@article{BuergerPfisterBronstert2021,
  author    = {B{\"u}rger, Gerd and Pfister, Angela and Bronstert, Axel},
  title     = {Zunehmende Starkregenintensit{\"a}ten als Folge der Klimaerw{\"a}rmung},
  series = {Hydrologie und Wasserbewirtschaftung : HyWa = Hydrology and water resources management, Germany / Hrsg.: Fachverwaltungen des Bundes und der L{\"a}nder},
  volume    = {65},
  journal   = {Hydrologie und Wasserbewirtschaftung : HyWa = Hydrology and water resources management, Germany / Hrsg.: Fachverwaltungen des Bundes und der L{\"a}nder},
  number    = {6},
  publisher = {Bundesanst. f{\"u}r Gew{\"a}sserkunde},
  address   = {Koblenz},
  issn      = {1439-1783},
  doi       = {10.5675/HyWa_2021.6_1},
  pages     = {262 -- 271},
  year      = {2021},
  abstract  = {Extreme rainfall events of short duration in the range of hours and below are increasingly coming into focus due to the resulting damage from flash floods and also due to their possible intensification by anthropogenic climate change. The current study investigates possible trends in heavy rainfall intensities for stations from Swiss and Austrian alpine regions as well as for the Emscher-Lippe area in North Rhine-Westphalia on the basis of partly very long (> 50 years) and temporally highly resolved time series (<= 15 minutes). It becomes clear that there is an increase in extreme rainfall intensities, which can be well explained by the warming of the regional climate: the analyses of long-term trends in exceedance counts and return levels show considerable uncertainties, but are in the order of 30 \% increase per century. In addition, based on an "average" climate simulation for the 21st century, this paper describes a projection for extreme precipitation intensities at very high temporal resolution for a number of stations in the Emscher-Lippe region. A coupled spatial and temporal "downscaling" is applied, the key innovation of which is the consideration of the dependence of local rainfall intensity on air temperature. This procedure involves two steps: First, large-scale climate fields at daily resolution are statistically linked by regression to station temperature and precipitation values (spatial downscaling). In the second step, these station values are disaggregated to a temporal resolution of 10 minutes using a so-called multiplicative stochastic cascade model (MC) (temporal downscaling). The novel, temperature-sensitive variant additionally considers air temperature as an explanatory variable for precipitation intensities. Thus, the higher atmospheric moisture content expected with warming, which results from the Clausius-Clapeyron (CC) relationship, is included in the temporal downscaling. <br /> For the statistical evaluation of the extreme short-term precipitation, the upper quantiles (99.9 \%), exceedance counts (P > 5mm), and 3-yr return levels of the <= 15-min duration step has been used. Only by adding temperature is the observed temperature observed of the extreme quantiles ("CC scaling") well reproduced. When comparing observed data and present-day simulations of the model cascade, the temperature-sensitive procedure shows consistent results. Compared to trends in recent decades, similar or even larger increases in extreme intensities are projected for the future. This is remarkable in that these appear to be driven primarily by local temperature, as the projected trends in daily precipitation values are negligible for this region.},
  language  = {de}
}
@article{Buerger2022,
  author    = {B{\"u}rger, Gerd},
  title     = {A conundrum of trends},
  series = {Journal of hydrology},
  volume    = {609},
  journal   = {Journal of hydrology},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0022-1694},
  doi       = {10.1016/j.jhydrol.2022.127745},
  pages     = {3},
  year      = {2022},
  abstract  = {This comment is meant to reiterate two warnings: One applies to the uncritical use of ready-made (openly available) program packages, and one to the estimation of trends in serially correlated time series. Both warnings apply to the recent publication of Lischeid et al. about lake-level trends in Germany.},
  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{Buerger2021,
  author    = {B{\"u}rger, Gerd},
  title     = {Intraseasonal oscillation indices from complex EOFs},
  series = {Journal of climate},
  volume    = {34},
  journal   = {Journal of climate},
  number    = {1},
  publisher = {American Meteorological Soc.},
  address   = {Boston},
  issn      = {0894-8755},
  doi       = {10.1175/JCLI-D-20-0427.1},
  pages     = {107 -- 122},
  year      = {2021},
  abstract  = {Indices of oscillatory behavior are conveniently obtained by projecting the fields in question into a phase space of a few (mostly just two) dimensions; empirical orthogonal functions (EOFs) or other, more dynamical, modes are typically used for the projection. If sufficiently coherent and in quadrature, the projected variables simply describe a rotating vector in the phase space, which then serves as the basis for predictions. Using the boreal summer intraseasonal oscillation (BSISO) as a test case, an alternative procedure is introduced: it augments the original fields with their Hilbert transform (HT) to form a complex series and projects it onto its (single) dominant EOF. The real and imaginary parts of the corresponding complex pattern and index are compared with those of the original (real) EOF. The new index explains slightly less variance of the physical fields than the original, but it is much more coherent, partly from its use of future information by the HT. Because the latter is in the way of real-time monitoring, the index can only be used in cases with predicted physical fields, for which it promises to be superior. By developing a causal approximation of the HT, a real-time variant of the index is obtained whose coherency is comparable to the noncausal version, but with smaller explained variance of the physical fields. In test cases the new index compares well to other indices of BSISO. The potential for using both indices as an alternative is discussed.},
  language  = {en}
}
@article{Buerger2019,
  author    = {B{\"u}rger, Gerd},
  title     = {A seamless filter for daily to seasonal forecasts, with applications to Iran and Brazil},
  series = {Quarterly Journal of the Royal Meteorological Society},
  volume    = {146},
  journal   = {Quarterly Journal of the Royal Meteorological Society},
  number    = {726},
  publisher = {WILEY-VCH},
  address   = {Weinheim},
  pages     = {14},
  year      = {2019},
  abstract  = {A digital filter is introduced which treats the problem of predictability versus time averaging in a continuous, seamless manner. This seamless filter (SF) is characterized by a unique smoothing rule that determines the strength of smoothing in dependence on lead time. The rule needs to be specified beforehand, either by expert knowledge or by user demand. As a result, skill curves are obtained that allow a predictability assessment across a whole range of time-scales, from daily to seasonal, in a uniform manner. The SF is applied to downscaled SEAS5 ensemble forecasts for two focus regions in or near the tropical belt, the river basins of the Karun in Iran and the Sao Francisco in Brazil. Both are characterized by strong seasonality and semi-aridity, so that predictability across various time-scales is in high demand. Among other things, it is found that from the start of the water year (autumn), areal precipitation is predictable with good skill for the Karun basin two and a half months ahead; for the Sao Francisco it is only one month, longer-term prediction skill is just above the critical level.},
  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{DidovetsKrysanovaBuergeretal.2019,
  author    = {Didovets, Iulii and Krysanova, Valentina and B{\"u}rger, Gerd and Snizhko, Sergiy and Balabukh, Vira and Bronstert, Axel},
  title     = {Climate change impact on regional floods in the Carpathian region},
  series = {Journal of hydrology : Regional studies},
  volume    = {22},
  journal   = {Journal of hydrology : Regional studies},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2214-5818},
  doi       = {10.1016/j.ejrh.2019.01.002},
  pages     = {14},
  year      = {2019},
  abstract  = {Study region: Tisza and Prut catchments, originating on the slopes of the Carpathian mountains. Study focus: The study reported here investigates (i) climate change impacts on flood risk in the region, and (ii) uncertainty related to hydrological modelling, downscaling techniques and climate projections. The climate projections used in the study were derived from five GCMs, downscaled either dynamically with RCMs or with the statistical downscaling model XDS. The resulting climate change scenarios were applied to drive the eco-hydrological model SWIM, which was calibrated and validated for the catchments in advance using observed climate and hydrological data. The changes in the 30-year flood hazards and 98 and 95 percentiles of discharge were evaluated for the far future period (2071-2100) in comparison with the reference period (1981-2010). New hydrological insights for the region: The majority of model outputs under RCP 4.5 show a small to strong increase of the 30-year flood level in the Tisza ranging from 4.5\% to 62\%, and moderate increase in the Prut ranging from 11\% to 22\%. The impact results under RCP 8.5 are more uncertain with changes in both directions due to high uncertainties in GCM-RCM climate projections, downscaling methods and the low density of available climate stations.},
  language  = {en}
}
@article{DoblerBuergerStoetter2013,
  author    = {Dobler, C. and B{\"u}rger, Gerd and St{\"o}tter, J.},
  title     = {Simulating future precipitation extremes in a complex Alpine catchment},
  series = {Natural hazards and earth system sciences},
  volume    = {13},
  journal   = {Natural hazards and earth system sciences},
  number    = {2},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1561-8633},
  doi       = {10.5194/nhess-13-263-2013},
  pages     = {263 -- 277},
  year      = {2013},
  abstract  = {The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.},
  language  = {en}
}
@article{BuergerSobieCannonetal.2013,
  author    = {B{\"u}rger, Gerd and Sobie, S. R. and Cannon, A. J. and Werner, A. T. and Murdock, T. Q.},
  title     = {Downscaling extremes an intercomparison of multiple methods for future climate},
  series = {Journal of climate},
  volume    = {26},
  journal   = {Journal of climate},
  number    = {10},
  publisher = {American Meteorological Soc.},
  address   = {Boston},
  issn      = {0894-8755},
  doi       = {10.1175/JCLI-D-12-00249.1},
  pages     = {3429 -- 3449},
  year      = {2013},
  abstract  = {This study follows up on a previous downscaling intercomparison for present climate. Using a larger set of eight methods the authors downscale atmospheric fields representing present (1981-2000) and future (2046-65) conditions, as simulated by six global climate models following three emission scenarios. Local extremes were studied at 20 locations in British Columbia as measured by the same set of 27 indices, ClimDEX, as in the precursor study. Present and future simulations give 2 x 3 x 6 x 8 x 20 x 27 = 155 520 index climatologies whose analysis in terms of mean change and variation is the purpose of this study. The mean change generally reinforces what is to be expected in a warmer climate: that extreme cold events become less frequent and extreme warm events become more frequent, and that there are signs of more frequent precipitation extremes. There is considerable variation, however, about this tendency, caused by the influence of scenario, climate model, downscaling method, and location. This is analyzed using standard statistical techniques such as analysis of variance and multidimensional scaling, along with an assessment of the influence of each modeling component on the overall variation of the simulated change. It is found that downscaling generally has the strongest influence, followed by climate model; location and scenario have only a minor influence. The influence of downscaling could be traced back in part to various issues related to the methods, such as the quality of simulated variability or the dependence on predictors. Using only methods validated in the precursor study considerably reduced the influence of downscaling, underpinning the general need for method verification.},
  language  = {en}
}
@article{BuergerReusserKneis2009,
  author    = {B{\"u}rger, Gerd and Reusser, Dominik and Kneis, David},
  title     = {Early flood warnings from empirical (expanded) downscaling of the full ECMWF Ensemble Prediction System},
  issn      = {0043-1397},
  doi       = {10.1029/2009wr007779},
  year      = {2009},
  language  = {en}
}