Snow cover response to temperature in observational and climate model ensembles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The relationship between land surface temperature and snow cover extent trends is examined in three distinct types of ensembles over the 1981–2010 period: an observation‐based ensemble, a representative selection of CMIP5 coupled climate model output, and two large initial condition coupled climate model ensembles. Observation‐based estimates of snow cover sensitivity are stronger than simulated over midlatitude and alpine regions. Observed sensitivity estimates over Arctic regions are consistent with simulated values. Anomalous snow cover extent trends present in one data set, the NOAA climate record, obscure the relationship to surface temperature seen in the rest of the analyzed data. The spread in modeled snow cover trends reflects roughly equal contributions from intermodel variability and from natural variability. Together, the anomalous relationship between surface temperature and snow cover expressed in the NOAA climate record and the large influence of natural variability present in the simulations highlight the importance of ensemble‐based approaches.
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.
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 it