Strengthening Climate Monitoring and Weather Forecasting Systems in India
UPSC / SSC current affairs note · IR
Why in news
The government has announced multiple measures to strengthen climate monitoring and weather forecasting systems in response to increasing frequency and intensity of extreme weather events. These include adoption of high-performance computing, AI/ML tools, and satellite-based observations. The initiatives aim to improve forecast accuracy at the panchayat level and enhance disaster preparedness.
Background
India faces rising extreme weather events due to climate change. The Ministry of Earth Sciences (MoES) operates a network of observatories, automatic weather stations, Doppler radars, and satellites. Mission Mausam and various modeling systems are used for short to long-term forecasts. The government is now integrating AI/ML and high-resolution models to improve predictions.
Key facts
Government has adopted high-performance computing (HPC) and advanced technologies for high-resolution numerical weather prediction (NWP) and climate modeling.
MoES operates a network including manual observatories, AWS, ARG, Agro-AWS, Doppler Weather Radars (DWR), upper-air observatories, and satellites.
Under Mission Mausam, two global modeling systems are operational: IMD's Global Forecast System (GFS) and NCMRWF's Mithuna-FS, both at 12 km horizontal resolution.
India Forecast System (IndiaFS) at 6 km resolution provides panchayat-level forecasts, improving local weather accuracy.
IMD, in collaboration with Ministry of Panchayati Raj, has launched panchayat-level weather forecasts covering nearly all gram panchayats, available on digital platforms like e-GramSwaraj, Meri Panchayat App, and Mausamgram.
AI/ML is used for climate change detection, attribution, and forecasting; three AI-based global models (Pangu Weather, FourCastNet, GraphCast) are routinely used.
Indigenous AI/ML tools developed include nowcasting tools and downscaled urban forecasts.
Satellites like INSAT-3DR, INSAT-3DS, and Oceansat-3 are used for cyclone prediction, storm monitoring, and landfall assessment.
Satellite observations are integrated with ground observations and NWP models to enhance forecast accuracy and timeliness.
ISRO uses advanced remote sensing and GIS technologies for systematic monitoring of Himalayan glaciers' extent, mass, movement, and dynamics.
Prelims pointers
- Ministry of Earth Sciences (MoES)
- Mission Mausam
- Global Forecast System (GFS) – IMD
- Mithuna-FS – NCMRWF
- India Forecast System (IndiaFS)
- INSAT-3DR, INSAT-3DS, Oceansat-3
- e-GramSwaraj, Meri Panchayat App, Mausamgram
- Pangu Weather, FourCastNet, GraphCast
- Doppler Weather Radar (DWR)
- Automatic Weather Station (AWS), Automatic Rain Gauge (ARG)
Mains angles
- GS3 Disaster Management: Role of technology in early warning systems and disaster risk reduction.
- GS3 Science and Technology: Application of AI/ML and HPC in weather forecasting and climate modeling.
- GS3 Environment: Climate change monitoring and adaptation strategies.
- GS2 Governance: Panchayat-level forecasting and digital platforms for last-mile delivery of weather information.