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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
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AIACC Projects:
“System”Under CurrentConditions
“System”Under FutureConditions
IMPACTSADAPTATION
Future Conditions:
Include Climate Change ScenariosInclude Scenarios of Other Changes
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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
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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
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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)
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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
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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
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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
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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
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Sensitivity (ranges of +Temp, % Precip, Variability)
Pro: Range will likely cover reality
Con: Range might be too wide to be useful
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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
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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)
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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
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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
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-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
Argentinean Pampas Region Argentinean Pampas Region
Mean Values
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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
Uruguayan Pampas Region Uruguayan Pampas Region
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
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-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
Argentinean Pampas Region Argentinean Pampas Region
Mean Values
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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
Uruguayan Pampas Region Uruguayan Pampas Region
-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
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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
Argentinean Pampas Region Argentinean Pampas Region
>240% >350% >530%
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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
Argentinean Pampas Region Argentinean Pampas Region
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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 %
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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 %
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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
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Characterize Climate Changes
In the last Century to
Generate “Synthetic” Weather
Scenarios Projecting
Observed Climate Changes
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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
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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
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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)
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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
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PRECIPITACIONES del MES de OCTUBREOBSERVADAS, SUAVIZADAS y REGRESIÓN
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
Linear regression and Binomial smoothing
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PRECIPITACIONES del MES de OCTUBRESUAVIZADAS y REGRESIÓN
INIA LA ESTANZUELA 1915-2003
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)
October Rainfall in SW Uruguay
1915 - 2002
Linear regression and Binomial smoothing
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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]
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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
Number of days (histogram interval)
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
Number of days (histogram interval)
1 2 3 4 5 6 7 8 9 10
Fre
qu
ency
(d
ays)
0
50
100
150
200
250
1915-19581958-2002
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Frost Spells (<0oC) INIA-LE in JJA
Number of days (histogram interval)
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
Number of days (histogram interval)
0 1 2 3 4 5 6 7 8 9 10
Fre
qu
ency
(d
ays)
0
1
2
3
4 1915-19581958-2002
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Hot Spells (>30oC) INIA-LE in DJF
Number of days (histogram interval)
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
Number of days (histogram interval)
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
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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
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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
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Climate Scenarios
GCM outputs (based on IPCC SRES)
Sensitivity (ranges of +Temp, % Precip, Variability)
Project changes in the future considering changes in the last century
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(daily data)(daily data)
Crop/Pasture Crop/Pasture Models Models
Climatic ScenariosClimatic Scenarios
Past ChangesPast ChangesGCM GCM Sensitivity analysys Sensitivity analysys
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