Scope to improve forecast on local heavy rain: Mrutyunjay Mohapatra | The Financial Express

Scope to improve forecast on local heavy rain: Mrutyunjay Mohapatra

`’We would acquire more than 30 Doppler radars to strengthen forecasting of extreme weather events like floods and heavy rainfall. We need to expand weather forecasting to the blocks and panchayats levels as our location specific forecast accuracy has not been high,’

Scope to improve forecast on local heavy rain: Mrutyunjay Mohapatra
However distribution of rainfall has been uneven as central India and the south peninsula get surplus rains, eastern and north-eastern regions have received deficient rainfall. 

More than three months into the southwest monsoon season (June-September), average pan-India rainfall is above normal (5% more than benchmark), as per prediction issued by India Meteorological Department (IMD). However distribution of rainfall has been uneven as central India and the south peninsula get surplus rains, eastern and north-eastern regions have received deficient rainfall. Mrutyunjay Mohapatra, director general, IMD, spoke to Sandip Das on challenges faced in localised weather forecasting and measures being taken to predict extreme weather events both in rural and urban areas in advance through deployment of Doppler radars and more observation points.

Q: Despite the large parts of the country getting normal to above normal rainfall since June, the distribution of rains has been uneven?

As IMD stated at the beginning of the monsoon season, we expected that it this year overall rainfall would in the ‘normal’ range and quantitatively it was predicted that cumulative rainfall would be 103% of the benchmark – long period average (LPA). So far cumulative monsoon rains have been 105% of the LPA. However, the Gangetic plains has become deficient and especially Uttar Pradesh which had received highly deficient rainfall so far. Deficiency in the rainfall over Bihar, West Bengal and Jharkhand, now ranges around 25% – 35% while Uttar Pradesh’s deficiency has been around 40% against the benchmark. However we had predicted that south peninsular region will get deficit rains which has not happened as Kerala and Tamil Nadu have got surplus rains this season.

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Q: What are factors which caused rainfall deficiency i Uttar Pradesh, Bihar, West Bengal and Jharkhand this monsoon season?

Till June 15, there was highly deficient rainfall across the country. From June 25 onwards monsoon rains picked up pace. In the month of June, there was no low pressure system which triggers rain. This led to delayed arrivals of monsoon in the central part of the country. It was not a classical advance of monsoon. During July and August, there was several consecutive low pressure systems. We saw 47 days of low pressure system against 41 days of low pressure usually we get during June-September, which triggered higher rainfall. All these low pressure system developed over north-bay of Bengal near Odisha coast moved north-west wards towards Madhya Pradesh, Chhattisgarh to Rajasthan. except the recent low pressure system which moved across Gangetic West Bengal.

Monsoon trough position which runs through Sri Ganganagar, Allahabad and Kolkata was located south of normal position. This had led to rains across Gujarat, Rajasthan, Madhya Pradesh, Chhattisgarh and Odisha.

Q: How robust is our weather forecasting system and what are areas of improvement in accurately predicting extreme weather events?

There has been large improvement in forecasting system especially in the last five years or so. Quantitatively, there has been 25%-30% increase in accuracy of prediction of severe weather events such as heavy rainfall, heat waver and thunderstorm compared to previous five years ago. At present, the forecast for weather events, we provide at the district level. We need to expand our weather forecasting to the blocks and panchayat levels. Although block level forecast, IMD has commenced since 2021, the forecast accuracy has to improve. When we go for location specific heavy rainfall events, accuracy has not been high. At the 36 divisional levels forecast IMD provides, accuracy is about 75% to 80%.

Currently we have 4500 weather observation stations in the country and number of these observation stations should increase manifold. We are setting up more automatic weather stations or automated rain gauge in collaboration with the state governments. We will soon start using drones for weather forecasting for which we have asked for expression of interest from the private entities.

Q: What are plans for adding more Doppler radars for improving weather forecasting?

We started to use Doppler radar since 2002 and in the next four years, four radars were installed at Visakhapatnam, Machilipatnam, Chennai and Kolkata. Currently, we have 34 radars installed at various locations to provide advance information about extreme weather events. Ideally we need more radars. We have plans of installation of 67 radars by 2025. Doppler radars of varying frequencies — S-band, C-band and X-band — are used by IMD to track the movement of weather systems and cloud bands, and gauge rainfall over its coverage area of 200 to 500 km. Doppler radars gauges the intensity of rainfall and impact area in real-time, which is beneficial for farmers as well as the local population.

We plan to install radars at the urban areas for provide forecasts about urban flooding. Currently, we have installed radars at Chennai and Delhi, we are planning to install radars in cities including Mumbai, Bengaluru, Pune, Bhubaneswar and Ahmedabad.

Q: On the impact of climate change in weather patterns and increase in the number of dry spells?

Since 1970 because of impact of climate change, the frequency of heavy rainfall events are increasing in India as well as all the tropical countries. Duration of dry spells is more and wet spell duration is less but more intense. Especially when there is a low pressure system, intensity increases. While mitigation strategy has to be localised, monsoon has is globalized phenomenon. We have to go for severe weather warnings, especially heavy rainfalls. We should increase the observation network so that all heavy rainfall events can be dedicated. We should go for high resolution modeling. Specific models for hilly areas and urban areas so that location specific warning cold be issued with more accuracy. We have 10 petaflops computing system and target is to reach 30 petaflops in the next two to three years.

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