1. Analysis of extreme events variability and quantification of model uncertainties
LABORATORIO DE EXTREMOS CLIMÁTICOS EN SUDAMÉRICA
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

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

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

4. Spatial distribution of return periods - 1956-2003
Observed Changes in Return Values of Annual Temperature Extremes over Argentina Matilde Rusticucci And Bárbara Tencer Journal Of Climate Volume 21
HTx 40ºC
HTn 25ºC
LTx 6ºC
LTn -5ºC
Spatial distribution of return periods

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

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

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

8. 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
Cold nights
Cold days
Warm nights
Warm days

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

10. Frost Days 1961-2000 mean Models overestimate
Figure 2: The same as Figure 1 except for FD: number of days where the minimum temperature was below 0ºC

11. R10 1961-2000 mean Models overestimate Models underestimate
Figure 3: The same as Figure 1 except for R10: number of days where the precipitation was over 10 mm/day.

12. Part 2: historical trends
TN90
R10
CDD

13. TN90 %
1960
1965
1970
1975
1980
1985
1990
1995
2000
R10
Days
1960
1965
1970
1975
1980
1985
1990
1995
2000
CDD
Days
1960
1965
1970
1975
1980
1985
1990
1995
2000

14. TN90 %
1960
1965
1970
1975
1980
1985
1990
1995
2000
R10
Days
1960
1965
1970
1975
1980
1985
1990
1995
CDD
Days
1960
1965
1970
1975
1980
1985
1990
1995
2000

15. Daily circulation patterns in Southern South America
Observed Circulation Types (CT) and percentage of days corresponding to each group during austral summer. DJF
CT2
CT4
With the`purpose to evaluate how much rainfall information for the core crop-producing region is contained in the circulation structures at regional scale.
19%
26.8%
highest contribution to heavy rainy days in the Pampas (blue square)
highest contribution to dry days in the Pampas (blue square)
Daily mean sea level pressure (SLP) fields

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

17. 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).
20th Century
Anomalies of the frequencies of the CTs
with respect to 20th Century in two horizons.

18. Estimate the frequency of extreme events in the coming years
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