El Niño’s Surprising Impact on India’s Spring Temperatures: What Climate Models Missed

The study examines how surface air temperature (SAT) over India changes during spring and early summer (April-June) following El Niño events. It uses simulations from 25 CMIP6 models and compares them with real-world data from 1951 to 2014. The models generally show higher SAT variability than observed, but most capture the El Niño-induced warming patterns. SAT increases significantly after El Niño, especially in south-central India, with a 52% higher warming compared to other regions.

This warming is linked to altered wind patterns during the El Niño decay phase, which reduces cloud cover and allows more sunlight to heat the surface. Around 50% of the models correctly predict that half of the warmest years in the study period are post-El Niño. However, the models overestimate the westward spread of sea surface temperature anomalies, affecting atmospheric circulation and SAT variability.

El Niño’s Surprising Impact on India’s Spring Temperatures: What Climate Models Missed

A recent study explored how El Niño events influence surface air temperatures across India during spring and early summer (April to June). By analyzing data from 1951 to 2014, researchers compared real-world observations with simulations from 25 climate models (part of the CMIP6 project). Their goal was to understand how these temperatures shift after El Niño—a climate phenomenon marked by warmer-than-average ocean temperatures in the Pacific—and whether the models accurately capture these changes.

The findings revealed that while the models generally mirrored real-world warming patterns linked to El Niño, they tended to overestimate temperature fluctuations compared to actual data. Most models successfully showed that India experiences significant warming after El Niño events, particularly in the south-central regions, where temperatures rose by about 52% more than in other parts of the country. This uneven warming highlights how regional climate responses can vary, even under broader global influences like El Niño.

The study identified a key mechanism behind this warming. During the decay phase of El Niño (when its effects start fading), wind patterns shift over the Western North Pacific (WNP), forming a high-pressure system known as an anticyclone. This system drives easterly winds toward southern India, which reduce cloud cover over the region. With fewer clouds, more sunlight reaches the ground, heating the land and boosting surface temperatures. This process explains why south-central India, in particular, feels the brunt of the heat during El Niño’s aftermath.

When testing the models’ accuracy, researchers found that roughly half of them correctly predicted that El Niño played a role in extreme heat. Specifically, about 50% of the warmest years recorded between 1951 and 2014 occurred shortly after El Niño events. This suggests that while many models can replicate the connection between El Niño and Indian temperature spikes, there’s still room for improvement. One major discrepancy emerged: several models overstated how far west the Pacific Ocean’s warmer sea surface temperatures (a hallmark of El Niño) extended. This error skewed simulations of wind patterns and, in turn, affected predictions of temperature variability in certain regions.

These model limitations matter because accurate wind and ocean temperature projections are critical for forecasting regional climate impacts. For instance, overestimating the reach of Pacific warming could lead to incorrect assumptions about rainfall patterns or heat extremes in India. The study emphasizes the need to refine how models represent interactions between oceans and the atmosphere, particularly during El Niño’s decay phase.

Overall, the research underscores El Niño’s lasting influence on India’s climate, even as the event weakens. The warming effect, especially in south-central India, has implications for agriculture, water resources, and public health. By pinpointing where models succeed or struggle, the study offers a roadmap for improving predictions, helping communities better prepare for heatwaves and shifting weather patterns in a warming world.