Syllabus: GS III Disaster and Disaster Management.
Examine the role of Mission Mausam in strengthening India’s weather forecasting capabilities. Discuss the challenges and opportunities associated with leveraging advanced technologies for enhanced disaster preparedness and climate resilience across different sectors.
Introduction
Weather forecasting plays a critical role in disaster preparedness, agriculture, aviation, energy, and environmental monitoring. In this context, Mission Mausam, approved by the Union Cabinet with a budget of ₹2,000 crores over two years, aims to strengthen India’s weather forecasting capabilities, making the nation “Weather Ready” and “Climate Smart.” The initiative reflects India’s commitment to enhancing its climate resilience and disaster management systems in the face of increasing extreme weather events driven by climate change.
Role of Mission Mausam in Strengthening Weather Forecasting Capabilities
- Enhanced Observational Networks:
Mission Mausam seeks to expand India’s observational infrastructure by increasing the number of Doppler radars, supercomputers, and other advanced instruments. Improved real-time data collection and enhanced resolution models (from 12 km to 6 km) will allow for more accurate, localized weather predictions, particularly for small-scale weather phenomena like thunderstorms and heavy rainfall.
Example: The use of Doppler radar technology will improve rainfall predictions, crucial for regions prone to floods and droughts, thereby enhancing preparedness and response capabilities. - Cloud Chamber and Weather Modifications:
The establishment of a cloud chamber at the Indian Institute of Tropical Meteorology (IITM) aims to study cloud behavior under rising temperatures and explore artificial rain-making techniques like cloud seeding. These technologies are essential for managing extreme weather events, particularly in flood-prone and drought-affected regions.
Example: Cloud seeding initiatives in Maharashtra, under CAIPEEX, have shown potential in augmenting rainfall and mitigating droughts, thus contributing to long-term climate resilience. - Improved Weather Models and Short-Term Forecasting:
The mission’s focus on increasing the frequency of nowcasts (short-term weather forecasts) from every 3 hours to every hour ensures timely warnings for rapidly changing weather events, such as flash floods, landslides, and cyclones.
Example: In regions like Himachal Pradesh, enhanced nowcasting capabilities could have minimized the impact of recent flash floods by providing real-time, accurate warnings. - Mausam GPT – AI-Powered Weather Chatbot:
The development of Mausam GPT by the India Meteorological Department (IMD) will enhance accessibility to weather information through AI-powered platforms, providing timely updates in both text and audio formats. This will improve awareness, particularly in rural and remote areas, facilitating better disaster preparedness.
Challenges in Integrating Advanced Technologies for Disaster Preparedness and Climate Resilience
- Lack of Adequate Infrastructure and Resources:
Despite the budget allocation, regions with poor connectivity and inaccessible terrain may struggle to fully implement advanced observational networks, leading to uneven access to weather information.
Example: Remote, hilly regions like the Western Ghats often lack sufficient radars and monitoring stations, hampering real-time data collection and forecasting. - Data Gaps and Quality Issues:
Inconsistent data collection due to outdated equipment, inadequate training, and limited coordination between agencies hinder the integration of advanced forecasting models.
Example: In recent disasters like the Wayanad landslides and flash floods in Himachal Pradesh, insufficient and fragmented data contributed to delayed responses. - Policy and Institutional Barriers:
Integrating advanced weather technologies across sectors requires coherent policy frameworks and institutional collaboration. Poor coordination between agencies such as IMD, NHAI, and the Ministry of Agriculture could undermine efforts to ensure timely warnings and effective response mechanisms.
Example: In the energy sector, lack of integration of weather forecasts into renewable energy planning has hindered the optimal utilization of wind and solar resources.
Opportunities in Leveraging Advanced Technologies for Climate Resilience
- Integration of AI and Machine Learning (ML):
Advanced AI algorithms can improve the accuracy of weather models, allowing for real-time predictive analytics and dynamic risk assessment.
Example: AI-driven tools like Mausam GPT can enhance weather predictions, helping in agriculture, aviation, and disaster management sectors. - Enhanced Inter-Sectoral Collaboration:
Integrating weather forecasting with sectors such as agriculture, disaster management, and renewable energy can foster better climate resilience. Real-time weather data can be used to optimize irrigation schedules, flood management strategies, and disaster response plans.
Example: Better coordination between IMD and agriculture ministries can enhance early warning systems, helping farmers plan for planting and harvesting based on weather conditions. - Community-Based Adaptation Strategies:
Empowering local communities, particularly vulnerable populations, through awareness campaigns and capacity-building initiatives can enhance their resilience to weather-related disasters.
Example: In regions like Sikkim and Himachal Pradesh, community-based forecasting systems can complement technological advancements to reduce vulnerabilities. - Financial and Technological Support from International Bodies:
Missions like Mission Mausam can benefit from global partnerships and funding for capacity building and technology transfer.
Example: International organizations like the WMO (World Meteorological Organization) can assist in improving observational networks, especially in data-sparse regions.
Conclusion
Mission Mausam represents a critical step towards making India more resilient to the growing threats of extreme weather events. By strengthening observational networks, improving weather models, and adopting advanced technologies like AI and cloud seeding, the mission holds the potential to enhance weather forecasting capabilities significantly. However, overcoming challenges such as data gaps, institutional coordination, and infrastructure deficits is essential to realizing these opportunities. A comprehensive, multi-sectoral approach, backed by international cooperation and community involvement, will ensure that India remains weather-ready and climate-smart in the face of increasing climate risks.
