Stochastic Space‐Time Downscaling of Rainfall Using Event‐Based Multiplicative Cascade Simulations
journal contributionposted on 24.06.2019 by Bhupendra A. Raut, Michael J Reeder, Christian Jakob, Alan W. Seed
Any type of content formally published in an academic journal, usually following a peer-review process.
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.
"This is the pre-peer reviewed version of the following article: [Raut, B. A., Reeder, M. J., Jakob, C., & Seed, A. W. ( 2019). Stochastic space‐time downscaling of rainfall using event‐based multiplicative cascade simulations. Journal of Geophysical Research: Atmospheres, 124, 3889– 3902. https://doi.org/10.1029/2018JD029343], which has been published in final form. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions."