05 Jun Super El Niño 2026: Science, Global Impacts & India’s Monsoon Under Threat
This article covers “Daily Current Affairs”
SYLLABUS MAPPING : GS Paper 3 : Environment
FOR PRELIMS : ENSO, El Niño, La Niña, ENSO-Neutral, ONI Index, Walker Circulation, Hadley Cell, IOD, MJO, IMD
FOR MAINS : A potential Super El Niño developing in late 2026 poses a compound risk to India’s food security, agricultural income, rural employment, and monetary policy space. Analyse the multi-sectoral cascading impacts of a Super El Niño on India’s economy and suggest a pre-emptive policy package — covering agricultural preparedness, food price management, rural safety nets, and monetary policy — that can minimise the damage to India’s growth trajectory and the livelihood of vulnerable rural communities.
Why in the News
NOAA’s Climate Prediction Centre (May 2026) flagged an increasingly probable Super El Niño developing in the equatorial Pacific — peaking October 2026 – February 2027. Multiple global models — ECMWF, IRI Columbia, NOAA — project sea surface temperatures in the Niño 3.4 region reaching nearly 1.5°C above average by October (borderline Strong El Niño / Super El Niño threshold). India’s IMD Director General Mrutyunjaya Mohapatra (April 13 briefing) projected monsoon 2026 at ~800 mm — 8% below the LPA of 870 mm. The probability of a deficient season (rainfall <90% of LPA) is 35% — more than double the long-term climatological probability of 16%. Partially offsetting factors: expected positive IOD (Indian Ocean Dipole) conditions and below-normal northern hemisphere snow cover could moderate El Niño’s suppressive effect on the monsoon. The last Super El Niño (2015–16) contributed to India’s worst drought in over 40 years (2015); the 1997–98 Super El Niño coincided with global commodity shocks. The RBI MPC has already flagged El Niño as a potential threat to India’s food inflation trajectory in its June 2026 monetary policy statement.
61%
NOAA probability of El Niño developing (May–Jul 2026)
+2°C
Threshold for “Super El Niño” (Niño 3.4 SST anomaly)
800 mm
IMD forecast for SW monsoon 2026 (vs LPA 870 mm)
35%
Probability of deficient monsoon season (2× climatological average)
60%
India’s farmers dependent on monsoon rainfall for kharif
ENSO — El Niño, La Niña & Neutral Phase
🔵 La Niña (Cool Phase)
Cooler-than-average SSTs in central/eastern equatorial Pacific. Strengthened trade winds push warm water to western Pacific. Upwelling of cold water intensifies off South America. India effect: Above-normal monsoon rainfall; higher agricultural output; flood risk in NE India. 2020–2023 saw an unusually prolonged triple-dip La Niña.
🟢 ENSO-Neutral
Sea surface temperatures near the long-term average. Trade winds and Walker Circulation near normal. Neither El Niño nor La Niña conditions prevail. India effect: Near-normal monsoon with outcomes driven by other factors (IOD, MJO, snow cover). Currently transitioning from La Niña to ENSO-Neutral (early 2026).
🔴 El Niño (Warm Phase)
Warmer-than-average SSTs in central/eastern equatorial Pacific. Weakened trade winds allow warm water to slosh eastward. Suppresses upwelling off South America. India effect: Suppressed/deficient southwest monsoon; drought risk; food price inflation. Occurs on average every 3–4 years; peaks Oct–Feb.
Mechanism of El Niño — Step-by-Step Science
Normal Conditions (Walker Circulation)
- Normally, strong trade winds blow westward along the equatorial Pacific — piling up warm surface water near Australia/Indonesia
- This creates the Walker Circulation: warm, moist air rises over the western Pacific → convection, heavy rainfall over Indonesia/Australia → cold, dry air descends over eastern Pacific (Peru coast)
- Thermocline (boundary between warm surface and cold deep water) is shallow in the east and deep in the west
- The Indo-Pacific Warm Pool (west Pacific/Indian Ocean) acts as the moisture engine for the Southwest monsoon; strong Walker Circulation drives warm moisture westward toward India
El Niño Development Mechanism
- Trade winds weaken — usually triggered by a Kelvin Wave (subsurface warm water pulse) propagating eastward across the Pacific
- Warm water sloshes eastward — the western Pacific warm pool shifts toward the central/eastern Pacific (Peru/Ecuador coast)
- Walker Circulation reverses or weakens — convection now occurs over the central/eastern Pacific instead of the western Pacific
- The moisture-rich convection moves away from the Indian Ocean region → the SW monsoon’s energy source is depleted → weaker, deficient monsoon over India
- Bjerknes feedback (positive feedback loop) — warming SSTs further weaken trade winds → more warm water moves east → even warmer SSTs → cycle intensifies
Key ENSO Measurement Indices
| Index / Region | Definition | El Niño Threshold |
|---|---|---|
| ONI (Oceanic Niño Index) | 3-month running average of SST anomalies in Niño 3.4 region (5°N–5°S, 120°W–170°W). The primary NOAA index for classifying El Niño/La Niña | ≥ +0.5°C for 5 consecutive overlapping seasons = El Niño; ≤ -0.5°C = La Niña; ≥ +2.0°C = Super El Niño |
| Niño 1+2 Region | 0°–10°S, 90°W–80°W — extreme eastern equatorial Pacific; first region to show warming; SST anomalies here indicate early El Niño development near South American coast | Supplementary index; not primary for ENSO classification |
| Niño 3 Region | 5°N–5°S, 90°W–150°W — central-eastern Pacific; historically used by WMO and earlier ENSO research; still widely cited | +0.5°C anomaly threshold |
| Niño 4 Region | 5°N–5°S, 150°W–160°E — central equatorial Pacific; warming here indicates “Modoki El Niño” (warm pool El Niño) which has different India monsoon impacts than canonical El Niño | +0.5°C threshold; Modoki has weaker India monsoon suppression |
| El Niño Modoki | Central Pacific warming (Niño 4) rather than eastern Pacific (Niño 3.4); different teleconnection pattern — may actually bring above-normal rainfall to parts of India unlike canonical El Niño | Distinct from canonical El Niño; India response variable |
| SOI (Southern Oscillation Index) | Atmospheric component of ENSO — difference in mean sea-level pressure between Tahiti (east Pacific) and Darwin, Australia (west Pacific). Negative SOI = El Niño (high pressure over Darwin, low over Tahiti) | Sustained negative SOI below -8 confirms El Niño atmospheric coupling |
What Makes a “Super El Niño”? — Classification
| Category | ONI (Niño 3.4 Anomaly) | Examples | India Monsoon Impact |
|---|---|---|---|
| Weak El Niño | +0.5°C to +0.9°C | 2004–05, 2006–07 | Marginal monsoon suppression; often near-normal rainfall |
| Moderate El Niño | +1.0°C to +1.4°C | 2002–03, 2009–10 | Below-normal monsoon; 2009 saw 78% of LPA — worst in 37 years |
| Strong El Niño | +1.5°C to +1.9°C | 1982–83, 1991–92 | Significant monsoon deficit; drought conditions in many states |
| Super El Niño | ≥ +2.0°C | 1997–98 (peak +2.8°C), 2015–16 (peak +2.6°C) | Severe monsoon suppression; catastrophic global food and weather disruption; 2015 — India’s worst drought in 40+ years |
Global Impacts of a Super El Niño
🌧 South/SE Asia
Drought in India, Sri Lanka, Indonesia, Philippines, Australia. Monsoon failure → food security crisis. 2015–16 Super El Niño caused severe drought across these nations simultaneously.
🌊 South America
Catastrophic flooding in Peru, Ecuador, Chile — Niño coast warms; rainfall shifts eastward. 1997–98 caused $35 billion damage in South America alone. Fisheries collapse as cold upwelling disappears.
🔥 East Africa
Heavy rainfall and floods in East Africa (Horn of Africa) — counter-intuitively, El Niño brings excess rain here. 2023–24 El Niño caused devastating floods in Kenya, Ethiopia.
🌡 Global Temperature
El Niño years are typically the warmest years on record. 2023–24 El Niño (not super) made 2023 and 2024 the hottest years ever. Super El Niño + climate change background warming = record-shattering global temperatures.
🌀 Atlantic Hurricanes
El Niño suppresses Atlantic hurricane activity by increasing upper-level wind shear — a rare silver lining. 2026 Atlantic hurricane season forecast is lower-than-average if El Niño develops strongly by August.
🐟 Fisheries & Food
Collapse of anchovy fisheries off Peru (normally sustained by cold upwelling). Global food commodity price spikes — rice, wheat, palm oil historically spike during Super El Niño years as multiple major agricultural regions fail simultaneously.
iOD & Other Modifiers of El Niño’s India Impact
Indian Ocean Dipole (IOD)
- IOD = difference in sea surface temperatures between the western Indian Ocean (Arabian Sea) and the eastern Indian Ocean (off Indonesia)
- Positive IOD — warmer western Indian Ocean, cooler eastern → enhances moisture supply to India → counters El Niño’s suppressive effect on the monsoon
- Negative IOD — cooler western, warmer eastern → reinforces El Niño → doubly suppresses monsoon
- 2026 forecast: IMD expects positive IOD conditions to develop — a critical partial offset to El Niño. IMD DG cited this as moderating the monsoon outlook from “deficient” to “below normal”
- IOD typically develops between June and October — its strength and timing determine how effectively it offsets El Niño
Other Monsoon Modifiers
- MJO (Madden-Julian Oscillation) — eastward-propagating 30–60 day oscillation of convection around the tropics. Active MJO phases over the Indian Ocean can significantly boost monsoon rainfall even during El Niño years
- Eurasian/Himalayan Snow Cover — below-normal northern hemisphere snow cover (forecast for 2026) accelerates land warming, strengthening the thermal gradient that drives monsoon circulation — partially offsetting El Niño
- Climate Change Background Warming — long-term warming adds excess atmospheric moisture; “moisture reservoir” effect can boost rainfall even when circulation is weak. Former IMD DG K.J. Ramesh notes this as a critical modifier
- El Niño Modoki vs Canonical — if warming centres in the central Pacific (Modoki type), impact on India is weaker than canonical eastern Pacific warming — model forecasts need to be watched for the warming centre
Impacts on India — Interactive Analysis
Agriculture
- Kharif crop failure risk — 60% of India’s farmers depend on monsoon for kharif sowing (rice, maize, cotton, pulses, groundnut, soybean). An 8% rainfall deficit translates to lower crop acreage and yield — particularly in rain-fed regions (Vidarbha, Marathwada, eastern UP, Jharkhand)
- Food inflation spike — poor kharif output drives up food prices; RBI has already flagged El Niño as an upside risk to CPI. Pulses and vegetables (highly sensitive to monsoon distribution) typically see 20–30% price spikes in drought years
- Rabi crop benefits — a silver lining: drier monsoon → soil is less waterlogged → better conditions for rabi wheat, mustard, and chickpea cultivation if post-monsoon temperatures are also favourable
- PM-AASHA and buffer stock activation — government will likely activate commodity price stabilisation through buffer releases from FCI, import duty reductions on pulses, and export restrictions on rice/sugar if kharif output disappoints
Economy
- GDP growth impact — agriculture is 14% of India’s GDP and employs 45%+ of the workforce. A poor kharif season reduces agricultural GDP growth by 2–4%; indirect effects on rural demand slow FMCG, two-wheeler, and tractor sales
- Inflation-growth trade-off for RBI — El Niño-driven food inflation limits RBI’s room to cut interest rates (despite growth concerns); MPC already flagged El Niño as an upside risk to the 4% inflation target
- Hydropower shortfall — lower reservoir levels reduce hydropower generation; higher thermal power use increases coal demand and energy costs for industry
- Rural MGNREGA demand surge — drought years historically see 20–30% jump in MGNREGA work demand as agricultural employment collapses; tests fiscal capacity at state level under the new VB-G RAM G framework
- Export opportunity — global food commodity prices spike during Super El Niño years; India (if surplus in some crops) can benefit from higher export realisation for basmati rice, spices, sugar
Water Security
- Reservoir depletion — India’s major reservoirs (monitored by CWC — 150 major reservoirs) depend on monsoon inflows. Below-normal monsoon → reservoirs at below-normal levels → water shortages for irrigation, drinking, and industrial use in the following year
- Groundwater stress — monsoon recharge accounts for 70–80% of groundwater replenishment in many states. A deficient year deepens India’s chronic groundwater depletion crisis (north-west India water table falling 0.5m/yr)
- Unequal spatial distribution — even in below-normal years, NE India and Kerala often receive normal or above-normal rainfall; the deficit is concentrated in central, peninsular, and northwest India — Maharashtra, Madhya Pradesh, Karnataka, Telangana, and Gujarat historically most vulnerable
- El Niño paradox — droughts in some areas coexist with floods elsewhere; extreme rainfall events (cloudburst, flash floods) can increase in localised areas even as seasonal totals fall — a climate change amplification effect
Heat & Health
- Intensified heatwaves — El Niño years consistently show higher temperature anomalies over India. 2026 already saw 48°C+ in UP in May; a Super El Niño developing by October–November will push global temperatures to new records
- Pre-monsoon heat stress amplified — delayed monsoon onset (a common El Niño effect) extends the pre-monsoon hot season into June–July, increasing heat-related mortality, especially among agricultural workers, elderly, and urban poor
- Reduced cloud cover → higher UV — reduced cloud formation in El Niño years means more direct solar radiation reaching the ground; increases heat stroke risk and crop sun damage
- Mental health and livelihood impacts — drought-linked crop failure correlates strongly with agrarian distress, farmer suicides (Vidarbha pattern), and rural-urban migration surges that strain urban infrastructure
Historical El Niño Episodes & India’s Monsoon Record
| Year / Episode | ONI Strength | India Monsoon | Key Impact on India |
|---|---|---|---|
| 1987 El Niño | Strong (+1.8°C) | 86% of LPA — deficient | Widespread drought; foodgrain output fell 9%; food prices spiked; emergency buffer stock release |
| 1997–98 Super El Niño | Super (+2.8°C peak) | 102% of LPA — near-normal | India paradoxically had a near-normal monsoon in 1997; global devastation but positive IOD partially offset. 1998 was the world’s hottest year at the time |
| 2002 El Niño | Moderate (+1.2°C) | 81% of LPA — severely deficient | Worst drought since 1987; foodgrain production fell 19 million tonnes; rural distress widespread |
| 2009 El Niño | Moderate (+1.3°C) | 78% of LPA — worst in 37 years | Sugar production collapsed (India became net importer); kharif sowing fell 10%; CPI food inflation exceeded 18% |
| 2015–16 Super El Niño | Super (+2.6°C peak) | 86% and 97% of LPA (2015, 2016) | 2015 — India’s worst drought in 40+ years; 330 million people affected; reservoir levels critically low; Vidarbha-Marathwada farm crisis |
| 2023–24 El Niño | Strong (+1.9°C — borderline super) | 94% of LPA — near-normal | Positive IOD in 2023 largely countered El Niño effect; 2024 saw below-normal in some months but overall manageable |
| 2026–27 (forecast) | Potential Super (≥+2.0°C) | ~800mm (92% of LPA) — IMD forecast | 35% probability of deficient season; kharif at risk; food inflation upside risk; RBI policy constrained |
India’s Preparedness & Government Response Mechanisms
Existing Strengths & Policy Tools
- IMD’s long-range forecast — India now has a 2-stage seasonal forecast system (April + June update); district-level downscaling enables state-wise agricultural planning ahead of kharif sowing
- Food buffer stocks — FCI’s buffer stock of ~75 million tonnes ensures food security even in drought years; PM-AASHA (Price Support Scheme) provides market intervention capability
- NDMA Drought Manual (2016) — comprehensive guidelines for drought declaration, relief operations, and MGNREGA demand management during El Niño-induced drought years
- PM-Fasal Bima Yojana (PMFBY) — crop insurance to compensate farmers for crop loss; El Niño years see high claim volumes — testing PMFBY’s financial architecture
- Pradhan Mantri Krishi Sinchai Yojana (PMKSY) — expanding irrigation coverage; reducing rain-fed acreage that is most vulnerable to monsoon deficit
Persistent Vulnerabilities & Gaps
- Rain-fed agriculture still 52% of India’s cultivated area — despite PMKSY, over half of India’s farmland remains entirely dependent on monsoon; a Super El Niño directly threatens these crops
- PMFBY coverage gap — only ~30% of gross cropped area insured; significant portions of small and marginal farmers remain outside crop insurance, leaving them exposed to complete income loss in drought years
- Groundwater over-exploitation — decades of over-extraction mean India’s aquifers cannot compensate for monsoon deficit as effectively as before; buffer is shrinking
- El Niño + climate change compound risk — the 2026 Super El Niño develops on top of a +1.2°C warmer baseline than pre-industrial; the combined effect is unprecedented in India’s historical experience with drought
Way Forward
- Pre-season agricultural advisory: IMD, ICAR, and state agriculture departments must immediately disseminate district-specific kharif crop advisories — recommending drought-tolerant varieties (ICAR’s heat/drought-tolerant rice and wheat lines), adjusting sowing windows, and prioritising assured irrigation regions for water-intensive crops to minimise yield loss.
- Pre-position food buffers: FCI must build buffer stocks above the quarterly norms for kharif crops — particularly rice, pulses, and oilseeds — before the monsoon season. Pre-emptive import of pulses and edible oils at advantageous prices (before global El Niño price spikes hit) should be initiated through NAFED/NCCF.
- Accelerate PMKSY micro-irrigation: Each percentage point increase in irrigated area coverage directly reduces the area vulnerable to El Niño-induced drought. Drip and sprinkler irrigation under PMKSY-Per Drop More Crop must be fast-tracked in Maharashtra, Karnataka, Telangana, and MP — the states historically most drought-affected during El Niño years.
- RBI pre-emptive inflation framework: The MPC must build El Niño’s food inflation risk into its forward guidance and rate decisions — potentially pausing rate cuts and maintaining a hawkish stance even if current inflation is benign, given the 6–12 month lag between monsoon failure and peak food inflation impact.
- Strengthen ENSO research & IOD coupling: India must invest in improving sub-seasonal to seasonal (S2S) prediction capabilities — particularly the IOD-ENSO interaction that determines whether positive IOD can offset El Niño. IMD’s Monsoon Mission must be expanded with new Bay of Bengal and Arabian Sea mooring buoys for real-time SST monitoring.
- Climate-proof the rural safety net: Under the new VB-G RAM G framework, drought-triggered demand surge clauses must be embedded — automatically releasing additional Central funding when a district is declared drought-affected, preserving the counter-cyclical function that MGNREGA served during 2009 and 2015 El Niño droughts.
Prelims Practice Question
Mains Practice Questions
“El Niño is not a simple on-off switch for India’s monsoon — it is one driver within a complex web of ocean-atmosphere interactions that determines whether India experiences drought, flood, or normal rainfall.” Explain the mechanism of El Niño formation in the equatorial Pacific Ocean, its teleconnection with India’s southwest monsoon through the Walker Circulation, and critically examine the role of modifying factors such as the Indian Ocean Dipole (IOD), El Niño Modoki, and MJO in determining the actual monsoon outcome in any given year.
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