Connecting Agriculture Stress Index Systems at the Sub-National Level to the Next Generation of Seasonal Climate Forecasts: A General Approach to Transition from Monitoring to Forecasting

Authors: Diego Pons*, Columbia University, Ángel G Muñoz, 1International Research Institute for Climate and Society (IRI). The Earth Institute at Columbia University, Palisades, 10964 USA, Lena Schubmann, World Food Program, Oscar Rojas, Food and Agriculture Organization FAO, Tufa Dinku, 1International Research Institute for Climate and Society (IRI). The Earth Institute at Columbia University, Palisades, 10964 USA., Carmen González, 1International Research Institute for Climate and Society (IRI). The Earth Institute at Columbia University, Palisades, 10964 USA., Amanda Grossi, 1International Research Institute for Climate and Society (IRI). The Earth Institute at Columbia University, Palisades, 10964 USA., Martin Leal, Climate Change Unit. Ministry of Agriculture, Livestock and food, Guatemala.
Topics: Hazards and Vulnerability, Climatology and Meteorology, Agricultural Geography
Keywords: Vegetation stress monitoring systems, Agricultural drought forecasting, NDVI, Food security.
Session Type: Virtual Paper
Day: 4/7/2021
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 17
Presentation File: No File Uploaded


Agriculture for food production remains a major contributor to the national economies of many developing countries. Often, these countries are characterized by agricultural landscapes dependent on rain for crop irrigation. In the face of climate variability and change, decision-making processes at both the institutional and farm level are becoming more complex. Anticipating a potential drought and the associated impacts on food production would facilitate an informed risk-management strategy in climate-vulnerable agricultural landscapes. Systems for monitoring vegetation stress around the world have been successfully implemented at different geographical scales, and are used by leading global developmental and humanitarian agencies. Yet, these systems could benefit from the incorporation of a combination of seasonal and sub-seasonal forecasts, to transition from monitoring to forecasting agricultural droughts months in advance. This approach can inform risk-management strategies at the farm and institutional level. The next generation of climate forecasts developed by the International Research Institute for Climate and Society (IRI), opens new avenues for state-of-the-art research and applied science that has the potential to transform policy-making processes, and help local governments and developmental and humanitarian agencies achieve their goals. Here w show the advantages of using a pattern-based-calibrated, multi-model ensemble, derived from the North American Multi-Model Ensemble, to forecast vegetation stress at subnational level and how this system can connect to agricultural monitoring systems worldwide. We discuss the general approach that could be used to transform the current agricultural stress monitoring systems to one incorporating forecasts at temporal and spatial scales relevant to smallholder farmers.

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