Snow thermal conductivity controls future winter carbon emissions in shrub–tundra
Bibliographic record
Abstract
Abstract. The Arctic winter is disproportionately vulnerable to climate warming and approximately 1700 Gt of carbon stored in high-latitude permafrost ecosystems is at risk of degradation in the future due to enhanced microbial activity. Few studies have been directed at high-latitude cold season land–atmosphere processes and it is suggested that the contribution of winter season greenhouse gas (GHG) fluxes to the annual carbon budget may have been underestimated. Snow, acting as a thermal blanket, influences the Arctic soil temperatures during winter and parameters such as snow effective thermal conductivity (Keff) are not well constrained in land surface models, which impacts our ability to accurately simulate wintertime soil carbon emissions. To address this, we investigated the impacts of implementing a Keff parameterisation more suitable to Arctic snowpacks into the Community Land Model (CLM5.0). A point-model version of CLM5.0 forced by an ensemble of NA-CORDEX (North American Coordinated Regional Downscaling Experiment) future climate realisations (RCP 4.5 and 8.5) indicates that median winter CO2 emissions will have more than tripled by the end of the century (2066–2096) under RCP 8.5. Implementing the refined Keff parameterisation increases simulated winter CO2 in the latter half of the century (2066–2096) by 130 % and CH4 flux by 50 % under RCP 8.5 compared to the widely used default Keff parameterisation. The influence of snow Keff parameterisation within CLM5.0 on future simulated CO2 and CH4 is at least as significant, if not more so, than climate variability from a range of NA-CORDEX projections to 2100. The average difference in refined Keff compared with the default Keff raises minimum winter soil temperatures by 4–7 °C by the end of the century under RCP 4.5 and 8.5. Furthermore, CLM5.0 simulations using the refined Keff show an extension of the early winter (September–October) zero-curtain period, by nearly a month under RCP 8.5. Consequently, recent increases in both zero-curtain duration and winter CO2 emissions appear set to continue to 2100. Modelled winter soil temperatures and carbon emissions further highlight the importance of climate mitigation in preventing a significant increase in winter carbon emissions from the Arctic in the future.
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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 | 0.001 |
| 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) | 0.002 | 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".