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- ItemEmulating atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 2: Applications(München : European Geopyhsical Union, 2011) Meinshausen, M.; Raper, S.C.B.; Wigley, T.M.L.Intercomparisons of coupled atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models are important for galvanizing our current scientific knowledge to project future climate. Interpreting such intercomparisons faces major challenges, not least because different models have been forced with different sets of forcing agents. Here, we show how an emulation approach with MAGICC6 can address such problems. In a companion paper (Meinshausen et al., 2011a), we show how the lower complexity carbon cycle-climate model MAGICC6 can be calibrated to emulate, with considerable accuracy, globally aggregated characteristics of these more complex models. Building on that, we examine here the Coupled Model Intercomparison Project's Phase 3 results (CMIP3). If forcing agents missed by individual AOGCMs in CMIP3 are considered, this reduces ensemble average temperature change from pre-industrial times to 2100 under SRES A1B by 0.4 °C. Differences in the results from the 1980 to 1999 base period (as reported in IPCC AR4) to 2100 are negligible, however, although there are some differences in the trajectories over the 21st century. In a second part of this study, we consider the new RCP scenarios that are to be investigated under the forthcoming CMIP5 intercomparison for the IPCC Fifth Assessment Report. For the highest scenario, RCP8.5, relative to pre-industrial levels, we project a median warming of around 4.6 °C by 2100 and more than 7 °C by 2300. For the lowest RCP scenario, RCP3-PD, the corresponding warming is around 1.5 °C by 2100, decreasing to around 1.1 °C by 2300 based on our AOGCM and carbon cycle model emulations. Implied cumulative CO2 emissions over the 21st century for RCP8.5 and RCP3-PD are 1881 GtC (1697 to 2034 GtC, 80% uncertainty range) and 381 GtC (334 to 488 GtC), when prescribing CO2 concentrations and accounting for uncertainty in the carbon cycle. Lastly, we assess the reasons why a previous MAGICC version (4.2) used in IPCC AR4 gave roughly 10% larger warmings over the 21st century compared to the CMIP3 average. We find that forcing differences and the use of slightly too high climate sensitivities inferred from idealized high-forcing runs were the major reasons for this difference.
- ItemEmulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration(München : European Geopyhsical Union, 2011) Meinshausen, M.; Raper, S.C.B.; Wigley, T.M.L.Current scientific knowledge on the future response of the climate system to human-induced perturbations is comprehensively captured by various model intercomparison efforts. In the preparation of the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), intercomparisons were organized for atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models, named "CMIP3" and "C4MIP", respectively. Despite their tremendous value for the scientific community and policy makers alike, there are some difficulties in interpreting the results. For example, radiative forcings were not standardized across the various AOGCM integrations and carbon cycle runs, and, in some models, key forcings were omitted. Furthermore, the AOGCM analysis of plausible emissions pathways was restricted to only three SRES scenarios. This study attempts to address these issues. We present an updated version of MAGICC, the simple carbon cycle-climate model used in past IPCC Assessment Reports with enhanced representation of time-varying climate sensitivities, carbon cycle feedbacks, aerosol forcings and ocean heat uptake characteristics. This new version, MAGICC6, is successfully calibrated against the higher complexity AOGCMs and carbon cycle models. Parameterizations of MAGICC6 are provided. The mean of the emulations presented here using MAGICC6 deviates from the mean AOGCM responses by only 2.2% on average for the SRES scenarios. This enhanced emulation skill in comparison to previous calibrations is primarily due to: making a "like-with-like comparison" using AOGCM-specific subsets of forcings; employing a new calibration procedure; as well as the fact that the updated simple climate model can now successfully emulate some of the climate-state dependent effective climate sensitivities of AOGCMs. The diagnosed effective climate sensitivity at the time of CO2 doubling for the AOGCMs is on average 2.88 °C, about 0.33 °C cooler than the mean of the reported slab ocean climate sensitivities. In the companion paper (Part 2) of this study, we examine the combined climate system and carbon cycle emulations for the complete range of IPCC SRES emissions scenarios and the new RCP pathways.
- ItemSensitivity of polar stratospheric ozone loss to uncertainties in chemical reaction kinetics(Göttingen : Copernicus GmbH, 2009) Kawa, S.R.; Stolarski, R.S.; Newman, P.A.; Douglass, A.R.; Rex, M.; Hofmann, D.J.; Santee, M.L.; Frieler, K.The impact and significance of uncertainties in model calculations of stratospheric ozone loss resulting from known uncertainty in chemical kinetics parameters is evaluated in trajectory chemistry simulations for the Antarctic and Arctic polar vortices. The uncertainty in modeled ozone loss is derived from Monte Carlo scenario simulations varying the kinetic (reaction and photolysis rate) parameters within their estimated uncertainty bounds. Simulations of a typical winter/spring Antarctic vortex scenario and Match scenarios in the Arctic produce large uncertainty in ozone loss rates and integrated seasonal loss. The simulations clearly indicate that the dominant source of model uncertainty in polar ozone loss is uncertainty in the Cl2O 2 photolysis reaction, which arises from uncertainty in laboratory-measured molecular cross sections at atmospherically important wavelengths. This estimated uncertainty in JCl 2O2 from laboratory measurements seriously hinders our ability to model polar ozone loss within useful quantitative error limits. Atmospheric observations, however, suggest that the Cl2O2 photolysis uncertainty may be less than that derived from the lab data. Comparisons to Match, South Pole ozonesonde, and Aura Microwave Limb Sounder (MLS) data all show that the nominal recommended rate simulations agree with data within uncertainties when the Cl2O2 photolysis error is reduced by a factor of two, in line with previous in situ ClOx measurements. Comparisons to simulations using recent cross sections from Pope et al. (2007) are outside the constrained error bounds in each case. Other reactions producing significant sensitivity in polar ozone loss include BrO + ClO and its branching ratios. These uncertainties challenge our confidence in modeling polar ozone depletion and projecting future changes in response to changing halogen emissions and climate. Further laboratory, theoretical, and possibly atmospheric studies are needed.
- ItemAdvances and visions in large-scale hydrological modelling: Findings from the 11th Workshop on Large-Scale Hydrological Modelling(München : European Geopyhsical Union, 2008) Döll, P.; Berkhoff, K.; Bormann, H.; Fohrer, N.; Gerten, D.; Hagemann, S.; Krol, M.Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future.
- ItemProcess verification of a hydrological model using a temporal parameter sensitivity analysis(Göttingen : Copernicus GmbH, 2015) Pfannerstill, M.; Guse, B.; Reusser, D.; Fohrer, N.
- ItemUncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model(Hoboken, NJ : Wiley, 2012) Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, JerryThis study aims to assess how high‐latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund‐Potsdam‐Jena (LPJ) simulations for the northern high latitudes (45oN and polewards) for the period 1900–2100. The LPJ Dynamic Global Vegetation Model (LPJ‐DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light‐use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter‐based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.
- ItemA new color image encryption scheme using CML and a fractional-order chaotic system(San Francisco, CA : Public Library of Science (PLoS), 2015) Wu, X.; Li, Y.; Kurths, J.
- ItemComparison of water flows in four European lagoon catchments under a set of future climate scenarios(Basel : MDPI AG, 2015) Hesse, C.; Stefanova, A.; Krysanova, V.
- ItemPopulation ageing and deaths attributable to ambient PM2·5 pollution: a global analysis of economic cost(Amsterdam : Elsevier, 2021) Yin, Hao; Brauer, Michael; Zhang, Junfeng (Jim); Cai, Wenjia; Navrud, Ståle; Burnett, Richard; Howard, Courtney; Deng, Zhu; Kammen, Daniel M.; Schellnhuber, Hans Joachim; Chen, Kai; Kan, Haidong; Chen, Zhan-Ming; Chen, Bin; Zhang, Ning; Mi, Zhifu; Coffman, D'Maris; Cohen, Aaron J.; Guan, Dabo; Zhang, Qiang; Gong, Peng; Liu, ZhuBackground: The health impacts of ambient air pollution impose large costs on society. Although all people are exposed to air pollution, the older population (ie, those aged ≥60 years) tends to be disproportionally affected. As a result, there is growing concern about the health impacts of air pollution as many countries undergo rapid population ageing. We investigated the spatial and temporal variation in the economic cost of deaths attributable to ambient air pollution and its interaction with population ageing from 2000 to 2016 at global and regional levels. Methods: In this global analysis, we developed an age-adjusted measure of the value of a statistical life-year (VSLY) to estimate the economic cost of deaths attributable to ambient PM2·5 pollution using Global Burden of Diseases, Injuries, and Risk Factors Study 2017 data and country-level socioeconomic information. First, we estimated the global age-specific and cause-specific mortality and years of life lost (YLLs) attributable to PM2·5 pollution using the global exposure mortality model and global estimates of exposure at 0·1° × 0·1° (about 11 km × 11 km at the equator) resolution. Second, for each year between 2000 and 2016, we translated the YLLs within each age group into a health-related cost using a country-specific, age-adjusted measure of VSLY. Third, we decomposed the major driving factors that contributed to the temporal change in health costs related to PM2·5. Finally, we did a sensitivity test to analyse the variability of the estimated health costs to four alternative valuation measures. We identified the uncertainty intervals (UIs) from 1000 draws of the parameters and concentration–response functions by age, cause, country, and year. All economic values are reported in 2011 purchasing power parity-adjusted US dollars. All simulations were done with R, version 3.6.0. Findings: Globally, in 2016, PM2·5 was estimated to have caused 8·42 million (95% UI 6·50–10·52) attributable deaths, which was associated with 163·68 million (116·03–219·44) YLLs. In 2016, the global economic cost of deaths attributable to ambient PM2·5 pollution for the older population was US$2·40 trillion (1·89–2·93) accounting for 59% (59–60) of the cost for the total population ($4·09 trillion [3·19–5·05]). The economic cost per capita for the older population was $2739 (2160–3345) in 2016, which was 10 times that of the younger population (ie, those aged <60 years). By assessing the factors that contributed to economic costs, we found that increases in these factors changed the total economic cost by 77% for gross domestic product (GDP) per capita, 21% for population ageing, 16% for population growth, −41% for age-specific mortality, and −0·4% for PM2·5 exposure. Interpretation: The economic cost of ambient PM2·5 borne by the older population almost doubled between 2000 and 2016, driven primarily by GDP growth, population ageing, and population growth. Compared with younger people, air pollution leads to disproportionately higher health costs among older people, even after accounting for their relatively shorter life expectancy and increased disability. As the world's population is ageing, the disproportionate health cost attributable to ambient PM2·5 pollution potentially widens the health inequities for older people. Countries with severe air pollution and rapid ageing rates need to take immediate actions to improve air quality. In addition, strategies aimed at enhancing health-care services, especially targeting the older population, could be beneficial for reducing the health costs of ambient air pollution. Funding: National Natural Science Foundation of China, China Postdoctoral Science Foundation, and Qiushi Foundation.