Search Results

Now showing 1 - 3 of 3
  • Item
    Evaluating changes of biomass in global vegetation models: the role of turnover fluctuations and ENSO events
    (Bristol : IOP Publ., 2018) García Cantú, Anselmo; Frieler, Katja; Reyer, Christopher P O; Ciais, Philippe; Chang, Jinfeng; Ito, Akihiko; Nishina, Kazuya; François, Louis; Henrot, Alexandra-Jane; Hickler, Thomas; Steinkamp, Jörg; Rafique, Rashid; Zhao, Fang; Ostberg, Sebastian; Schaphoff, Sibyll; Tian, Hanqin; Pan, Shufen; Yang, Jia; Morfopoulos, Catherine; Betts, Richard
    This paper evaluates the ability of eight global vegetation models to reproduce recent trends and inter-annual variability of biomass in natural terrestrial ecosystems. For the purpose of this evaluation, the simulated trajectories of biomass are expressed in terms of the relative rate of change in biomass (RRB), defined as the deviation of the actual rate of biomass turnover from its equilibrium counterpart. Cumulative changes in RRB explain long-term changes in biomass pools. RRB simulated by the global vegetation models is compared with its observational equivalent, derived from vegetation optical depth reconstructions of above-ground biomass (AGB) over the period 1993–2010. According to the RRB analysis, the rate of global biomass growth described by the ensemble of simulations substantially exceeds the observation. The observed fluctuations of global RRB are significantly correlated with El Niño Southern Oscillation events (ENSO), but only some of the simulations reproduce this correlation. However, the ENSO sensitivity of RRB in the tropics is not significant in the observation, while it is in some of the simulations. This mismatch points to an important limitation of the observed AGB reconstruction to capture biomass variations in tropical forests. Important discrepancies in RRB were also identified at the regional scale, in the tropical forests of Amazonia and Central Africa, as well as in the boreal forests of north-western America, western and central Siberia. In each of these regions, the RRBs derived from the simulations were analyzed in connection with underlying differences in net primary productivity and biomass turnover rate ̶as a basis for exploring in how far differences in simulated changes in biomass are attributed to the response of the carbon uptake to CO2 increments, as well as to the model representation of factors affecting the rates of mortality and turnover of foliage and roots. Overall, our findings stress the usefulness of using RRB to evaluate complex vegetation models and highlight the importance of conducting further evaluations of both the actual rate of biomass turnover and its equilibrium counterpart, with special focus on their background values and sources of variation. In turn, this task would require the availability of more accurate multi-year observational data of biomass and net primary productivity for natural ecosystems, as well as detailed and updated information on land-cover classification.
  • Item
    Short term policies to keep the door open for Paris climate goals
    (Bristol : IOP Publ., 2018) Kriegler, Elmar; Bertram, Christoph; Kuramochi, Takeshi; Jakob, Michael; Pehl, Michaja; Stevanović, Miodrag; Höhne, Niklas; Luderer, Gunnar; Minx, Jan C; Fekete, Hanna; Hilaire, Jérôme; Luna, Lisa; Popp, Alexander; Steckel, Jan Christoph; Sterl, Sebastian; Yalew, Amsalu Woldie; Dietrich, Jan Philipp; Edenhofer, Ottmar
    Climate policy needs to account for political and social acceptance. Current national climate policy plans proposed under the Paris Agreement lead to higher emissions until 2030 than cost-effective pathways towards the Agreements' long-term temperature goals would imply. Therefore, the current plans would require highly disruptive changes, prohibitive transition speeds, and large long-term deployment of risky mitigation measures for achieving the agreement's temperature goals after 2030. Since the prospects of introducing the cost-effective policy instrument, a global comprehensive carbon price in the near-term, are negligible, we study how a strengthening of existing plans by a global roll-out of regional policies can ease the implementation challenge of reaching the Paris temperature goals. The regional policies comprise a bundle of regulatory policies in energy supply, transport, buildings, industry, and land use and moderate, regionally differentiated carbon pricing. We find that a global roll-out of these policies could reduce global CO2 emissions by an additional 10 GtCO2eq in 2030 compared to current plans. It would lead to emissions pathways close to the levels of cost-effective likely below 2 °C scenarios until 2030, thereby reducing implementation challenges post 2030. Even though a gradual phase-in of a portfolio of regulatory policies might be less disruptive than immediate cost-effective carbon pricing, it would perform worse in other dimensions. In particular, it leads to higher economic impacts that could become major obstacles in the long-term. Hence, such policy packages should not be viewed as alternatives to carbon pricing, but rather as complements that provide entry points to achieve the Paris climate goals.
  • Item
    Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets
    (Bristol : IOP Publ., 2018) Wartenburger, Richard; Seneviratne, Sonia I; Hirschi, Martin; Chang, Jinfeng; Ciais, Philippe; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Gosling, Simon N; Gudmundsson, Lukas; Henrot, Alexandra-Jane; Hickler, Thomas; Ito, Akihiko; Khabarov, Nikolay; Kim, Hyungjun; Leng, Guoyong; Liu, Junguo; Liu, Xingcai; Masaki, Yoshimitsu; Morfopoulos, Catherine; Müller, Christoph; Müller Schmied, Hannes; Nishina, Kazuya; Orth, Rene; Pokhrel, Yadu; Pugh, Thomas A M; Satoh, Yusuke; Schaphoff, Sibyll; Schmid, Erwin; Sheffield, Justin; Stacke, Tobias; Steinkamp, Joerg; Tang, Qiuhong; Thiery, Wim; Wada, Yoshihide; Wang, Xuhui; Weedon, Graham P; Yang, Hong; Zhou, Tian
    Actual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatio-temporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we find that the model choice mostly dominates (24%–40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.