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Atlantic meridional overturning circulation (AMOC) plays an important role in transporting heat meridionally in the Earth’s climate system and is also a key metrical tool to verify oceanic general circulation models. Two OMIP (Ocean Model Intercomparison Project phase 1 and 2) simulations with LICOM3 (version 3 of the LASG/IAP Climate System Ocean Model) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics (IAP), are compared in this study. Both simulations well reproduce the fundamental characteristics of the AMOC, but the OMIP1 simulation shows a significantly stronger AMOC than the OMIP2 simulation. Because the LICOM3 configurations are identical between these two experiments, any differences between them must be attributed to the surface forcing data. Further analysis suggests that sea surface salinity (SSS) differences should be mainly responsible for the enhanced AMOC in the OMIP1 simulation, but sea surface temperature (SST) also play an unignorable role in modulating AMOC. In the North Atlantic, where deep convection occurs, the SSS in OMIP1 is more saline than that in OMIP1. We find that in the major region of deep convection, the change of SSS has more significant effect on density than the change of SST. As a result, the SSS was more saline than that in OMIP2, leading to stronger deep convection and subsequently intensify the AMOC. We conduct a series of numerical experiments with LICOM3, and the results confirmed that the changes in SSS have more significant effect on the strength of AMOC than the changes in SST.

The concentration of radiocarbon (14C) differs between ocean and atmosphere. Radiocarbon determinations from samples which obtained their 14C in the marine environment therefore need a marine-specific calibration curve and cannot be calibrated directly against the atmospheric-based IntCal20 curve. This paper presents Marine20, an update to the internationally agreed marine radiocarbon age calibration curve that provides a non-polar global-average marine record of radiocarbon from 0–55 cal kBP and serves as a baseline for regional oceanic variation. Marine20 is intended for calibration of marine radiocarbon samples from non-polar regions; it is not suitable for calibration in polar regions where variability in sea ice extent, ocean upwelling and air-sea gas exchange may have caused larger changes to concentrations of marine radiocarbon. The Marine20 curve is based upon 500 simulations with an ocean/atmosphere/biosphere box-model of the global carbon cycle that has been forced by posterior realizations of our Northern Hemispheric atmospheric IntCal20 14C curve and reconstructed changes in CO2 obtained from ice core data. These forcings enable us to incorporate carbon cycle dynamics and temporal changes in the atmospheric 14C level. The box-model simulations of the global-average marine radiocarbon reservoir age are similar to those of a more complex three-dimensional ocean general circulation model. However, simplicity and speed of the box model allow us to use a Monte Carlo approach to rigorously propagate the uncertainty in both the historic concentration of atmospheric 14C and other key parameters of the carbon cycle through to our final Marine20 calibration curve. This robust propagation of uncertainty is fundamental to providing reliable precision for the radiocarbon age calibration of marine based samples. We make a first step towards deconvolving the contributions of different processes to the total uncertainty; discuss the main differences of Marine20 from the previous age calibration curve Marine13; and identify the limitations of our approach together with key areas for further work. The updated values for ΔR, the regional marine radiocarbon reservoir age corrections required to calibrate against Marine20, can be found at the data base http://calib.org/marine/.

Mercury (Hg) is emitted to the atmosphere mainly as volatile elemental Hg0. Oxidation to water-soluble HgII plays a major role in Hg deposition to ecosystems. Here, we implement a new mechanism for atmospheric Hg0 ∕ HgII redox chemistry in the GEOS-Chem global model and examine the implications for the global atmospheric Hg budget and deposition patterns. Our simulation includes a new coupling of GEOS-Chem to an ocean general circulation model (MITgcm), enabling a global 3-D representation of atmosphere–ocean Hg0 ∕ HgII cycling. We find that atomic bromine (Br) of marine organobromine origin is the main atmospheric Hg0 oxidant and that second-stage HgBr oxidation is mainly by the NO2 and HO2 radicals. The resulting chemical lifetime of tropospheric Hg0 against oxidation is 2.7 months, shorter than in previous models. Fast HgII atmospheric reduction must occur in order to match the  ∼  6-month lifetime of Hg against deposition implied by the observed atmospheric variability of total gaseous mercury (TGM  ≡  Hg0 + HgII(g)). We implement this reduction in GEOS-Chem as photolysis of aqueous-phase HgII–organic complexes in aerosols and clouds, resulting in a TGM lifetime of 5.2 months against deposition and matching both mean observed TGM and its variability. Model sensitivity analysis shows that the interhemispheric gradient of TGM, previously used to infer a longer Hg lifetime against deposition, is misleading because Southern Hemisphere Hg mainly originates from oceanic emissions rather than transport from the Northern Hemisphere. The model reproduces the observed seasonal TGM variation at northern midlatitudes (maximum in February, minimum in September) driven by chemistry and oceanic evasion, but it does not reproduce the lack of seasonality observed at southern hemispheric marine sites. Aircraft observations in the lowermost stratosphere show a strong TGM–ozone relationship indicative of fast Hg0 oxidation, but we show that this relationship provides only a weak test of Hg chemistry because it is also influenced by mixing. The model reproduces observed Hg wet deposition fluxes over North America, Europe, and China with little bias (0–30 %). It reproduces qualitatively the observed maximum in US deposition around the Gulf of Mexico, reflecting a combination of deep convection and availability of NO2 and HO2 radicals for second-stage HgBr oxidation. However, the magnitude of this maximum is underestimated. The relatively low observed Hg wet deposition over rural China is attributed to fast HgII reduction in the presence of high organic aerosol concentrations. We find that 80 % of HgII deposition is to the global oceans, reflecting the marine origin of Br and low concentrations of organic aerosols for HgII reduction. Most of that deposition takes place to the tropical oceans due to the availability of HO2 and NO2 for second-stage HgBr oxidation.

The long-term response of the Atlantic meridional overturning circulation (AMOC) to climate change remains poorly understood, in part due to the computational expense associated with running atmosphere–ocean general circulation models (GCMs) to equilibrium. Here, we use a collection of millennial-length GCM simulations to examine the transient and equilibrium responses of the AMOC to an abrupt quadrupling of atmospheric carbon dioxide. We find that GCMs consistently simulate an AMOC weakening during the first century but exhibit diverse behaviors over longer time scales, showing different recovery levels. To explain the AMOC behavior, we use a thermal-wind expression, which links the overturning circulation to the meridional density difference between deep-water formation regions and the Atlantic basin. Using this expression, we attribute the evolution of the AMOC on different time scales to changes in temperature and salinity in distinct regions. The initial AMOC shoaling and weakening occurs on centennial time scales and is attributed to a warming of the deep-water formation region. A partial recovery of the AMOC occurs over the next few centuries, and is linked to a simultaneous warming of the Atlantic basin and a positive high-latitude salinity anomaly. The latter reduces the subsurface stratification and reinvigorates deep-water formation. GCMs that exhibit a prolonged AMOC weakening tend to have smaller high-latitude salinity anomalies and increased Arctic sea ice loss. After multiple millennia, the AMOC in some GCMs is stronger than the initial state due to warming of the low-latitude Atlantic. These results highlight the importance of considering high-latitude freshwater changes when examining the past and future evolution of the AMOC evolution on long time scales.

Atmosphere‐ocean general circulation models (AOGCMs) struggle to reproduce recently observed sea surface temperature (SST) trend patterns. Here, we quantify the relevance of this SST pattern uncertainty to global‐mean temperature projections through convolving Green's functions with SST pattern scenarios that differ from the ones AOGCMs produce by themselves. We find that future SST pattern uncertainty has a significant impact on projections, such as increasing total model uncertainty by 40% in a high‐emissions scenario by 2085. A reversal of the current cooling trend in the East Pacific over the next few decades could lead to a period of global‐mean warming with a 60% higher rate than currently projected. SST pattern uncertainty works through a destabilization of the shortwave cloud feedback to affect temperature projections. It is critical for climate change impact, adaptation, and mitigation assessments to incorporate this previously unaccounted for uncertainty until we trust the evolution of SST patterns in AOGCMs. Plain Language Summary Temperature projections from climate models guide global adaptation and mitigation efforts in response to anthropogenic climate change. However, these climate models are unable to reproduce the pattern of recently observed sea surface temperature (SST) trends in large regions. In this study, we demonstrate how this discrepancy between observations and models, which we define as SST pattern uncertainty, impacts future global‐mean temperature projections. We find that SST pattern uncertainty significantly impacts projections. In fact, when the current cooling SST trend in the East Pacific switches to a warming trend, the planet could experience a period of strong warming with a warming rate 60% greater than what current projections from climate models suggest. We recommend this uncertainty be incorporated into future climate change assessments until we thoroughly trust the pattern of SST evolution in climate models. Key Points Since climate models struggle to reproduce the recently observed sea surface temperature trend pattern, they may continue doing so in the future Accounting for this error in temperature projections increases uncertainty by as much as 40% in a high emissions scenario by 2085 A reversal of the cooling trend in the East Pacific could lead to a warming rate 60% higher than current projections

Experiments with CO₂ instantaneously quadrupled and then held constant are used to show that the relationship between the global-mean net heat input to the climate system and the global-mean surface air temperature change is nonlinear in phase 5 of the Coupled Model Intercomparison Project (CMIP5) atmosphere–ocean general circulation models (AOGCMs). The nonlinearity is shown to arise from a change in strength of climate feedbacks driven by an evolving pattern of surface warming. In 23 out of the 27 AOGCMs examined, the climate feedback parameter becomes significantly (95% confidence) less negative (i.e., the effective climate sensitivity increases) as time passes. Cloud feedback parameters show the largest changes. In the AOGCM mean, approximately 60% of the change in feedback parameter comes from the tropics (30°N–30°S). An important region involved is the tropical Pacific, where the surface warming intensifies in the east after a few decades. The dependence of climate feedbacks on an evolving pattern of surface warming is confirmed using the HadGEM2 and HadCM3 atmosphere GCMs (AGCMs). With monthly evolving sea surface temperatures and sea ice prescribed from its AOGCM counterpart, each AGCM reproduces the time-varying feedbacks, but when a fixed pattern of warming is prescribed the radiative response is linear with global temperature change or nearly so. It is also demonstrated that the regression and fixed-SST methods for evaluating effective radiative forcing are in principle different, because rapid SST adjustment when CO₂ is changed can produce a pattern of surface temperature change with zero global mean but nonzero change in net radiation at the top of the atmosphere (∼−0.5W m−2in HadCM3).

Across the stable density stratification of the abyssal ocean, deep dense water is slowly propelled upward by sustained, though irregular, turbulent mixing. The resulting mean upwelling determines large-scale oceanic circulation properties like heat and carbon transport. In the ocean interior, this turbulent mixing is caused mainly by breaking internal waves: generated predominantly by winds and tides, these waves interact nonlinearly, transferring energy downscale, and finally become unstable, break and mix the water column. This paradigm, long parameterized heuristically, still lacks full theoretical explanation. Here, we close this gap using wave-wave interaction theory with input from both localized and global observations. We find near-ubiquitous agreement between first-principle predictions and observed mixing patterns in the global ocean interior. Our findings lay the foundations for a wave-driven mixing parameterization for ocean general circulation models that is entirely physics-based, which is key to reliably represent future climate states that could differ substantially from today’s. The authors use interacting internal wave theory and global observational databases to calculate the turbulent energy rate available for ocean mixing, which is a critical metric for climate prediction that is still lacking rigorous understanding.

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

BRAN2020 (2020 version of the Bluelink ReANalysis) is an ocean reanalysis that combines observations with an eddy-resolving, near-global ocean general circulation model to produce a four-dimensional estimate of the ocean state. The data assimilation system employed is ensemble optimal interpolation, implemented with a new multiscale approach that constrains the broad-scale ocean properties and the mesoscale circulation in two steps. There is a separation in the scales that are corrected in the two steps: the high-resolution step corrects the mesoscale dynamics in the same way as previous versions of BRAN, while the extra coarse step is effective at correcting biases that develop at large scales. The reanalysis currently spans January 1993 to December 2019 and assimilates observations of in situ temperature and salinity, as well as of satellite sea-level anomaly and sea surface temperature. BRAN2020 is planned to be updated to within months of real time after this initial release, until an updated version of BRAN is available. Reanalysed fields from BRAN2020 generally show much closer agreement to observations than all previous versions with misfits between reanalysed and observed fields reduced by over 30 % for some variables, for subsurface temperature and salinity in particular. The BRAN2020 dataset is comprised of daily averaged fields of temperature, salinity, velocity, mixed-layer depth and sea level. Reanalysed fields realistically represent all of the major current systems within 75∘ S and 75∘ N, excluding processes relating to sea ice but including boundary currents, equatorial circulation, Southern Ocean variability and mesoscale eddies. BRAN2020 is publicly available at https://doi.org/10.25914/6009627c7af03 (Chamberlain et al., 2021b) and is intended for use by the research community.

A new version of the atmosphere–ocean general circulation model cooperatively produced by the Japanese research community, known as the Model for Interdisciplinary Research on Climate (MIROC), has recently been developed. A century-long control experiment was performed using the new version (MIROC5) with the standard resolution of the T85 atmosphere and 1° ocean models. The climatological mean state and variability are then compared with observations and those in a previous version (MIROC3.2) with two different resolutions (medres, hires), coarser and finer than the resolution of MIROC5. A few aspects of the mean fields in MIROC5 are similar to or slightly worse than MIROC3.2, but otherwise the climatological features are considerably better. In particular, improvements are found in precipitation, zonal mean atmospheric fields, equatorial ocean subsurface fields, and the simulation of El Niño–Southern Oscillation. The difference between MIROC5 and the previous model is larger than that between the two MIROC3.2 versions, indicating a greater effect of updating parameterization schemes on the model climate than increasing the model resolution. The mean cloud property obtained from the sophisticated prognostic schemes in MIROC5 shows good agreement with satellite measurements. MIROC5 reveals an equilibrium climate sensitivity of 2.6 K, which is lower than that in MIROC3.2 by 1 K. This is probably due to the negative feedback of low clouds to the increasing concentration of CO₂, which is opposite to that in MIROC3.2.