Model sensitivity in the effect of Antarctic sea ice and stratification on atmospheric pCO2

Several recent papers have demonstrated a decrease in atmospheric pCO(2) resulting from barriers to communication between the deep sea and the atmosphere in the Southern Ocean. Stephens and Keeling [2000] decreased pCO(2) by increasing Antarctic sea ice in a seven-box model of the world ocean, and Toggweiler [1999] showed a similar response to Southern Ocean stratification. In box models the pCO(2) of the atmosphere is controlled by the region of the surface ocean that fills the deep sea [Archer et al., 2000a]. By severing the Southern Ocean link between the deep sea and the atmosphere, atmospheric pCO(2) in these models is controlled elsewhere and typically declines, although the models range widely in their responses. "Continuum models,'' such as three-dimensional (3-D) and 2-D general circulation models, control pCO(2) in a more distributed way and do not exhibit box model sensitivity to high-latitude sea ice or presumably stratification. There is still uncertainty about the high-latitude sensitivity of the real ocean. Until these model sensitivities can be resolved, glacial pCO(2) hypotheses and interpretations based on Southern Ocean barrier mechanisms (see above mentioned references plus Elderfield and Rickaby [2000], Francois et al. [1998], Gildor and Tziperman [2001], Sigman and Boyle [2000], and Watson et al. [2000]) are walking on thin ice

Upscaling methane emission hotspots in boreal peatlands

Upscaling the properties and the effects of small-scale surface heterogeneities to larger scales is a challenging issue in land surface modeling. We developed a novel approach to upscale local methane emissions in a boreal peatland from the micro-topographic scale to the landscape-scale. We based this new parameterization on the analysis of the water table pattern generated by the Hummock–Hollow model, a micro-topography resolving model for peatland hydrology. We introduce this parameterization of methane hotspots in a global model-like version of the Hummock–Hollow model, that underestimates methane emissions. We tested the robustness of the parameterization by simulating methane emissions for the next century forcing the model with three different RCP scenarios. The Hotspot parameterization, despite being calibrated for the 1976–2005 climatology, mimics the output of the micro-topography resolving model for all the simulated scenarios. The new approach bridges the scale gap of methane emissions between this version of the model and the configuration explicitly resolving micro-topography

Sensitivity of a coupled climate-carbon cycle model to large volcanic eruptions

The sensitivity of the climate-biogeochemistry system to volcanic eruptions is investigated using the comprehensive Earth System Model developed at the Max Planck Institute for Meteorology. The model includes an interactive carbon cycle with modules for terrestrial biosphere as well as ocean biogeochemistry. The volcanic forcing is based on a recent reconstruction for the last 1200 yr. An ensemble of five simulations is performed and the averaged response of the system is analysed in particular for the largest eruption of the last millennium in the year 1258. After this eruption, the global annual mean temperature drops by 1 K and recovers slowly during 10 yr. Atmospheric CO2 concentration declines during 4 yr after the eruption by ca. 2 ppmv to its minimum value and then starts to increase towards the pre-eruption level. This CO2 decrease is explained mainly by reduced heterotrophic respiration on land in response to the surface cooling, which leads to increased carbon storage in soils, mostly in tropical and subtropical regions. The ocean acts as a weak carbon sink, which is primarily due to temperature-induced solubility. This sink saturates 2 yr after the eruption, earlier than the land uptake. © 2010 The Authors Tellus B © 2010 International Meteorological Institute in Stockholm

Biogeophysical feedbacks trigger shifts in the modelled vegetation-atmosphere system at multiple scales

Terrestrial vegetation influences climate by modifying the radiative-, momentum-, and hydrologic-balance. This paper contributes to the ongoing debate on the question whether positive biogeophysical feedbacks between vegetation and climate may lead to multiple equilibria in vegetation and climate and consequent abrupt regime shifts. Several modelling studies argue that vegetation-climate feedbacks at local to regional scales could be strong enough to establish multiple states in the climate system. An Earth Model of Intermediate Complexity, PlaSim, is used to investigate the resilience of the climate system to vegetation disturbance at regional to global scales. We hypothesize that by starting with two extreme initialisations of biomass, positive vegetation-climate feedbacks will keep the vegetation-atmosphere system within different attraction domains. Indeed, model integrations starting from different initial biomass distributions diverged to clearly distinct climate-vegetation states in terms of abiotic (precipitation and temperature) and biotic (biomass) variables. Moreover, we found that between these states there are several other steady states which depend on the scale of perturbation. From here global susceptibility maps were made showing regions of low and high resilience. The model results suggest that mainly the boreal and monsoon regions have low resiliences, i.e. instable biomass equilibria, with positive vegetation-climate feedbacks in which the biomass induced by a perturbation is further enforced. The perturbation did not only influence single vegetation-climate cell interactions but also caused changes in spatial patterns of atmospheric circulation due to neighbouring cells constituting in spatial vegetation-climate feedbacks. Large perturbations could trigger an abrupt shift of the system towards another steady state. Although the model setup used in our simulation is rather simple, our results stress that the coupling of feedbacks at multiple scales in vegetation-climate models is essential and urgent to understand the system dynamics for improved projections of ecosystem responses to anthropogenic changes in climate forcing

Changes in growing season duration and productivity of northern vegetation inferred from long-term remote sensing data

Monitoring and understanding climate-induced changes in the boreal and arctic vegetation is critical to aid in prognosticating their future. Weused a 33 year (1982-2014) long record of satellite observations to robustly assess changes in metrics of growing season (onset: SOS, end: EOS and length: LOS) and seasonal total gross primary productivity. Particular attention was paid to evaluating the accuracy of these metrics by comparing them to multiple independent direct and indirect growing season and productivity measures. These comparisons reveal that the derived metrics capture the spatio-temporal variations and trends with acceptable significance level (generally p < 0.05). We find that LOS has lengthened by 2.60 d dec(-1) (p < 0.05) due to an earlier onset of SOS (-1.61 d dec(-1), p < 0.05) and a delayed EOS (0.67 d dec(-1), p < 0.1) at the circumpolar scale over the past three decades. Relatively greater rates of changes in growing season were observed in Eurasia (EA) and in boreal regions than in North America (NA) and the arctic regions. However, this tendency of earlier SOS and delayed EOS was prominent only during the earlier part of the data record (1982-1999). During the later part (2000-2014), this tendency was reversed, i.e. delayed SOS and earlier EOS. As for seasonal total productivity, we find that 42.0% of northern vegetation shows a statistically significant (p < 0.1) greening trend over the last three decades. This greening translates to a 20.9% gain in productivity since 1982. In contrast, only 2.5% of northern vegetation shows browning, or a 1.2% loss of productivity. These trends in productivity were continuous through the period of record, unlike changes in growing season metrics. Similarly, we find relatively greater increasing rates of productivity in EA and in arctic regions than in NA and the boreal regions. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation during last three decades

Twenty-first-century compatible co2 emissions and airborne fraction simulated by cmip5 earth system models under four representative concentration pathways

PublishedJournal ArticleThe carbon cycle is a crucial Earth system component affecting climate and atmospheric composition. The response of natural carbon uptake to CO2 and climate change will determine anthropogenic emissions compatible with a target CO2 pathway. For phase 5 of the Coupled Model Intercomparison Project (CMIP5), four future representative concentration pathways (RCPs) have been generated by integrated assessment models (IAMs) and used as scenarios by state-of-the-art climate models, enabling quantification of compatible carbon emissions for the four scenarios by complex, process-based models. Here, the authors present results from 15 such Earth system GCMs for future changes in land and ocean carbon storage and the implications for anthropogenic emissions. The results are consistent with the underlying scenarios but show substantial model spread. Uncertainty in land carbon uptake due to differences among models is comparable with the spread across scenarios. Model estimates of historical fossil-fuel emissions agree well with reconstructions, and future projections for representative concentration pathway 2.6 (RCP2.6) and RCP4.5 are consistent with the IAMs. For high-end scenarios (RCP6.0 and RCP8.5), GCMs simulate smaller compatible emissions than the IAMs, indicating a larger climate-carbon cycle feedback in the GCMs in these scenarios. For the RCP2.6 mitigation scenario, an average reduction of 50% in emissions by 2050 from 1990 levels is required but with very large model spread (14%-96%). The models also disagree on both the requirement for sustained negative emissions to achieve the RCP2.6 CO2 concentration and the success of this scenario to restrict global warming below 28C. All models agree that the future airborne fraction depends strongly on the emissions profile with higher airborne fraction for higher emissions scenarios. ©2013 American Meteorological Society.MOHC authors were supported by the JointDECC/Defra MetOffice Hadley Centre Climate Programme (GA01101), and work to performHadGEM2- ES and MPI-ESM CMIP5 simulations was supported by the EU-FP7 COMBINE project (Grant 226520). JS was supported by the EU-FP7 CARBOCHANGE project (Grant 284679). We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. JT and CR were supported by the Research Council of Norway through the EarthClim (207711/E10) project

Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO2_{2}

Satellite data reveal widespread changes in Earth\u27s vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO$_{2}$ fertilization, climate change, and consequent disturbances such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at the biome level that can be scaled to a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies for vegetation changes and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying causal counterfactual theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). The probabilistic attribution method clearly identifies the CO$_{2}$ fertilization effect as the dominant driver in only two biomes, the temperate forests and cool grasslands, challenging the view of a dominant global-scale effect. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last 2 decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slowdown in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century

Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: A multi-model analysis

The responses of carbon dioxide (CO2) and other climate variables to an emission pulse of CO2 into the atmosphere are often used to compute the Global Warming Potential (GWP) and Global Temperature change Potential (GTP), to characterize the response timescales of Earth System models, and to build reduced-form models. In this carbon cycle-climate model intercomparison project, which spans the full model hierarchy, we quantify responses to emission pulses of different magnitudes injected under different conditions. The CO2 response shows the known rapid decline in the first few decades followed by a millennium-scale tail. For a 100 Gt-C emission pulse added to a constant CO2 concentration of 389 ppm, 25 ± 9% is still found in the atmosphere after 1000 yr; the ocean has absorbed 59 ± 12% and the land the remainder (16 ± 14%). The response in global mean surface air temperature is an increase by 0.20 ± 0.12 °C within the first twenty years; thereafter and until year 1000, temperature decreases only slightly, whereas ocean heat content and sea level continue to rise. Our best estimate for the Absolute Global Warming Potential, given by the time-integrated response in CO2 at year 100 multiplied by its radiative efficiency, is 92.5 × 10−15 yr W m−2 per kg-CO2. This value very likely (5 to 95% confidence) lies within the range of (68 to 117) × 10−15 yr W m−2 per kg-CO2. Estimates for time-integrated response in CO2 published in the IPCC First, Second, and Fourth Assessment and our multi-model best estimate all agree within 15% during the first 100 yr. The integrated CO2 response, normalized by the pulse size, is lower for pre-industrial conditions, compared to present day, and lower for smaller pulses than larger pulses. In contrast, the response in temperature, sea level and ocean heat content is less sensitive to these choices. Although, choices in pulse size, background concentration, and model lead to uncertainties, the most important and subjective choice to determine AGWP of CO2 and GWP is the time horizon

Impact of an extremely large magnitude volcanic eruption on the global climate and carbon cycle estimated from ensemble Earth System Model simulations

The response of the global climate-carbon cycle system to an extremely large Northern Hemisphere midlatitude volcanic eruption is investigated using ensemble integrations with the comprehensive Earth System Model MPIESM. The model includes dynamical compartments of the atmosphere and ocean and interactive modules of the terrestrial biosphere as well as ocean biogeochemistry. The MPIESM was forced with anomalies of aerosol optical depth and effective radius of aerosol particles corresponding to a super eruption of the Yellowstone volcanic system. The model experiment consists of an ensemble of fifteen model integrations that are started at different pre-ENSO states of a control experiment and run for 200 years after the volcanic eruption. The climate response to the volcanic eruption is a maximum global monthly mean surface air temperature cooling of 3.8K for the ensemble mean and from 3.3K to 4.3K for individual ensemble members. Atmospheric pCO2 decreases by a maximum of 5 ppm for the ensemble mean and by 3 ppm to 7 ppm for individual ensemble members approximately 6 years after the eruption. The atmospheric carbon content only very slowly returns to near pre-eruption level at year 200 after the eruption. The ocean takes up carbon shortly after the eruption in response to the cooling, changed wind fields and ice cover. This physics-driven uptake is weakly counteracted by a reduction of the biological export production mainly in the tropical Pacific. The land vegetation pool shows a decrease by 4 GtC due to reduced short-wave radiation that has not been present in a smaller scale eruption. The gain of the soil carbon pool determines the amplitude of the CO2 perturbation and the long-term behaviour of the overall system: an initial gain caused by reduced soil respiration is followed by a rather slow return towards pre-eruption levels. During this phase, the ocean compensates partly for the reduced atmospheric carbon content in response to the land's gain. In summary, we find that the volcanic eruption has long-lasting effects on the carbon cycle: After 200 years, the ocean and the land carbon pools are still different from the pre-eruption state by 3 GtC and 4 GtC, respectively, and the land carbon pools (vegetation and soil) show some long-lasting local anomalies that are only partly visible in the global signal. © Author(s) 2013. CC Attribution 3.0 License