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Abstract “Online” data assimilation (DA) is used to generate a seasonal-resolution reanalysis dataset over the last millennium by combining forecasts from an ocean–atmosphere–sea-ice coupled linear inverse model with climate proxy records. Instrumental verification reveals that this reconstruction achieves the highest correlation skill, while using fewer proxies, in surface temperature reconstructions compared to other paleo-DA products, particularly during boreal winter when proxy data are scarce. Reconstructed ocean and sea-ice variables also have high correlation with instrumental and satellite datasets. Verification against independent proxy records shows that reconstruction skill is robust throughout the last millennium. Analysis of the results reveals that the method effectively captures the seasonal evolution and amplitude of El Niño events, seasonal temperature trends that are consistent with orbital forcing over the last millennium, and polar-amplified cooling in the transition from the Medieval Climate Anomaly to the Little Ice Age.
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Coupled Atmosphere–Ocean Reconstruction of the Last Millennium Using Online Data Assimilation
Abstract We use online data assimilation to combine information from a linear inverse model of coupled atmosphere‐ocean dynamics with proxy records to create a new annual‐resolution reconstruction of atmosphere and ocean fields over the last millennium. Instrumental validation of reconstructed sea‐surface temperature and 0–700 m ocean heat content shows broad regions of positive spatial correlations, and high correlations (∼0.6–0.9) for global averages and indices of large‐scale modes of atmospheric variability. Compared to previous reconstructions, the online reconstructions show global and hemispheric averages with little‐to‐no millennial‐scale trend and global‐mean temperatures ∼0.25–0.5 K cooler during early periods (1000–1400 C.E.). The spatial anomaly differences of average temperature between an early (1000–1250 C.E.) and later (1400–1700 C.E.) period show warm anomalies over high‐latitude Europe and cool tropical conditions in partial agreement with previous assessments. The addition of online data assimilation, which provides dynamical memory to climate proxy information, is shown to be crucial for adequately characterizing decadal‐to‐centennial‐scale variability of 0–700 m ocean heat content. Furthermore, the climate forecasts provide model‐based physical constraints for atmosphere–ocean interaction, which become increasingly important during early periods when less proxy information is available for assimilation.
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- Award ID(s):
- 1702423
- PAR ID:
- 10448153
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Paleoceanography and Paleoclimatology
- Volume:
- 36
- Issue:
- 5
- ISSN:
- 2572-4517
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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