Temporal Seam Score for Assessing Continuity at Known Transitions in Time Series
Abstract
Long environmental records increasingly combine observations from successive observing or processing systems. Transitions between these systems create temporal seams that may reflect imperfect harmonization or changes in the observed process. We introduce the Temporal Seam Score (S-score, or S), a signed, robust measure for assessing continuity at a known transition time. The complete time series is fitted with a seam-blind model accounting for trend, seasonality, and optional covariates. The residual contrast between symmetric windows around the transition is compared with matched reference contrasts calculated within the contributing segments. The S-score is the standardized departure of the seam contrast from this reference. An S-score near zero indicates that the seam is consistent with ordinary temporal variability. Its sign indicates the direction of the discontinuity, while its magnitude (|S|) indicates how exceptional the discontinuity is. Simulation showed that |S| reflects the imposed discontinuity relative to residual variability: a 20% shift produced a median |S| of 2.58 at a residual coefficient of variation of 0.10, compared with 0.84 at 0.50. In a MODIS-to-Sentinel-3 vegetation record, 121 of 500 sites yielded finite S-scores, of which 90 met all reliability criteria. Among these reliable sites, median S was +0.217 and median |S| was 0.627, indicating little systematic directional displacement and a median seam departure below one reference spread. The S-score provides a general and auditable diagnostic for evaluating temporal continuity across generations of sensors, algorithms, and observing systems without requiring temporal overlap, thereby supporting harmonization quality assurance and more reliable attribution analyses based on long-term environmental records.
Related
- Notes on Uniform Policy Score Bounds and Lipschitz Continuity for Truncated Gaussian, Product Cauchy, Boltzmann, and Softmax Policies
- Assessing Temporal Dispersion of Time-Varying Channel at 38 GHz for Different Reference Signals
- Interval-valued circular time series: A toroidal score-driven approach with an application to wind direction
- Interval-valued circular time series: A cylindrical score-driven approach with an application to wind direction
- Rollcast: Proper-Score Gated Rolling Anchors for Adaptive Probabilistic Time-Series Forecasting
BibTeX
@misc{jin2026temporal,
title = {{Temporal Seam Score for Assessing Continuity at Known Transitions in Time Series}},
author = {Hongxiao Jin},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.15132},
eprint = {2609.15132},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.15132},
}
RIS
TY - UNPB
TI - Temporal Seam Score for Assessing Continuity at Known Transitions in Time Series
AU - Hongxiao Jin
PY - 2026
DA - 2026/09/14
PB - arXiv
DO - 10.48550/arxiv.2609.15132
UR - https://arxiv.org/abs/2609.15132
AB - Long environmental records increasingly combine observations from successive observing or processing systems. Transitions between these systems create temporal seams that may reflect imperfect harmonization or changes in the observed process. We introduce the Temporal Seam Score (S-score, or S), a signed, robust measure for assessing continuity at a known transition time. The complete time series is fitted with a seam-blind model accounting for trend, seasonality, and optional covariates. The residual contrast between symmetric windows around the transition is compared with matched reference contrasts calculated within the contributing segments. The S-score is the standardized departure of the seam contrast from this reference. An S-score near zero indicates that the seam is consistent with ordinary temporal variability. Its sign indicates the direction of the discontinuity, while its magnitude (|S|) indicates how exceptional the discontinuity is. Simulation showed that |S| reflects the imposed discontinuity relative to residual variability: a 20% shift produced a median |S| of 2.58 at a residual coefficient of variation of 0.10, compared with 0.84 at 0.50. In a MODIS-to-Sentinel-3 vegetation record, 121 of 500 sites yielded finite S-scores, of which 90 met all reliability criteria. Among these reliable sites, median S was +0.217 and median |S| was 0.627, indicating little systematic directional displacement and a median seam departure below one reference spread. The S-score provides a general and auditable diagnostic for evaluating temporal continuity across generations of sensors, algorithms, and observing systems without requiring temporal overlap, thereby supporting harmonization quality assurance and more reliable attribution analyses based on long-term environmental records.
ER -