Building capacity to assess the impact of climate change/variability and

Building capacity to assess the impact of Building capacity to assess the impact of climate change/variability and climate change/variability and

develop adaptive responses for the develop adaptive responses for the mixed crop/livestock production systems mixed crop/livestock production systems

in the Argentinean , Brazilian andin the Argentinean , Brazilian andUruguayan PampasUruguayan Pampas

Principal Scientists Principal Scientists

• Graciela Magrin, INTA, ArgentinaGraciela Magrin, INTA, Argentina• María I. Travasso, INTA, ArgentinaMaría I. Travasso, INTA, Argentina• Osvaldo Canziani, ArgentinaOsvaldo Canziani, Argentina

• Gilberto Cunha, BrazilGilberto Cunha, Brazil• Mauricio Fernandes, BrazilMauricio Fernandes, Brazil

• Agustin Gimenez, GRAS- INIA, UruguayAgustin Gimenez, GRAS- INIA, Uruguay• Walter E. Baethgen, IFDC, UruguayWalter E. Baethgen, IFDC, Uruguay

• Holger Meinke, APSRU, DPI, AustraliaHolger Meinke, APSRU, DPI, Australia

AIACC Projects:

“System”Under CurrentConditions

“System”Under FutureConditions

IMPACTSADAPTATION

Future Conditions:

Include Climate Change ScenariosInclude Scenarios of Other Changes

Climate ScenariosGreat uncertainty of climate change at regional

or local scales

AIACC Globally: Produce Scientific Results (e.g., IPCC’s FAR )

AIACC Regionally and Locally:

Introduce CC in the Political Agenda.(Planning and Decision Making)

Uncertainty must be “managed” to still be useful

Climate ScenariosDue to uncertainty of climate change at regional or local scales, we are considering a range of possible climates for the assessment of impacts of climate change on agricultural production including:

GCM outputs (based on IPCC SRES)

Sensitivity (ranges of +Temp, % Precip, Variability)

Project changes in the future considering changes in the last century

Generate daily data sets (for crop and pasture simulation models) IMPACTS and ADAPTATION

GCMs:1. Use Generated Climate Change Scenarios (Direct Output from GCM runs) (No)

2. Use RCM nested in GCM (hopefully)

3. Use GCM to get atmospheric variables and “generate” (e.g.) rainfall

4. Use Projected GCM Anomalies (Projected GCM – Climatology GCM) and Modify Observed Climatic Data

Evaluate GCM’s Ability to Represent CurrentConditions (Start with Climatology)

Methods for Generating Climate Change ScenariosNeeded for the Simulation Models (Crops, Pastures)

T. Max: Climatology GCM Hadley - NWS Cell 30_303.75

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7 8 9 10 11 12Month

NWS

GCM Hadley

Climatology GCM Hadley - Nat. Wth. Serv. Cell 30_303.75 (Rainfall)

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11 12

Month

DNM

GCM Hadley

Climatology GCM Hadley - Nat. Wth. Serv. Cell 32.5_303.75 (Rainfall)

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11 12

Month

DNM

GCM Hadley

Climate Scenarios

1. GCM outputs (based on IPCC SRES)

2. Sensitivity (ranges of +Temp, % Precip, Variability)

SCENARIOS are a COMBINATION of:

+1, 2 …. oC (different months)Tmax and Tmin

+/- 10, 20 …. % Rainfall (different months)

Changes in Means, Variability and Extremes


Pro: Range will likely cover reality

Con: Range might be too wide to be useful

Climate Scenarios

1. GCM outputs (based on IPCC SRES)

2. Sensitivity (ranges of +Temp, % Precip, Variability)

3. Project changes in the future considering changes in the last century

Changes inChanges in CLIMATE CLIMATE during the 20during the 20thth century century in the Argentinean and in the Argentinean and

Uruguayan Pampas RegionUruguayan Pampas Region(will add South Brazil) (will add South Brazil)

Differences in three-monthly Differences in three-monthly Precipitation Precipitation (mm) between (mm) between 1900-1930 and 1970-2000 in nine sites of the 1900-1930 and 1970-2000 in nine sites of the

Argentinean Pampas Region Argentinean Pampas Region

-30

-10

10

30

50

70

90

110

130

150

Jul-Aug-Sep

Oct-Nov-Dec

Jan-Feb-Mar

Apr-May-Jun

Jul-Aug-Sep

Oct-Nov-Dec

Jan-Feb-Mar

Apr-May-Jun

Diff

ere

nce

s in

pre

cipit

ati

on (

mm

)

Mean Values

Differences in three-monthly Differences in three-monthly Precipitation Precipitation (mm) between (mm) between 1930 and 2002 in eleven sites of the 1930 and 2002 in eleven sites of the

Uruguayan Pampas Region Uruguayan Pampas Region

-50

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9

Ch

an

ge

in R

ain

fall

(mm

)

Mean Values

JAS OND JFM AMJ JAS OND JFM AMJ

-0.3

-0.1

0.1

0.3

0.5

0.7

0.9

1.1

1.3

Jul-Aug-Sep

Oct-Nov-Dec

Jan-Feb-Mar

Apr-May-Jun

Jul-Aug-Sep

Oct-Nov-Dec

Jan-Feb-Mar

Apr-May-Jun

Diff

eren

ces

in M

inim

um

Tem

per

atu

re (

ºC)

Differences in three-monthly Differences in three-monthly Minimum TemperatureMinimum Temperature (ºC) (ºC) between 1950-1970 and 1970-2000 in nine sites of the between 1950-1970 and 1970-2000 in nine sites of the


Mean Values

Differences in three-monthly Differences in three-monthly Minimum TemperatureMinimum Temperature (ºC) (ºC) between 1915-1950 and 1950-2000 in one site of the between 1915-1950 and 1950-2000 in one site of the


0.0

0.2

0.4

0.6

0.8

1.0

1.2

0.8 1.3 1.8 2.3 2.8 3.3 3.8

Ch

ang

e in

T M

in (

oC

)

JAS OND JFM AMJ

-2

-1.8

-1.6

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

Jul-Aug-Sep

Oct-Nov-Dec

Jan-Feb-Mar

Apr-May-Jun

Jul-Aug-Sep

Oct-Nov-Dec

Jan-Feb-Mar

Apr-May-Jun

Diff

ere

nce

s in

Maxim

um

Tem

pera

ture

(ºC

)

Differences in three-monthly Differences in three-monthly Maximum TemperatureMaximum Temperature (ºC) (ºC) between 1950-1970 and 1970-2000 in nine sites of the between 1950-1970 and 1970-2000 in nine sites of the


Mean Values

Differences in three-monthly Differences in three-monthly Maximum TemperatureMaximum Temperature (ºC) (ºC) between 1915-1950 and 1950-2000 in one site of the between 1915-1950 and 1950-2000 in one site of the


-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.8 1.3 1.8 2.3 2.8 3.3 3.8

Ch

ang

e in

T M

ax (

oC

)

JAS OND JFM AMJ

0

1

2

3

4

5

6

Pig

ue

C.S

uare

Balc

arc

eVille

gas

Bolivar

Sala

dillo

Bra

gado

B. Air

es

Mean

Pig

ue

C.S

uare

Balc

arc

eVille

gas

Bolivar

Sala

dillo

Bra

gado

B. Air

es

Mean

Pig

ue

C.S

uare

Balc

arc

eVille

gas

Bolivar

Sala

dillo

Bra

gado

B. Air

es

Mean

Num

ber

of Sto

rms

1911-1970 1981-2000

>60mm >80mm >100mm

Differences in Differences in Number of StormsNumber of Storms between 1911-1970 and 1980-2000 in eigth sites of the between 1911-1970 and 1980-2000 in eigth sites of the


>240% >350% >530%

0

5

10

15

20

25

30

35

CA NJ RO MJ LA JU BB PE Mean

Fro

st F

requency

(days/

year)

-7

-6

-5

-4

-3

-2

-1

0

Fro

st inte

nsi

ty (

ºC)

Freq. 1960-70Freq. 1990-00Int. 1960-70Int. 1990-00

Changes in Changes in FROST FROST Frequency and Intensity in Frequency and Intensity in eigth sites of the eigth sites of the


ARGENTINAARGENTINA SUMMARY OF CHANGES SUMMARY OF CHANGES

ValuesValues ChangeChange Rel.ChangRel.Changee

Precip.Precip. 770-930770-930 + 160 + 160 mmmm

+ 20 %+ 20 %

StormsStorms 2.1-8.32.1-8.3 + 6 days+ 6 days + 400 %+ 400 %

T. minT. min 9.4-10.29.4-10.2 + 0.8 ºC+ 0.8 ºC + 9 %+ 9 %

T.MaxT.Max 22.9-22.122.9-22.1 - 0.8 ºC- 0.8 ºC - 4 %- 4 %

RadiatioRadiationn

16.4-15.916.4-15.9 - 0.5 Mj- 0.5 Mj - 3 %- 3 %

FrostsFrosts23.9-19.223.9-19.2 - 4.7 days- 4.7 days - 20 %- 20 %

-5.8/-4.8-5.8/-4.8 - 1 ºC - 1 ºC - 17 % - 17 %

URUGUAYURUGUAY SUMMARY OF CHANGES SUMMARY OF CHANGES (1915-1970 vs 1980-2002)(1915-1970 vs 1980-2002)

ValuesValues ChangeChange Rel.ChangRel.Changee

Precip.Precip. 1087-1087-12101210

+ 123 + 123 mmmm

+ 11 %+ 11 %

StormsStorms 3.7-3.93.7-3.9 +0.2 +0.2 daysdays

+5 %+5 %

T. minT. min 11.3-11.811.3-11.8 + 0.8 ºC+ 0.8 ºC + 4 %+ 4 %

T.MaxT.Max 21.8-21.721.8-21.7 - 0.1 ºC- 0.1 ºC - 1 %- 1 %

FrostsFrosts15.1-12.015.1-12.0 -3.0 days-3.0 days - 21 %- 21 %

-1.6/-1.3-1.6/-1.3 -0.3 ºC -0.3 ºC - 19 % - 19 %

0.0

0.5

1.0

1.5

2.0

2.5

3.0

1930 1950 1970 1990

Yie

ld (

t.ha

-1 )

Sunflower

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1930 1950 1970 1990

Yie

ld (

t.ha

-1 )

Wheat

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

1930 1950 1970 1990

Yie

ld (

t.ha

-1 )

Maize

0.0

0.5

1.0

1.5

2.0

2.5

3.0

1930 1950 1970 1990

Yie

ld (

t.ha

-1 )

Soybean

TotaTotall

ClimatClimatee

WhWh 5656 1313

SuSu 102102 1212

MzMz 110110 1818

SbSb -- 3838

Changes in Changes in Crop yieldsCrop yields During the 20During the 20thth century century

Yield increases (%) Yield increases (%) betweenbetween

1950-70 and 1970-001950-70 and 1970-00

Characterize Climate Changes

In the last Century to

Generate “Synthetic” Weather

Scenarios Projecting

Observed Climate Changes

MontMonthh

RAINRAIN WetSpeWetSpellll

DrySpelDrySpelll

TMeanTMean TRangeTRange SRADSRAD

(%)(%) (%)(%) (%)(%) (ºC)(ºC) (%)(%) MjMj

JanJan 1.61.6

1.41.4

1.01.0

1.01.0

0.70.7

1.01.0

-0.4-0.4

0.10.1

0.90.9

0.90.9

-0.8-0.8

-0.5-0.5FebFeb 1.61.6 1.01.0 0.90.9 -0.8-0.8 0.90.9 0.10.1

MarMar 1.31.3 1.01.0 0.90.9 0.70.7 0.90.9 -1.0-1.0

AprApr 1.41.4

1.31.3

1.31.3

1.01.0

1.01.0

0.90.9

0.60.6

0.30.3

0.90.9

0.90.9

0.10.1

0.00.0MayMay 1.51.5 1.01.0 0.90.9 0.10.1 0.90.9 0.00.0

JunJun 1.31.3 1.01.0 1.01.0 0.60.6 1.01.0 -0.3-0.3

JulJul 0.80.8

1.21.2

1.01.0

1.01.0

0.90.9

0.90.9

0.00.0

0.40.4

1.01.0

0.90.9

0.20.2

0.00.0AugAug 1.51.5 1.11.1 0.80.8 0.40.4 0.90.9 -0.8-0.8

SepSep 0.80.8 0.80.8 1.11.1 0.60.6 0.90.9 0.20.2

OctOct 1.01.0

1.31.3

0.90.9

1.11.1

0.90.9

0.90.9

0.90.9

0.10.1

0.90.9

0.90.9

-0.8-0.8

-0.4-0.4NovNov 1.41.4 0.80.8 0.90.9 -0.5-0.5 0.90.9 -0.8-0.8

DecDec 1.31.3 1.01.0 0.80.8 -0.3-0.3 0.90.9 -0.5-0.5

Changes in median values between Changes in median values between 1930-1960 and 1970-2000 1930-1960 and 1970-2000

LARS-WGLARS-WG

A Stochastic Wheather GeneratorA Stochastic Wheather Generatorfor use in for use in

Climate Impact Studies Climate Impact Studies

M.A. Semenov M.A. Semenov

TresArroyos

RA

IN0

20

04

00

60

08

00

La

st3

0

Syn

the

tic

Sce

na

rio

JAS

La

st3

0

Syn

the

tic

Sce

na

rio

OND

La

st3

0

Syn

the

tic

Sce

na

rio

JFM

La

st3

0

Syn

the

tic

Sce

na

rio

AMJ

SantaRosa

RA

IN0

20

04

00

60

0

La

st3

0

Syn

the

tic

Sce

na

rio

JAS

La

st3

0

Syn

the

tic

Sce

na

rio

OND

La

st3

0

Syn

the

tic

Sce

na

rio

JFM

La

st3

0

Syn

the

tic

Sce

na

rio

AMJ

Scenarios Comparison : Scenarios Comparison : Precipitation Precipitation

1- Last 30 years1- Last 30 years2- Synthetic serie 2- Synthetic serie 3- Future scenario 3- Future scenario (quarter)(quarter)

PRECIPITACIONES del MES de OCTUBREOBSERVADAS

INIA LA ESTANZUELA 1915-2003

AÑO

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

mm

/ m

es

0

50

100

150

200

250

300

350

October Rainfall in SW Uruguay

1915 - 2002

PRECIPITACIONES del MES de OCTUBREOBSERVADAS, SUAVIZADAS y REGRESIÓN


AÑO

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

mm

/ m

es

0

50

100

150

200

250

300

350


1915 - 2002

Linear regression and Binomial smoothing

PRECIPITACIONES del MES de OCTUBRESUAVIZADAS y REGRESIÓN


AÑO

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

mm

/ m

es

0

25

50

75

100

125

150

175

y = 0.74 x - 1359R2 = 0.49(7.4 mm cada 10 años)


1915 - 2002

Linear regression and Binomial smoothing

Method 2:

Characterize Changes in Statistical ParametersDuring the last Century

Use TRENDS for Generating Future Climate Scenarios

[SERIES WET and DRY] [WET and DRY series: mean and sd][DISTRIBUTIONS OF RAIN][RAIN MONTHLY max, min, N, mean and sd][MAX MONTHLY max, min, N, mean and sd][MAX DAILY max, min, N, mean and sd][MIN MONTHLY max, min, N, mean and sd][MIN DAILY max, min, N, mean and sd][SPELLS of FROST and HOT TEMPERATURE][WET MIN][WET MAX][DRY MIN][DRY MAX]

Dry Series for Site INIA-LE in MAM

Number of days (histogram interval)

0 10 20 30 40

Fre

qu

ency

(d

ays)

0

50

100

150

200

19515-19581958-2002

Dry Series for Site INIA-LE in SON


0 5 10 15 20 25 30 35 40

Fre

qu

ency

(d

ays)

0

50

100

150

1915-19581958-2002

Wet Series for Site INIA-LE in SON


1 2 3 4 5 6 7 8 9 10

Fre

qu

ency

(d

ays)

0

50

100

150

200

250

1915-19581958-2002

Frost Spells (<0oC) INIA-LE in JJA


0 1 2 3 4 5 6 7 8 9 10

Fre

qu

ency

(d

ays)

0

10

20

30

40

50

60

70

1915-19581958-2002

Frost Spells (<0oC) INIA-LE in MAM


0 1 2 3 4 5 6 7 8 9 10

Fre

qu

ency

(d

ays)

0

1

2

3

4 1915-19581958-2002

Hot Spells (>30oC) INIA-LE in DJF


0 2 4 6 8 10 12 14 16 18 20

Fre

qu

ency

(d

ays)

0

30

60

90

120

150

1915-19581958-2002

Hot Spells (>30oC) INIA-LE in SON


0 1 2 3 4 5 6 7 8 9 10F

req

uen

cy (

day

s)0

10

20

30

40

50

60

701915-19581958-2002

Maximum Monthly Rainfall in INIA-LE

Month

1 2 3 4 5 6 7 8 9 10 11 12

Rai

nfa

ll (m

m)

0

100

200

300

400

500

600

700

1915-19581958-2002

Minimum Monthly Rainfall in INIA-LE

Month

1 2 3 4 5 6 7 8 9 10 11 12R

ain

fall

(mm

)0

5

10

15

20

25

30

1915-19581958-2002

Mean Dry Series in INIA-LE

Month

1 2 3 4 5 6 7 8 9 10 11 12

Day

s

0

1

2

3

4

5

6

7

1915-19581958-2002

Mean Wet Series in INIA-LE

Month

1 2 3 4 5 6 7 8 9 10 11 12

Day

s

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

2.25

1915-19581958-2002

1. Characterize changes in statistical parameters

2. Project the trend for the next 30 years

Climate Scenarios

GCM outputs (based on IPCC SRES)


Project changes in the future considering changes in the last century

(daily data)(daily data)

Crop/Pasture Crop/Pasture Models Models

Climatic ScenariosClimatic Scenarios

Past ChangesPast ChangesGCM GCM Sensitivity analysys Sensitivity analysys

Documents

Building capacity to assess the impact of climate change/variability and