Committed and projected future changes in global peatlands – continued transient model simulations since the Last Glacial Maximum

Peatlands are diverse wetland ecosystems distributed mostly over the northern latitudes and tropics. Globally they store a large portion of the global soil organic carbon and provide important ecosystem services. The future of these systems under continued anthropogenic warming and direct human disturbance has potentially large impacts on atmospheric CO2 and climate. We performed global long-term projections of peatland area and carbon over the next 5000 years using a dynamic global vegetation model forced with climate anomalies from 10 models of the Coupled Model Intercomparison Project (CMIP6) and three standard future scenarios. These projections are seamlessly continued from a transient simulation from the Last Glacial Maximum to the present to account for the full transient history and are continued beyond 2100 with constant boundary conditions. Our results suggest short to long-term net losses of global peatland area and carbon, with higher losses under higher-emission scenarios. Large parts of today's active northern peatlands are at risk, whereas peatlands in the tropics and, in case of mitigation, eastern Asia and western North America can increase their area and carbon stocks. Factorial simulations reveal committed historical changes and future rising temperature as the main driver of future peatland loss and increasing precipitations as the driver for regional peatland expansion. Additional simulations forced with climate anomalies from a subset of climate models which follow the extended CMIP6 scenarios, transient until 2300, show qualitatively similar results to the standard scenarios but highlight the importance of extended transient future scenarios for long-term carbon cycle projections. The spread between simulations forced with different climate model anomalies suggests a large uncertainty in projected peatland changes due to uncertain climate forcing. Our study highlights the importance of quantifying the future peatland feedback to the climate system and its inclusion into future earth system model projections

Reversible and irreversible impacts of greenhouse gas emissions in multi-century projections with the NCAR global coupled carbon cycle-climate model

The legacy of historical and the long-term impacts of 21st century greenhouse gas emissions on climate, ocean acidification, and carbon-climate feedbacks are investigated with a coupled carbon cycle-climate model. Emission commitment scenarios with zero emissions after year 2100 and 21st century emissions of 1,800, 900, and 0 gigatons of carbon are run up to year 2500. The reversibility and irreversibility of impacts is quantified by comparing anthropogenically-forced regional changes with internal, unforced climate variability. We show that the influence of historical emissions and of non-CO2 agents is largely reversible on the regional scale. Forced changes in surface temperature and precipitation become smaller than internal variability for most land and ocean grid cells in the absence of future carbon emissions. In contrast, continued carbon emissions over the 21st century cause irreversible climate change on centennial to millennial timescales in most regions and impacts related to ocean acidification and sea level rise continue to aggravate for centuries even if emissions are stopped in year 2100. Undersaturation of the Arctic surface ocean with respect to aragonite, a mineral form of calcium carbonate secreted by marine organisms, is imminent and remains widespread. The volume of supersaturated water providing habitat to calcifying organisms is reduced from preindustrial 40 to 25% in 2100 and to 10% in 2300 for the high emission case. We conclude that emission trading schemes, related to the Kyoto Process, should not permit trading between emissions of relatively short-lived agents and CO2 given the irreversible impacts of anthropogenic carbon emission

Radiocarbon in the Land and Ocean Components of the Community Earth System Model

Large amounts of the carbon-isotope 14C, entering Earth's carbon cycle, were produced in the atmosphere by atomic bomb tests in the 1950s and 1960s. Here, we forced the ocean and land components of the Community Earth System Model with atmospheric 14CO2 over the historical period to constrain overturning time scales and fluxes. The uptake of bomb 14C by the land model is lower than observation-based estimates. This mismatch is likely linked to too-low 14C uptake by vegetation as the model overestimates 14C/C ratios of modern soils. This suggests model biases in forest productivity or wood carbon allocation and turnover, and, in turn, a bias in the forest sink of anthropogenic carbon. The ocean model matches the observation-based global bomb 14C inventories when applying the quadratic relationship between gas transfer piston velocity and wind speed of Wanninkhof (2014), https://doi.org/10.4319/lom.2014.12.351 and the wind products from Large and Yeager or the Japanese Reanalysis Project. Simulated natural radiocarbon ages in the deep ocean are many centuries older than data-based estimates, indicating too slow deep ocean ventilation. The sluggish circulation causes large biases in biogeochemical tracers and implies a delayed deep ocean uptake of heat and carbon in global warming projections. Our study suggests that 14C observations are key to constrain carbon fluxes and transport timescales for improved representations of land and ocean biogeochemical cycles and Earth system model projections

A modeling study of oceanic nitrous oxide during the Younger Dryas cold period

The marine production, cycling, and air-sea gas exchange of nitrous oxide (N2O) are simulated in a coupled climate-biogeochemical model of reduced complexity. The model gives a good representation of the large-scale features of the observed oceanic N2O distribution and emissions to the atmosphere. The transient behavior of the model is tested for the Younger Dryas (Y-D) cold period (12,700–11,550 BP), which is simulated by releasing a freshwater pulse into the North Atlantic, causing a temporary collapse of the model's Atlantic thermohaline circulation (THC). A temporary drop in atmospheric N2O of about 10 ppb results, while ice-core measurements show a total drop of 25 to 30 ppb. This suggests that terrestrial changes have also contributed to the observed variations. The main cause of the modeled reduction in atmospheric N2O is increased oceanic storage in the short-term and a reduction of new production in the long-term due to increased stratification

Revision of the global carbon budget due to changing air-sea oxygen fluxes

Carbon budgets inferred from measurements of the atmospheric oxygen to nitrogen ratio (O2/N2) are revised considering sea-to-air fluxes of O2 and N2 in response to global warming and volcanic eruptions. Observational estimates of changes in ocean heat content are combined with a model-derived relationship between changes in atmospheric O2/N2 due to oceanic outgassing and heat fluxes to estimate ocean O2 outgassing. The inferred terrestrial carbon sink for the 1990s is reduced by a factor of two compared with the most recent estimate by the Intergovernmental Panel on Climate Change (IPCC). This also improves the agreement between calculated ocean carbon uptake rates and estimates from global carbon cycle models, which indicate a higher ocean carbon uptake during the 1990s than the 1980s. The simulated decrease in oceanic O2 concentrations is in qualitative agreement with observed trends in oceanic O2 concentrations

The Bern Simple Climate Model (BernSCM) v1.0: an extensible and fully documented open source reimplementation of the Bern reduced form model for global carbon cycle-climate simulations

The Bern Simple Climate Model (BernSCM) is a free open-source re-implementation of a reduced-form carbon cycle–climate model widely used in science and IPCC assessments. BernSCM supports up to decadal time steps with high accuracy and is suitable for studies with high computational load, e.g., integrated assessment models (IAMs). Further applications include climate risk assessment in a business, public, or educational context and the estimation of benefits of emission mitigation options