How have indigenous HPC systems improved India's weather forecasting and disaster preparedness? Illustrate with examples.

To forecast the weather, a computer model must solve billions of equations before the weather actually arrives. India's dedicated weather High-Performance Computing (HPC) capacity rose from 6.8 PF to 22 PF with the launch of Arka and Arunika in 2024 [1]. With this capacity, India's forecasts are faster, more detailed and more focused on what the weather will do on the ground.

Evolution of India's weather HPC

• Pratyush (IITM Pune, 4 PF) and Mihir (NCMRWF Noida, 2.8 PF) made India 4th globally, after Japan, the UK and the USA, in HPC dedicated to weather and climate [2].
• Arka (11.77 PF) and Arunika (8.24 PF) came from a ₹850-crore MoES project and roughly tripled this capacity [1].
• Under the National Supercomputing Mission, PARAM Rudra systems built on the indigenous "Rudra" server [3] support climate modelling and disaster-management research [4].

Improvements in weather forecasting

• Finer resolution: India's own Bharat Forecast System runs at 6 km resolution on Arka, so it can capture local extreme rainfall [5].
• Speed: model run time fell from about 12 hours to 3–6 hours, so forecasts reach users while there is still time to act on them [5].
• Longer range: the same computing base supports short-range (up to 8 days), extended-range (about 20 days) and seasonal monsoon forecasts [2].

Gains in disaster preparedness

• Extreme events: forecasts of cyclones, heavy rainfall, heatwaves and droughts are more accurate and come with longer lead time [1]. This gives more time for evacuation and for pre-positioning relief.
• Floods: HPC supports river-flood mapping and climate modelling [6], which helps authorities identify the areas most at risk.
• Livelihoods: extended-range and seasonal outlooks [2] help plan sowing and contingency crops in drought-prone regions.
• Chain of action: observations → HPC model (Bharat Forecast System) → IMD warning → action by NDMA and state disaster authorities.

Remaining gaps

• Chip dependence: C-DAC is still designing AUM, India's own HPC processor, on Arm architecture [7].
• Scale: total NSM capacity of 68 PF is a small fraction of the world's fastest single machine, about 2.19 EF [6].

In sum, India's own HPC capacity has made forecasts faster, more detailed and longer-range, and has moved disaster management from relief after the event to preparation before it. Expanding capacity under Mission Mausam, completing AUM and investing in exascale research would build on these gains. That would help India meet the Sendai Framework and SDG 13 (Climate Action).