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Better Climate Adaptation Can Be Achieved Through Earlier Prediction Of Extreme Event, Say Scientists

Predicting events like El Nino, droughts or extreme rainfall could save thousands of lives and avoid billions in economic losses, say experts

High Impact Climate Events: Better Adaptation Through Earlier Prediction, Say Scientists
Experts devise new framework to predict extreme climate events beforehand that can help in making better adaptation strategies
Highlights
  • Extreme events like floods often arrive with no warning: Experts
  • Climate change is causing extreme event at various places: Experts
  • El Nino can be predicted a year earlier: Experts

Washington: The prediction of high impact climate phenomena can be substantially improved by a new mathematical approach that analyses the connectivity and patterns between geographical locations, scientists said in a new publication. This can potentially save thousands of lives and avoid billions in economic losses. Prediction times for events like El Nino, monsoons, droughts or extreme rainfall could be increased substantially, to a month or in some cases even a year in advance, depending on the type of the event.

Also Read: Was COP26 Glasgow Pact A Win For Climate? Time Will Tell

The new framework can thus become key for improving adaptation to the global warming crisis. The findings were published in the Proceedings of the US National Academy of Sciences (PNAS).

“The new forecasting approach has, in several instances over the past years, proven to be highly efficient in predicting different climate phenomena much earlier than before. El Nino for instance could be predicted up to one full year early, compared to about six months with the standard prediction methods,” explained Josef Ludescher from the Potsdam Institute for Climate Impact Research (PIK), lead author of the ‘Perspective’ article published in PNAS. Ludescher continued,

The onset of the Indian Summer Monsoon in central India, vital for the economy in this region, was predicted more than a month in advance, much earlier than the forecast currently used, thanks to the new approach.

Extreme events like floods, heatwaves or droughts often arrive with little or no warning time at all, making effective short-term adaption challenging if not impossible. The new prediction framework fundamentally improves this, as Jurgen Kurths from PIK, a pioneer of network application to climate-phenomena forecasting and co-author of the paper, underlined. He told,

Currently, for instance, there is no reliable prediction of heavy rainfall in the Easter Central Andes leading to floods and landslides with devastating impacts for the inhabitants in that part of South America. Our network-based approach can predict those events up to two days in advance – that is crucial time for the people to prepare, save lives and limit damages.

A mathematical approach to help save lives Traditional weather and climate forecasting rely predominantly on numerical models imitating atmospheric and oceanic processes. These models, while generally very useful, can’t perfectly simulate all underlying processes and phenomena like monsoon onsets, floods or droughts might be predicted too late. This is where network-based forecasting comes into play. Ludescher explained,

“As opposed to looking at a huge number of local interactions, which represent physical processes like heat or humidity exchange, we look directly at the connectivity between different geographical locations, which can span continents or oceans. This connectivity is detected by measuring the similarity in the evolution of physical quantities like air temperatures at these locations. For instance, in the case of El Nino, strong connectivity in the tropical Pacific tends to build up in the calendar year before the onset of the event. That’s a fundamentally different approach from traditional numerical modelling used in weather and climate forecasts. It does not simulate the entire Earth system, but analyses large-scale connectivity patterns in observational data.

These patterns, that are the connectivity between the locations and their evolution in time, can provide critical new information for forecasting – and, so we hope, make the respective regions safer. With this Perspective, we have brought together several success stories that demonstrate the scientific power of the network approach for forecasting – and, in consequence, for potentially saving thousands of lives and avoiding billions of economic costs, states co-author Maria Martin, also at PIK. Hans-Joachim Schellnhuber, former Director of the institute, concluded.

Also Read: Factbox: What’s In The Glasgow UN Climate Pact?

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

NDTV – Dettol have been working towards a clean and healthy India since 2014 via Banega Swachh India initiative, which is helmed by Campaign Ambassador Amitabh Bachchan. The campaign aims to highlight the inter-dependency of humans and the environment, and of humans on one another with the focus on One Health, One Planet, One Future – Leaving No One Behind. It stresses on the need to take care of, and consider, everyone’s health in India – especially vulnerable communities – the LGBTQ populationindigenous people, India’s different tribes, ethnic and linguistic minorities, people with disabilities, migrants, geographically remote populations, gender and sexual minorities. In wake of the current COVID-19 pandemic, the need for WASH (WaterSanitation and Hygiene) is reaffirmed as handwashing is one of the ways to prevent Coronavirus infection and other diseases. The campaign will continue to raise awareness on the same along with focussing on the importance of nutrition and healthcare for women and children, fight malnutrition, mental wellbeing, self care, science and health, adolescent health & gender awareness. Along with the health of people, the campaign has realised the need to also take care of the health of the eco-system. Our environment is fragile due to human activity,  that is not only over-exploiting available resources, but also generating immense pollution as a result of using and extracting those resources. The imbalance has also led to immense biodiversity loss that has caused one of the biggest threats to human survival – climate change. It has now been described as a “code red for humanity.” The campaign will continue to cover issues like air pollutionwaste managementplastic banmanual scavenging and sanitation workers and menstrual hygiene. Banega Swasth India will also be taking forward the dream of Swasth Bharat, the campaign feels that only a Swachh or clean India where toilets are used and open defecation free (ODF) status achieved as part of the Swachh Bharat Abhiyan launched by Prime Minister Narendra Modi in 2014, can eradicate diseases like diahorrea and the country can become a Swasth or healthy India.

World

26,27,61,966Cases
22,35,18,265Active
3,40,28,506Recovered
52,15,195Deaths
Coronavirus has spread to 196 countries. The total confirmed cases worldwide are 26,27,61,966 and 52,15,195 have died; 22,35,18,265 are active cases and 3,40,28,506 have recovered as on December 1, 2021 at 3:56 am.

India

3,45,96,776 8,954Cases
99,0231,520Active
3,40,28,506 10,207Recovered
4,69,247 267Deaths
In India, there are 3,45,96,776 confirmed cases including 4,69,247 deaths. The number of active cases is 99,023 and 3,40,28,506 have recovered as on December 1, 2021 at 2:30 am.

State Details

State Cases Active Recovered Deaths
Maharashtra

66,35,658 678

11,226 299

64,83,435 942

1,40,997 35

Kerala

51,41,814 4,723

44,314 824

50,57,368 5,370

40,132 177

Karnataka

29,96,148 291

6,445 462

29,51,492 745

38,211 8

Tamil Nadu

27,26,917 720

8,244 47

26,82,192 758

36,481 9

Andhra Pradesh

20,72,909 184

2,149 47

20,56,318 134

14,442 3

Uttar Pradesh

17,10,399 12

89 3

16,87,399 8

22,911 1

West Bengal

16,16,083 705

7,731 2

15,88,866 694

19,486 13

Delhi

14,40,934 34

287 2

14,15,549 32

25,098

Odisha

10,49,108 228

2,188 23

10,38,509 203

8,411 2

Chhattisgarh

10,06,813 34

318 0

9,92,902 34

13,593

Rajasthan

9,54,785 15

193 6

9,45,637 9

8,955

Gujarat

8,27,475 40

275 13

8,17,108 27

10,092

Madhya Pradesh

7,93,170 20

119 7

7,82,523 27

10,528

Haryana

7,71,709 17

163 2

7,61,492 19

10,054

Bihar

7,26,223 4

36 3

7,16,524 7

9,663

Telangana

6,75,994 196

3,591 10

6,68,411 184

3,992 2

Assam

6,16,852 144

2,625 30

6,08,124 109

6,103 5

Punjab

6,03,279 21

325 4

5,86,352 22

16,602 3

Jharkhand

3,49,244 12

98 3

3,44,006 9

5,140

Uttarakhand

3,44,255 28

141 9

3,36,706 19

7,408

Jammu And Kashmir

3,36,852 171

1,625 1

3,30,751 172

4,476

Himachal Pradesh

2,27,195 102

834 10

2,22,513 91

3,848 1

Goa

1,78,928 38

284 8

1,75,260 30

3,384

Mizoram

1,35,175 365

3,751 54

1,30,927 415

497 4

Puducherry

1,28,924 31

284 12

1,26,768 43

1,872

Manipur

1,25,205 36

649 6

1,22,579 40

1,977 2

Tripura

84,805 14

81 3

83,900 10

824 1

Meghalaya

84,480 19

294 9

82,713 9

1,473 1

Chandigarh

65,465 9

65 7

64,580 2

820

Arunachal Pradesh

55,276 3

35 0

54,961 3

280

Sikkim

32,242 9

124 3

31,715 6

403

Nagaland

32,122 13

133 7

31,293 20

696

Ladakh

21,578 38

276 26

21,088 12

214

Dadra And Nagar Haveli

10,683

1 0

10,678

4

Lakshadweep

10,394

24 0

10,319

51

Andaman And Nicobar Islands

7,683

6 2

7,548 2

129

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