@article{DelgadoVossBuergeretal.2018, author = {Delgado, Jos{\´e} Miguel Martins and Voss, Sebastian and B{\"u}rger, Gerd and Vormoor, Klaus Josef and Murawski, Aline and Rodrigues Pereira, Jos{\´e} Marcelo and Martins, Eduardo and Vasconcelos J{\´u}nior, Francisco and Francke, Till}, title = {Seasonal drought prediction for semiarid northeastern Brazil}, series = {Hydrology and Earth System Sciences}, volume = {22}, journal = {Hydrology and Earth System Sciences}, number = {9}, publisher = {Copernicus Publ.}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-22-5041-2018}, pages = {5041 -- 5056}, year = {2018}, abstract = {A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Cear{\´a}'s research foundation for meteorology)and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation,(b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.}, 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{BuergerPfisterBronstert2019, author = {B{\"u}rger, Gerd and Pfister, A. and Bronstert, Axel}, title = {Temperature-Driven Rise in Extreme Sub-Hourly Rainfall}, series = {Journal of climate}, volume = {32}, journal = {Journal of climate}, number = {22}, publisher = {American Meteorological Soc.}, address = {Boston}, issn = {0894-8755}, doi = {10.1175/JCLI-D-19-0136.1}, pages = {7597 -- 7609}, year = {2019}, abstract = {Estimates of present and future extreme sub-hourly rainfall are derived from a daily spatial followed by a sub-daily temporal downscaling, the latter of which incorporates a novel, and crucial, temperature sensitivity. Specifically, daily global climate fields are spatially downscaled to local temperature T and precipitation P, which are then disaggregated to a temporal resolution of 10 min using a multiplicative random cascade model. The scheme is calibrated and validated with a group of 21 station records of 10-min resolution in Germany. The cascade model is used in the classical (denoted as MC) and in the new T-sensitive (MC+) version, which respects local Clausius-Clapeyron (CC) effects such as CC scaling. Extreme P is positively biased in both MC versions. Observed T sensitivity is absent in MC but well reproduced by MC+. Long-term positive trends in extreme sub-hourly P are generally more pronounced and more significant in MC+ than in MC. In units of 10-min rainfall, observed centennial trends in annual exceedance counts (EC) of P > 5 mm are +29\% and in 3-yr return levels (RL) +27\%. For the RCP4.5-simulated future, higher extremes are projected in both versions MC and MC+: per century, EC increases by 30\% for MC and by 83\% for MC+; the RL rises by 14\% for MC and by 33\% for MC+. Because the projected daily P trends are negligible, the sub-daily signal is mainly driven by local temperature.}, language = {en} } @article{BuergerHeistermannBronstert2014, author = {B{\"u}rger, Gerd and Heistermann, Maik and Bronstert, Axel}, title = {Towards subdaily rainfall disaggregation via Clausius-Clapeyron}, series = {Journal of hydrometeorology}, volume = {15}, journal = {Journal of hydrometeorology}, number = {3}, publisher = {American Meteorological Soc.}, address = {Boston}, issn = {1525-755X}, doi = {10.1175/JHM-D-13-0161.1}, pages = {1303 -- 1311}, year = {2014}, abstract = {Two lines of research are combined in this study: first, the development of tools for the temporal disaggregation of precipitation, and second, some newer results on the exponential scaling of heavy short-term precipitation with temperature, roughly following the Clausius-Clapeyron (CC) relation. Having no extra temperature dependence, the traditional disaggregation schemes are shown to lack the crucial CC-type temperature dependence. The authors introduce a proof-of-concept adjustment of an existing disaggregation tool, the multiplicative cascade model of Olsson, and show that, in principal, it is possible to include temperature dependence in the disaggregation step, resulting in a fairly realistic temperature dependence of the CC type. They conclude by outlining the main calibration steps necessary to develop a full-fledged CC disaggregation scheme and discuss possible applications.}, language = {en} } @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{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.
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} }