Context: The Prime Minister recently unveiled the IMD’s Vision Document 2047, which outlines a strategy to achieve almost perfect weather predictions for up to three days and 90% accuracy for five-day forecasts by the year 2047.
| What is IMD’s Vision Document 2047? The Vision Document sets a goal of achieving flawless forecast accuracy for up to three days and 90% accuracy for five-day forecasts by 2047. This ambitious objective underscore India’s dedication to significantly advancing its weather prediction capabilities. Key Areas of Focus: The plan prioritizes upgrading weather monitoring technologies, enhancing atmospheric data collection, and utilizing high-performance computing systems. It also stresses the need to develop sophisticated earth system models and adopt data-driven approaches, incorporating technologies like artificial intelligence and machine learning. Why does India need an Earth warning system? High Seismic Vulnerability:India is situated in a region of high seismic activity, with areas such as Himachal Pradesh, Uttarakhand, and the Northeast being particularly susceptible to earthquakes. Implementing early warning systems in these regions can mitigate damage and save lives. Example: The 2001 Gujarat earthquake resulted in significant destruction and loss of life. Risk to Densely Populated Urban Areas: Metropolitan cities like Delhi, Mumbai, and Kolkata face heightened earthquake risks due to their dense populations and critical infrastructure. Early warning systems can aid in timely evacuations and safeguarding infrastructure, reducing casualties. Example: A powerful earthquake in Delhi could have devastating effects on millions of residents. Limited Preparedness and Response Time: Earthquakes occur suddenly, leaving little time for people to react. Early warning systems can provide crucial seconds or minutes for activating emergency measures, minimizing fatalities and property damage. Example: The 2015 Nepal earthquake caused extensive destruction in northern India, highlighting the need for better preparedness. |
How can India achieve zero-error accuracy in forecasting disasters?
- Technological Advancements: Mission Mausam incorporates the use of state-of-the-art radars, satellites equipped with advanced instruments, and high-performance computing technologies. These resources play a vital role in enhancing the accuracy of weather forecasting.
- Data Assimilation and Modeling: Strengthening data assimilation techniques and developing advanced earth system models are key to improving forecast reliability. Additionally, the adoption of AI and machine learning tools aims to further refine weather prediction capabilities.
- Capacity Building: The program emphasizes strengthening meteorological services to ensure all severe weather events are accurately detected. This involves training staff and improving operational systems for the efficient dissemination of forecasts.
What are the steps taken by the Indian Government in the past year?
- Amendment of the Disaster Management Act: In August 2024, the government introduced the Disaster Management (Amendment) Bill, 2024, in the Lok Sabha. This legislation aims to establish Urban Disaster Management Authorities for state capitals and major cities, develop comprehensive disaster databases at both national and state levels, and set up State Disaster Response Forces to enhance disaster response capabilities.
- Investment in Urban Flood Mitigation: In August 2024, India announced a plan to allocate approximately $300 million over two years to address urban flooding and promote water conservation in key cities like Mumbai, Chennai, and Bengaluru. The initiative focuses on expanding and restoring water bodies such as lakes and constructing efficient drainage systems to manage excessive monsoon rainfall.
- Addressing Urban Heat Islands: In June 2024, the government recognized that rapid urbanization has intensified the heat island effect, worsening the impact of heatwaves in cities. Efforts are underway to implement heat action plans, which include providing drinking water, enhancing medical facilities, rescheduling outdoor work timings, and increasing green cover to reduce urban heat.
- Enhancement of Early Warning Systems: Significant progress has been made in upgrading early warning systems for natural disasters like floods and heatwaves. These improvements aim to deliver timely alerts and minimize the impact on vulnerable communities.
- Capacity Building and Training: Emphasis has been placed on enhancing the skills and readiness of disaster response teams at the national and state levels. For example, in 2024, the National Disaster Response Force (NDRF) conducted a multi-agency mock drill in Assam, simulating a large-scale flood disaster response.
What are the challenges in forecasting a disaster?
- Data Gaps and Limited Technology: Accurate forecasting relies on real-time, high-quality data obtained through advanced technologies like satellite imagery, weather radars, and seismic sensors. However, in remote areas or regions with inadequate infrastructure, the lack of such data significantly limits prediction accuracy.
- Example: The 2013 Kedarnath floods in India were triggered by a cloudburst that went unforecasted due to insufficient localized meteorological data and the absence of advanced radar systems.
- Unpredictability of Natural Phenomena: Certain disasters, such as earthquakes and tsunamis, remain unpredictable as they result from abrupt geological changes that are difficult to anticipate.
- Example: The 2004 Indian Ocean tsunami was caused by a massive earthquake, but the absence of a regional tsunami warning system in the Indian Ocean prevented timely alerts to affected countries.
- Challenges in Communication and Dissemination: Even with precise forecasts, warnings often fail to reach vulnerable populations effectively due to barriers such as language differences, inadequate outreach, or a lack of awareness.
- Example: During Cyclone Tauktae (2021) in India, despite accurate forecasting, some fishermen disregarded evacuation warnings, leading to fatalities despite the availability of advanced cyclone prediction systems.
Way forward:
- Strengthening Technological and Data Infrastructure: Focus on establishing localized weather stations, deploying advanced radar systems, and installing seismic sensors in remote regions. Additionally, utilize artificial intelligence and machine learning to improve the accuracy of forecasts and facilitate real-time data integration.
Improving Community Awareness and Communication: Implement accessible, multilingual early warning systems and organize regular awareness campaigns to ensure effective communication of alerts and enhance community preparedness during disasters.
