The odds of a storm

So, there was an alert for a storm in North India on May 7 and 8. People prepared for it and waited for it like never before…it didn’t quite loom on the skies, they waited some more; the heightened expectation led to the prospect of every gust of wind or clap of thunder or lash of raind building up to the predicted squall, even as the preparation made them feel secure against the oncoming fury of nature. Stung by the huge loss of life (more than 100) and property in the ‘freak’ unexpected dust storm on May 2-3, the fresh warning seemed ominous. Not wanting to risk the children being caught in the coming monstrous squall, Haryana closed its schools for the two days. Some more areas panicked. But the weather proved to be as unpredictable as… well, as the weather. The rainy forecast was a damp squib, and the promised howling winds ended in a whimper. With the sun largely shining through May 7 and 8, the situation was ripe for jokes galore.

So, did the meteorologist deserve the ridicule? As per the response to an RTI query, nearly 44 per cent of heavy rainfall predictions issued by the India Meteorological Department in 2017 were incorrect. Compare this with the over 80 per cent accuracy rate of the advanced countries’ weather agencies. No doubt, it does warrant that we get hi-tech prediction tools to boost data processing capacity and hone the existing model’s accuracy so that not only do we get to manage disaster better but also don’t get unnecessarily worked up. While weather forecasts have advanced over the past couple of decades, we are still a long way from blaming the weatherman for the slip-ups.

Rather, it is better to err on the side of caution. After all, a warning is issued only for the people to take to the necessary precautions. The disaster may or may not strike. Being prepared for any eventuality is definitely preferable to the many instances when can be taken unawares. There is no knowing how many precious lives would have been saved had there been some advance notice for the May 2 thunderstorm or for the floods and other natural disasters that we face regularly.