Comment on bg-2022-229
Bibliographic record
Abstract
Abstract. Northern peatland stores a large amount of organic soil carbon and is considered to be one of the most significant CH4 sources among wetlands. The default wetland CH4 emission scheme in JULES (land surface model of the UK Earth System model) only takes into account the CH4 emissions from inundated areas in a simple way. However, it is known that the processes for peatland CH4 emission are complex. In this work, we coupled the process-based peatland CH4 emission model HIMMELI (HelsinkI Model of MEthane buiLd-up and emIssion for peatlands) with JULES (JULES-HIMMELI) by taking the HIMMELI input data from JULES simulations. Firstly, the soil temperature, water table depth (WTD) and soil carbon simulated by JULES, as well as the prescribed maximum leaf area index (LAI) in JULES were evaluated against available datasets at the studied northern wetland sites. Then, the simulated CH4 emissions from JULES and JULES-HIMMELI simulations were compared against the observed CH4 emissions at these sites. Moreover, sensitivities of CH4 emissions to the rate of anoxic soil respiration (anoxic Rs), surface soil temperature and WTD were investigated. Results show that JULES can well represent the magnitude and seasonality of surface (5–10 cm) and relatively deep (34–50 cm) soil temperatures, whereas the simulated WTD and soil carbon density profiles show large deviations from the site observations. The prescribed maximum LAI in JULES was within one standard deviation of the maximum LAIs derived from the Sentinel-2 satellite data for Siikaneva, Kopytkowo and Degerö sites, but lower for the other three sites. The simulated CH4 emissions by JULES have much smaller inter-annual variability than the observations. However, no specific simulation setup of the coupled model can lead to consistent improvements in the simulated CH4 emissions for all the sites. When using observed WTD or modified soil decomposition rate, there were only improvements in simulated CH4 fluxes at certain sites or years. Both simulated and observed CH4 emissions at sites strongly depend on the rate of anoxic Rs, which is the basis of CH4 emission estimates in HIMMELI. By excluding the effect from the rate of anoxic Rs on CH4 emissions, it is found that the Rs-log-normalized CH4 emissions (log normalization of the ratio of CH4 emission to anoxic Rs rate) show similar increasing trends with increased surface soil temperature from both observations and simulations, but different trends with raised WTD which may due to the uncertainty in simulated O2 concentration in HIMMELI. In general, we consider the JULES-HIMMELI model is more appropriate in simulating the wetland CH4 emissions than the default wetland CH4 emission scheme in JULES. Nevertheless, in order to improve the accuracy of simulated wetland CH4 emissions with the JULES-HIMMELI model, it is still necessary to better represent the peat soil carbon and hydrologic processes in JULES and the CH4 production and transportation processes in HIMMELI, such as plant transportation of gases, seasonality of parameters controlling oxidation and production, and adding microbial activities.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.181 | 0.132 |
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".