@article{VormoorRosslerBuergeretal.2017,
  author    = {Vormoor, Klaus Josef and Rossler, Ole and B{\"u}rger, Gerd and Bronstert, Axel and Weingartner, Rolf},
  title     = {When timing matters-considering changing temporal structures in runoff response surfaces},
  series = {Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change},
  volume    = {142},
  journal   = {Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {0165-0009},
  doi       = {10.1007/s10584-017-1940-1},
  pages     = {213 -- 226},
  year      = {2017},
  abstract  = {Scenario-neutral response surfaces illustrate the sensitivity of a simulated natural system, represented by a specific impact variable, to systematic perturbations of climatic parameters. This type of approach has recently been developed as an alternative to top-down approaches for the assessment of climate change impacts. A major limitation of this approach is the underrepresentation of changes in the temporal structure of the climate input data (i.e., the seasonal and day-to-day variability) since this is not altered by the perturbation. This paper presents a framework that aims to examine this limitation by perturbing both observed and projected climate data time series for a future period, which both serve as input into a hydrological model (the HBV model). The resulting multiple response surfaces are compared at a common domain, the standardized runoff response surface (SRRS). We apply this approach in a case study catchment in Norway to (i) analyze possible changes in mean and extreme runoff and (ii) quantify the influence of changes in the temporal structure represented by 17 different climate input sets using linear mixed-effect models. Results suggest that climate change induced increases in mean and peak flow runoff and only small changes in low flow. They further suggest that the effect of the different temporal structures of the climate input data considerably affects low flows and floods (at least 21\% influence), while it is negligible for mean runoff.},
  language  = {en}
}
@article{SunyerHundechaLawrenceetal.2015,
  author    = {Sunyer, M. A. and Hundecha, Y. and Lawrence, D. and Madsen, H. and Willems, Patrick and Martinkova, M. and Vormoor, Klaus Josef and B{\"u}rger, Gerd and Hanel, M. and Kriauciuniene, J. and Loukas, A. and Osuch, M. and Yucel, I.},
  title     = {Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe},
  series = {Hydrology and earth system sciences : HESS},
  volume    = {19},
  journal   = {Hydrology and earth system sciences : HESS},
  number    = {4},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1027-5606},
  doi       = {10.5194/hess-19-1827-2015},
  pages     = {1827 -- 1847},
  year      = {2015},
  abstract  = {Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30\% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis.},
  language  = {en}
}
@article{RottlerFranckeBuergeretal.2020,
  author    = {Rottler, Erwin and Francke, Till and B{\"u}rger, Gerd and Bronstert, Axel},
  title     = {Long-term changes in central European river discharge for 1869-2016},
  series = {Hydrology and Earth System Sciences},
  volume    = {24},
  journal   = {Hydrology and Earth System Sciences},
  number    = {4},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1027-5606},
  doi       = {10.5194/hess-24-1721-2020},
  pages     = {1721 -- 1740},
  year      = {2020},
  abstract  = {Recent climatic changes have the potential to severely alter river runoff, particularly in snow-dominated river basins. Effects of changing snow covers superimpose with changes in precipitation and anthropogenic modifications of the watershed and river network. In the attempt to identify and disentangle long-term effects of different mechanisms, we employ a set of analytical tools to extract long-term changes in river runoff at high resolution. We combine quantile sampling with moving average trend statistics and empirical mode decomposition and apply these tools to discharge data recorded along rivers with nival, pluvial and mixed flow regimes as well as temperature and precipitation data covering the time frame 1869-2016. With a focus on central Europe, we analyse the long-term impact of snow cover and precipitation changes along with their interaction with reservoir constructions. Our results show that runoff seasonality of snow-dominated rivers decreases. Runoff increases in winter and spring, while discharge decreases in summer and at the beginning of autumn. We attribute this redistribution of annual flow mainly to reservoir constructions in the Alpine ridge. During the course of the last century, large fractions of the Alpine rivers were dammed to produce hydropower. In recent decades, runoff changes induced by reservoir constructions seem to overlap with changes in snow cover. We suggest that Alpine signals propagate downstream and affect runoff far outside the Alpine area in river segments with mixed flow regimes. Furthermore, our results hint at more (intense) rain-fall in recent decades. Detected increases in high discharge can be traced back to corresponding changes in precipitation.},
  language  = {en}
}
@article{RottlerBronstertBuergeretal.2021,
  author    = {Rottler, Erwin and Bronstert, Axel and B{\"u}rger, Gerd and Rakovec, Oldrich},
  title     = {Projected changes in Rhine River flood seasonality under global warming},
  series = {Hydrology and earth system sciences : HESS / European Geosciences Union},
  volume    = {25},
  journal   = {Hydrology and earth system sciences : HESS / European Geosciences Union},
  number    = {5},
  publisher = {Copernicus Publications},
  address   = {G{\"o}ttingen},
  issn      = {1607-7938},
  doi       = {10.5194/hess-25-2353-2021},
  pages     = {2353 -- 2371},
  year      = {2021},
  abstract  = {Climatic change alters the frequency and intensity of natural hazards. In order to assess potential future changes in flood seasonality in the Rhine River Basin, we analyse changes in streamflow, snowmelt, precipitation, and evapotranspiration at 1.5, 2.0 and 3.0 ◦C global warming levels. The mesoscale Hydrological Model (mHM) forced with an ensemble of climate projection scenarios (five general circulation models under three representative concentration pathways) is used to simulate the present and future climate conditions of both, pluvial and nival hydrological regimes. Our results indicate that the interplay between changes in snowmelt- and rainfall-driven runoff is crucial to understand changes in streamflow maxima in the Rhine River. Climate projections suggest that future changes in flood characteristics in the entire Rhine River are controlled by both, more intense precipitation events and diminishing snow packs. The nature of this interplay defines the type of change in runoff peaks. On the sub-basin level (the Moselle River), more intense rainfall during winter is mostly counterbalanced by reduced snowmelt contribution to the streamflow. In the High Rhine (gauge at Basel), the strongest increases in streamflow maxima show up during winter, when strong increases in liquid precipitation intensity encounter almost unchanged snowmelt-driven runoff. The analysis of snowmelt events suggests that at no point in time during the snowmelt season, a warming climate results in an increase in the risk of snowmelt-driven flooding. We do not find indications of a transient merging of pluvial and nival floods due to climate warming.},
  language  = {en}
}
@article{MurawskiVorogushynBuergeretal.2018,
  author    = {Murawski, Aline and Vorogushyn, Sergiy and B{\"u}rger, Gerd and Gerlitz, Lars and Merz, Bruno},
  title     = {Do changing weather types explain observed climatic trends in the rhine basin?},
  series = {Journal of geophysical of geophysical research-atmosheres},
  volume    = {123},
  journal   = {Journal of geophysical of geophysical research-atmosheres},
  number    = {3},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-897X},
  doi       = {10.1002/2017JD026654},
  pages     = {1562 -- 1584},
  year      = {2018},
  abstract  = {For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). This approach assumes that changes in local climate are characterized by between-type changes of patterns. In this study we test this assumption by analyzing a previously developed WP classification for the Rhine basin, which is based on dynamic and thermodynamic variables. We quantify changes in pattern characteristics and associated climatic properties. The amount of between- and within-type changes is investigated by comparing observed trends to trends resulting solely from WP occurrence. To overcome uncertainties in trend detection resulting from the selected time period, all possible periods in 1901-2010 with a minimum length of 31 years are analyzed. Increasing frequency is found for some patterns associated with high precipitation, although the trend sign highly depends on the considered period. Trends and interannual variations of WP frequencies are related to the long-term variability of large-scale circulation modes. Long-term WP internal warming is evident for summer patterns and enhanced warming for spring/autumn patterns since the 1970s. Observed trends in temperature and partly in precipitation are mainly associated with frequency changes of specific WPs, but some amount of within-type changes remains. The classification can be used for downscaling of past changes considering this limitation, but the inclusion of thermodynamic variables into the classification impedes the downscaling of future climate projections.},
  language  = {en}
}
@article{MurawskiBuergerVorogushynetal.2016,
  author    = {Murawski, Aline and B{\"u}rger, Gerd and Vorogushyn, Sergiy and Merz, Bruno},
  title     = {Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin},
  series = {Hydrology and earth system sciences : HESS},
  volume    = {20},
  journal   = {Hydrology and earth system sciences : HESS},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1027-5606},
  doi       = {10.5194/hess-20-4283-2016},
  pages     = {4283 -- 4306},
  year      = {2016},
  abstract  = {To understand past flood changes in the Rhine catchment and in particular the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. This approach assumes a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. These presuppositions are unprecedentedly evaluated here using 111 years of daily climate data from 490 stations in the Rhine basin and comprehensively testing the number of classification parameters and GCM weather pattern characteristics. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis of atmospheric fields over central Europe with 40 weather types was found to be the most appropriate for stratifying six local climate variables. The corresponding skill is quite diverse though, ranging from good for radiation to poor for precipitation. Especially for the latter it was apparent that pressure fields alone cannot sufficiently stratify local variability. To test the skill of the latest generation of GCMs from the CMIP5 ensemble in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.},
  language  = {en}
}
@article{MtilatilaBronstertBuergeretal.2020,
  author    = {Mtilatila, Lucy Mphatso Ng'ombe and Bronstert, Axel and B{\"u}rger, Gerd and Vormoor, Klaus Josef},
  title     = {Meteorological and hydrological drought assessment in Lake Malawi and Shire River basins (1970-2013)},
  series = {Hydrological sciences journal = Journal des sciences hydrologiques},
  volume    = {65},
  journal   = {Hydrological sciences journal = Journal des sciences hydrologiques},
  number    = {16},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {0262-6667},
  doi       = {10.1080/02626667.2020.1837384},
  pages     = {2750 -- 2764},
  year      = {2020},
  abstract  = {The study assesses the variability and trends of both meteorological and hydrological droughts from 1970 to 2013 in Lake Malawi and Shire River basins using the standardized precipitation index (SPI) and standardized precipitation and evaporation index (SPEI) for meteorological droughts and the lake level change index (LLCI) for hydrological droughts. Trends and slopes in droughts and drought drivers are estimated using Mann-Kendall test and Sen's slope, respectively. Results suggest that meteorological droughts are increasing due to a decrease in precipitation which is exacerbated by an increase in temperature (potential evapotranspiration). The hydrological system of Lake Malawi seems to have a >24-month memory towards meteorological conditions, since the 36-month SPEI can predict hydrological droughts 10 months in advance. The study has found the critical lake level that would trigger hydrological drought to be 474.1 m a.s.l. The increase in drought is a concern as this will have serious impacts on water resources and hydropower supply in Malawi.},
  language  = {en}
}
@article{MenzelNiehoffBuergeretal.2002,
  author    = {Menzel, Lucas and Niehoff, Daniel and B{\"u}rger, Gerd and Bronstert, Axel},
  title     = {Climate change impacts on river flooding : a modelling study of three meso-scale catchments},
  year      = {2002},
  language  = {en}
}
@article{MenzelBronstertBuergeretal.2000,
  author    = {Menzel, Lucas and Bronstert, Axel and B{\"u}rger, Gerd and Krysanova, Valentina},
  title     = {Environmental change scenarios and flood responses in the Elbe catchment (Germany)},
  year      = {2000},
  language  = {en}
}
@article{KoehnReichBuerger2019,
  author    = {K{\"o}hn-Reich, Lisei and B{\"u}rger, Gerd},
  title     = {Dynamical prediction of Indian monsoon},
  series = {International Journal of Climatology},
  volume    = {39},
  journal   = {International Journal of Climatology},
  number    = {8},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0899-8418},
  doi       = {10.1002/joc.6039},
  pages     = {3574 -- 3581},
  year      = {2019},
  abstract  = {Ongoing development of dynamical atmosphere-ocean general circulation models keep expectations high regarding seasonal predictions of Indian monsoon rainfall. This study compares past and present skill of four currently operating forecasting systems, CFSv2 from NCEP, ENSEMBLES, System 4 and the newest SEAS5 from ECMWF, by analysing correlations of respective hindcasts with observed all-India summer rainfall. For the common time period 1982-2005, only ENSEMBLES and CFSv2 give significantly skilful forecasts. It is shown that skill is highly dependent on the chosen time period. Especially the intense El Nino of 1997 seems to degrade the predictions, most notably for SEAS4 and SEAS5 which seem to be linked to El Nino too strongly. We show that by discarding that year, a regime shift in the 1990s is no longer visible. Overall, we observe a convergence of skill towards the present with correlations of about 0.4 for CFSv2 and of 0.6 for System 4 and SEAS5.},
  language  = {en}
}