Satellite observations of annual variability in terrestrial carbon cycles and seasonal growing seasons at high northern latitudes
Bibliographic record
Abstract
Global satellite remote sensing records show evidence of recent vegetation greening and an advance in the onset of the growing season at high latitudes. We apply a terrestrial net primary production (NPP) model driven by satellite observations of vegetation properties and daily surface meteorology from an atmospheric GCM to assess spatial patterns, annual variability, and recent trends in vegetation productivity across Alaska and northwest Canada. We compare these results with regional observations of the timing of growing season onset derived from satellite passive microwave remote sensing measurements from the Special Sensor Microwave Imager, SSM/I. Our results show substantial variability in annual NPP for the region that appears to be driven largely by variations in canopy photosynthetic leaf area and average summer air temperatures. Variability in maximum canopy leaf area and NPP also correspond closely to remote sensing observations of the timing of the primary seasonal thaw event in spring. Relatively early spring thawing appears to enhance NPP, while delays in seasonal thawing and growing season onset reduce annual vegetation productivity. Our results indicate that advances in seasonal thawing and spring and summer warming for the region associated with global change are promoting a general increase in NPP.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".