climate change scenarios in the subclimate change ... · 12/4/2009  · climate change drivers 7500...

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 (santiago.cuadra@embrapa.br)

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)

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5500

6500

gC.y

ear-

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1500

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3500Tg

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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 <maria.bassols@embrapa.br>Bernardo Ueno <bernardo.ueno@embrapa.br>

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 <maria.bassols@embrapa.br>Bernardo Ueno <bernardo.ueno@embrapa.br>

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 <luis.antunes@embrapa.br>Carlos Reisser Junior <carlos.reisser@embrapa.br>

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?

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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

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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?

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Average Temperature ‐ Pelotas (RS), Brazil 

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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

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FREQ – OBS (%) FREQ (%) - SINFREQ (OBS) FREQ (SIN)

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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

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0,2JAN FEV MAR ABR MAIO JUNJUL AGO SET OUT NOV DEZ

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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)

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81

a-1)

OBS Simulated

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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

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MAIO JUN JUL AGOSET OUT NOV DEZ

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ability De

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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: santiago.cuadra@embrapa.brg @ p

Phone: (53) 3275-8273