An analog model for detecting the occurrence of extreme precipitation events in southeastern South America from synoptic-scale patterns

Abstract

This study is focused on the development, implementation and evaluation of an analog model designed to detect theoccurrence of extreme precipitation events in southeastern South America based on the associated prevailing synopticscale conditions. The approach is based on the use of synoptic patterns that allow the identification of different large-scaleatmospheric conditions associated with local-scale extreme precipitation events. Synoptic patterns were identified afterapplying a principal component analysis to the 850 hPa geopotential height for extreme precipitation days using ERA5reanalysis over the period 1979–2013. Two detection criteria were applied to the daily standardized anomaly circula-tion fields to identify an extreme precipitation day. One is based on the spatial correlation coefficient between the dailystandardized anomaly fields and the circulation patterns. The other is the consistency, over a selected region, of the signof several meteorological variable anomalies and the sign of the anomalous patterns identified. The model captures thenumber of observed events and the observed interannual variations in the seasonal frequency of extreme precipitationevents. This methodology also allowed understanding the mechanisms leading to higher or lower frequency of extremeprecipitation events at the interannual timescales.