Assessment of precipitation extremes in CMIP6 decadal hindcasts over India
<p>A skillful decadal precipitation prediction (DPP) is valuable for sustainable development, which currently face many challenges.Deriving reliable information from DPP is still a challenge because of the difficulties linked with precipitation predictions and coarse spatial resolution by General Circulation Models (GCMs) not able to be in a straight line appropriate for impact assessment.This study examines the decadal hindcast simulations of precipitation extreme over seven sub regions of India from different ocean-atmosphere coupled models from the Coupled Model Intercomparison Project(CMIP6) by applying quantile mapping approach.Each decadal hindcast consists of predictions for a 10-year period from the initial climate states of 1961 to 2014/2018 and the assessment of skill is carried out lead-wise from 1 to 10 for different season and different regions over India (both raw and bias corrected). The potential skill of precipitation extreme is examined in terms of&#160; extreme precipitation index (EPIs) i.e.cumulative wet days (CWD), cumulative dry days (CDD), precipitation events between P1020(10 and 20 mm),P20P40(20 and 40 mm), PG40(>40 mm) and &#160;annual maximum 1 & 5 day precipitation (Rx1day and Rx5day). The promising results revealed that the skills of DPPs are enhanced after the bias adjustment and the data product can be used as a key input for impacts assessments in the region.</p><p>&#160;</p>