Improving CMIP6 projections of daily precipitation using a mean-adjusted time variability correction technique

Abstract

Daily precipitation time series exhibit intermittent periods of high variability separated by periods of no rain, posing challenges to correct projected precipitation. To improve projected changes in probabilities of flooding and drought, it is critically important to improve temporal correlations of the precipitation time series. Previous work introduced a Time Variability Correction (TVC) method, which quantified and corrected time variability errors at differing time scales. This study extends TVC to post-process daily precipitation projections from 28 CMIP6 models over Australia, introducing a new mean adjustment procedure to eliminate negative precipitation values while ensuring that bo..