Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or-more generally-for the production of organic ...matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings-FPE declining with age-are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate.
The evolution of the Earth's climate over the twenty-first century depends on the rate at which anthropogenic carbon dioxide emissions are removed from the atmosphere by the ocean and land carbon ...cycles. Coupled climate-carbon cycle models suggest that global warming will act to limit the land-carbon sink, but these first generation models neglected the impacts of changing atmospheric chemistry. Emissions associated with fossil fuel and biomass burning have acted to approximately double the global mean tropospheric ozone concentration, and further increases are expected over the twenty-first century. Tropospheric ozone is known to damage plants, reducing plant primary productivity and crop yields, yet increasing atmospheric carbon dioxide concentrations are thought to stimulate plant primary productivity. Increased carbon dioxide and ozone levels can both lead to stomatal closure, which reduces the uptake of either gas, and in turn limits the damaging effect of ozone and the carbon dioxide fertilization of photosynthesis. Here we estimate the impact of projected changes in ozone levels on the land-carbon sink, using a global land carbon cycle model modified to include the effect of ozone deposition on photosynthesis and to account for interactions between ozone and carbon dioxide through stomatal closure. For a range of sensitivity parameters based on manipulative field experiments, we find a significant suppression of the global land-carbon sink as increases in ozone concentrations affect plant productivity. In consequence, more carbon dioxide accumulates in the atmosphere. We suggest that the resulting indirect radiative forcing by ozone effects on plants could contribute more to global warming than the direct radiative forcing due to tropospheric ozone increases.
This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO₂, to model the contemporary global carbon cycle. The DGVMs are also ...coupled to a fast 'climate analogue model', based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO₂ content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO₂ on plant production are not considered, implying a positive terrestrial climate-carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra-tropics in response to future climate. When both counteracting effects of climate and atmospheric CO₂ on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO₂ from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.
The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have ...demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.
This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface ...Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.
The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO
2 growth rate, fossil fuel emissions, and modeled (bottom‐up) land and ocean fluxes cannot be fully closed, leading to a ...“budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom‐up and top‐down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO
2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high‐resolution remote‐sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.
Key Points
Top‐down and bottom‐up estimates of net land‐atmosphere CO
2 fluxes agree well globally but show important mismatches at regional scales
Regional mismatches are dominated by differences between inversions and interannual variability in CO
2 fluxes
Mismatches between top‐down and bottom‐up data sets are explained by sensitivity to climate and by uncertainty in land use change forcing
Dynamic global vegetation models (DGVMs) have been shown to broadly reproduce seasonal and interannual patterns of carbon exchange, as well as realistic vegetation dynamics. To assess the ...uncertainties in these results associated with model parameterization, the Lund‐Potsdam‐Jena‐DGVM (LPJ‐DGVM) is analyzed in terms of model robustness and key sensitive parameters. Present‐day global land‐atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in global net primary production mainly propagating from uncertainty in parameters controlling assimilation rate, plant respiration and plant water balance. In response to climate change, water‐use efficiency driven increases in net carbon assimilation by plants, transient changes in vegetation composition and global warming effects on soil organic matter dynamics are robust model results. As a consequence, long‐term trends in land‐atmosphere fluxes are consistently modeled despite an uncertainty range of −3.35 ± 1.45 PgC yr−1 at the end of the twenty‐first century for the specific scenario used.
Cold‐season methane (CH4) emissions may be poorly constrained in wetland models. We examined cold‐season CH4 emissions simulated by 16 models participating in the Global Carbon Project model ...intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.5 Tg CH4 yr−1. While summer CH4 emissions were well simulated compared to in‐situ flux measurement observations, the models underestimated CH4 during September to May relative to annual total (27 ± 9%, compared to 45% in observations) and substantially in the months with subzero air temperatures (5 ± 5%, compared to 27% in observations). Because of winter warming, nevertheless, the contribution of cold‐season emissions was simulated to increase at 0.4 ± 0.8% decade−1. Different parameterizations of processes, for example, freezing–thawing and snow insulation, caused conspicuous variability among models, implying the necessity of model refinement.
Plain Language Summary
Wetlands in the northern high latitudes are a major source of methane (CH4) to the atmosphere, mainly during the warm season. Previously, models have assumed that cold‐season CH4 emissions are low, but recent observations suggest high‐latitude wetlands can be substantial sources even in winter. We compared CH4 emissions simulated by 16 state‐of‐the‐art wetland models, participating in a model intercomparison project with a focus on the cold‐season in northern wetlands. The model simulations indicated that nearly one third of annual emissions were simulated to occur from September to May, and CH4 emissions to the atmosphere were not negligible even under freezing air temperatures, although the results differed greatly among the models. However, field studies suggest cold‐season emissions account for an even larger fraction of annual emissions. These results highlight the contribution of cold‐season emissions to the annual CH4 budget, which future climatic warming is expected to affect severely, and they also show that simulations of cold‐season CH4 emissions from wetlands need to be improved.
Key Points
Cold‐season methane (CH4) emissions simulated by 16 Global Carbon Project‐CH4 wetland models were analyzed
Most models underestimate the cold‐season emissions in comparison with observational data
Further model improvement by including cold‐season processes is required to reduce the model bias and uncertainty
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