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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Short summary
Fine-resolution spatio-temporal precipitation data are important as input to urban hydrological models to assess performance issues under all possible conditions. In the present study synthetic data at very fine spatial and temporal resolution are generated using a stochastic model. Data are generated for both present and future climate conditions. The results show that it is possible to generate spatially distributed data at resolutions relevant for urban hydrology.
Articles | Volume 20, issue 4
Hydrol. Earth Syst. Sci., 20, 1387–1403, 2016
https://doi.org/10.5194/hess-20-1387-2016
Hydrol. Earth Syst. Sci., 20, 1387–1403, 2016
https://doi.org/10.5194/hess-20-1387-2016

Research article 08 Apr 2016

Research article | 08 Apr 2016

Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator

Hjalte Jomo Danielsen Sørup et al.

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Short summary
Fine-resolution spatio-temporal precipitation data are important as input to urban hydrological models to assess performance issues under all possible conditions. In the present study synthetic data at very fine spatial and temporal resolution are generated using a stochastic model. Data are generated for both present and future climate conditions. The results show that it is possible to generate spatially distributed data at resolutions relevant for urban hydrology.
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