Coupled multiscale paleoclimate reconstruction with four-dimensional variational data assimilation
Abstract
Paleoclimate archives extend climate knowledge beyond the instrumental era, registering different seasons, variables, time averages, and memory lengths. A longstanding problem is to integrate these heterogeneous sources of information within a unified methodology. Here we present a new data-assimilation framework, Last Millennium Reanalysis 4D-Var (LMR4D-Var), which reconstructs climate trajectories from these heterogeneous datasets while balancing errors in the model, observations, and initial conditions. We compare results using LMR4D-Var to assimilate proxies from PAGES2k, Temp12k, and borehole temperature profiles without treating them as instantaneous equivalents. Instrumental verification shows that LMR4D-Var achieves the highest skill compared with previous reconstructions. Borehole assimilation preserves skill against withheld annually resolved records, increases agreement between reconstructed 300--2000-m ocean heat content and independent estimates, and yields a cooler reconstructed Little Ice Age ocean. Results for Temp12k demonstrate assimilation of decadal-to-millennial records and the potential for Holocene and deeper-time applications with suitable emulators.
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BibTeX
@misc{meng2026coupled,
title = {{Coupled multiscale paleoclimate reconstruction with four-dimensional variational data assimilation}},
author = {Zilu Meng and Gregory J. Hakim and Julien Emile-Geay and Tanaya Gondhalekar and Eric J. Steig},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2608.19469},
eprint = {2608.19469},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.19469},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Coupled multiscale paleoclimate reconstruction with four-dimensional variational data assimilation
AU - Zilu Meng
AU - Gregory J. Hakim
AU - Julien Emile-Geay
AU - Tanaya Gondhalekar
AU - Eric J. Steig
PY - 2026
DA - 2026/09/09
PB - arXiv
DO - 10.48550/arxiv.2608.19469
UR - https://arxiv.org/abs/2608.19469
AB - Paleoclimate archives extend climate knowledge beyond the instrumental era, registering different seasons, variables, time averages, and memory lengths. A longstanding problem is to integrate these heterogeneous sources of information within a unified methodology. Here we present a new data-assimilation framework, Last Millennium Reanalysis 4D-Var (LMR4D-Var), which reconstructs climate trajectories from these heterogeneous datasets while balancing errors in the model, observations, and initial conditions. We compare results using LMR4D-Var to assimilate proxies from PAGES2k, Temp12k, and borehole temperature profiles without treating them as instantaneous equivalents. Instrumental verification shows that LMR4D-Var achieves the highest skill compared with previous reconstructions. Borehole assimilation preserves skill against withheld annually resolved records, increases agreement between reconstructed 300--2000-m ocean heat content and independent estimates, and yields a cooler reconstructed Little Ice Age ocean. Results for Temp12k demonstrate assimilation of decadal-to-millennial records and the potential for Holocene and deeper-time applications with suitable emulators.
ER -