Residents say water scarcity, inadequate cooling infrastructure and heat-trapping tin sheds worsen summer conditions.
| Photo Credit: Shubhangi Kshitizia Saurav/Mahima Rao

Singapore:

Climate change is driving changes in rainfall patterns across the world, scientists said in a paper published on Friday, which could also be intensifying typhoons and other tropical storms.

Taiwan, the Philippines and then China were lashed by the year’s most powerful typhoon this week, with schools, businesses and financial markets shut as wind speeds surged up to 227 kph (141 mph). On China’s eastern coast, hundreds of thousands of people were evacuated ahead of landfall on Thursday.

Stronger tropical storms are part of a wider phenomenon of weather extremes driven by higher temperatures, scientists say.

Researchers led by Zhang Wenxia at the China Academy of Sciences studied historical meteorological data and found about 75% of the world’s land area had seen a rise in “precipitation variability” or wider swings between wet and dry weather.

Warming temperatures have enhanced the ability of the atmosphere to hold moisture, which is causing wider fluctuations in rainfall, the researchers said in a paper published by the Science journal.

“(Variability) has increased in most places, including Australia, which means rainier rain periods and drier dry periods,” said Steven Sherwood, a scientist at the Climate Change Research Centre at the University of New South Wales, who was not involved in the study.

“This is going to increase as global warming continues, enhancing the chances of droughts and/or floods.”

FEWER, BUT MORE INTENSE, STORMS

Scientists believe that climate change is also reshaping the behaviour of tropical storms, including typhoons, making them less frequent but more powerful.

“I believe higher water vapour in the atmosphere is the ultimate cause of all of these tendencies toward more extreme hydrologic phenomena,” Sherwood told Reuters.

Typhoon Gaemi, which first made landfall in Taiwan on Wednesday, was the strongest to hit the island in eight years.

While it is difficult to attribute individual weather events to climate change, models predict that global warming makes typhoons stronger, said Sachie Kanada, a researcher at Japan’s Nagoya University.

“In general, warmer sea surface temperature is a favourable condition for tropical cyclone development,” she said.

In its “blue paper” on climate change published this month, China said the number of typhoons in the Northwest Pacific and South China Sea had declined significantly since the 1990s, but they were getting stronger.

Taiwan also said in its climate change report published in May that climate change was likely to reduce the overall number of typhoons in the region while making each one more intense.

The decrease in the number of typhoons is due to the uneven pattern of ocean warming, with temperatures rising faster in the western Pacific than the east, said Feng Xiangbo, a tropical cyclone research scientist at the University of Reading.

Water vapour capacity in the lower atmosphere is expected to rise by 7% for each 1 degree Celsius increase in temperatures, with tropical cyclone rainfall in the United States surging by as much as 40% for each single degree rise, he said.

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

The proposed Pennar-Palar-Cauvery link canal connects the Mahanadi and Godavari rivers with the deficit rivers further south

These days, the term Artificial Intelligence (AI) seems to be everywhere. The public has come to view it with mixed perceptions. On one side, it is a problem-solver: AI has helped in monitoring heart problems and eye conditions and offered treatment options; AI predicts protein structure, and aids in the development of new drug molecules. Likewise, it predicts cyclones, monsoon strengths, etc. On the dark side are fears that jobs may be lost to thinking machines that work 24/7 and do not need a Diwali vacation, and may intrude on your privacy and misuse your data. But nobody doubts that AI will help us in addressing large-scale problems that require the analysis of huge data.

As India’s development gathers momentum, we are faced with the eventuality of resource limitations. We may need much more than we have. This is especially true of water — every year we see floods in parts of the country, and drought in others. Engineers have long dreamt of building links between our rivers to mitigate these problems. But uncertainties over the effects of such large-scale changes have stalled many initiatives.

Benefits of linking rivers

For the nation’s planners, minimising the water deficit has become a critical goal in this age of climate change and unpredictable weather. Can AI tools be used to make predictions on how to bring about change? Computational modelers at the IIT-ISM, Dhanbad and the NITs in Tripura and Goa have done just this while examining the proposed Pennar-Palar-Cauvery link canal.

This canal is part of a scheme to connect the flood-prone Mahanadi and Godavari rivers with the ‘deficit’ rivers further south. The link canal would aid half-a-million hectares in a chain of districts, from Nellore in Andhra Pradesh to Cuddalore in Tamil Nadu. Such proposals have a complex set of objectives, which can be modeled in the search for maximum benefits to the most people.

Fulfilling many objectives

In a multi-objective model, the goal is to achieve more than one objective optimally. For example, a farmer may wish to get the maximum yield of his crop with the minimum use of water. He would tweak his system to a point where he can no longer improve one objective without worsening the other.

The IIT-NIT team has presented a model that aims to improve the returns from farms, without depleting groundwater or wasting the water in rivers and reservoirs (Agricultural Water Management, v-279, 2023). They used data that has been collected over the years by the National Water Development Agency on (a) water levels before and after monsoons in the 1.2 lakh wells and tube wells in these districts; (b) crop-sowing patterns; (c) prevailing minimum support price and the cost and benefits to farmers. This AI-based modeling effort suggests that favourable outcomes will come with a few adjustments to the choice of crops that are grown in the two seasons of July and November. Collecting more detailed data will help such AI-based models in making more focused predictions.

(The article was written in collaboration with Sushil Chandani, who works in molecular modelling)