Stochastic Space-Time Downscaling of Rainfall Using Event-Based Multiplicative Cascade Simulations

Bhupendra A. Raut, Michael J. Reeder, Christian Jakob, Alan W. Seed

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

A multiplicative cascade model called High-resolution Downscaling of Rainfall Using Short-Term Ensemble Prediction System (HiDRUS) is developed and tested in the greater Melbourne region (Australia) by downscaling coarse-resolution ERA-I rainfall to 1-km horizontal and 6-min temporal resolutions. The parameters required for the cascade model are computed from radar observations of rain events during 2008–2015, and a library of rainfall events and their associated synoptic conditions created. Each day, the area-averaged rainfall and synoptic conditions are taken from ERA-I and compared with the library. From the library, similar days are chosen randomly and downscaled using the cascade model. Ensembles of 100 realizations per day are produced for the period 1995–2004. The downscaled rainfall is compared with 6-min rain gauges and daily gridded rain gauge data at four locations in the greater Melbourne region. HiDRUS reproduces the monthly variability of rainfall, frequency distribution of daily and 6-min rainfall, and the autocorrelation function satisfactorily. Changes in heavy rainfall are also captured by HiDRUS but with increasing uncertainty as the intensities increase.

Original languageEnglish
Pages (from-to)3889-3902
Number of pages14
JournalJournal of Geophysical Research: Atmospheres
Volume124
Issue number7
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • climate change
  • hydrological impact
  • precipitation
  • statistical downscaling
  • stormwater harvesting
  • urban planning

Cite this