Extreme daily precipitation in southern South America: statistical characterization and circulation types using observational datasets and regional climate models

The main features of daily extreme precipitation and circulation types in southern South America (SSA) were evaluated and compared in both multiple observational datasets (rain gauges, CHIRPS, CPC and MSWEP) and simulations from four regional climate models (RCMs) driven by ERA-Interim during 1980-2010. The inter-comparison of extreme events, characterised in terms of their intensity, frequency and spatial coverage, varied across SSA showing large differences among observational datasets and RCMs and reflecting the current observational uncertainty when evaluating precipitation extremes at a daily scale. The spread between observational datasets was smaller than for the RCMs. Most of the RCMs successfully captured the spatial pattern of extreme precipitation across SSA, although RCA4 (REMO) usually underestimated (overestimated) precipitation intensities, particularly the maximum amounts in southeastern South America (SESA), where the extremes are remarkable. The synoptic circulation was described by a classification of circulation types (CTs) using Self-Organizing Maps (SOM). Specific CTs were found to significantly enhance the occurrence of extreme precipitation events in sectorized areas of SESA. The RCMs adequately reproduced the SOM node frequencies, although they tended to simplify the predominant CTs into a more reduced number of configurations. They appropriately represented the extreme precipitation frequencies conditioned by each CT, exhibiting some limitations in the location and intensity of the resulting precipitation systems. These sorts of evaluations contribute to a better understanding of the physical mechanisms responsible for extreme precipitation and of their future projections in a climate change scenario.

Automated summary

This study evaluated and compared daily extreme precipitation and circulation types in southern South America using multiple observational datasets and simulations from regional climate models during 1980-2010. The results showed differences in the intensity and spatial distribution of extreme events among observational datasets and models, highlighting the uncertainty in evaluating precipitation extremes at a daily scale.