Contents

1 Climate Prediction and Agriculture: Summary and the Way Forward

1.1 Introduction 1

1.2 Predicting Climate Fluctuations and Agricultural Impacts 2

1.3 Effectiveness of Seasonal Forecasts and Climate Risk Management 3

1.4 Economics of Climate Forecast Applications 5

1.5 Assessing Adoption and Benefit 6

1.6 Building on Farmers' Knowledge 7

1.7 Way Forward 8

1.7.1 Improve the Accuracy of Prediction Models 8

1.7.2 Generate Quantitative Evidence of the Usefulness of Forecasts 9

1.7.3 Give Greater Priority to Extension and Communication 9

1.7.4 Respond to Users' Needs and Involve Them More Actively 9

1.7.5 Learn From Non-Adoption Situations 10

1.7.6 Create Better Institutional and Policy Environment 10

1.7.7 Derive Economic Benefit through Applications to

Trade and Storage 11

1.8 Conclusions 11

Acknowledgements 11

References 11

2 Climate Downscaling: Assessment of the Added Values Using Regional Climate Models

2.1 Introduction 15

2.2 Smaller Spatial Scales 16

2.3 Predictability at Smaller Spatial and Temporal Scales 19

2.4 Dynamical Downscaling Forecasts 23

2.5 Future Directions 26

2.5.1 Improved Model Physics and Parameterizations 26

2.5.2 Land Initialization 27

2.5.3 Nesting Strategy 27

2.5.4 Downscaling Forecasts - Linking Prediction and Application 27

References 27

3 Development of a Combined Crop and Climate Forecasting System for Seasonal to Decadal Predictions

T. Wheeler • A. Challinor • T. Osborne • J. Slingo 31

3.1 Rationale 31

3.2 Numerical Crop and Climate Models 31

3.3 Combining Crop and Climate Models 32

3.4 Consideration of the Forecast Skill of a

Combined Crop-Climate Modeling System 34

3.5 An Integrated Approach to Climate-Crop Modeling 35

3.6 Conclusions 39

References 39

4 Delivering Climate Forecast Products to Farmers:

Ex Post Assessment of Impacts of Climate Information on Corn Production Systems in Isabela, Philippines

F.P. Lansigan • W.L. de los Santos • J. Hansen 41

4.1 Introduction 41

4.2.1 Determining Planting Dates Recommendation for

Corn Farmers in Isabela, Philippines 42

4.2.2 Field Implementation 42

4.2.3 Data Gathering 43

4.3.1 Farmers-Cooperators' Background 44

4.3.3 Income from Corn Production 45

4.4 Conclusions 46

Acknowledgements 47

References 47

5 Seasonal Predictions and Monitoring for Sahel Region

G. Maracchi • V. Capecchi • A. Crisci • F. Piani 49

5.1 Introduction 49

5.2 Data and Methods 50

5.3 Results 51

5.4 Conclusions 53

References 55

6 Institutionalizing Climate Forecast Applications for Agriculture

6.1 Introduction 57

6.2 Institutional Proclivity and Evolution 57

6.3 Role of Demonstration Studies in Institutionalization 59

6.4 Enabling Local Institutions 59

6.5 Conclusions 60

References 61

7 Climate Applications and Agriculture:

CGIAR Efforts, Capacities and Partner Opportunities

B. I. Shapiro ■ M. Winslow ■ P. S. Traore ■ V Balaji ■ P. Cooper ■ K.P.C. Rao ■ S. Wani ■ S. Koala 63

7.1 Introduction 63

7.2 CGIAR Inter-Center Initiatives 63

7.3 Getting a Grip on Variability 64

7.4 Improving Analytical Tools for Monitoring Drought and Desertification 64

7.5 Predicting Seasonal Rainfall 65

7.6 Predicting Climate Change and Its Consequences 65

7.7 Effects of Climate Variability on Agriculture 65

7.7.1 Effects on Crops 65

7.7.2 Crop-Environment Interactions 66

7.7.3 Effects on Pests 66

7.7.4 How Climate Variability Affects People 66

7.8 Farmer Perceptions of Drought 67

7.9 Livestock and Drought 67

7.10 Drought Insurance to Help Land Users Manage

Climatic Variability 67

7.11 Information Technology for Knowledge-Sharing 68

7.12 Conclusions: Future Climate Applications in CGIAR Centers and Partnership Opportunities 68

References 69

8 Institutional Capacity Building in Developing Countries through Regional Climate Outlook Forums (RCOFs) Process

8.1 Introduction 71

8.2 Origin of the COFs 72

8.3 COF and Associated Institutional Synergies 72

8.4 Capacity Building of the National Meteorological and

Hydrological Services (NMHSs) 73

8.5 Capacity Building of Users of Climate Information 74

8.6 Capacity Building of Journalist Institutions 74

8.7 Improving Regional and National Scientific and

Climate Research Capability 75

8.8 Institutional Challenges 75

8.9 Technical Challenges 76

8.10 Conclusions and Recommendations 76

References 77

9 Use of ENSO-Driven Climatic Information for Optimum Irrigation under Drought Conditions: Preliminary Assessment Based on Model Results for the Maipo River Basin, Chile

9.1 Introduction 79

9.2 Climate Variability and Agricultural Systems 80

9.3 Methodological Framework 82

9.4 Results and Discussion 85

Acknowledgements 87

References 87

10 Towards the Development of a Spatial Decision Support System (SDSS) for the Application of Climate Forecasts in Uruguayan Rice Production Sector

10.1 Introduction 89

10.2 Materials and Methods 89

10.3 Results and Discussion 90

10.3.1 ENSO Effects on Uruguayan Rice Production 90

10.3.2 Spatial Variability 91

10.3.3 Temporal Variability 94

10.3.4 Spatiotemporal Variability 94

10.4 Conclusions 95

References 97

11 Assessing the Use of Seasonal-Climate Forecasts to Support Farmers in the Andean Highlands

11.1 Introduction 99

11.2 Data and Methods 99

11.2.1 Study Area 99

11.2.2 Field Survey 100

11.2.3 Sea Surface Temperature Data 101

11.2.4 Spatial and Temporal Downscaling 101

11.2.5 Geospatial Modeling 102

11.3 Results and Discussion 103

11.3.1 Field Survey 103

11.3.2 Spatial and Temporal Downscaling 103

11.3.3 Geospatial Modeling 105

11.4 Conclusions 109

Acknowledgements 109

References 109

12 Application of Seasonal Climate Forecasts for Sustainable Agricultural Production in Telangana Subdivision of Andhra Pradesh, India

K. K. Singh ■ D. R. Reddy ■ S. Kaushik ■ L. S. Rathore ■ J. Hansen ■ G. Sreenivas 111

12.1 Introduction 111

12.2 Methods 112

12.2.1 Description of Key Sites 112

12.2.3 GCM Predictor Selection and Rainfall Hindcasts 113

12.2.4 Stochastic Disaggregation of Monthly Rainfall 114

12.2.5 Crop Simulation and CERES Models 114

12.2.6 Management Strategies Considered 115

12.3 Results and Discussion 118

12.3.1 Rainfall and Crop Yield Analysis 118

12.3.2 Hindcast of Rainfall 120

12.3.3 Crop Yield Simulation with Actual and Hindcast Rainfall 122

12.3.4 Farmers Perceptions 125

12.4 Conclusions 126

Acknowledgements 126

References 127

13 Localized Climate Forecasting System: Seasonal Climate and Weather Prediction for Farm-Level Decision-Making

R. Rengalakshmi 129

13.1 Introduction 129

13.2 Study Area 129

13.3 Methodology 130

13.4 Results and Discussion 131

13.5 Preliminary Conclusions 133

Acknowledgements 134

14 Use of Sea Surface Temperature for Predicting Optimum Planting Window for Potato at Pengalengan, West Java, Indonesia

14.1 Introduction 135

14.2 Methodology 136

14.3 Results and Discussion 137

Acknowledgements 140

References 140

15 Climate Forecast for Better Water Management in Agriculture: A Case Study for Southern India

15.1 Introduction 143

15.2 Description of the Study Area 143

15.3 Farm and Farmers Characteristics 144

15.4 ENSO Response Analysis 146

15.5 Spatiotemporal Variability in Water Table Levels 147

15.6 ENSO, Rainfall and PET 147

15.7 Crop Evapotranspiration and Irrigation Requirement 148

15.7.1 Maize 148

15.7.2 Cropping Systems 149

15.7.3 Crop Area Decisions Based on ENSO Phases 150

15.8 Conclusions 154

Acknowledgements 155

References 155

16 Linking Corn Production, Climate Information and Farm-Level Decision-Making: A Case Study in Isabela, Philippines

W. L. de los Santos • F.P. Lansigan • J. Hansen 157

16.1 Introduction 157

16.2 Methodology 158

16.2.1 Case Study Sites 158

16.2.2 Data Collection 159

16.3 Results and Discussion 159

16.3.1 The Impact of Climate Variability on Corn Production 159

16.3.2 Climate-Related Information Currently Accessible in Isabela 161

16.3.3 Impact of Seasonal Climate Forecast Information on Decision-Making 161

16.3.4 Forecast Information of Greatest Value to Corn Production 162

16.3.5 Effective Medium for Communicating

Climate Forecast Information 162

16.4 Summary and Conclusions 163

Acknowledgements 164

References 164

17 Use of ENSO-Based Seasonal Rainfall Forecasting for Informed Cropping Decisions by Farmers in the SAT India

V. Nageswara Rao • P. Singh • J. Hansen • T. Giridhara Krishna • S. K. Krishna Murthy 165

17.1 Introduction 165

17.2 Advances in Seasonal Climate Forecasting 165

17.3 Advances in Crop Modeling 166

17.4 Overall Objective 166

17.5 Specific Objectives 166

17.6 Study Area 167

17.7 Approach 168

17.7.1 Climate Analyses and Seasonal Prediction 168

17.7.2 Crop Yield Variability in Response to ENSO Phases 171

17.7.3 Farmers' Decision Options 174

17.7.4 Simulations of Cropping Systems 175

17.7.5 Simulation Scenarios of Baseline Management 177

17.7.6 Value of Seasonal Forecasting Skill 177

17.8 Results and Discussion 178

17.9 Conclusions 179

References 179

18 Application of Climate Prediction for Rice Production in the Mekong River Delta (Vietnam)

Nguyen T. Hien Thuan • Luong V. Viet • Nguyen T. Phuong • Le T. X. Lan • Nguyen D. Phu 181

18.1 Introduction 181

18.2 Data and Methodology 182

18.2.1 Weather Data 183

18.2.3 Soil Data 183

18.3 Results 183

18.3.1 Relationship between ENSO Indices and

Temperature and Rainfall 183

18.3.2 Field Surveys 183

18.3.3 Forecast Information for Dissemination to Farmers 185

18.3.4 Crop Simulation 185

18.4 Conclusions 186

Acknowledgements 187

References 187

19 Climate Prediction and Agriculture: What Is Different about Sudano-Sahelian West Africa?

P. C. S. Traoré • M. Kouressy • M Vaksmann • R. Tabo • I. Maikano • S. B. Traoré • P. Cooper 189

19.1 Introduction 189

19.2 The Context: Distinctive Climate Variability 189

19.2.1 A Variety of Forcings 189

19.2.2 The Problem: A Notoriously Unpredictable Growing Season 191

19.2.3 What are the Options in the Face of Climate Variability? 193

19.3 Forecasts for Smallholder Food Security: Which Way Forward? 194

19.3.2 Develop Dynamic Land Surface Schemes in

Climate Models (Long-Term) 195

19.3.3 Adapt Crop Models (Short-Term) 195

19.3.4 Apply GIS and Crop Models to Target Breeding

Strategies (Medium-Term) 195

19.3.5 Revisit Early Crop Yield Assessment

Techniques (Medium-Term) 198

19.4 Conclusions 198

References 200

20 Can ENSO Help in Agricultural Decision-Making in Ghana?

S. G. K. Adiku • F. D. Mawunya • J. W. Jones • M. Yangyouru 205

20.1 Introduction 205

20.2 Materials and Methods 206

20.2.2 Data Sources and Analysis 206

20.3 Results and Discussion 207

20.3.1 Rainfall Analyses 207

20.4 General Discussion 210

20.5 Conclusions 210

Acknowledgements 211

References 211

21 Application of Seasonal Climate Forecasts to Predict

Regional Scale Crop Yields in South Africa

21.1 Introduction 213

21.2 Study Area and Methodology 214

21.2.1 Crop Yield Model 214

21.2.2 Study Area 214

21.2.3 Climate Forecasts and Downscaling 214

21.2.4 Crop Yield Simulations Performed 216

21.2.5 Crop Model Inputs 218

21.3 Results 219

21.4 Discussion and Recommendations 220

Acknowledgements 223

References 223

22 Climate Information for Food Security:

Responding to User's Climate Information Needs

22.1 Introduction

22.2 Methodology 225

22.2.1 Survey Sites 226

22.2.2 Field Surveys 226

22.2.3 Weather Station Data 227

22.3 Results 229

22.3.1 Characteristics of Survey Areas 229

22.3.2 Crop and Livestock Production Systems 229

22.3.3 Rainfall Seasons in the Survey Areas 230

22.3.4 Production Problems 230

22.3.5 Indigenous Rainfall Indicators 232

22.4 Summary Findings for Wakiso Survey 238

22.5 Statistical Validation of Farmers' Knowledge 238

22.5.1 Onset Dates of 1st Wet Season 238

22.5.2 Correlation of Rainfall Onset Dates with

Maximum Temperatures 239

22.6 Regression Models Derived from the Relationships 241

22.6.1 Masindi District 241

22.6.2 Wakiso District 241

22.6.3 Jinja District 243

22.6.4 Tororo District 244

22.7 Discussion 244

22.7.1 Weather and Climate Knowledge Systems 244

22.7.2 Outputs from Knowledge-Sharing 245

22.7.3 Farmers' Use of Local Forecasts 245

22.8 Conclusions 246

References 246

Appendix 247

23 Improving Applications in Agriculture of ENSO-Based Seasonal Rainfall Forecasts Considering Atlantic Ocean Surface Temperatures

G. O. Magrin ■ M. I. Travasso ■ W. E. Baethgen ■ R. T. Boca 249

23.1 Introduction 249

23.2 Methods 250

23.3 Results 250

23.4 Conclusions 256

References 256

24 AGRIDEMA: An EU-Funded Effort to Promote the Use of Climate and Crop Simulation Models in Agricultural Decision-Making

24.1 Introduction 259

24.2 AGRIDEMA Description 260

24.3 AGRIDEMA Current Status 263

References 263

25 Web-Based System to True-Forecast Disease Epidemics -Case Study for Fusarium Head Blight of Wheat

J. M. C. Fernandes ■ E. M. Del Ponte ■ W Pavan ■ G. R. Cunha 265

25.1 Introduction 265

25.2 Material and Methods 266

25.3 Results and Discussion 267

Acknowledgements 270

References 270

26 Climate-Based Agricultural Risk Management Tools for Florida, Georgia and Alabama, USA

G. Hoogenboom ■ C. W. Fraisse ■ J. W. Jones ■ K. T. Ingram ■ J. O'Brien ■ J. G. Bellow ■

D. Zierden ■ D. E. Stooksbury ■ J. O. Paz ■ A. Garcia y Garcia ■ L. C. Guerra ■

D. Letson ■ N. E. Breuer ■ V. E. Cabrera ■ L. U. Hatch ■ C. Roncoli 273

26.1 Introduction 273

26.2 Methodology 274

26.3 Information Dissemination 275

26.4 Evaluation and Impact Assessment 278

Acknowledgements 278

27 Climate Prediction and Agriculture: Lessons Learned and Future Challenges from an Agricultural Development Perspective

27.1 Introduction 279

27.2 Need for the Assessment of the Value of Climate Forecasts 279

27.3 Climate Predictions and Risk Management 281

27.4 Climate Policy and Climate Predictions 282

References 282

28 Conclusions and Recommendations

28.1 Conclusions 285

28.2 Recommendations 285

28.2.1 Science 285

28.2.2 Capacity Building, Network Development and

Institutional Partnership 287

28.2.3 Other Recommendations 288

Subject Index 289

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