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  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  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> </p>

The Extreme Precipitation Index (EPI): A Coupled Dynamic–Thermodynamic Metric to Diagnose Midlatitude Floods Associated with Flow Reversal

The extreme precipitation index (EPI) is a coupled dynamic–thermodynamic metric that can diagnose extreme precipitation events associated with flow reversal in the mid- to upper troposphere (e.g., Rex and omega blocks, cutoff cyclones, Rossby wave breaks). Recent billion dollar (U.S. dollars) floods across the Northern Hemisphere midlatitudes were associated with flow reversal, as long-duration ascent (dynamics) occurred in the presence of anomalously warm and moist air (thermodynamics). The EPI can detect this potent combination of ingredients and offers advantages over model precipitation forecasts because it relies on mass fields instead of parameterizations. The EPI’s dynamics component incorporates modified versions of two accepted blocking criteria, designed to detect flow reversal during the relatively short duration of extreme precipitation events. The thermodynamic component utilizes standardized anomalies of equivalent potential temperature. Proof-of-concept is demonstrated using four high-impact floods: the 2013 Alberta Flood, Canada’s second costliest natural disaster on record; the 2016 western Europe Flood, which caused the worst flooding in France in a century; the 2000 southern Alpine event responsible for major flooding in Switzerland; and the catastrophic August 2016 Louisiana Flood. EPI frequency maxima are located across the North Atlantic and North Pacific mid- and high latitudes, including near the climatological subtropical jet stream, while secondary maxima are located near the Rockies and Alps. EPI accuracy is briefly assessed using pattern correlation and qualitative associations with an extreme precipitation event climatology. Results show that the EPI may provide potential benefits to flood forecasters, particularly in the 3–10-day range.