IRI@AGU: Climate Information for Food Systems
Sourcing seeds. Planting at the right time. Using fertilizer. Harvesting crops. Storing food. Shipping food. Setting prices. There are a multitude of decisions made in the systems that bring food to people around the world, and many of these decisions can be better informed by climate information. With the goal of improving the security and stability of our food systems, IRI scientists are studying how much climate plays a role in the global food supply, identifying food system vulnerabilities in specific areas, using new kinds of climate information in agricultural modeling, and more. More below on the work IRI is presenting in this realm at this month’s AGU meeting.
Weston Anderson – Climate Variability and Global Agriculture Markets
One of your findings is that 18% of global maize production variability comes from climate variability. Can you explain what this means?
There are many things that can affect crop yields: temperature, precipitation, pests, disease, management, etc. Estimating the relative importance of each of these factors can be difficult. Our analysis looks at crop yields from 1980-2010 and calculates that in that time ENSO accounted for a little under 1/5 of global maize production variability. To provide some context, other researchers estimated that all weather (not just that related to ENSO) accounted for 30-40% of global crop yield variability, and that the rest was due to factors such as pests, disease and management.
Why is a global picture of how climate variability affects crops relevant? Isn’t it important what might be happening in a particular region, especially in terms of decisions that can be made?
Our food production system is global. More than ever before, people — including those living below the poverty line — rely on some amount of imported food to meet their nutritional needs. To ensure that people have adequate access to sufficient food, countries care about what is happening to global grain markets. These global markets are particularly reactive if crops fail across multiple regions in the same year. Our analysis suggests that ENSO may be one of the few things (aside from random chance) that can force such synchronous global crop yield anomalies.
Colin Kelley – Identifying Agriculture and Climate Vulnerabilities
You mention that you’ll talk about countries from IRI’s ACToday project. Can you explain how climate variability and agriculture vulnerability are related, using one of the ACToday countries to illustrate?
Improving rainfall forecasts on subseasonal to seasonal (S2S) timescales is crucial for many vulnerable regions and nations, including Bangladesh. Rainfall prediction at the seasonal scale can be quite challenging in Bangladesh, for a number of reasons, including its climatic and topographic diversity. Its tropical monsoon climate receives large amounts of rainfall (~80% of its annual total) from late May through early October, with very large year-to-year variability. The topography includes a large and irregular deltaic plain, high elevations, and a relatively dry zone.
During the monsoon season dramatic flood events in coastal and low-lying areas occur regularly. Bangladesh is quite vulnerable to tropical cyclones, tornadoes and flood tides, and losses of life and property often result.
The country is densely populated and many farmers reside on and cultivate land that is regularly exposed to extreme weather events. The majority of people are employed by agriculture, which accounts for roughly 70% of the total land area.
Groundwater used for drinking water and irrigation is often contaminated, resulting in the spread of water-borne disease. Water tables have fallen in some regions due to overuse of groundwater. Bangladesh also faces increasing saltwater intrusion along the coast, soil erosion and degradation, widespread insecticide use and deforestation.
These are the vulnerabilities we’re addressing in ACToday in Bangladesh. We recently held our first course as part of a new academy on climate services, working with participants from different sectors to work through the decision-making process. An example is determining what crops to plant in a given location, or when best to plant them, informed by improved weather, subseasonal and seasonal climate information and forecasts. Tailored forecasts and climate services can help manage and reduce risk. Due to the acute vulnerability present, improved forecasting of monsoonal seasonal rainfall, as well as advanced warning of extreme events within the monsoon season, continue to be a high priority for Bangladesh.
Eunjin Han – Using Climate Knowledge for Agriculture Decisions
Han presents on Wednesday morning at 9:30 in Walter E Washington Convention Center – Salon B. She is also a co-author on several more activities. Full details in the IRI@AGU schedule and in the AGU program.
As a scientist who works at the intersection of climate and agriculture, what do you think of the new potential for forecasting at the subseasonal timescale?
As IRI has been issuing seasonal climate forecast every month, we have been trying to translate seasonal forecast information to agronomic terms for better decision supports – for example, strategies for planting, fertilizer, insurance, etc. With recent advances and efforts for “seamless forecasting” from weather forecasts to seasonal climate forecasts, I am excited to see the added value of subseasonal forecasts for agricultural decision making. Crop growth can be seriously affected by weather events certain growth stages and thus reliable information on the subseasonal timescale would definitely help agricultural decision making.
What is one key takeaway from one of the case studies you’re presenting?
Adopting a seasonal or susbseasonal forecast to a crop simulation model can improve crop yield prediction and help finding suitable planting windows, but uncertainties in the forecasts should be handled with care.