Irreducible Uncertainty Classes in Coherence-Constrained Paleoclimate Reconstruction

Irreducible Uncertainty Classes in Coherence-Constrained Paleoclimate Reconstruction | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 13 February 2026 V1 Latest version Share on Irreducible Uncertainty Classes in Coherence-Constrained Paleoclimate Reconstruction Author : Peter Brunzelle 0009-0005-7109-6745 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177100810.05072943/v1 169 views 97 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Coherence-constrained backward reconstruction frameworks substantially reduce the space of admissible historical trajectories by enforcing global consistency across heterogeneous proxy observations. Recent implementations, including the Synthesis & Estimation Architecture (SEA), demonstrate that large classes of historically inconsistent reconstructions can be eliminated without reliance on forward dynamical modeling. However, coherence constraints alone do not guarantee unique historical inference. This paper characterizes the residual uncertainty that persists after coherence-based reconstruction, demonstrating that remaining ambiguity collapses into a finite set of structurally irreducible identifiability classes. These residuals arise from limitations inherent to proxy structure, coupling observability, and temporal resolution, rather than from data scarcity or methodological insufficiency. We formalize six residual uncertainty classes, ground each in well-established paleoclimate case studies, explain why additional data within existing proxy subspaces cannot resolve them, and identify the types of new observables or constraints required for further reduction. This work defines the epistemic boundary between coherent reconstruction and uniquely identifiable history, and outlines how the proposed taxonomy can be operationally applied to ensemble interpretation in coherence-constrained and data-assimilation-adjacent reconstruction frameworks. This paper forms part of a broader series developing the Synthesis & Estimation Architecture (SEA) as a domain-general framework for coherence-constrained reconstruction and observabilitylimited inference. Supplementary Material File (irreducible_uncertainty_classes_in_coherence_constrained_paleoclimate_reconstruction (3).pdf) Download 341.40 KB Information & Authors Information Version history V1 Version 1 13 February 2026 Copyright This work is licensed under a Creative Commons Attribution 4.0 International License Keywords coherence-constrained reconstruction data assimilation ensemble interpretation identifiability paleoclimate proxies underdetermination Authors Affiliations Peter Brunzelle 0009-0005-7109-6745 [email protected] View all articles by this author Metrics & Citations Metrics Article Usage 169 views 97 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Peter Brunzelle. Irreducible Uncertainty Classes in Coherence-Constrained Paleoclimate Reconstruction. Authorea . 13 February 2026. DOI: https://doi.org/10.22541/au.177100810.05072943/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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