ROLLOUT OF WEATHER INFORMATION NETWORK DATA SYSTEM

Now I have sufficient facts (>4 from Tier-1 PIB sources). Writing the study note.

1. At a Glance

2. Why in the News

3. Background & Evolution

4. Core Static Facts

Item Detail
Full name Weather Information Network and Data System (WINDS)
Nodal Ministry Ministry of Agriculture & Farmers Welfare [S1]
Parent scheme Pradhan Mantri Fasal Bima Yojana (PMFBY) [S2]
Launch date 21 July 2023 [S2]
Core infra Automatic Weather Stations (AWS) + Automatic Rain Gauges (ARGs) [S1]
Data granularity Taluk/Block and Gram Panchayat level [S3]
States/UTs adopted Assam, Himachal Pradesh, Kerala, Odisha, Puducherry, Uttar Pradesh, Uttarakhand (7) [S1]
Sites approved 16,843 [S1]
Civil work completed 1,188 sites [S1]
AWS/ARGs installed 892 [S1]
Linked scheme YES-TECH (Yield Estimation System based on Technology) [S2][S4]

5. Multi-Dimensional Analysis

Economic - Reduces crop insurance dependence on subjective Crop Cutting Experiments (CCEs), lowering disputes and claim-settlement delays that raise fiscal burden on PMFBY. [S4] - Complements premium reduction from 17-18% to 8-9%, generating cited savings of ₹11,000 crore. [S2]

Scientific/Technological - Uses ground-based AWS/ARG sensor network for hyperlocal, long-term weather datasets — a shift from generalized regional forecasts to village-level data. [S1][S3] - Feeds into YES-TECH, which uses remote sensing plus ground weather data for objective yield estimation (2025-26 deployment: 12 states, 344 districts). [S4]

Administrative - Federal rollout is state-adoption based — only 7 states/UTs onboarded so far, indicating uneven uptake despite national ambition. [S1] - Implementation gap visible: only ~5% of approved sites (892/16,843) have installed AWS/ARGs, and ~7% have completed civil work — a bottleneck indicator. [S1]

Social - Aims to protect smallholder/remote farmers via localized advisories and faster, less-disputed insurance claims.

Governance/Ethical - Objective, sensor/tech-based data reduces scope for manual manipulation of yield/weather data in insurance claim assessment. [S4]

6. Recent Developments (last 12-18 months)

7. Prelims Hooks

8. Mains Relevance

9. Related Topics to Study Next

10. Common Errors / Trap Areas

11. Sources