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Indian Ocean Dipole May Offset El Niño Impact: IITM Director

Dr Anguluri Suryachandra Rao, Director of IITM Pune, in an interview with ETV Bharat says a positive IOD could support India's monsoon despite El Niño.

Dr Anguluri Suryachandra Rao talks about Indian Ocean Dipole impact on  El Niño weather.
Dr Anguluri Suryachandra Rao talks about Indian Ocean Dipole impact on El Niño weather. (ETV Bharat)
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By ETV Bharat English Team

Published : July 8, 2026 at 7:53 PM IST

3 Min Read
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Amaravati: An Indian Ocean Dipole (IOD) is likely to develop over the Indian Ocean and could help mitigate the adverse effects of El Niño, according to Dr Anguluri Suryachandra Rao, Director of the Indian Institute of Tropical Meteorology (IITM), Pune.

Speaking to ETV Bharat during his visit to Kondapavuluru near Vijayawada to participate in a programme organised by the National Disaster Management Authority, Dr Rao recalled that during the major El Niño event of 1997, the impact was significantly reduced due to the simultaneous occurrence of a dipole. Dr Rao also spoke to ETV Bharat about weather forecasts, rainfall, technology, and related topics.

What is the Ocean Dipole?

The Indian Ocean Dipole (IOD) is a climate phenomenon that refers to the temperature difference between the eastern and western regions of the Indian Ocean. A positive IOD has a beneficial impact on the monsoon, and even amid El Niño conditions, it can lead to rainfall.

What is the Monsoon Outlook?

The impact of a ‘Super El Niño’ has begun in the Pacific Ocean. Typically, it sets in during August or September, but this time, it arrived as early as June. This has delayed the monsoon's progress. The pattern of rainfall distribution has been disrupted; while it rains in some areas, other regions remain dry. We will be safe if the monsoon gains momentum over the next month or two.

Are rising temperatures driving extreme rainfall?

As atmospheric temperatures rise, the air’s capacity to retain moisture also increases. Since clouds often do not travel far, intense downpours occur in a single location. This is the reason behind the uneven distribution of rainfall,

Has weather forecasting become more accurate?

In the past, weather conditions were predicted using traditional methods involving charts and manual plotting. Weather prediction has improved through the Monsoon Mission, which utilises models and mathematical equations for forecasting. We have raised the accuracy level—measured on a scale of 0 to 1—from the previous 0.2–0.4 range to between 0.75 and 0.8. We can now accurately forecast the weather a week in advance and relay this information to farmers and disaster management officials. We have also refined the forecast resolution from a 38 km grid to a 6 km grid.

Have supercomputers strengthened disaster warnings?

We used to disseminate weather information via SMS. However, the proliferation of private apps has created confusion regarding which one to use. To address this, we are launching the ‘Mausam Vani’ app soon, designed along the lines of ChatGPT. This system works even without a smartphone. Farmers will be able to call a toll-free number and receive practical advice, such as whether to apply fertiliser or postpone agricultural operations if rainfall is expected.

Over 2,000 people in our country lose their lives to lightning strikes annually. To address this, we developed the ‘Damini’ app, which is available in 23 languages. It predicts potential lightning strikes within a 20-kilometre radius with an accuracy of 300 meters. Through the ‘Meghdoot’ app, we provide agricultural advice—such as which crops to plant and when to irrigate—along with details on market prices. Global warming is leading to cloudbursts and heavy rainfall.

There is very little lead time to detect these events in advance. Under ‘Mission Mausam,’ we are incorporating observational data to further refine our models. This enables us to issue accurate warnings about thunderstorms, lightning, and heavy rain much earlier. We are utilising supercomputers with a capacity of 12 petaflops at IITM. Additionally, we have established a virtual centre at IITM dedicated to AI and machine learning. With their help, we are able to predict—with kilometre-level accuracy—when and where events like flash floods, forest fires, and reservoir management issues will occur.


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