Recently IMD has made an error in predicting the monsoon.
What are the functions of IMD?
The India Meteorological Department (IMD), is an agency of the Ministry of Earth Sciences, responsible for meteorological observations, weather forecasting and seismology.
It is headquartered in Pune with regional offices at Mumbai, Kolkata, Nagpur and Delhi.
In April, the IMD had predicted “near normal” or 96% rains and then upgraded the figure to 98% a couple of months later.
These percentages refer to the proportion of rains to 89 cm, a 50-year average of monsoon rains.
What is the recent prediction error made by IMD?
The recent predictions made by IMD went wrong, at the end of this monsoon there were “below normal” rains (that is, less than 96% of the 50-year long period average).
A single number 96 or 95, has the power to brand rainfall as “near” or “below” normal.
A 98% forecast implies a range from 94% to 102% and so could span “below normal” to “above normal”.
The IMD continues to persevere with the meaningless practice of assigning an overall number to the quantum of rain expected during the monsoon.
This exercise of Monsoon prediction was initially conceived as a measure to warn the government about a draught or weak rains.
But now this has become just an exercise of numbers secured with statistical error margins to rationalise a wrong forecast.
What are the impacts of faulty prediction?
Faulty predictions of intra-seasonal variation or forecasting a change in global weather can affect agricultural outputs and normal lives of the people.
The outcome of focussing on quantitative numbershas ripple effects from policymakers to stock markets.
This leads to dilemma for policy makers for addressing the farmers who seek localised, actionable inputs on sowing or harvesting decisions.
Performance assessment of monsoon on agriculture and economy will be delayed due to the faulty prediction.
Way forward
India Meteorological Department is one of the six Regional Specialised Meteorological Centres of the World Meteorological Organization, faulty predictions will make its reliability dubious.
The rain estimates needs to warn threatening weather and must be operationally useful rather than reduce rain to numerical jugglery.
Thus IMD needs to take efforts to upgrade its supercomputers and sophisticated models to warn of weather changes at the district level.
