'Mission Mausam' promises: Cloud chambers, AI, better weather forecasting

Mission Mausam aims to enhance India's weather forecasting through advanced technology, cloud chambers, and AI, promising improved predictions and better climate change mitigation

The newly minted Mission Mausam is focusing on the research and development of technologies to improve India’s understanding of weather systems and finetune the ability to deliver accurate, localised weather forecasts. Among other things, the Mission will set up lab facilities to create clouds within enclosed spaces, and experimentally determine how such clouds could be seeded with chemicals to induce rain, or prevent rain by desiccation. Apart from boosting the scientific understanding of natural processes like cloud formation and rain, hail, and ice, by artificially suppressing or enhancing weather systems, the Mission has the mandate to improve weather observation. It will set up more radars, wind profilers, and radiosondes (telemetry sensors carried on weather balloons) to gather data. It will also invest in more computer resources and develop artificial intelligence (AI) tools to derive better forecasting models.

While the initial outlay for the Mission is Rs 2,000 crore, it will need far more financial resources as it goes along. Artificial cloud chambers are expensive to design, build, and maintain, and weather forecasting, along with its big brother, climate science, is among the most computationally intensive of modelling processes. Seeding clouds with chemicals like silver iodide to induce rain is not a new technology as such — it has been around for over 70 years. However, doing it experimentally at scale in controlled conditions, with a plethora of different chemicals, is difficult. Cloud chambers don’t just need to be enclosed. They need to be temperature- and humidity-controlled, with different temperature and humidity gradients at different locales within the chamber. There need to be systems that can deliver variable air pressure at different spots within the chamber, along with “wind-generators”, which move air around at different temperatures and velocities to try to replicate natural phenomena.

Multitudes of important variables need to be tracked in weather systems. They include air pressure, wind speeds, humidity, temperatures, ground conditions, and the Earth’s rotation. Weather and climate are classified as “chaotic” by physical scientists and mathematicians. “Chaotic” in this context is a system where tiny changes in one variable can lead to massive differences in the output and, thus, make weather or climate unpredictable. The chaotic quality makes weather very hard to model, and powerful supercomputers are tasked with weather prediction, making this a fertile field of research in applied mathematics and computer science. Breakthroughs in AI have helped to make predictions more granular and accurate and there is the promise of possible breakthroughs in quantum computing, which could accelerate number crunching. Regardless, weather and climate modelling will always remain intractable problems. Developing a better network of observational tools, including more radars, radiosondes, and satellite systems, will also be cost-intensive. But the data gathered will be invaluable. The direct payoffs from more accurate weather and climate predictions would be enormous. If it is known in advance where and when floods are likely and where there’s likely to be a rainfall deficit, taking countermeasures is much easier. In the long term, the mitigation of climate change should also be enabled by the Mission, which should be funded adequately and encouraged to expand its mandate, if necessary.