India’s weather forecast tool old, say US experts
Why have the country's meteorologists time and again failed to predict seasonal and climatic patterns accurately? US scientists blame it on the archaic model which the Indian Meteorological Department (IMD) follows to tell you whether it will be sunny or a rainy day. Joydeep Thakur reports.Updated: Jan 05, 2013 09:41 IST
Why have the country's meteorologists time and again failed to predict seasonal and climatic patterns accurately? US scientists blame it on the archaic model which the Indian Meteorological Department (IMD) follows to tell you whether it will be sunny or a rainy day.
Experts said that since the late 1980s, the IMD has been able to successfully predict the monsoon only nine times, whereas the US had accurately predicted the time and the place where Cyclone Sandy would hit.
“The IMD relies upon the statistical model which predicts seasonal and climatic patterns based on past information gathered from the US and European agencies. This model is unreliable and needs zero skill,” Jagadish Shukla, professor of George Mason University in the US, said. He said weather prediction systems across the world had developed in the past 20 years.
“But India missed it and has failed to update itself. Indian meteorologists have been adopting models from other countries. But they need to develop a system of their own. They will have to work hard and update,” Shukla said on the second day of the Indian Science Congress.
Ronald Prinn, director of the Centre for Global Change Science, MIT, said, “The dynamic model used in the US and Europe involves 3D mathematical simulation of the atmosphere on computers. Dynamic models are useful to predict rainfall over a smaller scale, which is not possible in a statistical forecasting system.”
Accepting the fact that dynamic models are the future of predictions, Shailesh Nayak, secretary, ministry of earth science, said Indian scientists were gradually shifting to the dynamic models.
“We are gradually switching over to the dynamic models with higher accuracy levels. But we have to continue with the statistical models since we don’t have enough skills to use the dynamic models,” he said.