Author
Abstract
Trust in climate data remains a significant barrier to effective climate action. Skepticism about data manipulation and politicization reduces confidence and hinders evidence-based policy. Existing climate data systems lack transparent verification and accessible analytical tools, limiting accountability and stakeholder engagement. This study presents a reproducible framework that applies blockchain technology to provide transparent verification, analysis, and governance of climate data. The architecture includes three layers: a data ingestion layer that standardizes verified observations, a blockchain layer that ensures immutability and provenance through proof-of-stake consensus, and a statistical analysis layer that uses deterministic methods for anomaly detection and trend evaluation. The framework was tested using 8,403 hours of temperature data from the Manila, Philippines monitoring station during 2024. Analysis identified 33 temperature anomalies ranging from 36.9 to 38.0 °C that aligned with documented April–May 2024 heat waves, confirming the ability to detect genuine meteorological extremes. Estimated transaction latency was 1–2 seconds per observation, with on-chain storage requirements of about 138 kilobytes and off-chain storage requirements of 2.1 megabytes for a 90-day deployment. Estimated energy use for the same period was approximately 0.06 kilowatt-hours, representing a 97–99 percent reduction compared with proof-of-work systems. These findings demonstrate that the proposed framework can securely record, verify, and analyze climate data while consuming very little energy. By combining blockchain immutability with transparent statistical methods, this approach directly addresses the trust deficit in climate science and provides a foundation for verifiable, reproducible, and efficient climate information systems.
Suggested Citation
Thomas F Heston, 2026.
"A proof-of-stake blockchain framework for transparent climate data verification,"
PLOS Climate, Public Library of Science, vol. 5(6), pages 1-14, June.
Handle:
RePEc:plo:pclm00:0000764
DOI: 10.1371/journal.pclm.0000764
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