Sub-grid scale representation of vegetation in global land surface schemes: implications for estimation of the terrestrial carbon sink
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. Terrestrial ecosystem models commonly represent vegetation in terms of plant functional types (PFTs) and use their vegetation attributes in calculations of the energy and water balance as well as to investigate the terrestrial carbon cycle. Sub-grid scale variability of PFTs in these models is represented using different approaches with the "composite" and "mosaic" approaches being the two end-members. The impact of these two approaches on the global carbon balance has been investigated with the Canadian Terrestrial Ecosystem Model (CTEM v 1.2) coupled to the Canadian Land Surface Scheme (CLASS v 3.6). In the composite (single-tile) approach, the vegetation attributes of different PFTs present in a grid cell are aggregated and used in calculations to determine the resulting physical environmental conditions (soil moisture, soil temperature, etc.) that are common to all PFTs. In the mosaic (multi-tile) approach, energy and water balance calculations are performed separately for each PFT tile and each tile's physical land surface environmental conditions evolve independently. Pre-industrial equilibrium CLASS-CTEM simulations yield global totals of vegetation biomass, net primary productivity, and soil carbon that compare reasonably well with observation-based estimates and differ by less than 5% between the mosaic and composite configurations. However, on a regional scale the two approaches can differ by > 30%, especially in areas with high heterogeneity in land cover. Simulations over the historical period (1959–2005) show different responses to evolving climate and carbon dioxide concentrations from the two approaches. The cumulative global terrestrial carbon sink estimated over the 1959–2005 period (excluding land use change (LUC) effects) differs by around 5% between the two approaches (96.3 and 101.3 Pg, for the mosaic and composite approaches, respectively) and compares well with the observation-based estimate of 82.2 ± 35 Pg C over the same period. Inclusion of LUC causes the estimates of the terrestrial C sink to differ by 15.2 Pg C (16%) with values of 95.1 and 79.9 Pg C for the mosaic and composite approaches, respectively. Spatial differences in simulated vegetation and soil carbon and the manner in which terrestrial carbon balance evolves in response to LUC, in the two approaches, yields a substantially different estimate of the global land carbon sink. These results demonstrate that the spatial representation of vegetation has an important impact on the model response to changing climate, atmospheric CO2 concentrations, and land cover.
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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 it