How IMD’s new model will sharpen weather forecast for farmers

New Delhi: The India Meteorological Department (IMD) is enhancing its forecasting capabilities by developing a high-resolution model that will increase its current 12-km grid spacing to 6 km by 2026. This move aims to improve weather predictions at the panchayat level, offering farmers more precise forecasts.

“Currently, we are providing panchayat-level forecasting, but that is based on the model run at the block level, so we will have to increase the panchayat-level model resolution," said Mrutyunjay Mohapatra, director general (meteorology), IMD, told Mint.

With the installation of radars, automated stations, wind profilers, and other instruments, IMD will expand coverage, improving forecast accuracy.

Presently, forecasts are generated for every 12 km. With the new model, predictions will be produced every 6 km, enhancing the detection of localized weather patterns. The grid point forecast model uses a network of points spread across the country, with the distance between these points defining the resolution.

In addition to refining resolution, the IMD is expanding its doppler weather radar network and integrating artificial intelligence (AI) and machine learning (ML) technologies to further improve accuracy.

“Currently, we have 40 doppler weather radars across the country and we are planning to have 126 by 2026. At present, 85% of the area is covered and once the full deployment is in place, we will have 100% of the area covered,” said Mohapatra.

This not only enhances the ability to track extreme weather events but also ensures redundancy—if one radar goes down, another can fill the gap, he added. Each radar costs ₹10- ₹20 crore.

The weather forecaster has started incorporating AI and ML into its forecasting processes and it will expand it further into other areas in coming years. “A dedicated team comprising experts from IMD, ministry of earth sciences and institutions like IITs and IIITs have been formed to spearhead the AI-based tool. IMD has started using AI tool marginally, but will expand in 2-3 years."

These technologies will help identify patterns and correlations within datasets, enhancing predictive models for greater precision.

Timely and accurate weather intelligence can be a game-changer for small farmers, said J.P. Tripathi, director of agriculture programs at Wadhwani AI.

"By leveraging AI and ML models built on IMD data, we're translating it into meaningful, crop-specific decisions for farmers. This helps reduce weather-related risks, improve yield resilience, and ensure that every intervention—from pest control to irrigation—is well-informed and better timed,” he said.

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Addressing climate change challenges

Climate change has made weather forecasting increasingly challenging, as localized extreme weather events grow more frequent.

“A denser observational network is needed to detect these localized phenomena and enhancing modeling systems to predict them accurately,” Mohapatra noted. “We are undertaking a lot of initiatives under Mission Mausam to address these challenges.”

Launched in December last year with a ₹2,000 crore allocation over two years, Mission Mausam aims to position India as a global leader in weather and climate sciences.

It seeks to enhance forecasting capabilities, improve dissemination of accurate and actionable information, and ensure sustainable development while safeguarding lives, livelihoods, and critical infrastructure.

The mission is expected to significantly bolster monitoring and response measures in regions like the northeast, where extreme weather events are common.

Also Read: Weather forecast: Stormy skies and lower food prices on the horizon