PIB Summaries 24 July 2025

Content

1. BHARAT FORECAST SYSTEM AND EARLY WARNING SYSTEMS FOR NATURAL DISASTERS
2. Outcome and Employment Generation under PMKVY

BHARAT FORECAST SYSTEM AND EARLY WARNING SYSTEMS FOR NATURAL DISASTERS

BharatFS: India’s Panchayat-Level Weather Revolution

Overview and Capabilities

• Officially adopted: 26 May 2025 by the India Meteorological Department (IMD).
• Resolution: 6 km horizontal grid — ideal for panchayat cluster-level forecasting.
• Objective: Improve short- and medium-range prediction of extreme weather (e.g., rainfall, storms).
• Not intended for: Long-range (seasonal or climate-scale) predictions.

Relevance : GS 3(Disaster Management )

Technological Innovations

• TCo (Triangular Cubic Octahedral) Grid: Enhances resolution over the tropics while reducing computational overhead.
• Improved physical representation: Orography, filtering, energy conservation.
• Model evolution: From 12 km GFS T1534 to BharatFS → 30% increase in extreme rainfall prediction accuracy (especially in Central India).
• Rigorous testing: Validated since 2022, extensively peer-reviewed.

India’s Early Warning Systems for Natural Disasters: A Global Benchmark

Institutional Backbone

• Spearheaded by Ministry of Earth Sciences (MoES).
• Key Agencies:
  • IMD – Weather, cyclone, rainfall warnings.
  • National Centre for Seismology (NCS) – Earthquake monitoring.
  • Central Water Commission (CWC) – Flood forecasting.
  • NDMA – Coordination & dissemination.

Observation & Modelling Infrastructure

• Surface & upper-air observations, radar (10 min interval) and satellite (15 min) data.
• GIS-based Decision Support System (DSS): End-to-end monitoring and dissemination platform.
• Numerical Weather Prediction (NWP): Integration of local, regional, global models.
• Supercomputing support: Arka and Arunika bolster processing of massive datasets.

Forecasting Evolution

• From conventional to:
  • Impact-Based Forecasting (IBF) – Area-specific risk analysis (district, sub-city).
  • Risk-Based Warning (RBW) – Colour-coded matrix for decision-makers.
• AI/ML Integration: Enhancing forecasting, pattern recognition, and bulletin customization.

Early Warning Dissemination: Multi-Platform & Multilingual

Mobile & Digital Tools

• Apps: Mausam, Meghdoot (Agromet), DAMINI (Lightning), UMANG, FloodWatch India v2.0.
• Social Media outreach: Facebook, X, YouTube, Instagram, Blogs.
• Common Alerting Protocol (CAP): Integrated alert mechanism across agencies.
• Customized bulletins for agriculture, urban floods, tourism, etc.

Mass Media & Traditional Channels

• AM/FM/Community Radio, Doordarshan, private broadcasters, newspapers, SMS, WhatsApp, fax, email.
• Weekly/Daily Weather Videos for public outreach.

Specialised Tools for Disaster Risk Reduction

Cyclone Monitoring & Management

• North Indian Ocean sees 7% of global cyclone events—many catastrophic.
• Zero-casualty achievement: Cyclone Biparjoy (2023), Cyclone Dana (2024).
• Result: Global recognition – IMD awarded UN Sasakawa Award 2025 for Disaster Risk Reduction.

Flood Forecasting

• CWC issues short-range forecasts (24 hrs lead time).
• FloodWatch App v2.0:
  • 7-day forecasts.
  • Real-time alerts.
  • Storage data of 150 major reservoirs.
• Integration with SDMAs and NDMA for proactive mitigation.

Hazard Vulnerability Atlas

• Web-based GIS “Climate Hazard & Vulnerability Atlas” for 13 meteorological hazards.
• Identifies hotspots for States & Disaster Agencies → key for climate-resilient infrastructure.

Earthquake Monitoring: Present Limitations

• No system globally can predict earthquakes (time, location, magnitude).
• NCS provides real-time seismological alerts via app, SMS, email, fax, and social media.
• Focus: Post-quake intensity maps, not early warning.

Key Milestones & Future Outlook

Mission Mausam (Central Sector Scheme)

• Vision: Make Bharat a weather-ready and climate-smart nation.
• Focus:
  • Strengthening AI/ML in forecasting.
  • Panchayat-level weather integration (via BharatFS).
  • Disaster-resilient infrastructure planning.

Innovation Highlights

• Panchayat Mausam Seva.
• Dynamic risk matrix.
• Cloud burst, heatwave, lightning-specific alerts.
• Regionalized alerts for Northeast, Himalayan belt, and coastal zones.

Global Benchmarking

• Recognized by UN and WMO for best practices.
• Deaths from cyclones reduced from 10,000+ (Odisha, 1999) to zero (2023–24).
• Model for Global South’s climate adaptation.

Conclusion

India’s Early Warning Systems—particularly with BharatFS and GIS-based DSS—have evolved into one of the world’s most advanced, hyperlocal, and integrated disaster resilience infrastructures. With real-time forecasting, AI-powered decision systems, and public engagement across 20+ platforms, India now stands at the forefront of global disaster preparedness and climate adaptation efforts.

Outcome and Employment Generation under PMKVY

PMKVY (2015–2025): A Decade of Skill Transformation

Scheme Structure and Evolution

• Launched: 2015 by MSDE
• Key components:
  • Short-Term Training (STT): For fresh entrants.
  • Recognition of Prior Learning (RPL): For up-skilling/re-skilling existing workers.
• Placement Linkage:
  • PMKVY 1.0 to 3.0 (2015–2022): Placement rate ~43% (STT only).
  • PMKVY 4.0 (2023–25): Focused on empowered career pathways, not just placement numbers.

Relevance : GS 2(Schemes) , GS 3(Employment )

Skilling Trends (2020–2025)

Total Candidates Trained Over 5 Years:

• Cumulative: 5.36 million (53.6 lakh) trained.
• Notable slump during COVID-19 years (2021–22: ~6.1 lakh) but strong post-pandemic recovery seen in:
  • FY 2023–24: 5.39 lakh
  • FY 2024–25: 20.34 lakh (highest in 5 years)

Top 5 Performing States (FY 2024–25):

Lowest Performing UTs (FY 2024–25):

• Lakshadweep: 120
• Dadra & Nagar Haveli and Daman & Diu: 1,407
• Goa: 236

Impact & Outcomes: Third-Party Evaluations

• Sambodhi Study (PMKVY 2.0):
• STT graduates: 15% higher average income than control group.
• RPL graduates: 19% higher income than unskilled peers.

• NITI Aayog (2020 Evaluation):
• 94% employers willing to hire PMKVY-trained candidates.
• 52% of RPL-placed candidates reported higher earnings or expectations thereof.

1. IIPA Impact Assessment:
2. 70.5% of surveyed candidates got placement in their desired skill sectors.

Paradigm Shift in PMKVY 4.0 (2023–25)

From Training to Employment Empowerment:

• Emphasis on career-oriented skilling, not just job linkage.
• Candidates given orientation to entrepreneurship, freelance gigs, and apprenticeships.

Skill India Digital Hub (SIDH):

• Launched: Under PMKVY 4.0
• Functions as a lifelong skilling ecosystem.
• Integrates:
  • Training and certification records
  • Job and apprenticeship marketplaces
  • Employer–trainee interface
• Trainee data available to employers in real-time.
• Supported by nationwide Rozgar Melas.

Challenges Noted

• Low average placement rate (43%) under STT until PMKVY 3.0.
• Inter-state disparities: Some large states like Telangana, Kerala, Gujarat underperformed compared to peers.
• No current impact report for PMKVY 4.0 released (yet); real outcomes remain to be quantitatively validated.

Way Forward: Strategy & Recommendations

• Strengthening Outcomes
• Conduct real-time impact audits for PMKVY 4.0.
• Incentivize demand-driven skilling based on regional employment patterns.

• Digital Leverage
• Fully integrate SIDH with e-Shram, NCS, Udyam, and CSC platforms for seamless migration of workers into formal economy.
• Use AI/ML tools to map candidate preferences with employer demand.

1. Improve Industry Linkage
2. Mandate on-the-job training/apprenticeship linkage for all STT courses.
3. Expand engagement with MSMEs and startup ecosystem to absorb trained manpower.

Conclusion: India’s Skill Push Reimagined

PMKVY has evolved from a training-centric scheme to an aspirational skill-building framework that empowers youth through income enhancement, entrepreneurship orientation, and digital integration. With platforms like SIDH, targeted Rozgar Melas, and growing employer trust, India’s skill development narrative is transitioning from quantity to quality and long-term employability.