TY - JOUR A1 - Bürger, Gerd A1 - Pfister, Angela A1 - Bronstert, Axel T1 - Zunehmende Starkregenintensitäten als Folge der Klimaerwärmung T1 - Increasing intensity of heavy rainfall caused by global warming BT - Datenanalyse und Zukunftsprojektion BT - data analysis and future projections JF - Hydrologie und Wasserbewirtschaftung : HyWa = Hydrology and water resources management, Germany / Hrsg.: Fachverwaltungen des Bundes und der Länder N2 - 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.
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. N2 - Extreme Regenereignisse von kurzer Dauer im Bereich von Stunden und darunter rücken aufgrund der dadurch bedingten Schäden durch Sturzfluten und auch wegen ihrer möglichen Intensivierungen durch den anthropogenen Klimawandel immer stärker in den Fokus. Die vorliegende Studie untersucht auf Basis von teilweise sehr langen (> 50 Jahre) und zeitlich hochaufgelösten Zeitreihen (≤ 15 Minuten) mögliche Trends in Starkregenintensitäten für Stationen aus schweizerischen und österreichischen Alpenregionen sowie für das Emscher-Lippe-Gebiet in Nordrhein-Westfalen. Es wird deutlich, dass es eine Zunahme der extremen Niederschlagsintensitäten gibt, welche gut durch die Erwärmung des regionalen Klimas erklärt werden kann: Die Analysen langfristiger Trends der Überschreitungssummen und Wiederkehrniveaus zeigen zwar erhebliche Unsicherheiten, lassen jedoch eine Zunahme in einer Größenordnung von 30 % pro Jahrhundert erkennen. Zudem wird in diesem Beitrag, basierend auf einer "mittleren" Klimasimulation für das 21. Jahrhundert, für ausgewählte Stationen der Emscher-Lippe-Region eine Projektion für extreme Niederschlagsintensitäten in sehr hoher zeitlicher Auflösung beschrieben. Dabei wird ein gekoppeltes räumliches und zeitliches "Downscaling" angewendet, dessen entscheidende Neuerung die Berücksichtigung der Abhängigkeit der lokalen Regenintensität von der Lufttemperatur ist. Dieses Verfahren beinhaltet zwei Schritte: Zuerst werden großräumige Klimafelder in täglicher Auflösung durch Regression mit den Temperatur- und Niederschlagswerten der Stationen statistisch verbunden (räumliches Downscaling). Im zweiten Schritt werden dann diese Stationswerte mithilfe eines sogenannten multiplikativen stochastischen Kaskadenmodells (MC) auf eine zeitliche Auflösung von 10 Minuten disaggregiert (zeitliches Downscaling). Die neuartige, temperatursensitive Variante berücksichtigt zusätzlich die Lufttemperatur als erklärende Variable für die Niederschlagsintensitäten. Dadurch wird der mit einer Erwärmung zu erwartende höhere atmosphärische Feuchtegehalt, welcher sich aus der Clausius-Clapeyron-Beziehung (CC) ergibt, mit in das zeitliche Downscaling einbezogen. Für die statistische Auswertung der extremen kurzfristigen Niederschläge wurden die oberen Quantile (99,9 %), Überschreitungssummen (ÜS, P > 5 mm) und 3-jährliche Wiederkehrniveaus (WN) einer Dauerstufe von ≤ 15-Minuten betrachtet. Diese Auswahl erlaubt die gleichzeitige Analyse sowohl von Extremwertstatistiken als auch von deren langfristigen Trends; leichte Abweichungen von dieser Wahl beeinflussen die Hauptergebnisse nur unwesentlich. Nur durch die Hinzunahme der Temperatur wird die beobachtete Temperaturabhängigkeit der extremen Quantile (CC-Scaling) gut wiedergegeben. Bei Vergleich von Beobachtungsdaten und Gegenwartssimulationen der Modellkaskade zeigt das temperatursensitive Verfahren konsistente Ergebnisse. Im Vergleich zu den Entwicklungen der letzten Jahrzehnte werden für die Zukunft ähnliche oder sogar noch stärkere Anstiege der extremen Niederschlagsintensitäten projiziert. Dies ist insofern bemerkenswert, als diese anscheinend hauptsächlich durch die örtliche Temperatur bestimmt werden, denn die projizierten Trends der Niederschlags-Tageswerte sind für diese Region vernachlässigbar. KW - heavy rainfall KW - short duration KW - global warming KW - Clausius-Clapeyron KW - equation KW - precipitation intensity KW - multiplicative cascade model KW - Strakregen KW - kurzfristige Dauerstufe KW - Klimawandel KW - Clausius-Clapeyron-Gleichung KW - Niederschlagsintensitäten KW - Multiplikatives Kaskadenmodel Y1 - 2021 U6 - https://doi.org/10.5675/HyWa_2021.6_1 SN - 1439-1783 SN - 2749-859X VL - 65 IS - 6 SP - 262 EP - 271 PB - Bundesanst. für Gewässerkunde CY - Koblenz ER - TY - JOUR A1 - Bürger, Gerd T1 - A conundrum of trends BT - comment on a paper by Lischeid et al. (2021) JF - Journal of hydrology N2 - 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. KW - Linear trends KW - Autocorrelation KW - Pre-whitening Y1 - 2022 U6 - https://doi.org/10.1016/j.jhydrol.2022.127745 SN - 0022-1694 SN - 1879-2707 VL - 609 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Rottler, Erwin A1 - Francke, Till A1 - Bürger, Gerd A1 - Bronstert, Axel T1 - Long-term changes in central European river discharge for 1869–2016 BT - impact of changing snow covers, reservoir constructions and an intensified hydrological cycle JF - Hydrology and Earth System Sciences N2 - 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. KW - empirical mode decomposition KW - atmospheric blocking KW - heavy precipitation KW - streamflow trends KW - climate-change KW - rhine basin KW - time-series KW - events KW - Switzerland KW - variability Y1 - 2020 U6 - https://doi.org/10.5194/hess-24-1721-2020 SN - 1027-5606 SN - 1607-7938 VL - 24 IS - 4 SP - 1721 EP - 1740 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Bürger, Gerd T1 - Intraseasonal oscillation indices from complex EOFs JF - Journal of climate N2 - 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. KW - Madden-Julian oscillation KW - Oscillations KW - Empirical orthogonal functions KW - Filtering techniques KW - Statistical techniques KW - Forecasting techniques Y1 - 2021 U6 - https://doi.org/10.1175/JCLI-D-20-0427.1 SN - 0894-8755 SN - 1520-0442 VL - 34 IS - 1 SP - 107 EP - 122 PB - American Meteorological Soc. CY - Boston ER - TY - JOUR A1 - Bürger, Gerd T1 - A seamless filter for daily to seasonal forecasts, with applications to Iran and Brazil JF - Quarterly Journal of the Royal Meteorological Society N2 - 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. KW - climate drift KW - ensemble prediction KW - seamless prediction KW - seasonal forecast skill Y1 - 2019 VL - 146 IS - 726 PB - WILEY-VCH CY - Weinheim ER - TY - JOUR A1 - Rottler, Erwin A1 - Bronstert, Axel A1 - Bürger, Gerd A1 - Rakovec, Oldrich T1 - Projected changes in Rhine River flood seasonality under global warming JF - Hydrology and earth system sciences : HESS / European Geosciences Union N2 - 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. Y1 - 2020 U6 - https://doi.org/10.5194/hess-25-2353-2021 SN - 1607-7938 SN - 1027-5606 VL - 25 IS - 5 SP - 2353 EP - 2371 PB - Copernicus Publications CY - Göttingen ER - TY - JOUR A1 - Didovets, Iulii A1 - Krysanova, Valentina A1 - Bürger, Gerd A1 - Snizhko, Sergiy A1 - Balabukh, Vira A1 - Bronstert, Axel T1 - Climate change impact on regional floods in the Carpathian region JF - Journal of hydrology : Regional studies N2 - 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. KW - Climate change impact KW - Floods KW - Hydrological modelling KW - SWIM KW - Tisza KW - Prut KW - Carpathians KW - Ukraine Y1 - 2019 U6 - https://doi.org/10.1016/j.ejrh.2019.01.002 SN - 2214-5818 VL - 22 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Dobler, C. A1 - Bürger, Gerd A1 - Stötter, J. T1 - Simulating future precipitation extremes in a complex Alpine catchment JF - Natural hazards and earth system sciences N2 - 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. Y1 - 2013 U6 - https://doi.org/10.5194/nhess-13-263-2013 SN - 1561-8633 VL - 13 IS - 2 SP - 263 EP - 277 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Bürger, Gerd A1 - Sobie, S. R. A1 - Cannon, A. J. A1 - Werner, A. T. A1 - Murdock, T. Q. T1 - Downscaling extremes an intercomparison of multiple methods for future climate JF - Journal of climate N2 - 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. Y1 - 2013 U6 - https://doi.org/10.1175/JCLI-D-12-00249.1 SN - 0894-8755 VL - 26 IS - 10 SP - 3429 EP - 3449 PB - American Meteorological Soc. CY - Boston ER - TY - JOUR A1 - Bürger, Gerd A1 - Reusser, Dominik A1 - Kneis, David T1 - Early flood warnings from empirical (expanded) downscaling of the full ECMWF Ensemble Prediction System Y1 - 2009 UR - http://www.agu.org/journals/wr/ U6 - https://doi.org/10.1029/2009wr007779 SN - 0043-1397 ER -