Matilde Rusticucci, Olga Penalba Assistant Researchers: Mariana Barrucand, María Laura Bettolli Post-Doc: Bárbara Tencer, Madeleine Renom, PhD Students: Federico Robledo, Natalia Zazulie, Juan Rivera, Vanesa Pántano, Gustavo Almeira Laboratorio de Extremos Climáticos de Sudamérica Departamento de Ciencias de la Atmósfera y los Océanos- FCEN- Universidad de Buenos Aires / CONICET LABORATORIO DE EXTREMOS CLIMÁTICOS EN SUDAMÉRICA

Cold Days MAX TEMP 10th perc. Warm Days MAX TEMP 90th perc. April-September October - March Cold Days MAX TEMP 10th perc. Warm Days MAX TEMP 90th perc. Barrucand, PhD thesis Extreme Temperatures ETCCDI Linear trend

TEMPORAL VARIABILITY Monthly accumulated extreme rainfall greater than 75th daily percentile. Tucumán November December Salta Annual Amount of Dry days Index DRY CONDITION WET CONDITION Penalba, Bettolli; Robledo; Rivera;. Pántano

return periods Spatial distribution of return periods HTn 25ºC LTn -5ºC HTx 40ºC LTx 6ºC Observed Changes in Return Values of Annual Temperature Extremes over Argentina Matilde Rusticucci And Bárbara Tencer Journal Of Climate Volume 2 1

GEV observed (black - - -) ERA-40 (solid black ) and GCMs. GEV ( - - -) (solid )

Covariability between daily intensity of extreme rainfall (DIER) and Sea Surface Temperature Second mode 17% (Singular Value Descomposition) DIER correlation of the second mode Austral Spring SON

De-trended annual time-series (blue) and smoothed with a 10-year running mean (red) of indices

Cold nightsCold days Warm nightsWarm days Interdecadal changes in the relationship between extreme temperature events in Uruguay and the general atmospheric circulation.Madeleine Renom, Matilde Rusticucci, Marcelo Barreiro accepted in Climate Dynamics, 2011) Summer

Regressions maps of TN10 onto, for summer SLPa vector wind at 925 hPa. vector wind at 200 hPa the negative phase of the SAM is associated with more frequent cold nights No relationship at all with the SAM.

Figure 2: The same as Figure 1 except for FD: number of days where the minimum temperature was below 0ºC Frost Days mean Models overestimate

Figure 3: The same as Figure 1 except for R10: number of days where the precipitation was over 10 mm/day. R mean Models overestimate Models underestimate

TN90 R10 CDD

TN90 R10 CDD Days %

Days % TN90 R10 CDD

Daily circulation patterns in Southern South America Daily mean sea level pressure (SLP) fields Observed Circulation Types (CT) and percentage of days corresponding to each group during austral summer. DJF 26.8% 19% highest contribution to dry days in the Pampas (blue square) highest contribution to heavy rainy days in the Pampas (blue square) CT2CT4

Evaluation of the capacity of a set of GCMs to reproduce these atmospheric structures 26.8% 19% CT2 CT4

Projected changes at different time horizons of 21th century Frequency (%) of CTs for summer for NCEP (red diamond), GCMs (circles) and ensemble of GCMs (blue diamond). 20 th Century Anomalies of the frequencies of the CTs with respect to 20 th Century in two horizons

Future plans: Evaluate the relevance of the decadal variability in the occurrence of extreme events Analyze the physical processes involved in the occurrence of extreme events Assess the ability of global models to reproduce the observed decadal variability of extreme events Contribute to greater understanding and prediction of future climate extremes. Estimate the frequency of extreme events in the coming years  Matilde Rusticucci, Olga Penalba  Assistant Researchers: Mariana Barrucand, María Laura Bettolli  Post-Doc: Bárbara Tencer, Madeleine Renom,  PhD Students: Federico Robledo, Natalia Zazulie, Juan Rivera, Vanesa Pántano, Gustavo Almeira  Laboratorio de Extremos Climáticos de Sudamérica  Departamento de Ciencias de la Atmósfera y los Océanos- FCEN-  Universidad de Buenos Aires / CONICET