Last Millennium Reanalysis (LMR) Seasonal: A Millennium of Climate Data

A seasonal-resolution climate reconstruction of the last 1200 years.

🚀 Quick Start Guide 📁 GitHub Repository 🌍 LMR Project

Overview

Welcome to the data portal for the LMR Seasonal Reanalysis dataset. This is a seasonal-resolution climate reconstruction for the last millennium, generated using "online" data assimilation (DA). The dataset is the result of combining forecasts from an ocean-atmosphere-sea-ice coupled linear inverse model with a global collection of climate proxy records.

Instrumental verification reveals that this reconstruction achieves the highest correlation skill 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 show high correlation with instrumental and satellite datasets. The reconstruction skill is robust throughout the last millennium, making it a valuable resource for studying past climate variability and change.

Key Features

High-Skill Reconstruction: Demonstrates leading correlation skill against instrumental data, even with fewer proxies.
Full Seasonal Resolution: Captures the seasonal evolution of climate phenomena, such as El Niño events and orbitally-forced temperature trends.
Comprehensive Variables: Includes key atmosphere, ocean, and sea-ice variables like surface temperature, ocean heat content, sea-ice concentration, and more.
Millennium-Long & Robust: Verified against independent proxy records, ensuring reliable skill throughout the last 1000 years.

Data Access & Download (Click File Name to Download)

The dataset is organized into three main categories: Climate Indices, Ensemble-Mean Gridded Fields, and Individual Ensemble Members. All data is provided in NetCDF (.nc) format.

⚠️ Important Note: All variables (except SIA and SIV) in this dataset are anomalies relative to the 1950-1980 climatological mean. This allows for direct comparison with other paleoclimate datasets and facilitates analysis of climate variability over the millennium.

📁 `index/` — Ensemble Climate Indices

These files contain time series of key climate indices, including all 800 ensemble members. They are ideal for analyzing large-scale climate variability.

Filename	Variable Description	Units	Dimensions
`GMOHC_ens.nc`	Global Mean Ocean Heat Content (0-300m)	J/m²	`(ens_num, time)`
`GMT_ens.nc`	Global Mean surface air Temperature	K	`(ens_num, time)`
`Nino34_ens.nc`	Niño 3.4 Index (ENSO)	K	`(ens_num, time)`
`SIA_ens.nc`	Northern Hemisphere Sea Ice Area	m²	`(ens_num, time)`
`SIV_ens.nc`	Northern Hemisphere Sea Ice Volume	m³	`(ens_num, time)`

📁 `mean/` — Ensemble-Mean Gridded Fields

These files contain spatially resolved (gridded) data fields, averaged across all ensemble members. Use these files to analyze the mean spatial patterns of climate variables over time.

Filename	Variable Description	Units	Dimensions
`sic_mean.nc`	Gridded Northern Hemisphere Sea Ice Concentration	%	`(time, lat, lon)`
`sit_mean.nc`	Gridded Northern Hemisphere Sea Ice Thickness	m	`(time, lat, lon)`
`tas_mean.nc`	Gridded Surface Air Temperature (2m)	K	`(time, lat, lon)`
`tos_mean.nc`	Gridded Sea Surface Temperature	K	`(time, lat, lon)`
`ohc300_mean.nc`	Gridded Ocean Heat Content (0-300m)	J/m²	`(time, lat, lon)`

📁 `members/` — Individual Ensemble Members (Click the file path to download)

This directory contains the full gridded output for each individual ensemble member. These files are essential for users who wish to analyze the reconstruction uncertainty or the full range of possible climate states consistent with the proxy data. We have 800 members in total (~2 TB in total), first we suggest exploring the mean/ directory for ensemble-mean fields before diving into the individual members. Then you can explore the members/ directory for around 30 members to estimate the whole distribution of full ensemble.

ohc300/: Ocean Heat Content (0-300m) for each member
sic/: Northern Hemisphere Sea Ice Concentration for each member
sit/: Northern Hemisphere Sea Ice Thickness for each member
tas/: Surface Air Temperature (2m) for each member
tos/: Sea Surface Temperature for each member

Methodology

This dataset was generated using an "online" data assimilation (DA) framework. In this method, forecasts from a fully coupled ocean-atmosphere-sea-ice linear inverse model (LIM) are updated as new proxy information becomes available through time. This approach allows for a physically consistent reconstruction that honors both model dynamics and the constraints provided by paleoclimate proxy records (e.g., tree rings, ice cores, corals). The skill of the final reconstruction has been rigorously verified against both modern instrumental/satellite datasets and independent proxy records not used in the assimilation process.

Citation

If you use this dataset in your research, please cite the following publication:

Meng, Z., G. J. Hakim, and E. J. Steig, 2025: Coupled Seasonal Data Assimilation of Sea Ice, Ocean, and Atmospheric Dynamics over the Last Millennium. J. Climate, https://doi.org/10.1175/JCLI-D-25-0048.1, in press.

License

This dataset is made available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. You are free to share and adapt the data for any purpose, even commercially, as long as you give appropriate credit.

Contact & Feedback

For questions, comments, or to report any issues with the data, please contact:
Zilu Meng (Homepage) - zilumeng@uw.edu
Gregory Hakim (Homepage) - ghakim@uw.edu