What does El Nino do to India?

Turning the stripes into a line reveals how one year’s rain follows the next, and how quickly the monsoon can flip from surplus to deficit.

This line traces the same monsoon departure figures from 1950 to 2025. It starts at +4.2% in 1950 and ends at +7.8% in 2025. The line swings visibly above and below the zero line. A cluster of wet years, like the early 1950s, can build up groundwater, while a sudden dry year like 1965 (-18.6%) can catch farmers off guard. The line’s upturns and downturns are the backdrop against which El Nino’s influence is measured. It shows that the monsoon is inherently jumpy, so attributing any single year to one cause is hard.

When the Pacific is in El Nino, India’s monsoon averages 3.2% below the long-period normal, but that figure hides a wide range of outcomes.

The chart groups all monsoon seasons since 1950 into three buckets: El Nino, neutral, and La Nina. The bars show the average departure for each group. El Nino years (26) averaged -3.2%, while neutral years (27) got +2% and La Nina years (23) got +5.9%. The numbers below the bars count how many years in each group fell below zero. In El Nino, 15 out of 26 were dry; in La Nina only 4 out of 23. The visual makes clear that the Pacific tilt is real, but it also shows that the average El Nino deficit is still inside the normal range, which is why the next chart on extremes is needed.

57.7% of El Nino monsoons finished below normal, compared to 33.3% for neutral years.

The chart shows the share of years in each Pacific category that finished below normal, using IMD’s definition. The El Nino bar reaches 57.7%, nearly double the neutral 33.3% and more than triple La Nina’s 17.4%. It also breaks out more extreme thresholds: 30.8% of El Nino years fell more than 10% below normal, against only 7.4% of neutral years. So the risk of a serious drought is much higher during El Nino. Still, the bar is not 100%, a point the next charts reinforce with exceptions and definition checks.

El Nino monsoons are driest in June and September, the onset and withdrawal months.

Two sets of bars compare the average monthly rainfall departure in El Nino monsoons against a typical year. In El Nino, June runs 10.3% below normal, July -6.1%, August -2.7% and September -10.8%. A typical year runs close to zero in all months. The chart reveals a U-shaped pattern: the deficit is deep at the start and end of the season, while August holds up best. For a farmer, a 10% shortfall in June means sowing is delayed, which can reduce yields even if July and August recover. A 10% shortfall in September saps the final grain-filling stage.

The rolling correlation between Pacific warmth and monsoon rainfall dipped near zero in the late 1990s but has since tightened.

The line shows a 21-year running correlation between the ONI and all-India monsoon rainfall. A more negative number means a stronger link (warmer Pacific, drier India). The correlation started at -0.53 in 1960, weakened to near zero around the late 1990s, and then strengthened again to -0.64 by 2015. The wobble is large enough that scientists have debated whether the relationship is breaking down. For the reader, the practical point is that the historical base rate from 1950-2025 is a guide, not a fixed law. The Pacific’s grip has not vanished, but it is not constant either.

The Pacific and the Indian Ocean often swing in different directions, creating a tug-of-war that shapes the monsoon.

Two lines are plotted together: the ONI (Pacific) and the DMI (Indian Ocean Dipole). The ONI shifted into a warm El Nino state in 1951, 1957, 1965, 1972, 1982, 1987, 1991, 1997, 2002, 2004, 2009, 2015 and 2023. In several of those years, the DMI was also positive, 1972, 1982, 1997, 2015, while in others it was negative or neutral. A positive DMI can add moisture to the monsoon, offsetting a drying Pacific. The chart lets a reader scan for years when both were unfavourable (El Nino with a negative dipole, like 1965) versus years when they opposed each other.

El Nino monsoons with a positive IOD averaged near-normal rain, while those without it averaged a clear deficit.

The chart splits all 26 El Nino monsoon seasons into two groups: 5 with a positive IOD and 21 without. The positive IOD group averaged just -0.3% rainfall departure, barely below normal. The other group averaged -3.9%. A comparison bar for all La Nina monsoons (+5.9%) is also shown. The sample of positive IOD years is small, but the difference is large enough to matter. The strongest supporting case is 1997, a record El Nino that was counterbalanced by a strong positive IOD, and the monsoon survived. The chart drives home the point that the Indian Ocean gets a vote.

11 El Nino monsoons still finished with near-normal or surplus rain, including 1958’s 14% surplus.

The chart lists the years when El Nino was present during the monsoon but the all-India rainfall departure was near normal or positive. Each bar is a single year, and the colour indicates the rainfall departure: blue for surplus, grey for near normal. The list starts with 1953 (+10.7%) and includes 1957 (-0.5%), 1958 (+14%), 1963 (+4.4%), 1969 (+3.8%), 1976 (+1.9%), 1977 (+3.4%), 1983 (+14%), 1991 (-1.4%) and 1992 (-1.4%). These 11 years, from a total of 26 El Nino monsoons, are the statistical basis for the page’s thesis: El Nino is a loaded dice, not a fixed outcome.

1972 and 2002 are the two worst El Nino monsoons on record, with deficits of 22.3% and 20.9%.

The chart lists the ten largest all-India rainfall deficits among El Nino monsoons since 1950. The bars are sorted from worst to least: 1972 (-22.3%), 2002 (-20.9%), 1965 (-18.6%), 2009 (-18.3%), 1987 (-14.3%), 1951 (-13.2%), 2015 (-12.7%), 1982 (-11.4%), 2004 (-9.6%) and 1986 (-8.5%). Each row also shows the ONI and DMI values for that season. The presence of 1982 and 2015, which had positive IODs, reminds us that a favourable Indian Ocean is not a full shield. These years are the cautionary tales.

Northwest India loses 14.2% of its typical monsoon rain during El Nino years, nearly double the national figure.

The chart averages the 17 monsoons when the Pacific was in El Nino all season, and shows the mean departure for each region. Northwest India tops the list at -14.2%, followed by Central India at -9.4%, South Peninsula at -7.4%, and the all-India figure at -6.8%. The northwest includes the wheat-and-pulses belt, where kharif crops like bajra, moong and cotton depend almost entirely on monsoon rainfall. This extra dryness is why El Nino often shows up in pulse and oilseed prices before cereal prices. The mechanism is that El Nino weakens the monsoon trough over northwest India.

El Nino’s rice-yield damage concentrates in the rainfed belt of eastern India, while yields in irrigated Punjab and Haryana often rise above normal.

The map shows the average kharif rice-yield change in El Nino years, measured against the crop’s own five-year normal. States in the rainfed eastern and central belt, Jharkhand, Bihar, Chhattisgarh, typically see yield declines, shaded in orange and red. The highly irrigated northwestern states of Punjab and Haryana are shaded green, indicating yields above their recent normal. The all-India rice yield is nearly flat, but that average cancels out the losses in the east against the gains in the northwest. The pattern is driven by irrigation access, which decouples the harvest from the rainfall in the canal and tubewell districts.

The correlation between monsoon rainfall and foodgrain output is 0.71, meaning they still rise and fall together most years.

The chart shows the cross-correlation between monsoon rainfall and annual crop output for six broad crop groups from 1950-51 to 2024-25. Foodgrains and rice both register a 0.71 correlation coefficient, a strong positive relationship. Oilseeds follow at 0.66. Coarse cereals and pulses are weaker at 0.51 and 0.41. Wheat, a winter crop that relies on stored moisture and irrigation, shows only 0.37. These numbers mean that while the monsoon is no longer the sole master of the harvest, it remains the single biggest driver of year-to-year swings in total food production. Irrigation and technology have not severed the link; they have loosened it.

Irrigated rice in the northwest gained 7.3% yield during El Nino years, while rainfed coarse cereals in the same region fell 11.8%, proving irrigation is the key buffer.

Two crops in the same regions tell the story. The top set of bars shows irrigated rice yields during El Nino years. In the northwest, rice averaged 7.3% above its recent five-year normal. But the bottom bars, showing rainfed coarse cereals, reveal a very different picture: in the northwest, they fell 11.8% below normal. In Central India, rice fell 3.1% while coarse cereals fell 1.2%. In the south, both were small positives. The chart makes the case that where canals and tubewells reach, the Pacific’s influence on yields is largely muted. Where they don’t, the rain deficit translates directly into lost harvest.

The same El Nino can cause a drought in one region and a surplus in another, as 2023 showed.

This visual splits El Nino monsoon years into the four IMD homogeneous regions and plots each region’s rainfall departure as a separate small line chart. The full set of years is shown, so a reader can swipe through the four panels. In 2023, the all-India line shows -5.3%, but the northeast line plunges to -17.5% while the northwest line rises to +1.2%. In 1951, northwest lost 27.9% while south peninsula lost only 6.7%. The charts demonstrate that a national average is a poor guide to local reality, and that El Nino’s local effect depends on the orientation of the monsoon trough and the path of rain-bearing systems.

Rainfed oilseeds and millets suffer the largest El Nino yield losses; irrigated crops like rice and sugarcane are barely affected.

The chart shows the average yield change in El Nino years for ten major crops, measured against each crop’s recent five-year normal. Groundnut leads the losses at -8.3%, followed by sorghum (-7.3%), pearl millet (-6.8%), pigeonpea (-5.1%) and oilseeds overall (-5.1%). Maize is down 2.4%. At the other end, rice is nearly flat (+0.3%), cotton is up 1.2% and sugarcane gains 1.7%. The pattern sorts by water source: crops that rely heavily on monsoon rainfall lose yield; crops supplied by irrigation hardly move. This explains why a weak monsoon shows up first in edible oil and dal prices.

India enters the 2026 monsoon with near-record production of foodgrains, rice and wheat, providing a substantial buffer against a weak kharif.

Based on the third advance estimates for 2025-26, foodgrain production is estimated at 3,765.63 lakh tonnes. Rice is pegged at 1,540.24 lakh tonnes, wheat at 1,206.57 lakh tonnes, pulses at 274.09 lakh tonnes and oilseeds at 430.59 lakh tonnes. Sugarcane is estimated at 5,000.63 lakh tonnes and cotton at 290.24 lakh tonnes. These are near-record levels. The large stocks of rice and wheat in government warehouses mean that a single poor southwest monsoon is unlikely to cause a cereal shortage. The risk for consumers concentrates in pulses and perishables, where public stocks are smaller and supply chains are more local.

Real agricultural GVA grows at 3.1% per year in El Nino years, compared to 6.3% in La Nina years, a drag but not a crash.

Using Reserve Bank of India national accounts data from 1951 to 2025, the chart averages annual real agriculture GVA growth under three Pacific states. In 16 El Nino monsoon years, growth averaged 3.1%. In 41 neutral years, it was 3.2%. In 17 La Nina years, it jumped to 6.3%. The divergence is clear: farm output grows about twice as fast in La Nina years as in El Nino ones. Yet the El Nino average remains positive, reflecting the growing weight of dairying, horticulture and winter crops that are not directly hit by the June-to-September rain. The chart tempers the drought narrative with the fact that the whole farm sector rarely shrinks.

The 2002 monsoon, the second-worst El Nino drought in the record, saw only 0.9% post-monsoon wholesale food inflation.

The chart lists eight El Nino monsoons since 1982 and their post-monsoon (October-December) wholesale food inflation. 1991, a near-normal monsoon, had the highest inflation at 23.1%, driven by a balance-of-payments crisis and rupee devaluation. The two worst monsoons, 1987 (-14.3% rain) and 2002 (-20.9% rain), saw food inflation of just 8.8% and 0.9%, respectively. In 2002, large public grain stocks and a global commodity lull kept prices low despite the drought. The monsoon is a trigger for food prices, but stocks, trade policy and global markets are the transmission mechanism. A dry year does not automatically mean dearer food.

In 2009, cereals rose 14.5% but pulses surged 32.6% and onions 29.2%; in 2002, despite a larger rain deficit, pulses and vegetables fell.

The chart splits post-monsoon wholesale food inflation into four commodity groups for four El Nino drought years. In 2009, all groups rose, but pulses jumped 32.6% and onions 29.2%, while cereals increased only 14.5%. In 2002, cereals were up a muted 3.1%, and pulses, vegetables and onions all posted negative inflation. The 2015 drought saw a 51.6% spike in pulses but only 1.3% in cereals. The pattern is clear: cereals, which are stored by the government, show small price moves in drought years. Perishable vegetables and the less-storable pulses show the sharp spikes. Food inflation after a poor monsoon is a story of a few items, not a uniform rise.

The tallest inflation spike in the record, 28% in 1974, happened in a year with no El Nino, driven by the global oil shock.

Three inflation lines are plotted from their respective start dates: headline CPI from 1960, wholesale food from 1983, and retail food from 2012. El Nino monsoon years are shaded in red. Many of the shaded years show no exceptional spike; some, like 2002, sit near zero. The 1974 peak, the highest on the chart, was an oil-price event. The 1991 spike was a currency crisis. The 2020 and 2022 spikes were not monsoon-driven. The wholesale-food line is the most sensitive to the monsoon, yet even it does not climb in every shaded band. The visual makes clear that El Nino is only one thread in the inflation story.

Defining El Nino strictly doubles the average deficit and almost doubles the share of below-normal years.

The chart shows three El Nino definitions and La Nina as contrast. The loosest, any El Nino during the season, gives a -3.2% average over 26 years. Restricting to monsoons where El Nino persisted all four months (JJAS ONI ≥ 0.5) yields -6.8% over 17 years, with 71% below normal. Strong El Ninos only (peak ONI ≥ 1.5) average -12.1% over 7 years, with 86% below normal. La Nina years average +6.8%. The bars and the shares make plain that the familiar -3.2% figure is the most generous reading. The El Nino monsoons that people remember are the strict and strong ones.

Agriculture’s share of GDP has fallen from 62% to 14%, but its share of employment has fallen only from 63% to 42%, leaving a wide gap.

Two lines tell the story of farming in modern India. The dark line, agriculture’s share of gross value added, drops from 61.7% in 1951 to 13.8% in 2026. The light line, agriculture’s share of total employment, falls from 63.1% in 1991 to 41.6% in 2025. The gap between the two is the reason a drought is a small event for GDP and a large event for livelihoods. Over 40% of Indian workers still depend on farming for their income, and food takes a large share of poor households’ budgets. So even when the monsoon barely dents the growth rate, it still sets rural wages and the price of a meal for millions.