The free interactive platform uses 35 years of climate and yield data to show how El Niño and La Niña conditions have affected corn, soybean, wheat, barley and sunflower production across Argentina.
Scientists from CONICET and INTA have developed AgroENSO, a free interactive web application that estimates how different phases of the El Niño–Southern Oscillation (ENSO) have affected Argentina’s major field crops.
The platform combines 35 years of climate information with official yield data for six crops: corn, first-crop soybeans, second-crop soybeans, wheat, barley and sunflower.
The project was led by CONICET researcher Juan Pablo Monzón, with contributions from INTA researchers Fernando Aramburu Merlos and Jorge Luis Mercau.
“The objective of AgroENSO is to visualize the real yields of different crops that the Ministry of Agriculture, Livestock and Fisheries reports every year, corrected for their technological trend, so that we can see them according to the El Niño phenomenon,” says Monzón, who works at the Faculty of Agricultural Sciences of the National University of Mar del Plata.
A Tool for the 2026-27 Growing Season
AgroENSO may be particularly relevant for the 2026-27 growing season as equatorial Pacific conditions remain consistent with a warm, or El Niño, phase.
Argentina’s National Meteorological Service reports a nearly 100% probability that El Niño conditions will persist during August, September and October. Projections from the U.S. National Oceanic and Atmospheric Administration indicate the phenomenon could strengthen during the final quarter of the year.
AgroENSO shows how crop responses to ENSO conditions vary geographically. It adjusts historical yields to account for improvements in technology and crop management, allowing users to compare growing seasons from different periods and better isolate yield variability associated with El Niño and La Niña, according to a press release.
Corn and Soybeans Show the Strongest Response
At the national level, ENSO’s effects are concentrated primarily in corn and soybeans. Winter crops such as wheat and barley, as well as sunflower, do not show a significant response nationally. However, those national averages conceal substantial regional differences.
Corn shows a significant climate signal in 33% of Argentina’s agricultural departments. Entre Ríos is the most sensitive province, recording an average yield deviation of 17.1% above the adjusted average during El Niño phases. The Villaguay and Tala departments recorded increases of 24% and 28%, respectively.
By contrast, the El Niño signal disappears in parts of southeastern Buenos Aires province and Argentina’s northwestern and northeastern regions.
Frequency Helps Explain Production Risk
The developers recommend examining not only average yield changes but also the frequency of above-average growing seasons, which can provide useful information for crop risk management.
National corn yields exceeded the adjusted average in 10 of the 12 El Niño seasons covered by the dataset. First-crop soybean yields were above average in 11 of those seasons.
During the 14 La Niña seasons in the historical record, however, Argentina’s national corn yield exceeded the overall average only twice.
“The tool is important to know what the impact of El Niño can be in each of the departments or regions of Argentina. In general, at the country level, with regard to the yield of summer crops, we see that there is a positive effect of El Niño and a negative impact of La Niña, but this varies according to each party in Argentina. What this tool allows is to put in numbers what the impact can be,” says Monzón.
Supporting Crop and Planting Decisions
The application’s developers caution that historical ENSO patterns should not be considered in isolation, noting that “looking at the sky without measuring the ground is half a tool.”
AgroENSO is intended to help growers refine probabilistic expectations and make field-level adjustments. Its historical climate signal can be considered alongside factors such as soil water availability at planting, water movement and a field’s position in the landscape.
The information could help producers decide when and how much corn to plant, prepare logistics for fields susceptible to flooding or determine whether ENSO conditions have historically influenced yields in their production area.
“The use of AgroENSO must be complemented, of course, with other information taken by the producer to the field, such as soil type or water content, but it allows us to have a new tool to quantify the effect of the El Niño phenomenon at the batch level,” concludes Monzón.
