At the new system’s core are two forecasting models whose predictions are “blended,” to sharpen accuracy. File
| Photo Credit: The Hindu

At the new system’s core are two forecasting models whose predictions are “blended,” to sharpen accuracy. File
| Photo Credit: The Hindu

Bhubaneswar/Kolkata:

A deep depression over east-central Bay of Bengal intensified into cyclonic storm ‘Dana’ on Wednesday morning, the India Meteorological Department (IMD) said.

The storm is likely to move in a northwestward direction, intensify further into a severe cyclonic storm over northwest Bay of Bengal and cross the Odisha-West Bengal coasts between Puri and Sagar Island in the early hours of October 25 with wind speeds of up to 120 kmph, the IMD added.

The system lay 560 km southeast of Paradip and 630 km south-southeast of Sagar Island at 5.30 am, it said.

Advising fishermen not to venture into the sea from October 23 to 25, the Met warned that wind speed is likely to reach 60 kilometres per hour (kmph) along and off Odisha-West Bengal coasts from October 23 and gradually increase to 100-110 kmph, gusting to 120 kmph, from October 24 night till October 25 morning.

More than 150 express/passenger trains running through South Eastern Railway jurisdiction have been cancelled in view of the severe cyclonic storm, an SER official said.

The trains cancelled were scheduled to depart their originating stations between October 23 and 25, the SER official said and added that more trains running through the SER zone may be cancelled if the situation demands.

The Kolkata-headquartered SER zone is spread over the states of West Bengal, Odisha and Jharkhand.

The Indian Coast Guard (ICG) said it is on high alert and has mobilised its vessels and aircraft to respond swiftly to any contingency over the Bay of Bengal.

It said the ICG has mobilised its vessels and aircraft, positioning them strategically to respond swiftly to any emergency situations. The NDRF said it has deployed 13 teams so far across south Bengal to respond to any emergency situation.

The storm is likely to bring very heavy rainfall in south Bengal districts on October 24 and 25, the IMD said.

Heavy to very heavy rainfall with extremely heavy downpour at one or two places is likely in the coastal districts of South 24 Parganas, Paschim Medinipur, Purba Medinipur and Jhargram districts.

Heavy to very heavy rainfall is likely in Kolkata, Howrah, Hooghly, North 24 Parganas, Purulia and Bankura districts between October 24 and 25, the Met said. 

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

Bengaluru:

Downpour since early Tuesday threw life out of gear in central and southern parts of Karnataka, including the state capital Bengaluru. India Meteorological Department officials said a low-pressure area that formed over the Bay of Bengal was the trigger for the widespread rainfall.

They said the arid regions of northern parts of the state would witness similar weather conditions in the next 24 hours. “This situation will prevail for the next three to four days,” an official said.

Students and office-goers in Bengaluru in particular had a tough time following road congestion due to rain. Many low-lying areas were waterlogged.

The city recorded 16 mm rainfall in the last 24 hours till 8.30 am on Tuesday.

IMD has issued a yellow alert — indicating worsening weather conditions that could disrupt daily life — for the districts of Tumakuru, Mysuru, Kodagu, Chikkamagaluru, Hassan, Kolar, Shivamogga and Chikkaballapura in addition to coastal Karnataka.

A yellow alert means heavy rainfall between 6 cm and 11 cm. 

Shimla:

A total of 117 roads were closed for vehicular traffic in Himachal Pradesh as rain continues to lash several parts of the state, officials said on Friday.

The meteorological office has warned of moderate flash flood risk in parts of Shimla and Sirmaur districts until Saturday.

Light rain continued in some parts of the state and Guler recorded the maximum rainfall at 64.2 mm since Thursday evening, followed by Palampur (46.4 mm), Dharamshala (41 mm), Slapper (27.1 mm), Chopal (21.4 mm), Sangla (20.8 mm), Kalpa (20.3 mm) and Naina Devi (18.4 mm).

A maximum of 81 roads are closed in Shimla, 21 in Mandi, 10 in Kangra, three in Kullu and one each in Bilaspur and Sirmaur district, as per the State Emergency Operation Centre (SEOC).

The number of power and water supply schemes affected by the rain in the state stand at 34 and 11, respectively, the SEOC said.

Since the monsoon onset in Himachal Pradesh on June 27, the state’s rainfall deficit till date stands at 20 per cent, with the state receiving 545.2 mm rainfall against an average of 682.4 mm.

According to the officials, 165 people died in rain-related incidents during the ongoing monsoon season from June 27 till Thursday (September 12), while 30 are still missing. The state has suffered losses to the tune of Rs 1,323 crore, they said. 

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

Tragedies like the Wayanad landslides repeat themselves partly because their lessons are not brought to bear on our understanding of the local amplifiers of extreme events. A view of a mountain of the Western Ghats in Wayanad, Kerala, November 15, 2022.
| Photo Credit: Nakkeeran Raveendran/Unsplash

At no place on the earth is the climate risk zero — yet when natural hazards strike, the resulting loss of lives, livelihoods, and assets sting. Disaster management and recovery play a crucial role in alleviating the pain. Unfortunately, however, a blame game may follow asking whether early warnings could have averted the tragedy.

Any early warning that may have been issued will always start with the weather forecast for the area where the hazard manifested. Proactively mitigating disasters instead of always managing them after they happen requires climate risk outlooks that go out to a decade or longer.

Further, post-facto analyses of deadly disasters — like the landslides in Wayanad, Kerala, on July 30 — often do not appreciate the fact that broad warnings of risks can hardly be translated to specific actions. For example, if we declare the entire Western Ghats to be vulnerable to landslides, governments can develop and enforce regulations to protect the whole range from deforestation, development, monoculture plantations, etc.

However, doing so will mitigate some landslides; it won’t get rid of extreme events induced by climate change anytime soon. Some landslides will occur anyway even if the Ghats enjoy the fullest protections from human perturbations because the risk is never zero.

Predictions for disaster management, mitigation

Similarly, the predictions of models will also always be imperfect. If we are to improve their ability to predict extreme events more accurately (in terms of their location and amplitude), we need to fully understand the effects of local drivers that could exacerbate the climate’s effects. After every extreme event, someone claims global warming is a contributor — yet the relationship between local events and global warming complicates the truth of such claims.

The drivers of climate extremes originate from a far-away place but are usually exacerbated by some regional, location-specific factors.

For instance, a 2015 study (which included this author) indicated that coastal sea surface temperatures have a strong influence on heavy rain along India’s west coast. Wayanad district lies about 80 km from this coast. Monsoon winds stream across the equator and continue to load up on moisture as they turn southwesterly and head towards the Western Ghats. As they approach the coast, the winds sense they will have to climb the Western Ghats and slow down. Slower winds reduce the evaporation over the coastal ocean and the coastal waters tend to warm up — and warm waters exert a strong control on the atmosphere and rainfall.

Such a warming is typically seen up to 10 days ahead of a heavy rain event over the coastal ocean. Global models typically miss such local, small-scale warming or cooling processes and tend to underestimate the amount of rain in an extreme event. Enhancing the coastal observations and assimilating them into forecast models is expected to improve predictions.

This is also why adopting location-specific measures like legal protections for biodiversity can help mitigate disasters. Governments can also bolster their regulatory strategies using predictions of the climate up to a decade in the future and combining each prediction with hyperlocal risks.

Similarly, national and local governments will have to work together and share monitoring, reporting, and verification responsibilities to mitigate risk. Finally, all these consequences of the relationship between global warming and local events will have to be accounted for in budgetary provisions. Otherwise, mitigating disasters may not be sustainable.

Further, predictions with a lead time of a few weeks could help disaster management personnel mobilise towards locales with the highest imminent risk and avoid surprises. This is where the location-specific drivers can help ensure the hyperlocal risk information is reliable in crisis times.

Coarse global to fine hyperlocal

Global models provide seasonal outlooks and predictions at the short (1-3 days), medium (3-10 days), and extended (2-4 weeks) ranges. They have been getting better at offering outlooks of the monsoon, the El Niño and La Niña events, and early extreme-event warnings. Researchers around the world — in academia and national laboratories — constantly diagnose imperfections in these models and remove them.

One particular approach to improving the models is called downscaling, especially to enhance predictions of extreme events like small-scale heavy rain. In downscaling, researchers use a global model to drive local predictions in a higher resolution regional model to capture the weather at scales that the global model will miss.

Of late, they have been executing such two-tier strategies using techniques in artificial intelligence and machine learning (AI/ML). Their costs are lower than those incurred by running a high-resolution regional model. Such AI/ML approaches are also many times faster than regional models, further lending themselves to more effective disaster management.

Spotting location-specific amplifiers

Tragedies like that in Wayanad on July 30 tend to repeat themselves partly because their lessons are not always brought to bear on our understanding of the local amplifiers of extreme events. Simple changes in land use patterns — associated with urbanisation, say, or the deforestation of mountain slopes — could lead to a crushing cloudburst and or a punishing hailstorm.

The relatively more coarse resolutions of global models — which deal with changes in the tens of kilometres — tend to miss such local features and add to their imperfections. To acquire a better sense of the effects of these features and thus enable regional dynamic or AI/ML downscaling for hyperlocal predictions, we need more local data of weather and climate variables.

Disaster mitigation efforts are crucial to weather-proof the country and make it more climate-resilient at longer timescales. To this end we urgently need a data network that supports the mapping of local extreme event amplifiers.

Raghu Murtugudde is a professor, IIT Bombay, and emeritus professor, University of Maryland.

Pedestrians walk on a road amid heavy monsoon rains in Navi Mumbai, July 13, 2024.
| Photo Credit: PTI

We are in the middle of the monsoon season of 2024. The monsoon onset happened on time on May 30 but its evolution thus far has sprung some surprises. The distribution of rainfall looks as patchy as ever, albeit with some unexpected patterns. The seasonal outlook by the India Meteorological Department (IMD) has predicted a normal to above-normal amount of rainfall based on the expectation that a La Niña appears to be likely. But this La Niña appears to be playing truant so far.

After the on-time onset, the northward movement of the monsoon trough seemed to be quite rapid. But then the trough stalled and produced a fairly dry June for large swaths of the country. Even the entire stretch of the Western Ghats received below-normal rainfall levels into July. An unusual pattern of excess rain stretching from south to north persists to this day, with dry patches over large parts of Uttar Pradesh, Bihar, Jharkhand, and Odisha, as well as northwestern India into Jammu & Kashmir.

A useful index with disclaimers

I have used this analogy before and it still works well. As the Sun crosses into the Northern Hemisphere and starts warming the Indian subcontinent like a popcorn kettle, monsoon systems pop like kernels of corn in the kettle. The temperature inside the kettle will be essentially uniform but kernels will still pop randomly, here and there.

These kernels are like the rainfall: its patchy pattern is visible on day-to-day data as well as data averaged over the whole season and even over a whole decade.

However, the convenience of using the ‘all India monsoon rainfall’ index for providing seasonal outlooks — as the IMD does — is undermined by the uncertainty India’s farmers face at the local levels. Our forecasts of rain days or weeks ahead of a given date are getting better but they concomitantly increase the demand for and value of even more accurate and hyperlocal forecasts.

This demand is not only from farmers but also water managers and energy companies, among others. We need a broader perspective of the monsoon circulation to help understand where the limitations exist and how they can be resolved.

The circulation beyond India

People know the summer monsoon as the “southwest monsoon” because the winds sweep in from the southwest over the Arabian Sea into mainland India, across the Western Ghats. The western edge of the winds graze the African highlands, and some experts have often argued that they are critical for steering the southwesterly winds. The active Bay of Bengal, which is full of convective events, can be expected to ‘pull’ the winds towards India as well.

Convection in the atmosphere refers to rain events that release condensation heat.

The heating over West Asia and even the dust from the deserts there contribute to the monsoon circulation and its variability, as well as the changes it is experiencing due to global warming. Pakistan is very much a part of the monsoon circulation and it experiences high rainfall variability. This is because the edges of the monsoon circulation tend to be highly variable.

The land encompassed by the Himalayan foothills, and thus Nepal and Bhutan as well as the eastern edge of the Bay of Bengal (including Myanmar), is also involved in regulating the monsoon and the transfer of its heat to the Indian subcontinent. Bangladesh is of course ensconced between Northeast India and mainland India. We don’t pay attention to the role of heating over Bangladesh or the ocean-land-atmosphere dynamics that creates the beautiful monsoon and its heartbreaking vagaries every year.

The heating centres over the subcontinent are very strong and they maintain a sustained demand for moisture to sustain the convection centers. Indeed, the circulation that sweeps the oceans and the subcontinent can’t be represented accurately in rainfall models unless we capture all the heating centres from Pakistan and West Asia in the west to Myanmar in the east, and the Indian Ocean from about 10º south to its northern edge against the subcontinent.

Detail gaps beyond India’s borders

As hard as the IMD and its labs are working to improve their monsoon forecasting abilities at all timescales, their efforts are also undermined by a lack of rainfall and other weather data over parts of the subcontinent beyond India. Satellites can help to some extent but the amount of data available in near real-time to initiate forecasts is often quite inadequate.

These rainfall models are global for most subcontinent-scale forecasts even though the IMD also develops regional model forecasts, at the levels of cities, and at the national scale. The global models ingest data about the oceans and the planetary atmosphere to initiate forecasts and the volume of data can appear to be large and adequate — but this is often not the case.

Monitoring the whole subcontinent

India has been fortunate enough to have a rainfall monitoring network since the 19th century, and the advantages are now bearing fruit with investments in forecasting infrastructure. At this point, we need a few important steps to reach the next level in forecast accuracy. This is also essential to sustain continuous economic growth for India, especially in terms of food, water, and energy security.

In fact, even our national security depends heavily on weather and climate forecasts — for India as well as for the country’s more climate-vulnerable neighbors. Debilitating natural disasters can quickly turn into national security concerns, especially with some neighbors having to seek aid from non-allies.

India does share its forecasts with some countries but it may benefit more by extending this strategy to also establish a broad network to monitor weather and climate across the subcontinent. Improved forecasts for the subcontinent will make everybody safe and less vulnerable. This can only mean better opportunities for safety for all, including food, water, and energy, as well as better health.

Raghu Murtugudde is a professor, IIT Bombay, and emeritus professor, University of Maryland.

Dehradun:

The ongoing Char Dham Yatra in Uttarakhand will remain suspended on Sunday due to the heavy rain alert issued by the India Meteorological Department (IMD) for July 7-8.

Garhwal Divisional Commissioner Vinay Shankar Pandey issued an order in this regard late Saturday and urged pilgrims en route to the temples to avoid proceeding further and stay where they are.

He appealed to pilgrims not to travel beyond Rishikesh in view of the weather department’s heavy rain forecast and landslides on various routes.

Pilgrims have been advised to proceed further only when the weather is clear.

The IMD on Saturday issued an alert for heavy to very heavy rainfall in all the districts of Uttarakhand on Sunday and Monday.

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

New Delhi:

The national capital recorded a maximum temperature of 37.1 degrees Celsius on Sunday, a couple of days after Delhi was lashed by 228.1 mm of rains, bringing the city to its knees and claiming multiple lives.

According to the weather department, 9 mm of rain was recorded in the city on Sunday, while humidity was 60 per cent at 5.30 pm.

The India Meteorological Department has predicted overcast conditions and heavy rain on Monday and Tuesday. It also said that heavy rains at isolated places in Delhi and adjoining states are very likely till July 4.

The weather department has predicted moderate rain and thunderstorm accompanied with gusty winds on Sunday night.

The Air Quality Index (AQI) of the national capital was in the “moderate” category with a reading of 118 at 6 pm, according to the Central Pollution Control Board.

An AQI between zero and 50 is considered “good”, 51 and 100 “satisfactory”, 101 and 200 “moderate”, 201 and 300 “poor”, 301 and 400 “very poor”, and 401 and 500 “severe”. 

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)