Warming oceans make it harder to forecast cyclones in Arabian Sea

Source: The post is based on the article “Warming oceans make it harder to forecast cyclones in Arabian Sea” published in The Hindu on 17th June 2023

What is the News?

Experts say cyclones in the Bay of Bengal are far more frequent and were better understood. But in recent times, the Arabian Sea is heating up more than average. This might create greater and increasingly stronger cyclones like Biparjoy.

About the IMD forecast of cyclones in the Arabian Sea and the Bay of Bengal

IMD forecast of cyclones in the Bay of Bengal: Cyclones in the Bay of Bengal, being far more frequent, were better understood. Cyclone Mocha in 2023, Cyclone Yaas in 2021, Cyclone Mandous in 2022 and Cyclone Gulab in 2021 in recent years have made landfall and followed recurring paths predicted by the IMD at least four or more days in advance.

IMD forecast of cyclones in the Arabian Sea: Cyclones in the Bay of Bengal, being far more frequent, were not better understood in comparison to Bay of Bengal cyclones. For instance, in the recent forecast of Biparjoy, the IMD earlier predicted it might reach land in either Kutch, Gujarat or Pakistan. Only four days before IMD first suggest that the storm would strike India.

What are the challenges in the IMD forecast of cyclones in the Arabian Sea?

IMD’s forecast of cyclones in the Arabian Sea is impacted by many reasons. Such as

a) Nearly 48% of cyclones here never reached land, as opposed to 13% in the Bay of Bengal,

b) Steering winds are the winds present in the upper reaches of the atmosphere. They influence the direction and recurving of cyclones. Heat within the ocean layers also determines the strength and duration of cyclones. IMD’s prediction models fully capture the heat within the ocean but not the  steering winds.

c) There are factors unique to the Arabian Sea that influence a cyclone’s intensity and movement. For example, The Arabian Sea has a much deeper — up to 40 metres – layer of warm water compared to the Bay of Bengal. These sub-surface values aren’t captured in the IMD’s prediction models