Rapid intensification of tropical cyclones is challenging India's early-warning systems. Examine with reference to recent cyclones on the east coast.

Rapid intensification (RI) is a sharp rise in a cyclone's sustained winds within about a day. On IMD's scale, a storm can jump from Severe (48–63 kt) to Very Severe (64–89 kt) or higher before warnings catch up [2]. As the Bay of Bengal warms, RI is making warning lead-time the weakest link in India's cyclone management.

How RI strains early-warning systems

• Intensity error: models forecast a storm's track better than its strength. If the forecast category is too low, fewer villages are evacuated.
• Compressed lead-time: evacuation orders, fishing bans and shutdowns depend on the forecast category. RI leaves districts hours to act, not days.
• Hidden ocean heat: satellites measure the sea surface, but the deeper warm water that feeds sudden strengthening is hard to observe.

Evidence from recent east-coast cyclones

• Amphan (2020): it intensified rapidly over 24 hours and became the first Super Cyclonic Storm over the Bay since 1999 [3].
• Arnab (2026): IMD forecast winds of 115–125 km/h, gusting to 140 km/h, for landfall day [1]. The storm reportedly grew stronger than some models predicted. It then crossed the Andhra coast hours early and at night, cutting short the evacuation window.

Gaps in the warning chain

• Delayed infrastructure: a Parliamentary Standing Committee, cited by PRS, found that some early-warning projects for Odisha and Andhra Pradesh commissioned in 2015 had not started [4].
• Last-mile alerts: under the World Bank-funded NCRMP-II, the siren target was cut from 750 to 200 [5]. Sirens matter most for a night landfall, when people are asleep.

Way forward

• Plan for the worst plausible case: IMD and INCOIS should issue probabilistic intensity forecasts. Evacuation zones should be drawn for the upper category, not only the most likely one.
• Better ocean data: feed sub-surface heat readings from buoys and Argo floats into intensity models.
• Impact-based forecasting: target shutdowns to the zones most at risk, so warnings stay credible.
• Community warning teams: Bangladesh's Cyclone Preparedness Programme has 76,000+ volunteers [6]. Its experience shows that trained villagers can act within a short warning window.

RI does not make India's zero-casualty model obsolete. It shifts the task from predicting a storm precisely to preparing for uncertainty. Combining better ocean science with community-led, last-mile warning, as the Disaster Management Act, 2005 and the Sendai Framework envisage, can protect the gains Odisha and Andhra Pradesh have made as the Bay warms.