Matilde Rusticucci, Olga Penalba Assistant Researchers: Mariana Barrucand, María Laura Bettolli Post-Doc: Bárbara Tencer, Madeleine Renom, PhD Students:

Matilde Rusticucci, Olga Penalba

Assistant Researchers: Mariana Barrucand, María Laura BettolliPost-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

TX10

NOVIEMBRE

TX10

DICIEMBRE

TX10

ENERO

TX10

FEBRERO

TX10

MARZO

TX10

OCTUBRE

DIA

S F

RIO

S

TX90

TX90

TX90

TX90

TX90

TX90

DÍA

S C

ÁL

IDO

S

TX10

MAYO

TX10

JUNIO

TX10

JULIO

TX10

AGOSTO

TX10

SETIEMBRE

TX10

ABRIL

DIA

S F

RIO

S

TX90

TX90

TX90

TX90

TX90

TX90

DIA

S C

AL

IDO

S

Cold DaysMAX TEMP 10th perc.

Warm DaysMAX TEMP 90th perc.

April-September

October - March

Cold DaysMAX TEMP 10th perc.

Warm DaysMAX TEMP 90th perc.

Barrucand, PhD thesis

Extreme Temperatures

ETCCDILinear trend 1959-

2003

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

1 to 5 5 to 10 10 to 50 50 to 100 100 to 4000000> 100 years




Spatial distribution of return return periodsperiods - 1956-2003

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 21

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

GEV 1981-1999( - - -) 2010-2040(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

-70 -60

-50

-40

-30

SVD 2 17%

0.35 to 1 0.26 to 0.35 0.2 to 0.26 0.01 to 0.2 -0.01 to 0.01 -0.2 to -0.01 -0.26 to -0.2 -0.35 to -0.26 -1 to -0.35

Austral Spring SON

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

1946-1975 1976-2005 1946-1975 1976-2005

Cold nights Cold days

Warm nights Warm 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.

1949-1975 1976-2003

SLPa

vector wind at 925 hPa.

vector wind at 200 hPa

the negative phase of the SAM is associated with more frequent cold

nightsNo 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

1961-2000 mean

Models overestimate

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

R10

1961-2000 mean

Models overestimate

Models underestimate

1960 1965 1970 1975 1980 1985 1990 1995 20000

5

10

15

20

25

%

SE Regional Mean for tn90

StationsKrigedStations

MIROC

GFDL0

GFDLCCSM

CNRM

INM

MIRMEDPCM

1960 1965 1970 1975 1980 1985 1990 1995 200010

15

20

25

30

35

40

45

50

55

60

Days

SE Regional Mean for r10


MIROC

GFDL0

GFDLCCSM

CNRM

INM

MIRMEDPCM

1960 1965 1970 1975 1980 1985 1990 1995 20000

10

20

30

40

50

60

70

Days

SE Regional Mean for cdd

StationsKriged

Stations

MIROC

GFDL0

GFDL

CCSM

CNRM

INM

MIRMED

PCM

TN90

R10

CDD

1960 1965 1970 1975 1980 1985 1990 1995 20004

6

8

10

12

14

16

18

20

22%

Caixa2 Regional Mean for tn90


MIROC

GFDL0

GFDLCCSM

CNRM

INM

MIRMEDPCM

1960 1965 1970 1975 1980 1985 1990 1995 200010

15

20

25

30

35

40

45

50

55

60

Days

Caixa2 Regional Mean for r10


MIROC

GFDL0

GFDLCCSM

CNRM

INM

MIRMEDPCM

1960 1965 1970 1975 1980 1985 1990 1995 20000

20

40

60

80

100

120

140

Days

Caixa2 Regional Mean for cdd


MIROC

GFDL0

GFDLCCSM

CNRM

INM

MIRMEDPCM

TN90

R10

CDD

Day

sD

ays

%

1990 1995 2000198519801975197019651960

1990 1995 2000198519801975197019651960

1990 1995 2000198519801975197019651960

1960 1965 1970 1975 1980 1985 1990 1995 200010

20

30

40

50

60

70

80

Days

Caixa3 Regional Mean for r10


MIROC

GFDL0

GFDLCCSM

CNRM

INM

MIRMEDPCM

1960 1965 1970 1975 1980 1985 1990 1995 20000

10

20

30

40

50

60

70

80

90

Days

Caixa3 Regional Mean for cdd

StationsKriged

Stations

MIROC

GFDL0

GFDL

CCSM

CNRM

INM

MIRMED

PCM

1960 1965 1970 1975 1980 1985 1990 1995 20002

4

6

8

10

12

14

16

18

20

22

%

Caixa3 Regional Mean for tn90

StationsKriged

Stations

MIROC

GFDL0

GFDL

CCSM

CNRM

INM

MIRMED

PCM

Day

sD

ays

%TN90

R10

CDD

1990 1995 2000198519801975197019651960

1990 1995198519801975197019651960

1990 1995 2000198519801975197019651960

Daily circulation patterns in Southern South America

Daily mean sea level pressure (SLP) fields. 1979-1999.

Observed Circulation Types (CT) and percentage of days corresponding to each group during austral summer. DJF

-90 -85 -80 -75 -70 -65 -60 -55 -50 -45

Longitude

-60

-55

-50

-45

-40

-35

-30

-25

-20

-15

Latit

ude

26.8%-90 -85 -80 -75 -70 -65 -60 -55 -50 -45

Longitude

-60

-55

-50

-45

-40

-35

-30

-25

-20

-15

Latit

ude

19%

highest contribution to dry days in the Pampas (blue square)

highest contribution to heavy rainy days in the Pampas (blue square)

CT2 CT4

Evaluation of the capacity of a set of GCMs to reproduce these atmospheric structures

500

1000

0

400

0

800

0

1200

1

0.99

0.95

0.9

0.8

0.7

0.6

0.50.4

0.30.20.10

Sta

ndar

d D

evia

tion

Co

rr

el

at

io

n

RM

S

D

CT 2

Ref

AB

CDE

F

GH

I JK

L

GCMs LetterBCCR-BCM2.0 A

CNRM-CM3 BCSIRO-Mk3.0 C

ECHAM5MPI-OM DEGMAM E

GFDL-CM2.0 FGFDL-CM2.1 G

GISS-EH HGISS-ER I

INGV-SXG JIPSL-CM4 K

UKMO-HadCM3 L

-90 -85 -80 -75 -70 -65 -60 -55 -50 -45

Longitude

-60

-55

-50

-45

-40

-35

-30

-25

-20

-15

Latit

ude

26.8%

-90 -85 -80 -75 -70 -65 -60 -55 -50 -45

Longitude

-60

-55

-50

-45

-40

-35

-30

-25

-20

-15

Latit

ude

19%

500

1000

0

400

0

800

0

1200

1

0.99

0.95

0.9

0.8

0.7

0.6

0.50.4

0.30.20.10

Sta

ndar

d D

evia

tion

Co

rr

el

at

io

n

RM

S

D

CT 4

Ref

AB

CDE

F

GH

IJ

KL

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).

0

5

10

15

20

25

30

35

40

45

50

CT1s CT2s CT3s CT4s CT5s

Fre

qu

en

cy

(%

)

20th Century

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

2046-2065

2081-2099

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

Documents

Matilde Rusticucci, Olga Penalba Assistant Researchers: Mariana Barrucand, María Laura Bettolli Post-Doc: Bárbara Tencer, Madeleine Renom, PhD Students: