An ensemble-based coupled reanalysis of the climate from 1860 to the present (CoRea1860+)

Abstract. Climate reanalyses are essential for studying climate variability, understanding climate processes, and initializing climate predictions. We present CoRea1860+ (Wang and Counillon, 2025, https://doi.org/10.11582/2025.00009), a 30-member coupled reanalysis spanning from 1860 to the present, produced using the Norwegian Climate Prediction Model (NorCPM) and assimilating sea surface temperature (SST) observations. NorCPM combines the Norwegian Earth System Model with the ensemble Kalman filter data assimilation method. SST, available throughout the entire period, serves as the primary source of instrumental oceanic measurements prior to the 1950s. CoRea1860+ belongs to the category of sparse-input reanalyses, designed to minimize artefacts arising from changes in the observation network over time. By exclusively assimilating oceanic data, this reanalysis offers valuable insights into the ocean's role in driving climate system variability, including its influence on the atmosphere and sea ice. This study first describes the numerical model, the SST dataset, and the assimilation implementation used to produce CoRea1860+. It then provides a comprehensive evaluation of the reanalysis across four key aspects, namely reliability, ocean variability, sea ice variability, and atmospheric variability, benchmarked against more than 10 independent reanalyses and observational datasets. Overall, CoRea1860+ demonstrates strong reliability, particularly in observation-rich periods, and provides a reasonable representation of climate variability. It successfully captures key features such as multi-decadal variability and long-term trends in ocean heat content, the Atlantic meridional overturning circulation, and sea ice variability in both hemispheres. Furthermore, to some extent, CoRea1860+ agrees with the reference atmospheric datasets for surface air temperature, precipitation, sea level pressure, and 500 hPa geopotential height, especially in the tropics where air–sea interactions are most pronounced.

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Publication Details

Journal
Earth system science data
Published
2025-08-28
DOI
https://doi.org/10.5194/essd-17-4185-2025
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00

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article

An ensemble-based coupled reanalysis of the climate from 1860 to the present (CoRea1860+)

Patrick Laloyaux, Yiguo Wang, Ping‐Gin Chiu, Eric de Boisséson et al.
Earth system science data
Climate variability and models
article

An ensemble-based coupled reanalysis of the climate from 1860 to the present (CoRea1860+)

Patrick Laloyaux, Yiguo Wang, Ping‐Gin Chiu, Eric de Boisséson, Lea Svendsen, Noel Keenlyside, François Counillon, Mariko Koseki
article en

Abstract

Abstract. Climate reanalyses are essential for studying climate variability, understanding climate processes, and initializing climate predictions. We present CoRea1860+ (Wang and Counillon, 2025, https://doi.org/10.11582/2025.00009), a 30-member coupled reanalysis spanning from 1860 to the present, produced using the Norwegian Climate Prediction Model (NorCPM) and assimilating sea surface temperature (SST) observations. NorCPM combines the Norwegian Earth System Model with the ensemble Kalman filter data assimilation method. SST, available throughout the entire period, serves as the primary source of instrumental oceanic measurements prior to the 1950s. CoRea1860+ belongs to the category of sparse-input reanalyses, designed to minimize artefacts arising from changes in the observation network over time. By exclusively assimilating oceanic data, this reanalysis offers valuable insights into the ocean's role in driving climate system variability, including its influence on the atmosphere and sea ice. This study first describes the numerical model, the SST dataset, and the assimilation implementation used to produce CoRea1860+. It then provides a comprehensive evaluation of the reanalysis across four key aspects, namely reliability, ocean variability, sea ice variability, and atmospheric variability, benchmarked against more than 10 independent reanalyses and observational datasets. Overall, CoRea1860+ demonstrates strong reliability, particularly in observation-rich periods, and provides a reasonable representation of climate variability. It successfully captures key features such as multi-decadal variability and long-term trends in ocean heat content, the Atlantic meridional overturning circulation, and sea ice variability in both hemispheres. Furthermore, to some extent, CoRea1860+ agrees with the reference atmospheric datasets for surface air temperature, precipitation, sea level pressure, and 500 hPa geopotential height, especially in the tropics where air–sea interactions are most pronounced.

Earth system science dataVol. 17(8)
European Centre for Medium-Range Weather Forecasts (GB), Bjerknes Centre for Climate Research (NO), University of Bergen (NO)
Norges Forskningsråd, Bjerknessenteret for klimaforskning, Universitetet i Bergen
Openalex Percentile: Top 79%
Climate variability and models
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