Search Results
Corrigendum: Air quality and health implications of 1.5 °C–2 °C climate pathways under considerations of ageing population: a multi-model scenario analysis (2021 Environ. Res. Lett. 16 045005)
2021, Rafaj, Peter, Kiesewetter, Gregor, Krey, Volker, Schoepp, Wolfgang, Bertram, Christoph, Drouet, Laurent, Fricko, Oliver, Fujimori, Shinichiro, Harmsen, Mathijs, Hilaire, Jérôme, Huppmann, Daniel, Klimont, Zbigniew, Kolp, Peter, Aleluia Reis, Lara, van Vuuren, Detlef
We have identified an error in the text of section 3.3 where the health co-benefits of 1.5 °C + MFR scenario in the whole of Asia are compared to the reference. In the last paragraph of the section 3.3 (page 11), the manuscript states that 'Across the Asia domain, this reduction is approximately 2.5-3 million cases or 40%-51% depending on the IAM used'. Unfortunately, the numbers quoted here were accidentally taken from a sensitivity analysis using different integrated exposure-response curves (GBD-2010, obtained from Global Burden of Disease Collaborative Network 2013), which have not been used in the results shown in the paper-our results are based on the GBD-2013 version, reported by Forouzanfar et al (2015). The correct statement is: 'Across the Asia domain, this reduction is approximately 1.2-1.5 million cases or 33%-42% depending on the IAM used'. The same correction applies to the statement in the Conclusions section 5 (4th paragraph, page 14), which should read: 'The 1.5 °C + MFR scenario decreases premature deaths by 33%-42% across Asia, compared to NPi'.
Climate impact emergence and flood peak synchronization projections in the Ganges, Brahmaputra and Meghna basins under CMIP5 and CMIP6 scenarios
2022, Gädeke, Anne, Wortmann, Michel, Menz, Christoph, Islam, AKM Saiful, Masood, Muhammad, Krysanova, Valentina, Lange, Stefan, Hattermann, Fred Fokko
The densely populated delta of the three river systems of the Ganges, Brahmaputra and Meghna is highly prone to floods. Potential climate change-related increases in flood intensity are therefore of major societal concern as more than 40 million people live in flood-prone areas in downstream Bangladesh. Here we report on new flood projections using a hydrological model forced by bias-adjusted ensembles of the latest-generation global climate models of CMIP6 (SSP5-8.5/SSP1-2.6) in comparison to CMIP5 (RCP8.5/RCP2.6). Results suggest increases in peak flow magnitude of 36% (16%) on average under SSP5-8.5 (SSP1-2.6), compared to 60% (17%) under RCP8.5 (RCP2.6) by 2070-2099 relative to 1971-2000. Under RCP8.5/SSP5-8.5 (2070-2099), the largest increase in flood risk is projected for the Ganges watershed, where higher flood peaks become the ‘new norm’ as early as mid-2030 implying a relatively short time window for adaptation. In the Brahmaputra and Meghna rivers, the climate impact signal on peak flow emerges after 2070 (CMIP5 and CMIP6 projections). Flood peak synchronization, when annual peak flow occurs simultaneously at (at least) two rivers leading to large flooding events within Bangladesh, show a consistent increase under both projections. While the variability across the ensemble remains high, the increases in flood magnitude are robust in the study basins. Our findings emphasize the need of stringent climate mitigation policies to reduce the climate change impact on peak flows (as presented using SSP1-2.6/RCP2.6) and to subsequently minimize adverse socioeconomic impacts and adaptation costs. Considering Bangladesh’s high overall vulnerability to climate change and its downstream location, synergies between climate change adaptation and mitigation and transboundary cooperation will need to be strengthened to improve overall climate resilience and achieve sustainable development.
Magnitude and robustness associated with the climate change impacts on global hydrological variables for transient and stabilized climate states
2018, Boulange, Julien, Hanasaki, Naota, Veldkamp, Ted, Schewe, Jacob, Shiogama, Hideo
Recent studies have assessed the impacts of climate change at specific global temperature targets using relatively short (30 year ) transient time-slice periods which are characterized by a steady increase in global mean temperature with time. The Inter-Sectoral Impacts Model Intercomparison Project Phase 2b (ISIMIP2b) provides trend-preserving bias-corrected climate model datasets over six centuries for four global climate models (GCMs) which therefore can be used to evaluate the potential effects of using time-slice periods from stabilized climate state rather than time-slice periods from transient climate state on climate change impacts. Using the H08 global hydrological model, the impacts of climate change, quantified as the deviation from the pre-industrial era, and the signal-to-noise (SN) ratios were computed for five hydrological variables, namely evapotranspiration (EVA), precipitation (PCP), snow water equivalent (SNW), surface temperature (TAR), and total discharge (TOQ) over 20 regions comprising the global land area. A significant difference in EVA for the transient and stabilized climate states was systematically detected for all four GCMs. In addition, three out of the four GCMs indicated that significant differences in PCP, TAR, and TOQ for the transient and stabilized climate states could also be detected over a small fraction of the globe. For most regions, the impacts of climate change toward EVA, PCP, and TOQ are indicated to be underestimated using the transient climate state simulations. The transient climate state was also identified to underestimate the SN ratios compared to the stabilized climate state. For both the global and regional scales, however, there was no indication that surface areas associated with the different classes of SN ratios changed depending on the two climate states (t-test, p > 0.01). Transient time slices may be considered a good approximation of the stabilized climate state, for large-scale hydrological studies and many regions and variables, as: (1) impacts of climate change were only significantly different from those of the stabilized climate state for a small fraction of the globe, and (2) these differences were not indicated to alter the robustness of the impacts of climate change.
Attributing observed permafrost warming in the northern hemisphere to anthropogenic climate change
2022, Gudmundsson, Lukas, Kirchner, Josefine, Gädeke, Anne, Noetzli, Jeannette, Biskaborn, Boris K
Permafrost temperatures are increasing globally with the potential of adverse environmental and socio-economic impacts. Nonetheless, the attribution of observed permafrost warming to anthropogenic climate change has relied mostly on qualitative evidence. Here, we compare long permafrost temperature records from 15 boreholes in the northern hemisphere to simulated ground temperatures from Earth system models contributing to CMIP6 using a climate change detection and attribution approach. We show that neither pre-industrial climate variability nor natural drivers of climate change suffice to explain the observed warming in permafrost temperature averaged over all boreholes. However, simulations are consistent with observations if the effects of human emissions on the global climate system are considered. Moreover, our analysis reveals that the effect of anthropogenic climate change on permafrost temperature is detectable at some of the boreholes. Thus, the presented evidence supports the conclusion that anthropogenic climate change is the key driver of northern hemisphere permafrost warming.
Theoretical and paleoclimatic evidence for abrupt transitions in the Earth system
2022, Boers, Niklas, Ghil, Michael, Stocker, Thomas F.
Specific components of the Earth system may abruptly change their state in response to gradual changes in forcing. This possibility has attracted great scientific interest in recent years, and has been recognized as one of the greatest threats associated with anthropogenic climate change. Examples of such components, called tipping elements, include the Atlantic Meridional Overturning Circulation, the polar ice sheets, the Amazon rainforest, as well as the tropical monsoon systems. The mathematical language to describe abrupt climatic transitions is mainly based on the theory of nonlinear dynamical systems and, in particular, on their bifurcations. Applications of this theory to nonautonomous and stochastically forced systems are a very active field of climate research. The empirical evidence that abrupt transitions have indeed occurred in the past stems exclusively from paleoclimate proxy records. In this review, we explain the basic theory needed to describe critical transitions, summarize the proxy evidence for past abrupt climate transitions in different parts of the Earth system, and examine some candidates for future abrupt transitions in response to ongoing anthropogenic forcing. Predicting such transitions remains difficult and is subject to large uncertainties. Substantial improvements in our understanding of the nonlinear mechanisms underlying abrupt transitions of Earth system components are needed. We argue that such an improved understanding requires combining insights from (a) paleoclimatic records; (b) simulations using a hierarchy of models, from conceptual to comprehensive ones; and (c) time series analysis of recent observation-based data that encode the dynamics of the present-day Earth system components that are potentially prone to tipping.
Targeted policies can compensate most of the increased sustainability risks in 1.5 °C mitigation scenarios
2018, Bertram, Christoph, Luderer, Gunnar, Popp, Alexander, Minx, Jan Christoph, Lamb, William F, Stevanović, Miodrag, Humpenöder, Florian, Giannousakis, Anastasis, Kriegler, Elmar
Meeting the 1.5 °C goal will require a rapid scale-up of zero-carbon energy supply, fuel switching to electricity, efficiency and demand-reduction in all sectors, and the replenishment of natural carbon sinks. These transformations will have immediate impacts on various of the sustainable development goals. As goals such as affordable and clean energy and zero hunger are more immediate to great parts of global population, these impacts are central for societal acceptability of climate policies. Yet, little is known about how the achievement of other social and environmental sustainability objectives can be directly managed through emission reduction policies. In addition, the integrated assessment literature has so far emphasized a single, global (cost-minimizing) carbon price as the optimal mechanism to achieve emissions reductions. In this paper we introduce a broader suite of policies—including direct sector-level regulation, early mitigation action, and lifestyle changes—into the integrated energy-economy-land-use modeling system REMIND-MAgPIE. We examine their impact on non-climate sustainability issues when mean warming is to be kept well below 2 °C or 1.5 °C. We find that a combination of these policies can alleviate air pollution, water extraction, uranium extraction, food and energy price hikes, and dependence on negative emissions technologies, thus resulting in substantially reduced sustainability risks associated with mitigating climate change. Importantly, we find that these targeted policies can more than compensate for most sustainability risks of increasing climate ambition from 2 °C to 1.5 °C.
Crop productivity changes in 1.5 °C and 2 °C worlds under climate sensitivity uncertainty
2018, Schleussner, Carl-Friedrich, Deryng, Delphine, Müller, Christoph, Elliott, Joshua, Saeed, Fahad, Folberth, Christian, Liu, Wenfeng, Wang, Xuhui, Pugh, Thomas A. M., Thiery, Wim, Seneviratne, Sonia I., Rogelj, Joeri
Following the adoption of the Paris Agreement, there has been an increasing interest in quantifying impacts at discrete levels of global mean temperature (GMT) increase such as 1.5 °C and 2 °C above pre-industrial levels. Consequences of anthropogenic greenhouse gas emissions on agricultural productivity have direct and immediate relevance for human societies. Future crop yields will be affected by anthropogenic climate change as well as direct effects of emissions such as CO2 fertilization. At the same time, the climate sensitivity to future emissions is uncertain. Here we investigate the sensitivity of future crop yield projections with a set of global gridded crop models for four major staple crops at 1.5 °C and 2 °C warming above pre-industrial levels, as well as at different CO2 levels determined by similar probabilities to lead to 1.5 °C and 2 °C, using climate forcing data from the Half a degree Additional warming, Prognosis and Projected Impacts project. For the same CO2 forcing, we find consistent negative effects of half a degree warming on productivity in most world regions. Increasing CO2 concentrations consistent with these warming levels have potentially stronger but highly uncertain effects than 0.5 °C warming increments. Half a degree warming will also lead to more extreme low yields, in particular over tropical regions. Our results indicate that GMT change alone is insufficient to determine future impacts on crop productivity.
Corrigendum: The role of storage dynamics in annual wheat prices (2017 Environ. Res. Lett. 12 054005)
2018, Schewe, Jacob, Otto, Christian, Frieler, Katja
[no abstract available]
Global mean temperature indicators linked to warming levels avoiding climate risks
2018, Pfleiderer, Peter, Schleussner, Carl-Friedrich, Mengel, Matthias, Rogelj, Joeri
International climate policy uses global mean temperature rise limits as proxies for societally acceptable levels of climate change. These limits are informed by risk assessments which draw upon projections of climate impacts under various levels of warming. Here we illustrate that indicators used to define limits of warming and those used to track the evolution of the Earth System under climate change are not directly comparable. Depending on the methodological approach, differences can be time-variant and up to 0.2 °C for a warming of 1.5 °C above pre-industrial levels. This might lead to carbon budget overestimates of about 10 years of continued year-2015 emissions, and about a 10% increase in estimated 2100 sea-level rise. Awareness of this definitional mismatch is needed for a more effective communication between scientists and decision makers, as well as between the impact and physical climate science communities.
Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets
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.
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