Southern Ocean Overturning Compensation in an Eddy-Resolving Climate Simulation

The Southern Ocean’s Antarctic Circumpolar Current (ACC) and meridional overturning circulation (MOC) response to increasing zonal wind stress is, for the first time, analyzed in a high-resolution (0.1° ocean and 0.25° atmosphere), fully coupled global climate simulation using the Community Earth System Model. Results from a 20-yr wind perturbation experiment, where the Southern Hemisphere zonal wind stress is increased by 50% south of 30°S, show only marginal changes in the mean ACC transport through Drake Passage—an increase of 6% [136–144 Sverdrups (Sv; 1 Sv ≡ 10^6 m^3 s^(−1))] in the perturbation experiment compared with the control. However, the upper and lower circulation cells of the MOC do change. The lower cell is more affected than the upper cell with a maximum increase of 64% versus 39%, respectively. Changes in the MOC are directly linked to changes in water mass transformation from shifting surface isopycnals and sea ice melt, giving rise to changes in surface buoyancy forcing. The increase in transport of the lower cell leads to upwelling of warm and salty Circumpolar Deep Water and subsequent melting of sea ice surrounding Antarctica. The MOC is commonly supposed to be the sum of two opposing components: a wind- and transient-eddy overturning cell. Here, the transient-eddy overturning is virtually unchanged and consistent with a large-scale cancellation of localized regions of both enhancement and suppression of eddy kinetic energy along the mean path of the ACC. However, decomposing the time-mean overturning into a time- and zonal-mean component and a standing-eddy component reveals partial compensation between wind-driven and standing-eddy components of the circulation

Water mass transformation variability in the Weddell Sea in ocean reanalyses

This study investigates the variability of water mass transformation (WMT) within the Weddell Gyre (WG). The WG serves as a pivotal site for the Meridional Overturning Circulation (MOC) and ocean ventilation because it is the primary origin of the largest volume of water mass in the global ocean: Antarctic Bottom Water (AABW). Recent mooring data suggest substantial seasonal and interannual variability of AABW properties exiting the WG, and studies have linked the variability to the large-scale climate forcings affecting wind stress in the WG region. However, the specific thermodynamic mechanisms that link variability in surface forcings to variability in water mass transformations and AABW export remain unclear. This study explores how current state-of-the-art data-assimilating ocean reanalyses can help fill the gaps in our understanding of the thermodynamic drivers of AABW variability in the WG via WMT volume budgets derived from Walin's classic WMT framework. The three ocean reanalyses used are the following: Estimating the Circulation and Climate of the Ocean state estimate (ECCOv4), Southern Ocean State Estimate (SOSE) and Simple Ocean Data Assimilation (SODA). From the model outputs, we diagnose a closed form of the water mass budget for AABW that explicitly accounts for transport across the WG boundary, surface forcing, interior mixing and numerical mixing. We examine the annual mean climatology of the WMT budget terms, the seasonal climatology and finally the interannual variability. Our finding suggests that the relatively coarse resolution of these models did not realistically capture AABW formation, export and variability. In ECCO and SOSE, we see strong interannual variability in AABW volume budget. In SOSE, we find an accelerating loss of AABW during 2005–2010, driven largely by interior mixing and changes in surface salt fluxes. ECCO shows a similar trend during a 4-year time period starting in late 2007 but also reveals such trends to be part of interannual variability over a much longer time period. Overall, ECCO provides the most useful time series for understanding the processes and mechanisms that drive WMT and export variability in the WG. SODA, in contrast, displays unphysically large variability in AABW volume, which we attribute to its data assimilation scheme. We also examine correlations between the WMT budgets and large-scale climate indices, including El Niño–Southern Oscillation (ENSO) and Southern Annular Mode (SAM), and find no strong relationships.</p

Southern Ocean Overturning Compensation in an Eddy-Resolving Climate Simulation

The Southern Ocean’s Antarctic Circumpolar Current (ACC) and meridional overturning circulation (MOC) response to increasing zonal wind stress is, for the first time, analyzed in a high-resolution (0.1° ocean and 0.25° atmosphere), fully coupled global climate simulation using the Community Earth System Model. Results from a 20-yr wind perturbation experiment, where the Southern Hemisphere zonal wind stress is increased by 50% south of 30°S, show only marginal changes in the mean ACC transport through Drake Passage—an increase of 6% [136–144 Sverdrups (Sv; 1 Sv ≡ 10^6 m^3 s^(−1))] in the perturbation experiment compared with the control. However, the upper and lower circulation cells of the MOC do change. The lower cell is more affected than the upper cell with a maximum increase of 64% versus 39%, respectively. Changes in the MOC are directly linked to changes in water mass transformation from shifting surface isopycnals and sea ice melt, giving rise to changes in surface buoyancy forcing. The increase in transport of the lower cell leads to upwelling of warm and salty Circumpolar Deep Water and subsequent melting of sea ice surrounding Antarctica. The MOC is commonly supposed to be the sum of two opposing components: a wind- and transient-eddy overturning cell. Here, the transient-eddy overturning is virtually unchanged and consistent with a large-scale cancellation of localized regions of both enhancement and suppression of eddy kinetic energy along the mean path of the ACC. However, decomposing the time-mean overturning into a time- and zonal-mean component and a standing-eddy component reveals partial compensation between wind-driven and standing-eddy components of the circulation

The role of ocean gateways in the dynamics and sensitivity to wind stress of the early Antarctic Circumpolar Current

The date of inception of the Antarctic Circumpolar Current is debated due to uncertainty in the relative opening times of Drake Passage and the Tasman Seaway. Using an idealized eddy-resolving numerical ocean model, we investigate whether both ocean gateways have to be open to allow for a substantial circumpolar current. We find that overlapping continental barriers do not impede a circumpolar transport in excess of 50Sv, as long as a circumpolar path can be traced around the barriers. However, the presence of overlapping barriers does lead to an increased sensitivity of the current's volume transport to changes in wind stress. This change in sensitivity is interpreted in terms of the role of pressure drops across continental barriers and submerged bathymetry in balancing the momentum input by the surface wind stress. Specifically, when the pressure drop across continents is the main balancing sink of momentum, the zonal volume transport is sensitive to changes in wind stress. Changes in zonal volume transport take place via altering the depth-independent part of the circumpolar transport rather than that arising from thermal wind shear. In such a scenario, isopycnals continue to slope steeply across the model Southern Ocean, implying a strong connection between the deep and surface oceans. This may have consequences for the meridional overturning circulation and its sensitivity to wind stress

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs. We developed novel emulators relating emission changes in five key anthropogenic sectors (residential, industry, land transport, agriculture, and power generation) to winter ambient fine particulate matter (PM2.5) concentrations across China. The emulators were optimized based on Gaussian process regressors with Matern kernels. The emulators predicted 99.9% of the variance in PM2.5 concentrations for a given input configuration of emission changes. PM2.5 concentrations are primarily sensitive to residential (51%–94% of first‐order sensitivity index), industrial (7%–31%), and agricultural emissions (0%–24%). Sensitivities of PM2.5 concentrations to land transport and power generation emissions are all under 5%, except in South West China where land transport emissions contributed 13%. The largest reduction in winter PM2.5 exposure for changes in the five emission sectors is by 68%–81%, down to 15.3–25.9 μg m−3, remaining above the World Health Organization annual guideline of 10 μg m−3. The greatest reductions in PM2.5 exposure are driven by reducing residential and industrial emissions, emphasizing the importance of emission reductions in these key sectors. We show that the annual National Air Quality Target of 35 μg m−3 is unlikely to be achieved during winter without strong emission reductions from the residential and industrial sectors

CO2 storage and release in the deep Southern Ocean on millennial to centennial timescales

This work was supported by NERC Standard Grant NE/N003861/1 to J.W.B.R. and L.F.R., a NOAA Climate and Global Change VSP Fellowship to J.W.B.R, NERC Standard Grant NE/M004619/1 to AB and JWBR, a NERC Strategic Environmental Science Capital Grant to A.B. and J.W.B.R., Marie Curie Career Integration Grant CIG14-631752 to AB, an ERC consolidator grant to L.F.R., NSF grant OCE-1503129 to J.F.A., and NERC studentships to B.T. and E.L.The cause of changes in atmospheric carbon dioxide (CO2) during the recent ice ages is yet to be fully explained. Most mechanisms for glacial–interglacial CO2 change have centred on carbon exchange with the deep ocean, owing to its large size and relatively rapid exchange with the atmosphere1. The Southern Ocean is thought to have a key role in this exchange, as much of the deep ocean is ventilated to the atmosphere in this region2. However, it is difficult to reconstruct changes in deep Southern Ocean carbon storage, so few direct tests of this hypothesis have been carried out. Here we present deep-sea coral boron isotope data that track the pH—and thus the CO2 chemistry—of the deep Southern Ocean over the past forty thousand years. At sites closest to the Antarctic continental margin, and most influenced by the deep southern waters that form the ocean’s lower overturning cell, we find a close relationship between ocean pH and atmospheric CO2: during intervals of low CO2, ocean pH is low, reflecting enhanced ocean carbon storage; and during intervals of rising CO2, ocean pH rises, reflecting loss of carbon from the ocean to the atmosphere. Correspondingly, at shallower sites we find rapid (millennial- to centennial-scale) decreases in pH during abrupt increases in CO2, reflecting the rapid transfer of carbon from the deep ocean to the upper ocean and atmosphere. Our findings confirm the importance of the deep Southern Ocean in ice-age CO2 change, and show that deep-ocean CO2 release can occur as a dynamic feedback to rapid climate change on centennial timescales.PostprintPeer reviewe

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climate simulators that can sidestep Moore's Law by outsourcing compute-hungry, short, high-resolution simulations to ML emulators. However, this hybrid ML-physics simulation approach requires domain-specific treatment and has been inaccessible to ML experts because of lack of training data and relevant, easy-to-use workflows. We present ClimSim, the largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator's macro-scale physical state.The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators. We implement a range of deterministic and stochastic regression baselines to highlight the ML challenges and their scoring. The data (https://huggingface.co/datasets/LEAP/ClimSim_high-res) and code (https://leap-stc.github.io/ClimSim) are released openly to support the development of hybrid ML-physics and high-fidelity climate simulations for the benefit of science and society