Short answer
The impact of ENSO on Brazilian and Argentinian corn and soybean yields differs. For Brazil, no statistically significant national yield relationship with the Niño 3.4 tropical Pacific Ocean sea-surface temperature index is detected for soybeans, first-season corn (primeira safra), or second-season corn (safrinha). For Argentina, statistically significant positive relationships between the Niño 3.4 index and national corn and soybean yield deviations are detected. The impact of ENSO on country-level weather relationships also differs: Brazil shows its strongest national production-weighted relationship in minimum temperature, while Argentina shows a clear precipitation relationship.
Why is ENSO relevant to the 2026/27 South American crop season?
As of the September 10, 2026 update, the NOAA Climate Prediction Center says El Niño is strengthening and assigns a greater than 90% chance of a very strong event during Northern Hemisphere fall and winter 2026-27. NOAA CPC ENSO Diagnostic Discussion.
Map shows the SST anomaly (°C) from the week ending on September 9, 2026 via the World Climate Service Seasonal Weekly SST History tool.
With the South American corn and soybean season approaching, this analysis addresses what the historical record shows about ENSO, crop weather, and yield. It measures historical association, not causality, using Brazil and Argentina crop production-weighted weather indices and yield deviations from trend.
How does El Niño impact Brazil soybean weather?
The strongest January-February impact is on minimum temperature.
For Brazil soybeans production-weighted weather, the national precipitation relationship with Relative Niño 3.4 is weak. Maximum temperature has a larger relationship than precipitation in this window, but it is not statistically significant. Minimum temperature has the strongest relationship and is statistically significant.
Across the Brazilian crop-region series examined, minimum temperature is most often the strongest of the three weather relationships. A national production-weighted precipitation index alone is not representative of the weather relationships estimated in this analysis.
Why is there a weak relationship between El Niño and Brazilian Precipitation?
State-level relationships can offset one another.
The state-level Brazil soybeans production-weighted precipitation correlations in this analysis include both positive and negative values. When those relationships are combined into a national production-weighted index, opposing regional signals can reduce the national correlation.
Rio Grande do Sul and Mato Grosso illustrate a contrasting January-February precipitation/Relative Niño 3.4 relationship. A weak national relationship therefore does not mean that every Brazilian crop producing state has the same historical relationship with ENSO.
What is the relationship between ENSO and Brazilian final crop yields?
No statistically significant ENSO vs. national corn and soybean yield relationship is detected in this analysis.
Brazilian soybean, first-season corn, and second-season corn yield deviations from trend do not show statistically significant relationships with Relative Niño 3.4. The strongest of the three simple linear relationships has an R² below 5% in this sample.
This result applies to trend-adjusted yield at the national level. However, it does not imply that regional weather/crop yield relationships are absent nor that that ENSO has no physical influence on Brazil crop weather.
The topic has been reviewed in the academic literature and confirms our finding. Mello et al, 2026 used an ONI-based ENSO measure also found weak and spatially heterogeneous relationships between ENSO and Brazilian soybean yields, with mixed municipal relationships that weakened with aggregation.
What is the impact of ENSO on Argentina corn and soybean weather and yields?
Argentina demonstrates a statistically significant production-weighted precipitation relationship in this analysis.
Argentina soybeans production-weighted precipitation has a positive, statistically significant relationship with Relative Niño 3.4 over the January-April analysis window. National corn and soybean yield deviation from trend also show statistically significant positive relationships with the Niño 3.4 index.
For national yield, the simple linear relationship between crop yield and the Niño 3.4 index has an R² of approximately 27% for corn and 19% for soybeans. Those values indicate that Argentinian historical yield variables are partially associated with ENSO. However, the relatively low R² suggests variations in final yield remains outside this one-factor relationship.
The province-level precipitation relationships in the Argentina analysis are also more consistent in sign than the state-level Brazil soybean relationships. That produces a clearer national production-weighted precipitation relationship in the Argentina sample.
What does the ENSO phase analysis show for Argentina?
In the Argentina soybean sample, La Niña seasons average below trend.
Argentina soybean yield deviations from trend average below trend in La Niña seasons and above trend in neutral and El Niño seasons in this sample. The soybean phase differences are statistically significant. The El Niño and strong-phase groups contain relatively few seasons, so the phase averages should not be treated as deterministic yield forecasts.
This phase analysis provides historical context rather than a direct forecast for the current crop year. It summarizes how final yields were distributed across previous ENSO categories; it does not isolate ENSO from all other weather, agronomic, or market-relevant factors.
What does the 2026 El Niño imply for the 2026/27 South American crop season?
ENSO provides historical climate context, not a deterministic yield forecast.
This analysis suggests assigning a single Brazil or Argentina yield outcome based on the ENSO phase alone is not warranted. Brazil has no statistically significant national yield relationship in this sample while it also has regional precipitation relationships with opposing signs. Argentina has statistically significant precipitation and national yield relationships, but ENSO still accounts for only part of historical yield variation around trend.
For the 2026/27 season, the ENSO index alone does not specify the regional production-weighted precipitation and temperature pattern or the final yield outcome.
How was the analysis conducted?
Weather observations come from the Point-in-Time (PiT) Weather Forecast API. Gridded observations have been aggregated using crop production weights to create grain market-relevant indices such as Brazil soybeans production-weighted maximum temperature and Argentina corn production-weighted precipitation. The Brazil production-weighted weather history begins in 2009/10, and the Argentina history begins in 2000.
Yield data come from the CropProphet Modeler SFTP service. The Brazil analysis uses historical final yield estimates, provided by IBGE, and evaluates yield in terms of its deviation from the technology trend. The Argentina analysis uses the CropProphet cross-validated Modeler yield forecast history, including final yield and the trend estimate provided by MAGYP. Climate indices include NOAA CPC Niño 3.4 and Relative Niño 3.4 supplied through the World Climate Service.
Relative Niño 3.4 adjusts the Niño 3.4 sea-surface temperature anomaly for the tropical-mean sea-surface temperature anomaly. This reduces the influence of broad tropical warming when comparing ENSO conditions across time. NOAA CPC operational ENSO status is presented separately using its standard monitoring framework.
The analysis windows follow the crop periods used in the research: Brazil soybeans January-February, Brazil first-season corn January, Brazil second-season corn March-June, Argentina corn January-March, and Argentina soybeans January-April. Precipitation is evaluated as percent of normal over the window, temperature as departure from normal, and yield as percent deviation from trend. The statistics describe historical association and do not establish causality.
Important interpretation limits
- Brazil’s production-weighted weather history is shorter than the yield history, so statistical significance is more limited for the weather relationships.
- Interpret regional results cautiously when many states or provinces are tested, because some nominally significant results can occur by chance.
- Correlation does not establish causality. Final yield also reflects the timing and distribution of weather, soil moisture, crop development, management, technology, and other climate variability.
Track South American crop weather and yield risk with CropProphet
CropProphet provides crop weather and yield analytics for grain-market participants. Use the lead form below the article to request more information about CropProphet and the data used in this analysis.