ERRATIC monsoons always make good news copy in India. It is the official weather forecasting agency, the India Meteorological Department (IMD), that bears the brunt of criticism. Sometimes justifiably so, for often its take on the southwest monsoon goes off the mark, as it happened in July this year. IMD said July would have 98 per cent of the rains it normally gets. As if on non-cue, rains stayed away for the best part of the month from many agriculturally important areas such as the north and north-western regions of the country.
In jumped Kapil Sibal, minister of state for science and technology (independent charge). Coming to the rescue of the moribund agency, he said the fault lies with obsolete and aged equipment used to gather weather data. To rectify this, he has sought Rs 500 crore for state-of-the-art gadgets.
The need to replace archaic, manually-read instruments with ones that have digital sensors is understandable. But a question remains: are machines the only problem that bugs the monsoon forecasting system? Could it have more to do with humanpower?
With just two universities -- Andhra and Cochin -- offering a Masters-level course in meteorology in India, quality humanpower is a real problem. Out of some 40-odd students who pass out from these institutions, the best talent flies off to developed countries; the majority of the rest find it easier to hunt jobs in other areas.
IMD's attitude is also a problem. Most meteorologists working outside the field of operational weather forecasting complain that it is seriously loathe to part with real-time weather data. To the research community, this is a major constraint on working out more accurate forecasting models.
Official forecasting models currently in use in India are empirical in nature: the forecast is based on past ocean, land and atmosphere data. An ideal alternative could be dynamical models. These enjoy an edge because forecasting here uses real-time observations to replicate processes that occur in the ocean and the atmosphere. With ever-enhancing computing power, such models can be dovetailed to accurately predict the Indian monsoon too. But what is lacking is adequate data on atmospheric-ocean phenomena that influence the monsoon and a better understanding of the underlying physics that drives the climate in the region.
This entails much more than money. Perhaps a drastic change in mindset will work better?