4 results
Search Results
Now showing 1 - 4 of 4
- ItemLow atmospheric CO2 levels before the rise of forested ecosystems([London] : Nature Publishing Group UK, 2022) Dahl, Tais W.; Harding, Magnus A. R.; Brugger, Julia; Feulner, Georg; Norrman, Kion; Lomax, Barry H.; Junium, Christopher K.The emergence of forests on Earth (~385 million years ago, Ma)1 has been linked to an order-of-magnitude decline in atmospheric CO2 levels and global climatic cooling by altering continental weathering processes, but observational constraints on atmospheric CO2 before the rise of forests carry large, often unbound, uncertainties. Here, we calibrate a mechanistic model for gas exchange in modern lycophytes and constrain atmospheric CO2 levels 410–380 Ma from related fossilized plants with bound uncertainties of approximately ±100 ppm (1 sd). We find that the atmosphere contained ~525–715 ppm CO2 before continents were afforested, and that Earth was partially glaciated according to a palaeoclimate model. A process-driven biogeochemical model (COPSE) shows the appearance of trees with deep roots did not dramatically enhance atmospheric CO2 removal. Rather, shallow-rooted vascular ecosystems could have simultaneously caused abrupt atmospheric oxygenation and climatic cooling long before the rise of forests, although earlier CO2 levels are still unknown.
- ItemPhotosynthetic productivity and its efficiencies in ISIMIP2a biome models: Benchmarking for impact assessment studies(Bristol : IOP Publishing, 2017) Ito, Akihiko; Nishina, Kazuya; Reyer, Christopher P.O.; François, Louis; Henrot, Alexandra-Jane; Munhoven, Guy; Jacquemin, Ingrid; Tian, Hanqin; Yang, Jia; Pan, Shufen; Morfopoulos, Catherine; Betts, Richard; Hickler, Thomas; Steinkamp, Jörg; Ostberg, Sebastian; Schaphoff, Sibyll; Ciais, Philippe; Chang, Jinfeng; Rafique, Rashid; Zeng, Ning; Zhao, FangSimulating vegetation photosynthetic productivity (or gross primary production, GPP) is a critical feature of the biome models used for impact assessments of climate change. We conducted a benchmarking of global GPP simulated by eight biome models participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a) with four meteorological forcing datasets (30 simulations), using independent GPP estimates and recent satellite data of solar-induced chlorophyll fluorescence as a proxy of GPP. The simulated global terrestrial GPP ranged from 98 to 141 Pg C yr−1 (1981–2000 mean); considerable inter-model and inter-data differences were found. Major features of spatial distribution and seasonal change of GPP were captured by each model, showing good agreement with the benchmarking data. All simulations showed incremental trends of annual GPP, seasonal-cycle amplitude, radiation-use efficiency, and water-use efficiency, mainly caused by the CO2 fertilization effect. The incremental slopes were higher than those obtained by remote sensing studies, but comparable with those by recent atmospheric observation. Apparent differences were found in the relationship between GPP and incoming solar radiation, for which forcing data differed considerably. The simulated GPP trends co-varied with a vegetation structural parameter, leaf area index, at model-dependent strengths, implying the importance of constraining canopy properties. In terms of extreme events, GPP anomalies associated with a historical El Niño event and large volcanic eruption were not consistently simulated in the model experiments due to deficiencies in both forcing data and parameterized environmental responsiveness. Although the benchmarking demonstrated the overall advancement of contemporary biome models, further refinements are required, for example, for solar radiation data and vegetation canopy schemes.
- ItemSimulating the Earth system response to negative emissions(Bristol : IOP Publishing, 2016) Jones, C.D.; Ciais, P.; Davis, S.J.; Friedlingstein, P.; Gasser, T.; Peters, G.P.; Rogelj, J.; van Vuuren, D.P.; Canadell, J.G.; Cowie, A.; Jackson, R.B.; Jonas, M.; Kriegler, E.; Littleton, E.; Lowe, J.A.; Milne, J.; Shrestha, G.; Smith, P.; Torvanger, A.; Wiltshire, A.Natural carbon sinks currently absorb approximately half of the anthropogenic CO2 emitted by fossil fuel burning, cement production and land-use change. However, this airborne fraction may change in the future depending on the emissions scenario. An important issue in developing carbon budgets to achieve climate stabilisation targets is the behaviour of natural carbon sinks, particularly under low emissions mitigation scenarios as required to meet the goals of the Paris Agreement. A key requirement for low carbon pathways is to quantify the effectiveness of negative emissions technologies which will be strongly affected by carbon cycle feedbacks. Here we find that Earth system models suggest significant weakening, even potential reversal, of the ocean and land sinks under future low emission scenarios. For the RCP2.6 concentration pathway, models project land and ocean sinks to weaken to 0.8 ± 0.9 and 1.1 ± 0.3 GtC yr−1 respectively for the second half of the 21st century and to −0.4 ± 0.4 and 0.1 ± 0.2 GtC yr−1 respectively for the second half of the 23rd century. Weakening of natural carbon sinks will hinder the effectiveness of negative emissions technologies and therefore increase their required deployment to achieve a given climate stabilisation target. We introduce a new metric, the perturbation airborne fraction, to measure and assess the effectiveness of negative emissions.
- ItemConstraining modelled global vegetation dynamics and carbon turnover using multiple satellite observations([London] : Macmillan Publishers Limited, part of Springer Nature, 2019) Forkel, Matthias; Drüke, Markus; Thurner, Martin; Dorigo, Wouter; Schaphoff, Sibyll; Thonicke, Kirsten; von Bloh, Werner; Carvalhais, NunoThe response of land ecosystems to future climate change is among the largest unknowns in the global climate-carbon cycle feedback. This uncertainty originates from how dynamic global vegetation models (DGVMs) simulate climate impacts on changes in vegetation distribution, productivity, biomass allocation, and carbon turnover. The present-day availability of a multitude of satellite observations can potentially help to constrain DGVM simulations within model-data integration frameworks. Here, we use satellite-derived datasets of the fraction of absorbed photosynthetic active radiation (FAPAR), sun-induced fluorescence (SIF), above-ground biomass of trees (AGB), land cover, and burned area to constrain parameters for phenology, productivity, and vegetation dynamics in the LPJmL4 DGVM. Both the prior and the optimized model accurately reproduce present-day estimates of the land carbon cycle and of temporal dynamics in FAPAR, SIF and gross primary production. However, the optimized model reproduces better the observed spatial patterns of biomass, tree cover, and regional forest carbon turnover. Using a machine learning approach, we found that remaining errors in simulated forest carbon turnover can be explained with bioclimatic variables. This demonstrates the need to improve model formulations for climate effects on vegetation turnover and mortality despite the apparent successful constraint of simulated vegetation dynamics with multiple satellite observations.