climate change scenarios in the subclimate change ... · 12/4/2009 · climate change drivers 7500...
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Climate change scenarios in the sub-Climate change scenarios in the subtropical Brazil: possible adaptations
th h R h d D l t fthrough Research and Development of crop germplasmp g p
Dr. Santiago Vianna Cuadra, Ph.D ([email protected])
Embrapa Temperate climate, Embrapa
EMBRAPA B ili A i lt l R h AEMBRAPA - Brazilian Agricultural Research Agency
Embrapa Temperate climate, Embrapa
Pelotas-RS (31°40’S; 52°26’W)Pelotas-RS (31 40 S; 52 26 W)
Professional preparation:
Atmospheric Science, B.S. 2003.
Atmospheric Science, M.S. 2005.
Agrometeorology, Ph.D. 2010.
Appointments
2010-2012. Associate Professor; CEFET/RJ.
2012-Present. Embrapa.
Climate ChangeClimate Change
DriversDrivers
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Carbon Emission by Fossil Fuel (red) andLand Use Change (Black)
4500
5500
6500
gC.y
ear-
1
500
1500
2500
3500Tg
-500
500
1850 1870 1890 1910 1930 1950 1970 1990Year
Climate Change - GLOBALClimate Change - GLOBAL
Evidences: Berkeley Earth TeamEvidences: ySurface Temperature trends
Climate Change - REGIONALClimate Change - REGIONAL
Evidences: •Cold nights: Percentage of days with Tmin 10th percentile %Evidences: g g y p•Warm nights: Percentage of days with Tmin 90th percentile %
Climate Change - LOCALClimate Change - LOCAL
Evidences:Evidences:» Minimum Temperature trend over Pelotas (Embrapa’s Station)
Climate Change and the AgricultureClimate change mitigation and adaptation
Climate Change and the Agriculture
Mitigation (of climate change) Adaptation
A human intervention to reduce the sources or Initiatives to reduce theA human intervention to reduce the sources or enhance the sinks of greenhouse gases (GHG).
Initiatives to reduce the vulnerability of natural and human systems against actual or expected climateactual or expected climate change effects.
Driver (Climate Change) Mitigation Adaptation
Climate Change MitigationClimate Change MitigationMitigation: Embrapa supports the “Program for Low Carbon Agriculture (ABC)”(ABC)Goals: promote the adoption of technologies that reduce GHG emissions in agriculture
Ex. No-Tillage System •Minimizes fossil fuel use•Increase soil C
Climate Change MitigationClimate Change MitigationMitigation: ex. Conventional tillage and minimum tillage technologies adopted by southern Brazilian farmerstechnologies adopted by southern Brazilian farmers.
Climate Change MitigationClimate Change MitigationMitigation: Reduce fossil fuel use
Biofuel: Ethanol & Biodiesel
•Ethanol of first generation •Ethanol of second generationSugarcane Sugarcane
Sucrose Bagasse
Rice (giant) Rice
Starch Husk/straw
Climate Change AdaptationClimate Change AdaptationResearch and Development on crop germplasm
January Annual JulyJanuary Annual July
Climate Over Brazil - Precipitation
Climate Change AdaptationClimate Change AdaptationResearch and Development on crop germplasm
January (max) Annual (avg) July (min)
Ex. Potato breeding for tropical and subtropical ecosystems of Brazil
January (max) Annual (avg) July (min)
Climate Over Brazil - Precipitation
Climate Change AdaptationClimate Change AdaptationResearch and Development on crop germplasm
Land available for agriculture expansion
140
Permanent crops Temporary cropsRangelands Pastureland
80100120140
Use
(M h
a)0
204060
Land
Year
AgricultureYear
Climate Change AdaptationClimate Change AdaptationResearch and Development on crop germplasm (Embrapa Temperate climate)
PEACH :• Low need for chilling and heat tolerance in early flowering
PEACH (greenhouses) PEACH (fungal disease)
g• Identify sources of resistance to the fungal disease (e.g., Monilinia fructicola)
PEACH (greenhouses) PEACH (fungal disease)
Contact: Maria Do Carmo Bassols Raseira <[email protected]>Bernardo Ueno <[email protected]>
Climate Change AdaptationClimate Change AdaptationResearch and Development on crop germplasm (Embrapa Temperate climate)
PEACH (greenhouses):Pistil abortion after occurrence of high
Blackberry (greenhouses) :From left to right: fruits from plants grown in the field, plants kept at 20 oC, and plants subjected
t 29 C f 10 dPistil abortion after occurrence of high temperature (Temperature > 29 oC, during
July ) at flower bud swelling stage.
to 29 oC for 10 days.
Contact: Maria Do Carmo Bassols Raseira <[email protected]>Bernardo Ueno <[email protected]>
Climate Change AdaptationClimate Change AdaptationResearch and Development on crop germplasm (Embrapa Temperate climate)
STRAWBERRY: • P
STRAWBERRY (hydroponic production in greenhouses)STRAWBERRY (hydroponic production in greenhouses)
Contact: Luis Eduardo Correa Antunes <[email protected]>Carlos Reisser Junior <[email protected]>
Climate Change AdaptationClimate Change AdaptationResearch and Development on crop germplasm (Embrapa Temperate climate)
POTATO : • Application of DNA-markers for d l t f d ht t l t t t
POTATO (greenhouses) POTATO (drought tolerance)
development of drought tolerant potato germplasm
POTATO (greenhouses) POTATO (drought tolerance)MSTT (g/plant)
Genotype Spring Fall Averag. CV (%)
Control Dry Control DryAgata 20 41b 0 62c 12 72bcd 7 41cde 10 10c 81 3Agata 20,41b 0,62c 12,72bcd 7,41cde 10,10c 81,3Ana 0,29b 0,12c 29,55a 24,95b 18,23b 114,6Atlantic 24,99ab 5,56b 8,84cd 6,08cde 10,06c 80,9Baronesa 17,54b 1,42c 7,00cd 4,31de 6,93cd 92,9C2337-06-02 0,00b 0,00c 16,72bc 12,13cde 9,62c 118,4C2360-07-02 4,64b 0,00c 34,77a 47,56a 28,22a 106,3, ,CIP388615 0,65b 0,09c 16,01bc 14,58bcd 10,32c 110,3Caesar 0,11b 0,46c 1,66d 1,98e 1,31d 86,2Clara 46,53a 10,34a 23,54ab 17,32bc 23,10ab 64,2Desiree 15,06b 0,81c 12,46bcd 9,10cde 9,83c 66,2Macaca 9,15b 2,45c 5,69cd 4,17de 5,22cd 53,1
Contact: Caroline Marques Castro; Carlos Reisser Jr.; Arione da Silva Pereira.
PCDAG 03-11 2,08b 0,35c 7,32cd 4,92de 4,48cd 83,9General Average
11,79A 1,85B 14,71A 12,88A 55,9
Climate Change AdaptationClimate Change AdaptationResearch and Development on crop germplasm (Embrapa Temperate climate)
POTATO : • Selection of germplasm with good tuber th d t b ith t d f iti
Spring/Summer field experiment POTATO (Heat Tolerance)
growth and tuber without deformities
Spring/Summer field experiment POTATO (Heat Tolerance)
ToleranceTolerance
Contact: Caroline Marques Castro; Carlos Reisser Jr.; Arione da Silva Pereira.
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5
FifthFifth Assessment Report (AR5)Report (AR5)
2013
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5Projections: New ScenariosProjections: New Scenarios Representative Concentration Pathways (RCPs)
RCP8.5 - represents the more pessimistic of the non-mitigation futures. Representative C t ti P th (RCP )Concentration Pathways (RCPs)
RCP2.6 represents the lower end of possible mitigation strategies
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5Projections: Earth system ModelsProjections: Earth system Models
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5Projections: Atmosphere Models
Not solved
Projections: Atmosphere Models
Solved
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5Projections: Model Grid ResolutionProjections: Model Grid Resolution The spatial resolution of CMIP5 coupled models will range for the atmosphere component from 0.5° to 4°
+ denotes on Grid Point with ~ 0 5o x 0 5o+ denotes on Grid Point with ~ 0.5o x 0.5o
X Denotes one Grid Point with 3.2 o lat. by 5.6 olong.
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5Projections: Regional Climate Models
May improve not only resolution but also parameterizations
Projections: Regional Climate Models
Observation
After Calibration
Before Calibration
da Rocha et al. (2012) – Climate Research.
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5IPCC (RegCM4) – Present generation Regional ClimateIPCC (RegCM4) Present generation Regional Climate Model Projections
Llopart et al. (2013) – Climatic Change special issue, submitted.
Cli t Ch T d IPCC AR5IPCC (RegCM4) – Present generation Regional Climate
Climate Change: Towards IPCC AR5IPCC (RegCM4) Present generation Regional Climate Model Projections
Cli t Ch T d IPCC AR5How important is the Precipitation Average and Standard
Climate Change: Towards IPCC AR5How important is the Precipitation Average and Standard Deviation?
250,0
th)
Monthly Prec. (SDV)
150,0
200,0
atio
n (m
m/m
t
100,0
hly
Prec
ipita
0,0
50,0
Mon
th
1 2 3 4 5 6 7 8 9 10 11 12
Months
Cli t Ch T d IPCC AR5How important is the Precipitation Average and Standard
Climate Change: Towards IPCC AR5How important is the Precipitation Average and Standard Deviation?
250,0
th)
Monthly Prec. (SDV)
150,0
200,0
atio
n (m
m/m
t
100,0
hly
Prec
ipita
0,0
50,0
Mon
th
1 2 3 4 5 6 7 8 9 10 11 12
Months
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5IPCC (CMIP5) – Present generation GLOBAL ClimateIPCC (CMIP5) Present generation GLOBAL Climate Models Projections
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5IPCC (CMIP5) – Present generation GLOBAL ClimateIPCC (CMIP5) Present generation GLOBAL Climate Models Projections
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5IPCC (CMIP5) – Present generation GLOBAL ClimateIPCC (CMIP5) Present generation GLOBAL Climate Models Projections
Cli t Ch T d IPCC AR5Climate Change: Towards IPCC AR5Should we include Standard Deviation?Should we include Standard Deviation?
0,16
0,18
unct
ion FEB JUL25
Average Temperature ‐ Pelotas (RS), Brazil
0,08
0,1
0,12
0,14
lity
Den
sity
Fu
15
20
ature (oC)
0
0,02
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Pro
babi
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Tempe
ra
0-5 -1,5 2 5,5 9 12,5 16 19,5 23 26,5 30 33,5
Temperature
0
JAN MAR MAY JUL SEPT NOV
Months
Climate: Average & VariabilityClimate: Average & Variability
How include the climate Changes (Avg. and SD.)?How include the climate Changes (Avg. and SD.)?
» Gamma distribution often provides a good fit for Precipitation
12025
FREQ – OBS (%) FREQ (%) - SINFREQ (OBS) FREQ (SIN)
80
100
15
20
uenc
y (%
)
(%)
40
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ulat
ive
Freq
u
Freq
uenc
y
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5 Cum
001 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79
Precipitation (mm/day)
Climate: Average & VariabilityClimate: Average & Variability
How include the climate Changes (Avg. and SD.)?How include the climate Changes (Avg. and SD.)?
» Normal distribution often provides a good fit for Temperature
0 6
0,2JAN FEV MAR ABR MAIO JUNJUL AGO SET OUT NOV DEZ
0,12
0,16ty Fun
ction
0,08
ability Den
si
0,04Prob
a
0
‐5 ‐1,5 2 5,5 9 12,5 16 19,5 23 26,5 30 33,5Temperature
Climate ChangeClimate Change
Models as a tool to scaling-up and test hypothesis:Models as a tool to scaling up and test hypothesis: Mitigation and Adaptation
» Biophysical Models
T i T q c
PAR, gs, ci, AnLAIupper
water snow
po
PAR, gs, ci, AnLAIlower puddle
water snow
Tair, Tleaf,qair, csoa
p
Tair, Tleaf,qair, cswater ice
puddlesnow
10 cm15 cm25 cm
50 cm
100 cm Tsoil5 θ5 θice5
Tsoil1 θ1 θice1 Tsoil2 θ2 θice2 Tsoil3 θ3 θice3 Tsoil4 θ4 θice4
200 cm
p
s
Tsoil6 θ6 θice6
Tsoil7 θ7 θ ice7 400 cm
Tsoil8 θ8 θ ice8 400 cm
Climate ChangeClimate Change
Models as a tool to scaling-up and test hypothesis:Models as a tool to scaling up and test hypothesis: Mitigation and Adaptation
» Biophysical Models: Photosynthesis
An = Ag – RdAn: net photosynthesisAg: gross photosynthesis
Ag = min (Je, Jc)
Ph h i Li i d b li h
g g p yRd: maintenance respiration
*2 Γ−= iCOPARJ α Photosynthesis Limited by light
Ph t th i Li it d b R bi
*23 2
Γ+
=i
e COPARJ α
( )⎞⎛
Γ−= im COVJ *2
Photosynthesis Limited by Rubisco
M i R bi ffi i
⎟⎟⎠
⎞⎜⎜⎝
⎛++
oci
c
KOKCO
J][ 1 2
2
STVV Maximum Rubisco efficiencyStTVV vmm max=
Climate ChangeClimate Change
Models as a tool to scaling-up and test hypothesis:Models as a tool to scaling up and test hypothesis: Mitigation and Adaptation
» Biophysical Models: Photosynthesis
Climate ChangeClimate Change
Models as a tool to scaling-up and test hypothesis:Models as a tool to scaling up and test hypothesis: Mitigation and Adaptation
» Biophysical Models: Coupling Photosynthesis and Evapotranspiration
Collatz equations (1991): Collatz equations (1991):
Leuning equation (1995):
Climate Change and the AgricultureClimate Change and the Agriculture
» Models may help to planning (scaling-up and testingMitigation (of climate change)
Driver (Climate
» Models may help to planning (scaling-up and testing scenarios) the developmento of the agriculture with lower, as possible, GHGs emissions and direct Climate ImpactsDriver (Climate
Change)Climate Impacts
MitigationMitigation
Climate ChangeClimate Change
Models as a tool to scaling-up and test hypothesis:Models as a tool to scaling up and test hypothesis: Mitigation and Adaptation
» Biophysical Models: May simulate crop
» Biophysical Models: Coupling Photosynthesis and Evapotranspiration
81
Biophysical Models: May simulate crop growth and yield (considering not only the impacts of average changes but also its distribution)
79
80
81
a-1)
OBS Simulated
76
77
78
Yiel
d (t.
ha75
Araçatuba Bauru Ribeirão Preto
S. J. do Rio Preto
Meso RegionsMeso-Regions
Cuadra et al. (2012) – Global Change Biology Bioenergy
Climate: Average & VariabilityClimate: Average & VariabilityMain recommendation
» Crop development is affected not only by the mean atmospheric conditions (average climate), but also by the frequency of extreme events such as frost, heat waves, floods, and droughts; or even recurrent conditions unfavorable to crop growth.
» Photosynthesis is not linear related with temperature
» GHG may change not only the average, but also the frequency
0,2JAN FEV MAR ABR
0,12
0,16
nsity
Fun
ction
MAIO JUN JUL AGOSET OUT NOV DEZ
0,04
0,08
Prob
ability De
0
‐5 ‐1,5 2 5,5 9 12,5 16 19,5 23 26,5 30 33,5
Temperature
Many ThanksMany Thanks.
Dr. Santiago Vianna Cuadra, Ph.D
Brazilian Agricultural Research Corporation -Embrapa, National Temperate Agriculture Research b apa, Nat o a e pe ate g cu tu e esea c
Centre, Brazile-mail: [email protected] @ p
Phone: (53) 3275-8273