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Urban water infrastructure has very long planning horizons, and planning isthus very dependent on reliable estimates of the impacts of climate change.Many urban water systems are designed using time series with a high temporalresolution. To assess the impact of climate change on these systems,similarly high-resolution precipitation time series for future climate arenecessary. Climate models cannot at their current resolutions provide thesetime series at the relevant scales. Known methods for stochastic downscalingof climate change to urban hydrological scales have known shortcomings inconstructing realistic climate-changed precipitation time series at thesub-hourly scale. In the present study we present a deterministic methodologyto perturb historical precipitation time series at the minute scale toreflect non-linear expectations to climate change. The methodology shows goodskill in meeting the expectations to climate change in extremes at the eventscale when evaluated at different timescales from the minute to the dailyscale. The methodology also shows good skill with respect to representingexpected changes of seasonal precipitation. The methodology is very robustagainst the actual magnitude of the expected changes as well as the directionof the changes (increase or decrease), even for situations where the extremesare increasing for seasons that in general should have a decreasing trend inprecipitation. The methodology can provide planners with valuable time seriesrepresenting future climate that can be used as input to urban hydrologicalmodels and give better estimates of climate change impacts on these systems

Formulating and testing a method for perturbing precipitation time series to reflect anticipated climatic changes