Editorial: Connecting Mountain Hydroclimate Through the American Cordilleras
Bibliographic record
Abstract
Connecting Mountain Hydroclimate Through the American CordillerasMountains are key hydroclimatic features that couple large-scale atmospheric processes with the earth surface, influencing the development of diverse waterscapes.Decades of transformative research have highlighted how mountains are valuable for society, revealing that changes in these landscapes exert significant impacts on downstream hydrological regimes that support lives and livelihoods of millions (Viviroli et al., 2020).Yet despite sharing common features of verticality and orographic uplift, the complexity of mountain environments is an inherent feature that inevitably leads to geographic particularities, and challenges maintaining consistent observations.Nowadays, many of these mountain waterscapes are undergoing significant alterations in the context of ongoing climate and environmental changes (Immerzeel et al., 2020).The vast latitudinal expanse of the Cordilleras that span from Patagonia to Alaska provides abundant examples of mountain hydroclimatic dynamics as they traverse entire atmospheric systems and delimit diverse climatic regions.Along this interhemispheric transect are similarities and contrasts in both biophysical and human components, whereby intercomparisons may broaden understanding.How similar and how distinct is the research emerging in this context?Can we, as a community of researchers, leverage our geographic diversity to gain new insights that so far have not been described in a frame facilitating cross comparisons along the American Cordilleras?The present collection of research papers aims to move us forward to questioning our perspectives and advance coordinated efforts, with studies highlighting different aspects of the hydroclimate along the American mountains.Our intention with this special edition is to show diverse research-distinct in methodology, scale, and topic-that is linked to a common mountain hydroclimatic theme.The context of rapid climate and environmental change raises the value and urgency of mountain research that allows for comparative views along the American Cordilleras, and we anticipate that such efforts might elucidate constructive perspectives into changes taking place at unprecedented rates, and ideally may support future strategies to tackle these emergent challenges.Instrumental and satellite observations are vital tools for accurate hydroclimatic characterization.For mountain areas, acquiring, curating and organizing data remain challenging and thus systematization efforts need to be encouraged.Condom et al. have likely produced one of the most exhaustive analysis of available hydroclimatic datasets from the Andes.The study shows that in almost all countries actual instrumental records comprise a small percentage of national networks.They suggest that satellite data may become a crucial source for hydroclimatic analysis given the increasing coverage over the region, albeit with diverse spatiotemporal resolutions that necessitate
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.028 | 0.018 |
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".