The ELSI-TSI composite covers total solar irradiance data from 1979 to 2025. It was created by Victor Manuel Velasco Herrera using the Explainable Layered Statistical Inference (ELSI) AI framework, which reduces instrumental uncertainty by about a factor of four. The data preserves dominant signatures of solar variability and reveals long-range memory and subdiffusive behavior in irradiance.
Use Cases
- Modeling solar influence on climate based on the 1979–2025 total solar irradiance composite.
- Analyzing long-range memory and subdiffusive variability in solar output as described in the framework.
- Validating solar dynamo models using the reduced-uncertainty irradiance signatures.
- Studying solar cycle variability using the multi-decade time series.
Strengths
- Covers a 46-year time range from 1979 to 2025.
- Reduces instrumental uncertainty by about a factor of four compared to prior methods.
- Preserves dominant signatures of solar variability as described in the framework.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- Victor Manuel Velasco Herrera Dataverse
- Collection Method
- Reconstructed using the Explainable Layered Statistical Inference (ELSI) AI framework without sequential cross-calibration.
- Time Range
- 1979–2025
- Freshness
- Last updated 2026-07-01 12:52:55; freshness should be verified.