record
Abstract
Rapid environmental change in the tropical Andes may have significant impacts on glacial melt rates and water resources provided by those glaciers. We analyzed a high-resolution (i.e. hourly) archive of spatially distributed climate observations from the Cordillera Blanca (8-10°S) between July 2006 and July 2010. We collected these observations using a network of Lascar Data Loggers. The network consists of nine lascars arranged throughout the Llanganuco valley. The lascars range from 3458 to 4775 meters above sea level. Analyses of the four-year data set were conducted on three temporal scales: diurnal, seasonal, and inter-annual. Altitudinal variability was also considered. Data processing was comprised of five levels of analyses: (1) steps taken to consolidate and give confidence to the collected data; (2) a review of diurnal variability and trends; (3) a review of seasonal variability; (4) a review of inter-annual variability and trends; and (5) an evaluation of trends across elevation gradients. The evaluation of diurnal and vertical patterns between seasons was conducted in a similar fashion. These data were then compared to regional data archives for comparison. The data collected by the lascar network in Llanganuco can be used as an input to our glacier mass balance and flow model. Providing a model to predict glacial mass balance changes can be a valuable tool for scientists and policy-makers alike in determining management practices for water resources in the Cordillera Blanca.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".