Advanced Institute on Advanced Institute on Climatic Variability and Climatic Variability and

Food SecurityFood Security

Synthesis ReportSynthesis Report

Objectives of The InstituteObjectives of The Institute

MOTIVATIONMOTIVATION Climate variability affects people. Climate variability affects people. There are opportunities to take advantage of There are opportunities to take advantage of

the knowledge generated by different the knowledge generated by different disciplines:disciplines:• Climate Science Climate Science • Agricultural Science Agricultural Science • Socioeconomic science Socioeconomic science

The goal is to generate new knowledge and The goal is to generate new knowledge and serve the needs of the people affectedserve the needs of the people affected

Objectives of The InstituteObjectives of The Institute

STRATEGYSTRATEGY An effective action over highly complex An effective action over highly complex

systems calls for multidisciplinary worksystems calls for multidisciplinary work But it is also necessary to have people trained But it is also necessary to have people trained

to facilitate communication among disciplines to facilitate communication among disciplines and to carry out integrated research. and to carry out integrated research.

Holistic view of the systemHolistic view of the system

Training PhaseTraining Phase Scientific basis of climatic predictabilityScientific basis of climatic predictability

ENSOENSO Downscaling Downscaling

Translating climate variability into yield Translating climate variability into yield outcomesoutcomes Crop ModelingCrop Modeling

Undestanding decission makers needs and Undestanding decission makers needs and perceptionsperceptions Socioeconomic approachSocioeconomic approach

Identify cuantitative indicators of performanceIdentify cuantitative indicators of performance Constraints of the systemConstraints of the system

Training PhaseTraining Phase

Iterative process. Iterative process. Lessos learned Lessos learned Opportunities Opportunities Achivements.Achivements.

Consistent improvements towards a main Consistent improvements towards a main goalgoal

Research Projects.Research Projects.

Samuel Adiku (Ghana)Samuel Adiku (Ghana)

““Operationalizing ENSO-based climate forecasts for Operationalizing ENSO-based climate forecasts for Agricultural Planning in Ghana”Agricultural Planning in Ghana” Investigate tele-connections between OND ENSO Investigate tele-connections between OND ENSO

and rainfall at nine farming zones.and rainfall at nine farming zones. Demonstrate the impact of ENSO on crop yields via Demonstrate the impact of ENSO on crop yields via

crop modeling and explore management practices.crop modeling and explore management practices. Develop a framework for operationalizing ENSO-Develop a framework for operationalizing ENSO-

based seasonal forecast.based seasonal forecast. ENSO impact on seasonal rainfall was significant ENSO impact on seasonal rainfall was significant Short duration varieties were found to be more Short duration varieties were found to be more

productive in zones with ENSO footprint productive in zones with ENSO footprint

Pierre Sibiry Traore (Mali)Pierre Sibiry Traore (Mali)

““Seasonal forecasting and climate risk in the Sudano-Seasonal forecasting and climate risk in the Sudano-Sahelian zone: Progress towards new opportunities for Sahelian zone: Progress towards new opportunities for improving sorghum varieties”improving sorghum varieties” Translating climate forecasts into enhanced food Translating climate forecasts into enhanced food

security in the Sahelsecurity in the Sahel DSSAT family of cropping systems was improved to DSSAT family of cropping systems was improved to

simulate sorghum and millet phenology and growthsimulate sorghum and millet phenology and growth Seasonal IRI probabilistic forecasts were evaluated Seasonal IRI probabilistic forecasts were evaluated

against station and satellite dataagainst station and satellite data Dynamic satellite time series were assembled to Dynamic satellite time series were assembled to

evaluate cotton growing beltevaluate cotton growing belt

Trevor Lumsden (South Africa)Trevor Lumsden (South Africa)

““Application of seasonal climate forecasts to predict Application of seasonal climate forecasts to predict regional scale crop yields in south africa”regional scale crop yields in south africa” Reserch methods to produce crop yield forecasts for Reserch methods to produce crop yield forecasts for

small scale agriculture in S.A. and evaluate quality of small scale agriculture in S.A. and evaluate quality of forecastsforecasts

Assess the potential application of crop yield Assess the potential application of crop yield forecasts to improve crop management decissionsforecasts to improve crop management decissions

Proposal submitted to carry out case studies at five sites Proposal submitted to carry out case studies at five sites where forecasts will be used to implement crop where forecasts will be used to implement crop management decisions.management decisions.

Milton Waiswa (Uganda)Milton Waiswa (Uganda)

““Providing farmers with needed climatic information Providing farmers with needed climatic information through linking indigenous and scientific climate through linking indigenous and scientific climate knowledge systems”knowledge systems” Identify (validate) how farmers traditionally use local Identify (validate) how farmers traditionally use local

temperatures and winds to forecast rainfall onset. temperatures and winds to forecast rainfall onset. Develop statistical models for forecasting rainfall Develop statistical models for forecasting rainfall

onsetonset Linkages between indigenous and scientific Linkages between indigenous and scientific

climate knowledge systemsclimate knowledge systems Models can be used to forecast the onset of Models can be used to forecast the onset of

rainfall 2-3months in advancerainfall 2-3months in advance

Kamalesh Kumar Singh (India)Kamalesh Kumar Singh (India)““Application of seasonal climate forecasts for sustainable Application of seasonal climate forecasts for sustainable

agricultural prediction in Telangana sub-division of Andhra agricultural prediction in Telangana sub-division of Andhra Pradesh, India”Pradesh, India”

Maximize crop yield through application of seasonal Maximize crop yield through application of seasonal climate forecast in agriculture for selected locations.climate forecast in agriculture for selected locations.

Generate seasonal rainfall hindcast for selected Generate seasonal rainfall hindcast for selected locations. locations.

Select sowing window for selected crops.Select sowing window for selected crops. ECHAM model showed better rainfall hindcast at ECHAM model showed better rainfall hindcast at

seasonal/sub-seasonal scaleseasonal/sub-seasonal scale Awareness was created among reserachers and end users Awareness was created among reserachers and end users

about utility and limitations of seasonal climate forecast for about utility and limitations of seasonal climate forecast for application in agricultureapplication in agriculture

Rengalakshmi Raj (India)Rengalakshmi Raj (India)

““Localized Climate Forecasting System: Seasonal Climate Localized Climate Forecasting System: Seasonal Climate and Weather Prediction for Farm Level Decision Making”and Weather Prediction for Farm Level Decision Making” Study seasonal climate variations, traditional farmers Study seasonal climate variations, traditional farmers

knowledge and coping strategiesknowledge and coping strategies Translate forecast information into farmer friendly Translate forecast information into farmer friendly

versions for its practical use in livelihood enhancementversions for its practical use in livelihood enhancement Framework for farmer friendly localized forecasting systemFramework for farmer friendly localized forecasting system Social stratification of knowledge was documentedSocial stratification of knowledge was documented Special program on “climate, adaptation and vulnerability” Special program on “climate, adaptation and vulnerability”

was evolved was evolved

Rizaldi Boer (Indonesia)Rizaldi Boer (Indonesia)

““Reducing climate risk in Chili and Potato production at Reducing climate risk in Chili and Potato production at Pengalengan District, West Java”Pengalengan District, West Java” Study relations between climate forcing factors Study relations between climate forcing factors

and rainfall variabilityand rainfall variability Evaluate use of CFF for planting strategy designEvaluate use of CFF for planting strategy design Develop models for optimum planting date and Develop models for optimum planting date and

crop yields based on CFF indicescrop yields based on CFF indices Rainfall variability was influenced not only by ENSO Rainfall variability was influenced not only by ENSO

but also by Indian Dipole Modebut also by Indian Dipole Mode SOI and DMI can be used to predict optimum SOI and DMI can be used to predict optimum

planting date and yieldplanting date and yield Follow up project has been developed and submitted Follow up project has been developed and submitted

Ramasamy Selvaraju (India)Ramasamy Selvaraju (India)

““Improving Food Security and Resource Use of Irrigated Improving Food Security and Resource Use of Irrigated Crop Production Systems through Climate Forecasts in Crop Production Systems through Climate Forecasts in Southern India”Southern India” Assess and manage the impact of climate variability on Assess and manage the impact of climate variability on

the irrigated crop production systems to improve the irrigated crop production systems to improve smallholder food security in a highly vulnerable semi-smallholder food security in a highly vulnerable semi-arid India.arid India.

Quantify the impact of ENSO on water availability and Quantify the impact of ENSO on water availability and on crop yield through system simulation approacheson crop yield through system simulation approaches

A generic water allocation crop choice framework A generic water allocation crop choice framework prototype was developed for the case study region prototype was developed for the case study region incorporating ENSO information.incorporating ENSO information.

Felino Lansigan (Philippines)Felino Lansigan (Philippines)

““Delivering climate forecasts products to farmers: Delivering climate forecasts products to farmers: Agronomic and economic impacts of advanced climate Agronomic and economic impacts of advanced climate information on corn production systems in Isabela, information on corn production systems in Isabela, Philippines”Philippines” Determine perceptions and linkages of climate Determine perceptions and linkages of climate

information with crop production systemsinformation with crop production systems Evaluate agronomic and economic impacts of Evaluate agronomic and economic impacts of

advanced information on corn productionadvanced information on corn production Use of climate information to determine planting date has Use of climate information to determine planting date has

resulted in higher yields and higher net incomesresulted in higher yields and higher net incomes Department of agriculture is now funding the Department of agriculture is now funding the

development of a crop forecasting systemdevelopment of a crop forecasting system

Nageswara Rao (India)Nageswara Rao (India)

““Farmers’ Participatory Approach to Manage Climate Variability”Farmers’ Participatory Approach to Manage Climate Variability” Provide seasonal climate Prediction to farmers based on Provide seasonal climate Prediction to farmers based on

coupled atmospheric General Circulation Model (GCM) coupled atmospheric General Circulation Model (GCM) output statistical (MOS) downscaling.output statistical (MOS) downscaling.

Provide forecast-based simulated crop management Provide forecast-based simulated crop management options for farmers’ choice, and evaluate the value of options for farmers’ choice, and evaluate the value of forecast to farmers with their participation.forecast to farmers with their participation.

Better Forecast skill was identified for Kurnool and Anantapur Better Forecast skill was identified for Kurnool and Anantapur districts in AP, India by stepwise regression, and ENSO phase districts in AP, India by stepwise regression, and ENSO phase relationship with rainfallrelationship with rainfall

Farmers were responsive to forecast decision options and took Farmers were responsive to forecast decision options and took up double cropping in both the districtsup double cropping in both the districts

Thuan Nguyen (Vietnam)Thuan Nguyen (Vietnam)

““Application of Climate Prediction in Rice Production in the Application of Climate Prediction in Rice Production in the Mekong River Delta (Vietnam)”Mekong River Delta (Vietnam)” Study relations between ENSO, rainfall and Study relations between ENSO, rainfall and

temperature in the regiontemperature in the region Prepare/disseminate forecasts for two selected Prepare/disseminate forecasts for two selected

districtsdistricts Perform Rice crop simulationPerform Rice crop simulation

Significant lag-time correlations between SST, SOI and Significant lag-time correlations between SST, SOI and climate variables was foundclimate variables was found

Forecast bulletins were issued and disseminated to Forecast bulletins were issued and disseminated to farmers (Climate variables + water level and salinity)farmers (Climate variables + water level and salinity)

Crop simulation is identified as useful tool for decision Crop simulation is identified as useful tool for decision making, but requires validationmaking, but requires validation

Alvaro Roel (Uruguay)Alvaro Roel (Uruguay)

““Towards the development of a Spatial Decision Support System Towards the development of a Spatial Decision Support System (SDSS) for the Application of Climate Forecasts in Uruguayan (SDSS) for the Application of Climate Forecasts in Uruguayan Rice Production Sector”Rice Production Sector” Evaluate ENSO effects on Uruguayan rice production Evaluate ENSO effects on Uruguayan rice production

systemssystems Evaluate Ceres-Rice performance in recreating temporal Evaluate Ceres-Rice performance in recreating temporal

and spatial variabilityand spatial variability Simulate rice yields under different seasonal forecasts Simulate rice yields under different seasonal forecasts

scenariosscenarios Rice yield is affected by ENSO phasesRice yield is affected by ENSO phases Ceres-Rice was able to capture spatial and temporal yield Ceres-Rice was able to capture spatial and temporal yield

variabilityvariability

Francisco Meza (Chile)Francisco Meza (Chile)

““Where and When do we need water?: Development of a Where and When do we need water?: Development of a regional crop yield and water demand model based on regional crop yield and water demand model based on Sea surface temperature forecasts”Sea surface temperature forecasts” Characterize the main components of the agricultural Characterize the main components of the agricultural

hydrological cycle hydrological cycle Assess possible crop yield outcomes of irrigated sectors Assess possible crop yield outcomes of irrigated sectors

under ENSO scenarios under drought conditionsunder ENSO scenarios under drought conditions ENSO does play a role determining evapotranspiration ENSO does play a role determining evapotranspiration

ratesrates It is possible to use climate forecasts in water resources It is possible to use climate forecasts in water resources

allocation at the farm level (Mathematical programming allocation at the farm level (Mathematical programming approach)approach)

ATI OutcomesATI Outcomes

Increase awareness about the impacts of Increase awareness about the impacts of climate variability and possibilities of climate variability and possibilities of adaptationadaptation

Contribution to scientific and technical Contribution to scientific and technical literatureliterature

Regional capacity building throughout Regional capacity building throughout farmers participation and specific farmers participation and specific workshopsworkshops

ATI network/colleagues ATI network/colleagues