Climate Variability and Climate Change: Decision Making under Uncertainty
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Climate Variability and Climate Change: Decision Making under Uncertainty Gerrit Hoogenboom Director, AgWeatherNet & Professor of Agrometeorology Washington State University, USA AgMIP–Pakistan Kickoff Workshop & International Seminar on Climate Change University of Agriculture Faisalabad, Pakistan June 4-6, 2013
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Climate Variability and Climate Change: Decision Making under Uncertainty. Gerrit Hoogenboom Director, AgWeatherNet & Professor of Agrometeorology Washington State University, USA. AgMIP –Pakistan Kickoff Workshop & International Seminar on Climate Change - PowerPoint PPT Presentation
Transcript of Climate Variability and Climate Change: Decision Making under Uncertainty
Climate Variability and Climate Change: Decision Making under Uncertainty
Gerrit HoogenboomDirector, AgWeatherNet &
Professor of AgrometeorologyWashington State University, USA
AgMIP–Pakistan Kickoff Workshop &International Seminar on Climate Change
University of Agriculture Faisalabad, PakistanJune 4-6, 2013
4,000 km
Winter OutlookWeather and Agriculture
• Weather has an important impact on agriculture, both crop and animal production.
• For dryland agriculture more than 90% of the variability in yield can be explained by weather conditions.
Winter OutlookClimate and Weather
• Does a farmer have options to modify or change his production system?
• If so, what are these options?• Can weather and climate information play a
role?• How do we provide this information?
National Weather Service
• Cooperative Weather Station Network– Volunteer data collection network– Limited set of data (temperature and rainfall)– Approximately 85 stations in Georgia– Long-term records– Data collected at Griffin Experiment Station since 1926
Georgia Automated Environmental Monitoring Network
First weather station was installed in 1991
Air temperature, rainfall, relative humidity, wind speed and direction, solar radiation, soil moisture
Georgia Automated Environmental Monitoring Network
Weather StationWeather Station
Web ServerWeb Server
SatelliteSatellite
FTP FTP
TransferTransfer
Weather ServerWeather Server
InternetInternet
Current ConditionsCurrent Conditions
Climate DataClimate Data
Water BalanceWater Balance
Crop ModelingCrop Modeling
www.Georgiaweather.net
Winter OutlookWind Machines & Frost
Weather Data and Applications
Climate in the southeastern USAWhy should farmers care?
Climate Variability and Climate Change
Climate Variability2-3 months
Inter-annual
Decadal
Climate ChangeSeveral decades
50+ years
Centuries
Changing Ocean Temperatures
Impacts the climateacross the globe
El Niño and La Niña• El Niño: above-average
sea-surface temperatures that develop across the east-central equatorial Pacific.
• La Niña: cold phase
Why are El Niño and La Niña important?
Effects of El Niño
Why are El Niño and La Niña important?
Effects of La Niña
El Niño, La Niña and Neutral Phases
Climate in the southeastern USAWhy should farmers care?
Deviation From the Mean
-80
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NEUTRAL LA NINA EL NINO
De
via
tion
fro
m m
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(%
)
Field observations (188 fields, 5 seasons)
ENSO and Tomato Spotted Wilt Virus (TSWV) severity in peanut
a b
* Courtesy of Dr. D. Riley, UGA
(a). Leaf symptoms of TSWV on peanut (b). Western Flower Thrips (vector)
Farmers and Climate: Why models?
• Traditional agronomic approach:– Experimental trial and error
• Systems Approach– Computer models– Experimental data
• Understand Predict Control & Manage– (H. Nix, 1983)
• Options for adaptive management and risk reduction
Soil Conditions Weather data
Model Model
Simulation Simulation
Crop Management Genetics
GrowthGrowth DevelopmentDevelopment
YieldYield
Soil Conditions Weather data
Model Model
Simulation Simulation
Crop Management Genetics
GrowthGrowth DevelopmentDevelopment
YieldYield
Net IncomeNet IncomePollutionPollution Resource UseResource Use
Linkage Between Data and Simulations
Model credibility and evaluation Input data needs:
Weather and soil dataCrop ManagementSpecific crop and cultivar informationEconomic data
Observed Yield vs. Rainfall (mm/d)
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Rainfall (mm/d)
Yie
ld (
kg/h
a)
Simulated Yield vs. Rainfall (mm/d)
0
500
1000
1500
2000
2500
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3500
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0 2 4 6 8
Rainfall (mm/d)
Yie
ld (
kg/h
a)
Observed and simulated soybean yield as a function of seasonal average rainfall (Georgia
yield trials)
Observed Yields
0500
1000150020002500300035004000
25 27 29 31 33
Max Temp Average (C)
Yie
ld (
kg/h
a)
Simulated Yields
0500
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2500300035004000
25 27 29 31 33
Max Temp Average (C)
Yie
ld (
kg/h
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Observed and simulated soybean yield as a function of average max temperature
(Georgia yield trials)
• Three representative soil profiles for each county• Soil surface data• Soil horizons
• Crop management options:– Crop selection– Variety selection– Planting date– Irrigated versus rainfed– Fertilizer applications
• Prices and production costs
Spatial DataAlabama, Florida and Georgia
Simulations: Cotton Yield Variety “DP555 BG/RR”
9 planting dates, rainfed vs irrigated38 – 107 years of daily historical weather data
-150
-100
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0
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Planting date
Rainfed
Yie
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Irrigated
El Niño
La Niña
Climate in the southeastern USAHow do farmers make decisions?
Farmers and Climate Interviews
• 38 farmers
• 21 counties in GA
• Semi-structured interviews - Risk management
strategies
- Access of weather & climate information
Farmers and Climate Risk Reducing Options
Potential Use Freq.Crop selection 23
Planting timing 16
Input management 14
Land management 13
Variety selection 11
Marketing 8
Harvesting dates 4
Insurance 3
Herd management 2
Hog lagoon mgmt. 1
Farmers and Climate Risk Reducing Options
Potential Use Freq.Crop selection 23
Planting timing 16
Input management 14
Land management 13
Variety selection 11
Marketing 8
Harvesting dates 4
Insurance 3
Herd management 2
Hog lagoon mgmt. 1
Forecast Use: Irwin CountySpring 2006 forecast for summer drought widespread shift from
long- to short-cycle peanut variety
Farmer Joe’s Questions
El NiñoLa Niña
Management Decisions• Crop selection• Variety selection• Planting dates• Acreage allocation• Irrigation• Pest management• Amount and type of crop
insurance
WWW.AGROCLIMATE.ORG
Historical weather data (1900-2005)
ENSO Phases
Planting dates
Soil types
Select AL, FL, GAcounties
Yield
Total amount of irrigation
No. of irrigationeventsCSM-CROPGRO
Peanut Model
April 16, 23May 1, 8, 15, 22, 29June 5, 12
Crop Simulations
Georgia
Crop Simulations: Research Analysis
Crop Simulations: AgroClimateExtension, Producers and Consultants
AgroClimate Tools
Interaction &Participation
Forecasts,Climatology
Web-based DSSwww.AgroClimate.org
Climate-based Management
Options
Stand aloneDecision Aid
Tools
Needs for Specific Commodities
Crop Models & Climate-based Tools
Extension Agents& Specialists
Farmers/Growers
Climate in the SoutheasternUSA: How do
farmers make decisions?
Climate Change and Climate Variability
The impact of climate change and climate variability on agricultural production and the potential for mitigation and adaptation
• Future issues can only be studied with simulation models
• “What-If” type of scenarios
Agriculture and Climate ChangeImpact and Adaptation
Camilla, Mitchell County, Georgia
Maximum and Minimum Temperature
Precipitation
Maize Yield (kg/ha) Mitchell County, Georgia, USA
4 varieties, 3 soils, rainfed and irrigatedLong-term historical weather data
Corn Yield (kg/ha) Agriculture and Climate Change
Mitchell County, Georgia, USA4 varieties, 3 soils, rainfed and irrigated
Historical weather GCM-ModifiedCSIROMK2, Scenario IS92a, 2010-2039
Agricultural Irrigation Water Demand forecast for 2011 to 2050
• University of Georgia (UGA) and the State of Georgia Environmental Protection Division
• Purpose: – Prepare forecasts of irrigation water demand
that meet the needs for the agricultural sector of the Georgia economy during the first half of this century.
Model Evaluation
• DSSAT Version 4.5• Five cropping seasons: 2000-2004• Crop Management : UGA Extension
Production Guidelines• Field specific water use data:
Agricultural Water Pumping (AWP) project
Irrigation Depth for CornMitchell County
Irrigation by Month
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S1 S2 S3 Obs
Irrigation by Year
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Year
Inch
es
S1 S2 S3 Obs
Irrigation Water Amount by Crop
Estimation of Irrigation Amounts
• Use crop models to simulate irrigation depths for multiple years
• Weather data : 1950 to 2007
• For major producing counties – 3 most important soils on which irrigation
occurs – Average planting date for county or region– Estimate daily water application; sum by
month• Corn and Cotton 88• Peanut and Soybean 66
March AprilMay
June July
Maize Monthly Irrigation Amounts
Soybean
CottonMaize
Peanut
Winter OutlookCommunication & Information
Communication & Information
Winter OutlookCell Phone Alerts
Winter OutlookWeather Insurance
• ““We like to tackle and solve some of the world’s most challenging problems,” Friedberg says, on what’s next for The Climate Corporation beyond insuring farmers, “A farmer is about as analog as it gets. To be able tell a farmer this is what’s going to happen at the end of a season, that’s mind-blowing.” TechCrunch, June 14, 2012
The Climate Corporation
Winter OutlookRainfall Insurance
Why do we need a model?
Weather/Climate and Modeling: Crop and Pest Prediction
Current Weather Weather Prediction Climate Prediction
Crop/Livestock/Pest/Disease/Irrigation Model
Bud Break Flowering Harvest Maturity
Information delivery to producers
Social scientists/agronomists/atmospheric scientists & engineers
DSSAT 2014
International Training Program on Crop
Modeling
May 19-24, 2014The University of Georgia,
Griffin, Georgia, USA
Weather conditions and weather-based decision support tools
www.weather.wsu.eduwww.georgiaweather.net
Southeast climate information and tools: www.agroclimate.org
For crop model information: www.DSSAT.net
