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Start date: 2010 × Type: Text × Subject: Climate change × Subject: Climate models ×

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Now showing 1 - 10 of 21
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    Overview: The Baltic Earth Assessment Reports (BEAR)
    (Göttingen : Copernicus Publ., 2023) Meier, H. E. Markus; Reckermann, Marcus; Langner, Joakim; Smith, Ben; Didenkulova, Ira
    Baltic Earth is an independent research network of scientists from all Baltic Sea countries that promotes regional Earth system research. Within the framework of this network, the Baltic Earth Assessment Reports (BEARs) were produced in the period 2019-2022. These are a collection of 10 review articles summarising current knowledge on the environmental and climatic state of the Earth system in the Baltic Sea region and its changes in the past (palaeoclimate), present (historical period with instrumental observations) and prospective future (until 2100) caused by natural variability, climate change and other human activities. The division of topics among articles follows the grand challenges and selected themes of the Baltic Earth Science Plan, such as the regional water, biogeochemical and carbon cycles; extremes and natural hazards; sea-level dynamics and coastal erosion; marine ecosystems; coupled Earth system models; scenario simulations for the regional atmosphere and the Baltic Sea; and climate change and impacts of human use. Each review article contains an introduction, the current state of knowledge, knowledge gaps, conclusions and key messages; the latter are the bases on which recommendations for future research are made. Based on the BEARs, Baltic Earth has published an information leaflet on climate change in the Baltic Sea as part of its outreach work, which has been published in two languages so far, and organised conferences and workshops for stakeholders, in collaboration with the Baltic Marine Environment Protection Commission (Helsinki Commission, HELCOM).
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    The challenge to detect and attribute effects of climate change on human and natural systems
    (Dordrecht [u.a.] : Springer, 2013) Stone, D.; Auffhammer, M.; Carey, M.; Hansen, G.; Huggel, C.; Cramer, W.; Lobell, D.; Molau, U.; Solow, A.; Tibig, L.; Yohe, G.
    Anthropogenic climate change has triggered impacts on natural and human systems world-wide, yet the formal scientific method of detection and attribution has been only insufficiently described. Detection and attribution of impacts of climate change is a fundamentally cross-disciplinary issue, involving concepts, terms, and standards spanning the varied requirements of the various disciplines. Key problems for current assessments include the limited availability of long-term observations, the limited knowledge on processes and mechanisms involved in changing environmental systems, and the widely different concepts applied in the scientific literature. In order to facilitate current and future assessments, this paper describes the current conceptual framework of the field and outlines a number of conceptual challenges. Based on this, it proposes workable cross-disciplinary definitions, concepts, and standards. The paper is specifically intended to serve as a baseline for continued development of a consistent cross-disciplinary framework that will facilitate integrated assessment of the detection and attribution of climate change impacts.
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    Deforestation in Amazonia impacts riverine carbon dynamics
    (München : European Geopyhsical Union, 2016) Langerwisch, Fanny; Walz, Ariane; Rammig, Anja; Tietjen, Britta; Thonicke, Kirsten; Cramer, Wolfgang
    Fluxes of organic and inorganic carbon within the Amazon basin are considerably controlled by annual flooding, which triggers the export of terrigenous organic material to the river and ultimately to the Atlantic Ocean. The amount of carbon imported to the river and the further conversion, transport and export of it depend on temperature, atmospheric CO2, terrestrial productivity and carbon storage, as well as discharge. Both terrestrial productivity and discharge are influenced by climate and land use change. The coupled LPJmL and RivCM model system (Langerwisch et al., 2016) has been applied to assess the combined impacts of climate and land use change on the Amazon riverine carbon dynamics. Vegetation dynamics (in LPJmL) as well as export and conversion of terrigenous carbon to and within the river (RivCM) are included. The model system has been applied for the years 1901 to 2099 under two deforestation scenarios and with climate forcing of three SRES emission scenarios, each for five climate models. We find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90%) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO2 concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO2 concentrations increase riverine inorganic carbon amount by up to 20% (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60% due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40% under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean.
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    Global cotton production under climate change – Implications for yield and water consumption
    (Munich : EGU, 2021) Jans, Yvonne; von Bloh, Werner; Schaphoff, Sibyll; Müller, Christoph
    Being an extensively produced natural fiber on earth, cotton is of importance for economies. Although the plant is broadly adapted to varying environments, the growth of and irrigation water demand on cotton may be challenged by future climate change. To study the impacts of climate change on cotton productivity in different regions across the world and the irrigation water requirements related to it, we use the process-based, spatially detailed biosphere and hydrology model LPJmL (Lund Potsdam Jena managed land). We find our modeled cotton yield levels in good agreement with reported values and simulated water consumption of cotton production similar to published estimates. Following the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) protocol, we employ an ensemble of five general circulation models under four representative concentration pathways (RCPs) for the 2011 2099 period to simulate future cotton yields. We find that irrigated cotton production does not suffer from climate change if CO2 effects are considered, whereas rainfed production is more sensitive to varying climate conditions. Considering the overall effect of a changing climate and CO2 fertilization, cotton production on current cropland steadily increases for most of the RCPs. Starting from _ 65 million tonnes in 2010, cotton production for RCP4.5 and RCP6.0 equates to 83 and 92 million tonnes at the end of the century, respectively. Under RCP8.5, simulated global cotton production rises by more than 50% by 2099. Taking only climate change into account, projected cotton production considerably shrinks in most scenarios, by up to one-Third or 43 million tonnes under RCP8.5. The simulation of future virtual water content (VWC) of cotton grown under elevated CO2 results for all scenarios in less VWC compared to ambient CO2 conditions. Under RCP6.0 and RCP8.5, VWC is notably decreased by more than 2000m3 t1 in areas where cotton is produced under purely rainfed conditions. By 2040, the average global VWC for cotton declines in all scenarios from currently 3300 to 3000m3 t1, and reduction continues by up to 30% in 2100 under RCP8.5. While the VWC decreases by the CO2 effect, elevated temperature acts in the opposite direction. Ignoring beneficial CO2 effects, global VWC of cotton would increase for all RCPs except RCP2.6, reaching more than 5000m3 t1 by the end of the simulation period under RCP8.5. Given the economic relevance of cotton production, climate change poses an additional stress and deserves special attention. Changes in VWC and water demands for cotton production are of special importance, as cotton production is known for its intense water consumption. The implications of climate impacts on cotton production on the one hand and the impact of cotton production on water resources on the other hand illustrate the need to assess how future climate change may affect cotton production and its resource requirements. Our results should be regarded as optimistic, because of high uncertainty with respect to CO2 fertilization and the lack of implementing processes of boll abscission under heat stress. Still, the inclusion of cotton in LPJmL allows for various large-scale studies to assess impacts of climate change on hydrological factors and the implications for agricultural production and carbon sequestration. © 2021 BMJ Publishing Group. All rights reserved.
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    Assessing the influence of the Merzbacher Lake outburst floods on discharge using the hydrological model SWIM in the Aksu headwaters, Kyrgyzstan/NW China
    (Chichester : John Wiley and Sons Ltd, 2013) Wortmann, M.; Krysanova, V.; Kundzewicz, Z.W.; Su, B.; Li, X.
    Glacial lake outburst floods (GLOF) often have a significant impact on downstream users. Including their effects in hydrological models, identifying past occurrences and assessing their potential impacts are challenges for hydrologists working in mountainous catchments. The regularly outbursting Merzbacher Lake is located in the headwaters of the Aksu River, the most important source of water discharge to the Tarim River, northwest China. Modelling its water resources and the evaluation of potential climate change impacts on river discharge are indispensable for projecting future water availability for the intensively cultivated river oases downstream of the Merzbacher Lake and along the Tarim River. The semi-distributed hydrological model SWIM was calibrated to the outlet station Xiehela on the Kumarik River, by discharge the largest tributary to the Aksu River. The glacial lake outburst floods add to the difficulties of modelling this high-mountain, heavily glaciated catchment with poor data coverage and quality. The aims of the study are to investigate the glacier lake outburst floods using a modelling tool. Results include a two-step model calibration of the Kumarik catchment, an approach for the identification of the outburst floods using the measured gauge data and the modelling results and estimations of the outburst flood volumes. Results show that a catchment model can inform GLOF investigations by providing 'normal' (i.e. without the outburst floods) catchment discharge. The comparison of the simulated and observed discharge proves the occurrence of GLOFs and highlights the influences of the GLOFs on the downstream water balance.
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    Bio-IGCC with CCS as a long-term mitigation option in a coupled energy-system and land-use model
    (Amsterdam [u.a.] : Elsevier, 2011) Klein, D.; Bauer, N.; Bodirsky, B.; Dietrich, J.P.; Popp, A.
    This study analyses the impact of techno-economic performance of the BIGCC process and the effect of different biomass feedstocks on the technology's long term deployment in climate change mitigation scenarios. As the BIGCC technology demands high amounts of biomass raw material it also affects the land-use sector and is dependent on conditions and constraints on the land-use side. To represent the interaction of biomass demand and supply side the global energy-economy-climate model ReMIND is linked to the global land-use model MAgPIE. The link integrates biomass demand and price as well as emission prices and land-use emissions. Results indicate that BIGCC with CCS could serve as an important mitigation option and that it could even be the main bioenergy conversion technology sharing 33% of overall mitigation in 2100. The contribution of BIGCC technology to long-term climate change mitigation is much higher if grass is used as fuel instead of wood, provided that the grass-based process is highly efficient. The capture rate has to significantly exceed 60 % otherwise the technology is not applied. The overall primary energy consumption of biomass reacts much more sensitive to price changes of the biomass than to technoeconomic performance of the BIGCC process. As biomass is mainly used with CCS technologies high amounts of carbon are captured ranging from 130 GtC to 240 GtC (cumulated from 2005-2100) in different scenarios.
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    Future changes in extratropical storm tracks and baroclinicity under climate change
    (Bristol : IOP, 2014) Lehmann, J.; Coumou, D.; Frieler, K.; Eliseev, A.V.; Levermann, A.
    The weather in Eurasia, Australia, and North and South America is largely controlled by the strength and position of extratropical storm tracks. Future climate change will likely affect these storm tracks and the associated transport of energy, momentum, and water vapour. Many recent studies have analyzed how storm tracks will change under climate change, and how these changes are related to atmospheric dynamics. However, there are still discrepancies between different studies on how storm tracks will change under future climate scenarios. Here, we show that under global warming the CMIP5 ensemble of coupled climate models projects only little relative changes in vertically averaged mid-latitude mean storm track activity during the northern winter, but agree in projecting a substantial decrease during summer. Seasonal changes in the Southern Hemisphere show the opposite behaviour, with an intensification in winter and no change during summer. These distinct seasonal changes in northern summer and southern winter storm tracks lead to an amplified seasonal cycle in a future climate. Similar changes are seen in the mid-latitude mean Eady growth rate maximum, a measure that combines changes in vertical shear and static stability based on baroclinic instability theory. Regression analysis between changes in the storm tracks and changes in the maximum Eady growth rate reveal that most models agree in a positive association between the two quantities over mid-latitude regions.
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    Comparing impacts of climate change on streamflow in four large African river basins
    (Göttingen : Copernicus GmbH, 2014) Aich, V.; Liersch, S.; Vetter, T.; Huang, S.; Tecklenburg, J.; Hoffmann, P.; Koch, H.; Fournet, S.; Krysanova, V.; Müller, E.N.; Hattermann, F.F.
    This study aims to compare impacts of climate change on streamflow in four large representative African river basins: the Niger, the Upper Blue Nile, the Oubangui and the Limpopo. We set up the eco-hydrological model SWIM (Soil and Water Integrated Model) for all four basins individually. The validation of the models for four basins shows results from adequate to very good, depending on the quality and availability of input and calibration data.

    For the climate impact assessment, we drive the model with outputs of five bias corrected Earth system models of Coupled Model Intercomparison Project Phase 5 (CMIP5) for the representative concentration pathways (RCPs) 2.6 and 8.5. This climate input is put into the context of climate trends of the whole African continent and compared to a CMIP5 ensemble of 19 models in order to test their representativeness. Subsequently, we compare the trends in mean discharges, seasonality and hydrological extremes in the 21st century. The uncertainty of results for all basins is high. Still, climate change impact is clearly visible for mean discharges but also for extremes in high and low flows. The uncertainty of the projections is the lowest in the Upper Blue Nile, where an increase in streamflow is most likely. In the Niger and the Limpopo basins, the magnitude of trends in both directions is high and has a wide range of uncertainty. In the Oubangui, impacts are the least significant. Our results confirm partly the findings of previous continental impact analyses for Africa. However, contradictory to these studies we find a tendency for increased streamflows in three of the four basins (not for the Oubangui). Guided by these results, we argue for attention to the possible risks of increasing high flows in the face of the dominant water scarcity in Africa. In conclusion, the study shows that impact intercomparisons have added value to the adaptation discussion and may be used for setting up adaptation plans in the context of a holistic approach.
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    Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile
    (Göttingen : Copernicus GmbH, 2018) Liersch, S.; Tecklenburg, J.; Rust, H.; Dobler, A.; Fischer, M.; Kruschke, T.; Koch, H.; Hattermann, F.F.
    Climate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth system models and 10 regional climate models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970-1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasize magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics and the effect of bias correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.
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    Impacts of future deforestation and climate change on the hydrology of the Amazon Basin: A multi-model analysis with a new set of land-cover change scenarios
    (Göttingen : Copernicus GmbH, 2017) Guimberteau, M.; Ciais, P.; Pablo, Boisier, J.; Paula Dutra Aguiar, A.; Biemans, H.; De Deurwaerder, H.; Galbraith, D.; Kruijt, B.; Langerwisch, F.; Poveda, G.; Rammig, A.; Andres Rodriguez, D.; Tejada, G.; Thonicke, K.; Von, Randow, C.; Randow, R.; Zhang, K.; Verbeeck, H.
    Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO2 levels. On the one hand, elevated CO2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Bolivian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3ĝ€°C by 2100 which drives up the evaporative demand, whereby precipitation increases by 8.5 %, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14ĝ€%, respectively. However, in south-east Amazonia, precipitation decreases by 10ĝ€% at the end of the dry season and the three LSMs produce a 6ĝ€% decrease of ET, which is less than precipitation, so that runoff decreases by 22 %. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31ĝ€% in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34ĝ€% over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the south-east, however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27ĝ€% in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast, we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.