Historic El Niño caused massive famine

In the 1870s, an unusually strong El Niño event led to a global famine, resulting in millions of deaths across China, India, and Brazil. This event, which occurred between 1876 and 1879, is considered the most powerful El Niño in recorded history, with temperatures 2.88°C above the average.

Famine led to extreme survival measures

During the 1876 to 1879 period, between 20 and 30 million people died in China, India, and Brazil, with the total global death toll reaching 50 million. Hunger forced people to resort to extreme measures, including eating sick animals, tree roots, and even mud, while epidemics of cholera and smallpox further reduced populations.

Colonial policies worsened the crisis

At the time, colonial authorities in India exacerbated the crisis by continuing to hoard grain and export food to England, while corrupt officials in China looted food reserves. Scientific understanding of El Niño was limited, with only Peruvian fishermen recognizing the phenomenon before modern research began.

Modern research reveals past El Niño's strength

In 1969, meteorologist Jacob Bjerknes mapped the global dynamics of El Niño for the first time. Later, researchers from the United States Oceanic and Atmospheric Administration (NOAA) used modern data analysis to estimate that the 1877 and 1878 El Niño was as intense as today’s most powerful events.

2026 El Niño expected to be historic

The current El Niño event in 2026 is predicted to be "the strongest in human memory," with sea surface temperatures in the tropical Pacific possibly reaching 4°C above normal. This would surpass the intensity of the 1870s event, according to climate models.

Modern prediction tools improve preparedness

Unlike the 19th century, scientists today can predict El Niño events several months in advance, allowing governments and emergency services to prepare for droughts, famines, and floods. Researchers are now exploring artificial intelligence to predict El Niño as far as two years in advance, which could improve outcomes significantly.