@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{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{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}
}
@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}
}