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- ItemRegional effects of atmospheric aerosols on temperature: An evaluation of an ensemble of online coupled models(Katlenburg-Lindau : EGU, 2017) Baró, Rocío; Palacios-Peña, Laura; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, PedroThe climate effect of atmospheric aerosols is associated with their influence on the radiative budget of the Earth due to the direct aerosol-radiation interactions (ARIs) and indirect effects, resulting from aerosol-cloud-radiation interactions (ACIs). Online coupled meteorology-chemistry models permit the description of these effects on the basis of simulated atmospheric aerosol concentrations, although there is still some uncertainty associated with the use of these models. Thus, the objective of this work is to assess whether the inclusion of atmospheric aerosol radiative feedbacks of an ensemble of online coupled models improves the simulation results for maximum, mean and minimum temperature at 2m over Europe. The evaluated models outputs originate from EuMetChem COST Action ES1004 simulations for Europe, differing in the inclusion (or omission) of ARI and ACI in the various models. The cases studies cover two important atmospheric aerosol episodes over Europe in the year 2010: (i) a heat wave event and a forest fire episode (July-August 2010) and (ii) a more humid episode including a Saharan desert dust outbreak in October 2010. The simulation results are evaluated against observational data from the E-OBS gridded database. The results indicate that, although there is only a slight improvement in the bias of the simulation results when including the radiative feedbacks, the spatiotemporal variability and correlation coefficients are improved for the cases under study when atmospheric aerosol radiative effects are included.
- ItemFormation of organic aerosol in the Paris region during the MEGAPOLI summer campaign: Evaluation of the volatility-basis-set approach within the CHIMERE model(Göttingen : Copernicus, 2013) Zhang, Q.J.; Beekmann, M.; Drewnick, F.; Freutel, F.; Schneider, J.; Crippa, M.; Prevot, A.S.H.; Baltensperger, U.; Poulain, L.; Wiedensohler, A.; Sciare, J.; Gros, V.; Borbon, A.; Colomb, A.; Michoud, V.; Doussin, J.-F.; Denier Van Der Gon, H.A.C.; Haeffelin, M.; Dupont, J.-C.; Siour, G.; Petetin, H.; Bessagnet, B.; Pandis, S.N.; Hodzic, A.; Sanchez, O.; Honoré, C.; Perrussel, O.Simulations with the chemistry transport model CHIMERE are compared to measurements performed during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer campaign in the Greater Paris region in July 2009. The volatility-basis-set approach (VBS) is implemented into this model, taking into account the volatility of primary organic aerosol (POA) and the chemical aging of semi-volatile organic species. Organic aerosol is the main focus and is simulated with three different configurations with a modified treatment of POA volatility and modified secondary organic aerosol (SOA) formation schemes. In addition, two types of emission inventories are used as model input in order to test the uncertainty related to the emissions. Predictions of basic meteorological parameters and primary and secondary pollutant concentrations are evaluated, and four pollution regimes are defined according to the air mass origin. Primary pollutants are generally overestimated, while ozone is consistent with observations. Sulfate is generally overestimated, while ammonium and nitrate levels are well simulated with the refined emission data set. As expected, the simulation with non-volatile POA and a single-step SOA formation mechanism largely overestimates POA and underestimates SOA. Simulation of organic aerosol with the VBS approach taking into account the aging of semi-volatile organic compounds (SVOC) shows the best correlation with measurements. High-concentration events observed mostly after long-range transport are well reproduced by the model. Depending on the emission inventory used, simulated POA levels are either reasonable or underestimated, while SOA levels tend to be overestimated. Several uncertainties related to the VBS scheme (POA volatility, SOA yields, the aging parameterization), to emission input data, and to simulated OH levels can be responsible for this behavior. Despite these uncertainties, the implementation of the VBS scheme into the CHIMERE model allowed for much more realistic organic aerosol simulations for Paris during summertime. The advection of SOA from outside Paris is mostly responsible for the highest OA concentration levels. During advection of polluted air masses from northeast (Benelux and Central Europe), simulations indicate high levels of both anthropogenic and biogenic SOA fractions, while biogenic SOA dominates during periods with advection from Southern France and Spain.
- ItemModeling forest plantations for carbon uptake with the LPJmL dynamic global vegetation model(Göttingen : Copernicus Publ., 2019) Braakhekke, Maarten C.; Doelman, Jonathan C.; Baas, Peter; Müller, Christoph; Schaphoff, Sibyll; Stehfest, Elke; van Vuuren, Detlef P.We present an extension of the dynamic global vegetation model, Lund-Potsdam-Jena Managed Land (LPJmL), to simulate planted forests intended for carbon (C) sequestration. We implemented three functional types to simulate plantation trees in temperate, tropical, and boreal climates. The parameters of these functional types were optimized to fit target growth curves (TGCs). These curves represent the evolution of stemwood C over time in typical productive plantations and were derived by combining field observations and LPJmL estimates for equivalent natural forests. While the calibrated model underestimates stemwood C growth rates compared to the TGCs, it represents substantial improvement over using natural forests to represent afforestation. Based on a simulation experiment in which we compared global natural forest versus global forest plantation, we found that forest plantations allow for much larger C uptake rates on the timescale of 100 years, with a maximum difference of a factor of 1.9, around 54 years. In subsequent simulations for an ambitious but realistic scenario in which 650Mha (14% of global managed land, 4.5% of global land surface) are converted to forest over 85 years, we found that natural forests take up 37PgC versus 48PgC for forest plantations. Comparing these results to estimations of C sequestration required to achieve the 2°C climate target, we conclude that afforestation can offer a substantial contribution to climate mitigation. Full evaluation of afforestation as a climate change mitigation strategy requires an integrated assessment which considers all relevant aspects, including costs, biodiversity, and trade-offs with other land-use types. Our extended version of LPJmL can contribute to such an assessment by providing improved estimates of C uptake rates by forest plantations. © 2019 American Institute of Physics Inc.. All rights reserved.
- ItemThe effect of univariate bias adjustment on multivariate hazard estimates(Göttingen : Copernicus Publ., 2019) Zscheischler, Jakob; Fischer, Erich M.; Lange, StefanBias adjustment is often a necessity in estimating climate impacts because impact models usually rely on unbiased climate information, a requirement that climate model outputs rarely fulfil. Most currently used statistical bias-adjustment methods adjust each climate variable separately, even though impacts usually depend on multiple potentially dependent variables. Human heat stress, for instance, depends on temperature and relative humidity, two variables that are often strongly correlated. Whether univariate bias-adjustment methods effectively improve estimates of impacts that depend on multiple drivers is largely unknown, and the lack of long-term impact data prevents a direct comparison between model outputs and observations for many climate-related impacts. Here we use two hazard indicators, heat stress and a simple fire risk indicator, as proxies for more sophisticated impact models. We show that univariate bias-adjustment methods such as univariate quantile mapping often cannot effectively reduce biases in multivariate hazard estimates. In some cases, it even increases biases. These cases typically occur (i) when hazards depend equally strongly on more than one climatic driver, (ii) when models exhibit biases in the dependence structure of drivers and (iii) when univariate biases are relatively small. Using a perfect model approach, we further quantify the uncertainty in bias-adjusted hazard indicators due to internal variability and show how imperfect bias adjustment can amplify this uncertainty. Both issues can be addressed successfully with a statistical bias adjustment that corrects the multivariate dependence structure in addition to the marginal distributions of the climate drivers. Our results suggest that currently many modeled climate impacts are associated with uncertainties related to the choice of bias adjustment. We conclude that in cases where impacts depend on multiple dependent climate variables these uncertainties can be reduced using statistical bias-adjustment approaches that correct the variables' multivariate dependence structure. © 2019 Copernicus GmbH. All rights reserved.
- ItemThe impact of climate change and variability on the generation of electrical power(Stuttgart : Gebrueder Borntraeger Verlagsbuchhandlung, 2015) Koch, H.; Vögele, S.; Hattermann, F.F.; Huang, S.
- ItemForests under climate change: Potential risks and opportunities(Stuttgart : Gebrueder Borntraeger Verlagsbuchhandlung, 2015) Lasch-Born, P.; Suckow, F.; Gutsch, M.; Reyer, C.; Hauf, Y.; Murawski, A.; Pilz, T.
- ItemDiverging importance of drought stress for maize and winter wheat in Europe([London] : Nature Publishing Group UK, 2018) Webber, Heidi; Ewert, Frank; Olesen, Jørgen E.; Müller, Christoph; Fronzek, Stefan; Ruane, Alex C.; Bourgault, Maryse; Martre, Pierre; Ababaei, Behnam; Bindi, Marco; Ferrise, Roberto; Finger, Robert; Fodor, Nándor; Gabaldón-Leal, Clara; Gaiser, Thomas; Jabloun, Mohamed; Kersebaum, Kurt-Christian; Lizaso, Jon I.; Lorite, Ignacio J.; Manceau, Loic; Moriondo, Marco; Nendel, Claas; Rodríguez, Alfredo; Ruiz-Ramos, Margarita; Semenov, Mikhail A.; Siebert, Stefan; Stella, Tommaso; Stratonovitch, Pierre; Trombi, Giacomo; Wallach, DanielUnderstanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984–2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years.
- ItemClimate change and its effect on agriculture, water resources and human health sectors in Poland(Göttingen : Copernicus GmbH, 2010) Szwed, M.; Karg, G.; Pińskwar, I.; Radziejewski, M.; Graczyk, D.; Kȩdziora, A.; Kundzewicz, Z.W.Multi-model ensemble climate projections in the ENSEMBLES Project of the EU allowed the authors to quantify selected extreme-weather indices for Poland, of importance to climate impacts on systems and sectors. Among indices were: number of days in a year with high value of the heat index; with high maximum and minimum temperatures; length of vegetation period; and number of consecutive dry days. Agricultural, hydrological, and human health indices were applied to evaluate the changing risk of weather extremes in Poland in three sectors. To achieve this, model-based simulations were compared for two time horizons, a century apart, i.e., 1961-1990 and 2061-2090. Climate changes, and in particular increases in temperature and changes in rainfall, have strong impacts on agriculture via weather extremes-droughts and heat waves. The crop yield depends particularly on water availability in the plant development phase. To estimate the changes in present and future yield of two crops important for Polish agriculture i.e., potatoes and wheat, some simple empirical models were used. For these crops, decrease of yield is projected for most of the country, with national means of yield change being:-2.175 t/ha for potatoes and-0.539 t/ha for wheat. Already now, in most of Poland, evapotranspiration exceeds precipitation during summer, hence the water storage (in surface water bodies, soil and ground) decreases. Summer precipitation deficit is projected to increase considerably in the future. The additional water supplies (above precipitation) needed to use the agro-potential of the environment would increase by half. Analysis of water balance components (now and in the projected future) can corroborate such conclusions. As regards climate and health, a composite index, proposed in this paper, is a product of the number of senior discomfort days and the number of seniors (aged 65+). The value of this index is projected to increase over 8-fold during 100 years. This is an effect of both increase in the number of seniors (over twofold) and the number of senior-discomfort days (nearly fourfold).
- ItemClimate change impacts on hydrology and water resources(Stuttgart : Gebrueder Borntraeger Verlagsbuchhandlung, 2015) Hattermann, F.F.; Huang, S.; Koch, H.
- ItemA protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0(Göttingen : Copernicus GmbH, 2018) Tittensor, D.P.; Eddy, T.D.; Lotze, H.K.; Galbraith, E.D.; Cheung, W.; Barange, M.; Blanchard, J.L.; Bopp, L.; Bryndum-Buchholz, A.; Büchner, M.; Bulman, C.; Carozza, D.A.; Christensen, V.; Coll, M.; Dunne, J.P.; Fernandes, J.A.; Fulton, E.A.; Hobday, A.J.; Huber, V.; Jennings, S.; Jones, M.; Lehodey, P.; Link, J.S.; MacKinson, S.; Maury, O.; Niiranen, S.; Oliveros-Ramos, R.; Roy, T.; Schewe, J.; Shin, Y.-J.; Silva, T.; Stock, C.A.; Steenbeek, J.; Underwood, P.J.; Volkholz, J.; Watson, J.R.; Walker, N.D.Model intercomparison studies in the climate and Earth sciences communities have been crucial to building credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within-and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment and the consequent effects on food security, biodiversity, marine industries, and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size), and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem and implies that the assemblage of all models is more likely to include a greater number of relevant processes than any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (CMIP6) in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between and uncertainties within models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation, and comparison of results from Fish-MIP will inform an understanding of the range of plausible changes in marine ecosystems and improve our capacity to define and convey the strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium-and long-term projections of marine ecosystems.
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