Status: this preprint is open for discussion and under review for Geochronology (GChron).
Overcoming multimodalities in age–depth model posteriors using On–the–fly Probability Enhanced Sampling and Parallel Tempering
Hanna Kjellson,Andreas Nilsson,and Anders Irbäck
Abstract. Bayesian age-depth models are central to paleoclimate research, linking depth in natural archives to calendar age. When synchronizing variable data from different sites, inference in these models requires sampling from high-dimensional, often multimodal posteriors. Consequently, standard samplers become trapped in local optima, miss plausible chronologies, and bias downstream analyses. Here, we investigate two enhanced sampling approaches, On-the-fly Probability Enhanced Sampling (OPES) and Parallel Tempering (PT), and find that tempering only the likelihood components that drive multimodality can improve exploration. Our results suggest that OPES and PT combined with targeted tempering provide robust age-depth models with implications for a wide range of applications in Earth sciences, including paleoclimate and paleomagnetic reconstructions.
Received: 30 Jun 2026 – Discussion started: 15 Jul 2026
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Natural records provide valuable information about past climate variability. However, age uncertainties limit our ability to resolve the timing of climate events and identify leads and lags within the climate system. In this project, we successfully combine Bayesian modeling with problem-specific enhanced sampling techniques to reduce these uncertainties on four datasets. Applied to complete climate reconstructions, this could improve our understanding of past and future climate change.
Natural records provide valuable information about past climate variability. However, age...
