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Record W4408293601 · doi:10.1073/pnas.2417155122

Negative trend in total solar irradiance over the satellite era

2025· article· en· W4408293601 on OpenAlexaff
Ted Amdur, Peter Huybers

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsImpact
FundersNuclear Safety and Security CommissionNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsSolar irradianceSatelliteEnvironmental scienceIrradianceRadiometerSolar cycleProxy (statistics)Atmospheric sciencesClimatologyLinear regressionMeteorologyRemote sensingStatisticsGeographyMathematicsPhysicsGeologySolar wind

Abstract

fetched live from OpenAlex

Linear trends in total solar irradiance (TSI) between different reconstructions of the satellite era, defined as 1978 to 2023, disagree by up to 0.17 W/m 2 per decade. Furthermore, high-quality satellite radiometer observations of the most recent solar cycle, 24, systematically differ from estimates that rely on TSI proxies for reasons that have been unclear. Using a Bayesian Kalman filtering approach to estimate TSI from both satellite-based observations and proxies gives two complementary explanations: recent satellite-based observations of TSI contain unaccounted-for positive linear drifts, and regression-based reconstructions are affected by commonly used solar magnetic proxies becoming less sensitive to TSI variations at low values. After accounting for satellite instrument drifts and reduced sensitivity, direct and proxy observations come into agreement and together indicate a linear trend in overall TSI of −0.15 W/m 2 per decade with a 95% CI of −0.17 to −0.13 W/m 2 per decade between 1980 and 2023.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.155

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.281
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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