📷 Image: Wikimedia Commons / Basile Morin
Weather
Monsoon Ends in Tri‑City as Rainfall Drops 15.9%, Machine‑Learning to Forecast Future Showers
✍️ Amar Ujala · Mohali
🗓 01 Oct 2026, 09:15 AM
👁 13
The monsoon season officially concluded in the Chandigarh‑Mohali‑Panchkula region on September 30, with total rainfall 15.9% lower than the seasonal average. Meteorologists now plan to use machine‑learning models to predict when and how much rain will return.
The monsoon spell that typically blankets the northern Indian plains came to a formal close on September 30 in the tri‑city area comprising Chandigarh, Mohali and Panchkula. Local weather stations recorded the last measurable rainfall on that day, marking the official end of the season for the region.
According to data released by the India Meteorological Department, the cumulative rainfall during the current monsoon was 15.9% below the long‑term average for the same period. The shortfall has raised concerns among farmers and water‑resource managers who rely on a full monsoon to replenish groundwater and fill reservoirs.
In response, the department announced the deployment of machine‑learning algorithms to generate short‑term precipitation forecasts. The models, trained on historical satellite imagery and ground observations, aim to predict the timing and intensity of any post‑monsoon showers that may arrive in the coming weeks.
Officials said the new predictive tools could help authorities issue timely advisories, optimise irrigation schedules, and better manage flood‑risk in downstream areas. While the monsoon has ended, the region remains vigilant for any unexpected rain events that could affect agriculture and urban water supply.
The initiative reflects a broader push across Indian meteorological services to incorporate artificial intelligence into climate monitoring, with the goal of delivering more accurate and actionable weather information to citizens and policymakers alike.
According to data released by the India Meteorological Department, the cumulative rainfall during the current monsoon was 15.9% below the long‑term average for the same period. The shortfall has raised concerns among farmers and water‑resource managers who rely on a full monsoon to replenish groundwater and fill reservoirs.
In response, the department announced the deployment of machine‑learning algorithms to generate short‑term precipitation forecasts. The models, trained on historical satellite imagery and ground observations, aim to predict the timing and intensity of any post‑monsoon showers that may arrive in the coming weeks.
Officials said the new predictive tools could help authorities issue timely advisories, optimise irrigation schedules, and better manage flood‑risk in downstream areas. While the monsoon has ended, the region remains vigilant for any unexpected rain events that could affect agriculture and urban water supply.
The initiative reflects a broader push across Indian meteorological services to incorporate artificial intelligence into climate monitoring, with the goal of delivering more accurate and actionable weather information to citizens and policymakers alike.