Transient Stochastic Downscaling of Quantitative Precipitation Estimates for Hydrological Applications

Nogueira, Miguel; Barros, Ana

iial nside continuineated vishowons itous multifractal bange of scales (results lds is intrinsically transient wic environment. These findings provide aetween spatial scales of observeents of hydrometeorological and ted to CRFs is presented and appcts from radar derived Stage IV E) over the Integrated PrecipitaA. The methodology can produce lg the coarse resolution information and generating coherent small-scale variability and field sth-resolution rainfall realizatioe observed streamflow, especialling resolution from 1 km to 250 m. Probabilistic simulations of ralized framework for producing fast and reliable probabilistic forecasts and their associated uncertainty for extreme events anABSTRACT: Rainfall fields are heavily thresholded and highly intermittent resulting in large areas of zero values. This deforms their stochastic spatial scale-invariant behavior, introducing scaling breaks and curvature in the spatal scale spectrum. To address this problem, spatscaling analysis was performed ious rainfall features (CRFs) dela cluster analysis. The results that CRFs from single realizatiof hourly rainfall display ubiquehavior that holds over a wide rfrom 1 km up to 100’s km). The further show that the aggregate scaling behavior of rainfall fieith the scaling parameters explicitly dependent on the atmospher framework for robust stochastic downscaling, bridging the gap bd and simulated rainfall fields and the high-resolution requiremhydrological studies. Here, a fractal downscaling algorithm adaplied to generate stochastically downscaled hourly rainfall produ(4 km grid resolution) quantitative precipitation estimates (QPtion and Hydrology Experiment (IPHEx) domain in the southeast USarge ensembles of statistically robust high-resolution fields without additional data or any calibration requirements, conservinatistics, hence adding value to the original fields. Moreover, it is computationally inexpensive enabling fast production of higns with latency adequate for forecasting applications. When the transient nature of the scaling behavior is considered, the results show a better ability to reproduce the statistical structure of observed rainfall compared to using fixed scaling parameters derived from ensemble mean analysis. A 7-year data set of 50 hourly realizations of downscaled Stage IV rainfall fields at 1 km resolution for the IPHEx domain is publicly available from iphex.pratt.duke.edu. The value of the downscaled products is demonstrated through hydrological simulations of two distinct storm events in the Southern Appalachians, a winter storm that caused multiple landslides and a summer tropical event that caused flashfloods. The simulations are forced by the entire span of plausible fractally downscaled rainfall fields at two distinct resolutions (1 km and 250 m). The results show very good skill against thy with regard to the timing and peak discharge of the hydrograph, and the accuracy is enhanced by increasing the target downscalboth events capture the observed behavior indicating that the proposed CRFbased stochastic fractal interpolation provides a gened risk management of hydrometeorological hazards, as well as long-term hydrologic modeling.

Transient Stochastic Downscaling of Quantitative Precipitation Estimates for Hydrological Applications

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