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Acceleration of the ocean warming from 1961 to 2022 unveiled by large-ensemble reanalyses

Earth Sciences

Acceleration of the ocean warming from 1961 to 2022 unveiled by large-ensemble reanalyses

A. Storto and C. Yang

Discover groundbreaking findings by Andrea Storto and Chunxue Yang as they explore ocean warming over the past six decades. This research reveals a striking acceleration in ocean heat content, particularly in high latitudes, with 2022 marking an unprecedented peak. Join in on the revelations surrounding regional uncertainties and their implications for our understanding of oceanic changes.

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Playback language: English
Introduction
Ocean warming, primarily driven by anthropogenic greenhouse gas emissions, poses a significant threat to the marine environment. This threat manifests in various ways, including sea-ice decline, sea-level rise, and increased frequency and intensity of marine heatwaves, all of which impact the marine ecosystem. The ocean warms unevenly due to varying heat uptake from the atmosphere and surface wind variability, coupled with heat redistribution through advection and mixing. Ocean heat content (OHC), representing the total heat stored in the ocean, serves as a crucial indicator of climate change in the ocean. While interannual OHC variations are influenced by both internal climate variability and external forcing, the long-term increase is attributed to human-induced increases in climate-altering gas concentrations. Accurately quantifying ocean warming and associated uncertainties is paramount for monitoring Earth's energy budget and climate. Reconstructing OHC before the well-instrumented Argo era (pre-2000s) is challenging due to uncertainties stemming from observations (expendable bathythermograph data, horizontal mapping methods, vertical interpolation), model-based reconstructions (vertical physics parameterization, systematic model errors, data assimilation assumptions, input datasets), and intrinsic ocean variability. This study aims to reassess OHC trends and uncertainties using a large-ensemble reanalysis system, comparing these findings to objective analyses to identify and rank uncertainty sources. The focus is on quantifying warming, evaluating uncertainties, and clarifying their sources in OHC reconstruction.
Literature Review
Numerous studies have investigated ocean warming using various methods, including objective analyses (statistical mapping of observations), reanalyses (using ocean general circulation models with data assimilation), combinations thereof, proxy data (inferring OHC from sea-level variations), and machine learning. Reanalyses offer a multi-variate, four-dimensional characterization of the ocean, beneficial for process-oriented studies and initializing long-range prediction systems. However, they are computationally expensive. This study builds upon previous research by employing a large-ensemble reanalysis system to comprehensively assess OHC trends and uncertainties, comparing them with objective analyses to validate the findings and better understand the relative contributions of various uncertainties.
Methodology
This study utilizes the Cnr Ismar Global historical Reanalysis (CIGAR), a 32-member large-ensemble reanalysis system. The ocean model employed is NEMO version 4.0.7, coupled with the S³ sea-ice model, at approximately 1° horizontal resolution (enhanced in the tropics). The model uses bulk formulas from the AERO BULK package for air-sea heat flux, a 3-band RGB scheme for penetrating radiation, and the TKE scheme for vertical mixing. Surface forcing is derived from the ECMWF ERA5 reanalysis, with heat and freshwater fluxes adjusted through a relaxation scheme nudging sea surface temperature (SST) and salinity (SSS) toward external analyses (UKMO EN4 for SSS, and UKMO HadISST and JMA COBE for SST). Freshwater discharge is from the JMA JRA-55-do reanalysis. A 3DVAR assimilation scheme is used, assimilating various in-situ profiles (MBT, XBT, CTD, moorings, floats, gliders, and animal-borne sensors) from the UKMO EN4 dataset, with observation errors calibrated using a posterior method. A large-scale model bias correction (LSMBC) scheme is applied, weakly relaxing deep ocean waters (below 500 m) toward external objective analyses. An objective analysis (OA) scheme, sharing the data assimilation configuration but lacking model time integration, serves as a comparison. The CIGAR ensemble encompasses major uncertainty sources: observation bias correction (using two XBT correction algorithms), SST datasets (HadISST and COBE), initial conditions (from two previous assimilation experiments), atmospheric forcing (using two ERA5 ensemble members), and air-sea flux formulations (NCEP/CORE and ECMWF). Stochastic parameter perturbation and observation perturbations further augment the ensemble. A total of 32 ensemble members are generated through all possible combinations of these uncertainty sources.
Key Findings
CIGAR estimates a total ocean warming of 0.43 ± 0.08 W m⁻² (1961-2022), consistent with the latest GCOS assessments. A significant global warming acceleration of 0.15 ± 0.04 W m⁻² dec⁻¹ is observed. The OHC time series reveals enhanced interannual variability compared to other estimates, with a sharper increase after approximately 1997-2000. Comparison with independent estimates (geodetic and CERES-based) shows good agreement at lower frequencies. Sensitivity experiments with the objective analysis (OA) indicate that enhanced interannual variability in CIGAR is not spurious but depends on assimilation frequency, background field, and error length scales in the objective analyses. Regional analysis highlights the largest interannual variability and trends in the extratropics (particularly the Southern Ocean), with steadier increase and reduced variability in the tropics. High latitudes appear as warming hotspots, consistent with previous studies. The maps of OHC trends and accelerations show significant heat accumulation in the Southern Ocean and Arctic, with moderate warming in the tropics. Analysis of the OHC increase in 2022 compared to 2021 shows statistically significant increases in large portions of the mid-latitude Southern Hemisphere, Atlantic and Pacific Oceans, and Tropics. In 11.6% of the global ocean, 2022 recorded the highest OHC, almost doubling any previous year. Uncertainty analysis reveals that the tropics are the most uncertain latitudinal band. Global uncertainty drops from approximately 40% to 15% between the 1960s and the last decade. Regional trend uncertainty is mainly affected by observation procedures (high latitudes) and SST data uncertainty (low latitudes). For the global trend, all uncertainty sources contribute significantly. The reanalysis initialization uncertainty plays a relatively minor role except in specific regions.
Discussion
The findings confirm the robust acceleration of ocean warming, particularly at high latitudes and near the equator. The enhanced interannual variability observed in CIGAR is shown to be not an artifact of the reanalysis system but rather reflects the sensitivity of objective analysis methods to assimilation parameters. The comprehensive uncertainty analysis, considering various sources and their regional impact, strengthens the reliability of the OHC estimates. The large ensemble approach proves valuable in quantifying both the signal and its uncertainty, particularly in the pre-Argo era where data scarcity is a significant factor. The identification of primary uncertainty sources – observation procedures and SST data uncertainty – can guide the development of improved reconstruction systems.
Conclusion
This study quantifies global and regional ocean warming and acceleration from 1961-2022 using a large-ensemble reanalysis system, comprehensively accounting for major uncertainty sources. Key findings include a significant warming trend and acceleration, with high-latitude hotspots and a substantial OHC increase in 2022. The study elucidates the hierarchical importance of different uncertainty sources, primarily observation procedures and SST data uncertainty at regional scales. This work highlights the benefits of large-ensemble reanalysis for robust climate monitoring and informs the design of future climate reconstruction systems. Further research could explore the interaction of ocean warming with other climate change impacts (e.g., ocean acidification) and investigate the underlying mechanisms of regional warming patterns.
Limitations
While CIGAR incorporates major uncertainty sources, other factors might introduce additional uncertainties, including exchanges of heat between ocean and sea ice, small-scale energy exchanges unresolved by the model's resolution, systematic errors in atmospheric forcing not captured by ERA5 ensemble members, and observational sampling errors. The study's focus on the 1961-2022 period limits the generalization to other time periods. The 32-member ensemble, while reducing sampling error substantially, might benefit from an even larger ensemble for improved uncertainty quantification.
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