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  - 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  -