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Scientists deliberate better prediction of extreme weather events at IITM, Pune

Prof. Kerry Emanuel highlighted the importance of extreme events prediction. "Three times as many people live along the coasts as compared to 1971. This is much higher than the rate of population growth and highlights the need for better cyclone predictions," he said.

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Last Updated: Nov 25, 2019, 09.40 PM IST|Original: Nov 25, 2019, 09.40 PM IST
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Although climatologically, tropical cyclone over lower latitude near Kerala coast are relatively rare, this event posed a challenge to the numerical forecaster, as it required enhancing the model fidelity to predict such rare extreme event with sufficient lead time.
Present status and future Prospect (IP4) & Annual Climate Change Workshop was inaugurated on the November 25, 2019 by M. Rajeevan, Secretary, MoES, Government of India. Prof Kerry Emanuel , Cecil & Ida green professor of atmospheric science and co-director, Lorenz Center, MIT, USA and Prof. Graeme Stephens, director of the centre for climate sciences JPL, NASA, USA and the director of IITM, Prof. R. S. Nanjundiah along with the executive director for the centre for climate change research (CCCR), Dr. R. Krishnan and the convener of the IP4 workshop, Dr P. Mukhopadhyay were present.

Prof. Kerry Emanuel highlighted the importance of extreme events prediction. "Three times as many people live along the coasts as compared to 1971. This is much higher than the rate of population growth and highlights the need for better cyclone predictions," he said.

Prof. Stephens said that precipitation all over the world will increase as a global mean with further warning. But regional changes will not be the same. Precipitation changes will be non-linear’. These two issues show the need to improved prediction skill of extreme precipitation events and tropical cyclones.

Dr. Rajeevan showed the improvement in India saying that our predictions of weather and climate have improved over the last few years because of improved data assimilation and better computer models. "We now have ensemble simulations at par with any other country. In fact, this unusual monsoon season had five cyclone and we were able to predict them all in advance and with high accuracy.

The workshop gives an opportunity to highlight the developments of the earth system model developed by CCCR. "We are very happy to report that CCCR has developed the first model to be a part of the international Coupled Model Intercomparison Project Phase 6 (CMIP6) contributing the Intergovernmental Panel on Climate Change sixth assessment report. The reason to conduct the 10th annual climate change workshop along with IP4 was to make the most of the international expertise attending the IP4 workshop," said Dr Krishnan.

Over the next four days, several experts from around the world will deliberate on these and related topics and lead to exchange of knowledge across different institutions globally.

During 2017 November/December and during monsoon season of 2018, the southern state of India: Kerala experienced unusually extreme weather systems causing unprecedented damage of public property and loss of life. The event that struck during 29 November – 6 December 2017, was the tropical cyclone (TC) “Ockhi”. TC “Ockhi” was a very severe cyclonic storm that devastated the state of Kerala.

Although climatologically, tropical cyclone over lower latitude near Kerala coast are relatively rare, this event posed a challenge to the numerical forecaster, as it required enhancing the model fidelity to predict such rare extreme event with sufficient lead time. The other event that shook the whole globe was the exceptionally heavy rainfall over Kerala during the month of August 2018. The state received around 164% more rainfall than its climatology during 1-19 August.

Such unprecedented and exceptionally heavy rain caused wide spread flooding over the whole state of Kerala and caused loss of precious life and immense damage to public property. Apart from these events, there were other extreme events over Mumbai, Chennai and many other places over India such as Uttarakhand heavy rain and flood etc., which posed the challenge of accurate forecasting of extremes with longer lead time.

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