Rapid urban expansion and shifting land use patterns are increasingly undermining the accuracy of weather and climate forecasts, prompting India’s premier climate research institutions to overhaul how cities are represented in prediction systems. The challenge was underscored this week in Pune, where climate scientists and geospatial experts warned that conventional forecasting tools are struggling to keep pace with the speed at which Indian cities are transforming.
Senior officials from national climate and remote sensing agencies highlighted that land use and land cover once treated as slow-changing background variables have become highly dynamic in urban regions. Dense construction, loss of vegetation, new transport corridors and altered surface materials can now change local weather behaviour within days, not decades. For fast-growing cities, this directly affects rainfall estimates, heatwave alerts and wind predictions that urban planners and emergency agencies rely on. To respond, the Indian Institute of Tropical Meteorology is redesigning its forecasting framework to better capture real-time changes on the ground. Advanced land and vegetation models are being integrated to simulate how buildings, roads, tree cover and soil layers interact vertically with the atmosphere. According to officials involved in the programme, this is essential for cities where concrete expansion is altering heat retention, airflow and moisture exchange.
The implications extend well beyond meteorology. Urban economists and infrastructure planners note that inaccurate forecasts can disrupt construction schedules, raise insurance risks, strain drainage systems and worsen public health outcomes during extreme heat or intense rainfall. As Indian metros pursue higher densities and transit-oriented development, climate-aware planning is becoming a financial as well as environmental necessity. Artificial intelligence and machine learning are also playing a growing role. Climate agencies now process massive streams of data from ground instruments, satellites and atmospheric sensors using automated systems that detect patterns humans would miss. These tools are enabling highly localised forecasts, narrowing prediction grids to neighbourhood-scale resolutions. For city governments, such “hyperlocal” data can support flood preparedness, traffic management and energy demand planning.
Remote sensing experts at the event cautioned that demographic pressure is accelerating physical changes to the planet. With a global population nearing nine billion, human activity is reshaping land surfaces at an unprecedented rate through emissions, aerosols and engineered landscapes. India’s expanding satellite fleet now numbering more than 50 Earth-observation missions is seen as a critical asset for tracking these shifts and feeding predictive models. Urban planners argue that observation and forecasting must translate into policy action. Better land data can inform zoning decisions, green cover mandates and low-carbon mobility strategies such as electric transport, which reduces heat and pollution loads in dense neighbourhoods. As Indian cities push outward and upward, the message from scientists is clear: weather forecasting can no longer treat urban land as static. Adapting models to reflect constant change is becoming foundational to building climate-resilient, economically stable and liveable cities.
