Quality of a climate reconstruction for the CADSES regions

Böhm, Uwe; Keuler, Klaus; Österle, Hermann; Kücken, Martin; Hauffe, Detlef

doi:10.1127/0941-2948/2008/0318

Cited by 11 publications

(3 citation statements)

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“…As the General Circulation Models (GCMs) cannot provide climate information with sufficient spatial resolution for regional studies due to their coarse horizontal resolution, several RCMs were developed in the recent years in Germany. There are so‐called ‘dynamical downscaling models’, such as REMO (Jacob, 2001) and CCLM (Böhm et al , 2008). Besides, there are also other approaches, such as a combination of a statistical with an analogous downscaling approach, WettReg (Enke and Spekat, 1997) and a statistical downscaling technique, STAR (Orlowsky et al , 2008).…”

Section: Methodsmentioning

confidence: 99%

Simulation of spatiotemporal dynamics of water fluxes in Germany under climate change

Huang

Krysanova

Österle

et al. 2010

Hydrological Processes

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Abstract:In most of Europe, an increase in average annual surface temperature of 0Ð8°C is observed, and a further increase is projected. Precipitation tends to increase in northern Europe and decrease in southern Europe, with variable trends in central Europe. The climate scenarios for Germany suggest an increase in precipitation in western Germany and a decrease in eastern Germany, and a shift of precipitation from summer to winter. When investigating the effects of climate change, impacts on water resources are among the main concerns. In this study, the first German-wide impact assessment of water fluxes dynamics under climate change is presented in a spatially and temporally distributed manner using the state-of-the-art regional climate model, Statistical Regional (STAR) model and the semi-distributed process-based eco-hydrological model, soil and water integrated model (SWIM). All large river basins in Germany (lower Rhine, upper Danube, Elbe, Weser and Ems) are included. A special focus of the study was on data availability, homogeneity of data sets, related uncertainty propagation in the model results and scenario-related uncertainty. After the model calibration and validation (efficiency from 0Ð6 to 0Ð9 in 80% of cases) the water flow components were simulated at the hydrotope level, and the spatial distributions were compared with those in the Hydrological Atlas of Germany. The actual evapotransipration is likely to increase in most parts of Germany, while total runoff generation may decrease in south and east regions. The results for the second scenario period 2051-2060 show that water discharge in all six rivers would be 8-30% lower in summer and autumn compared with the reference period, and the strongest decline is expected for the Saale, Danube and Neckar. Higher winter flow is expected in all of these rivers, and the increase is most significant for the Ems (about 18%). However, the uncertainty of impacts, especially in winter and for high water flows, remains high.

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Section: Methodsmentioning

confidence: 99%

Simulation of spatiotemporal dynamics of water fluxes in Germany under climate change

Huang

Krysanova

Österle

et al. 2010

Hydrological Processes

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“…In an ongoing toolbox development various catchment processes are internally coupled in OGS and, in addition, OGS is coupled to external codes . Recently implemented interfaces are to the climate model CCLM (Böhm et al 2008), the stochastic meso-scale surface runoff model mHM (Samaniego et al 2010), the water uptake model aRoot (Schneider et al 2010), the groundwater modeling system GMS (Owen et al 1996;Sun et al, 2011), and the reactive transport model BRNS (Regnier et al 2002;Centler et al 2010). Just as important is efficient OpenMP and MPI parallelization (see e.g.…”

Section: Introductionmentioning

confidence: 99%

Coupling hydrogeological with surface runoff model in a Poltva case study in Western Ukraine

et al. 2011

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This paper presents the hydrological coupling of the software framework OpenGeoSys (OGS) with the EPA Storm Water Management Model (SWMM). Conceptual models include the Saint Venant equation for river flow, the 2D Darcy equations for confined and unconfined groundwater flow, a two-way hydrological coupling flux in a compartment coupling approach (conductance concept), and Lagrangian particles for solute transport in the river course. A SWMM river-OGS aquifer inter-compartment coupling flux is examined for discharging groundwater in a systematic parameter sensitivity analysis. The parameter study involves a small perturbation (first-order) sensitivity analysis and is performed for a synthetic test example baseby-base through a comprehensive range of aquifer parametrizations. Through parametrization, the test cases enables to determine the leakance parameter for simulating streambed clogging and non-ocillatory river-aquifer water exchange rates with the sequential (partitioned) coupling scheme. The implementation is further tested with a hypothetical but realistic 1D river-2D aquifer model of the Poltva catchment, where discharging groundwater in the upland area affects the river-aquifer coupling fluxes downstream in the river course (propagating feedbacks). Groundwater contribution in the moving river water is numerically determined with Lagrangian particles. A numerical experiment demonstrates that the integrated river-aquifer model is a serviceable and realistic constituent in a complete compartment model of the Poltva catchment.

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“…To achieve these objectives, the impact of climate change on water balance was simulated using two conceptually different models. After calibration and validation, the models were driven by two different RCMs, the regional model (REMO) (Jacob, ) and the COSMO model in climate mode (CCLM) (Böhm et al ., ), and two statistical DAs, STAR and the weather‐type regionalization method (WettReg) in the 2010 version (Spekat et al ., ). The RCMs and the statistical DAs have already been applied in different climate change impact studies in Germany (Graham et al ., ; Huang et al ., ; Hattermann et al ., ; Bormann et al ., ; Conradt et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Analysis of uncertainties in the hydrological response of a model‐based climate change impact assessment in a subcatchment of the Spree River, Germany

Gädeke

Hölzel

Koch

et al. 2013

Hydrological Processes

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Climate change impact assessments form the basis for the development of suitable climate change adaptation strategies. For this purpose, ensembles consisting of stepwise coupled models are generally used [emission scenario → global circulation model → downscaling approach (DA) → bias correction → impact model (hydrological model)], in which every item is affected by considerable uncertainty. The aim of the current study is (1) to analyse the uncertainty related to the choice of the DA as well as the hydrological model and its parameterization and (2) to evaluate the vulnerability of the studied catchment, a subcatchment of the highly anthropogenically impacted Spree River catchment, to hydrological change. Four different DAs are used to drive four different model configurations of two conceptually different hydrological models (Water Balance Simulation Model developed at ETH Zürich and HBV-light). In total, 452 simulations are carried out. The results show that all simulations compute an increase in air temperature and potential evapotranspiration. For precipitation, runoff and actual evapotranspiration, opposing trends are computed depending on the DA used to drive the hydrological models. Overall, the largest source of uncertainty can be attributed to the choice of the DA, especially regarding whether it is statistical or dynamical. The choice of the hydrological model and its parameterization is of less importance when long-term mean annual changes are compared. The large bandwidth at the end of the modelling chain may exacerbate the formulation of suitable climate change adaption strategies on the regional scale. Figure 6. Frequency plot for daily (top, precipitation > 10 mm/day not displayed) and monthly (bottom) precipitation for the reference period (CCLM: COSMO model in climate mode; REMO: regional model; WettReg: weather-type regionalization method) 3990A. GÄDEKE ET AL. Figure 8. Comparison between the interannual course of measured and simulated (reference 1963-1992 and scenario period 2031-2060) temperatures for the Weißer Schöps River catchment (interpolation by the inverse distance method) (CCLM: COSMO model in climate mode; REMO: regional model; STAR: Statistical Regional model; WettReg: weather-type regionalization method) 3992 A. GÄDEKE ET AL.

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Quality of a climate reconstruction for the CADSES regions

Cited by 11 publications

References 0 publications

Simulation of spatiotemporal dynamics of water fluxes in Germany under climate change

Simulation of spatiotemporal dynamics of water fluxes in Germany under climate change

Coupling hydrogeological with surface runoff model in a Poltva case study in Western Ukraine

Analysis of uncertainties in the hydrological response of a model‐based climate change impact assessment in a subcatchment of the Spree River, Germany

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