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The ocean carbon reservoir controls atmospheric carbon dioxide (CO2) on millennial timescales. Radiocarbon (14C) anomalies in eastern North Pacific sediments suggest a significant release of geologic 14C‐free carbon at the end of the last ice age but without evidence of ocean acidification. Using inverse carbon cycle modeling optimized with reconstructed atmospheric CO2 and 14C/C, we develop first‐order constraints on geologic carbon and alkalinity release over the last 17.5 thousand years. We construct scenarios allowing the release of 850–2,400 Pg C, with a maximum release rate of 1.3 Pg C yr−1, all of which require an approximate equimolar alkalinity release. These neutralized carbon addition scenarios have minimal impacts on the simulated marine carbon cycle and atmospheric CO2, thereby demonstrating safe and effective ocean carbon storage. This deglacial phenomenon could serve as a natural analog to the successful implementation of gigaton‐scale ocean alkalinity enhancement, a promising marine carbon dioxide removal method. Plain Language Summary: The ocean is the largest carbon reservoir on Earth's surface and, as such, it controls the concentration of the greenhouse gas carbon dioxide (CO2) in the atmosphere over long time periods. When CO2 was rising at the end of the last ice age, marine sediment evidence indicates a regional carbon release into the ocean, due to a distinct carbon isotope fingerprint left behind. Using a carbon cycle model and atmospheric data, we simulated different geologic carbon addition scenarios since the last ice age. We find that substantial carbon addition to the ocean could have occurred (up to 1.3 billion tons per year) without causing significant changes to the carbon cycle, but only if the carbon is neutralized by alkalinity in an approximate 1:1 ratio. This neutralized release is similar to an approach of carbon removal called ocean alkalinity enhancement (OAE), which aims to reduce atmospheric CO2 as a potential solution for climate change. These findings suggest that neutralized carbon addition—in the form of "neutralized" bicarbonate ion HCO3− $\left({\text{HCO}}_{3}^{-}\right)$ instead of "acidic" CO2—could explain the low levels of radiocarbon during the last deglaciation and shows that large‐scale OAE is feasible without causing major changes to the marine carbon cycle. Key Points: Observed deglacial changes in atmospheric CO2 and 14C/C allow for up to 2,396 Pg of neutralized geologic carbon (i.e., bicarbonate) releaseThe global carbon cycle is essentially "blind" to neutralized carbon release, only constrained by 14C budgetThis gigaton‐scale neutralized carbon release may be a natural analog to the marine CO2 removal method of ocean alkalinity enhancement [ABSTRACT FROM AUTHOR]

We quantify an elevated occurrence of abrupt changes in ocean environmental conditions under human‐induced climate forcing using Earth system model output through a novel analysis method that compares the temporal evolution of the forcings applied with the development of local ocean state changes for temperature, oxygen concentration, and carbonate ion concentration. Through a multi‐centennial Earth system model experiment, we show that such an increase is not fully reversible after excess greenhouse gas emissions go back to zero. The increase in occurrence of regional abrupt changes in marine environmental conditions has not yet been accounted for adequately in climate impact analyses that usually associate ecosystem shifts large‐scale variability or extreme events. Estimates for remaining greenhouse gas emission targets need thus to be more conservative. Plain Language Summary: The ocean warms up, gets more acidic, and loses oxygen under progressing anthropogenic climate change putting ecosystems under stress. Regionally, abrupt changes in temperature, acidity, and dissolved oxygen concentration can occur and may make it impossible for organisms to adjust to these new environmental conditions, thereby increasing the risk for deterioration of entire ecosystems. The study provides evidence for elevated occurrence of regional abrupt changes in marine environmental conditions that is not yet accounted for appropriately in climate impact analyses that usually associate ecosystem shifts with changes in large‐scale variability or extreme events. Therefore, the time window for effective climate mitigation to prevent unwanted marine ecosystem impacts may close sooner than previously expected. Key Points: There is an elevated occurrence of abrupt changes in key ocean state variables under human‐induced climate forcingThe occurrence of abrupt changes in the upper ocean peaks around the maximum of the rate of change in human‐induced forcingA multi‐centennial legacy is expected for abrupt shifts in environmental conditions, long after a stop of anthropogenic CO2 emissions [ABSTRACT FROM AUTHOR]

Vertical mixing parameterizations in ocean models are formulated on the basis of the physical principles that govern turbulent mixing. However, many parameterizations include ad hoc components that are not well constrained by theory or data. One such component is the eddy diffusivity model, where vertical turbulent fluxes of a quantity are parameterized from a variable eddy diffusion coefficient and the mean vertical gradient of the quantity. In this work, we improve a parameterization of vertical mixing in the ocean surface boundary layer by enhancing its eddy diffusivity model using data‐driven methods, specifically neural networks. The neural networks are designed to take extrinsic and intrinsic forcing parameters as input to predict the eddy diffusivity profile and are trained using output data from a second moment closure turbulent mixing scheme. The modified vertical mixing scheme predicts the eddy diffusivity profile through online inference of neural networks and maintains the conservation principles of the standard ocean model equations, which is particularly important for its targeted use in climate simulations. We describe the development and stable implementation of neural networks in an ocean general circulation model and demonstrate that the enhanced scheme outperforms its predecessor by reducing biases in the mixed‐layer depth and upper ocean stratification. Our results demonstrate the potential for data‐driven physics‐aware parameterizations to improve global climate models. Plain Language Summary: The upper region of the ocean is highly energetic and is responsible for transferring mass, energy and biogeochemical tracers between the atmosphere and the deeper regions of the ocean. This transport takes place because of turbulent swirling motions, which are found to be of varying sizes. Climate models cannot represent all of these motions because smaller‐scale swirls are complex and require additional computational resources. As we cannot neglect those small swirls, we try to approximate their effects on larger‐scale motions using mathematical models. These models have a few ad hoc or empirical assumptions that lead to uncertainty when these climate models are used to project the future climate. To reduce this uncertainty, we augment an existing model of turbulent swirling process with machine learning, which replaces some ad hoc approximations with data‐driven neural networks. Neural networks can learn those missing processes more accurately than a traditional physics‐based model. The neural networks are shown to improve physics in climate simulations. Although we only touch on one component in an ocean climate model, this approach can be replicated to improve any other component that was using ad hoc assumptions and replace them with data‐driven models using techniques from machine learning. Key Points: We improve a parameterization of vertical mixing in the ocean surface boundary layer using neural networksNeural networks are trained to predict the diffusivity of second moment closure and maintain energetic constraints of the original parameterizationThe improved scheme reduces biases of mixed layer depth and thermocline in an atmospherically forced ocean model [ABSTRACT FROM AUTHOR]

In the last decade, an enormous amount of georeferenced oceanographic data, co-located with catch information, have been collected through the use of commercial fishing vessels operating in the Adriatic Sea and belonging to the fleet monitored by the AdriFOOS (Adriatic Fishery and Oceanography Observing System) infrastructure. This document describes the dataset of depth (pressure) and temperature profiles collected by means of AdriFOOS in the period 2012–2020 (available at 10.17882/73008, Penna et al., 2020) and briefly illustrates the structure of this facility, the oceanographic dataset validation procedures, and some of the results achieved, and it also lists some possible operational applications. This information is of the utmost importance to provide data to feed oceanographic models and advance knowledge on climate change, as well as to improve the ecosystem approach to fishery management. [ABSTRACT FROM AUTHOR]

Past intensity of methane release from deep-ocean methane hydrates continues to be challenging to reconstruct reliably. Here, we used fossil ostracode fauna paired with foraminiferal δ13C values in a marine sediment core from Vestnesa Ridge, western Svalbard margin, to reconstruct methane seepage activity during the late Quaternary and to examine faunal response to deglacial climatic changes. Benthic foraminiferal δ13C values indicate methane seepage activity was relatively strong during marine isotope stage 2, corresponding to a high percentage of the ostracode Rosaliella svalbardensis in the assemblage. In contrast, this species was absent under conditions of no or very strong seepage of methane. Faunal changes in other taxa were more related to global climate changes regardless of the seepage activity. This result indicates that Rosaliella svalbardensis is a potential new useful proxy for past methane release. [ABSTRACT FROM AUTHOR]

This document describes the dataset of depth (pressure)/temperature profiles collected by means of the AdriFOOS infrastructure in the period 2012-2020 and briefly illustrates the structure of this facility, the oceanographic dataset validation procedures, some of the results achieved, and also lists some possible operational applications. In fact, in the last decade, CNR IRBIM's AdriFOOS has collected an enormous amount of georeferenced oceanographic and catch data through the use of commercial fishing vessels operating in the Adriatic Sea. This information is of the utmost importance to provide data to feed oceanographic models and advance knowledge on climate change, as well as to improve the ecosystem approach to fisheries management. [ABSTRACT FROM AUTHOR]

We consider the sea level, air–sea heat flux, and wind stresses and use an ocean model to investigate the evolution of the Kuroshio path and intensity during the last 35,000 years. Relative to the present, the Kuroshio during the last glacial period traveled the same path albeit with higher surface velocity in the East China Sea, while it migrated northward south of Japan and southward at the Kuroshio Extension (KE). The southward migrations of the KE axis were closely related to the positions of zero wind‐stress curl. To a certain extent, stronger glacial trade winds enhanced the North Equatorial Current. Consequently, Kuroshio transport increased in the southern and middle Okinawa Trough. Regarding Kuroshio strength, we suggest that the horizontal gradient of the subsurface temperature would be a better indicator than the upper‐ocean vertical thermal gradient, which is a commonly used index in paleoceanography. Plain Language Summary: The last glacial age was characterized by millennial‐scale climate variations and sea‐level changes. Although the path and intensity of the Kuroshio during the last glacial age have been studied extensively, the evolution of the Kuroshio is still poorly understood because of limited observations and incomplete model configurations. Using an improved ocean model and paleoclimate air–sea forcing field, we simulated the changes in the Kuroshio and Kuroshio Extension (KE) from 35,000 years ago to the present. Compared to the present, the North Pacific subtropical gyre including its southern and northern boundaries (i.e., North Equatorial Current and KE) shifted southward during the glacial age, which was associated with the changes in the wind‐stress curl over the North Pacific. The North Equatorial Current and its northern branch (i.e., Kuroshio) was enhanced during the last glacial period. Consequently, the Kuroshio transport increased with a higher surface velocity in the southern and middle East China Sea. With sea level lowering and climatic variations at glacial times, the Kuroshio path south of Japan shifted northward. The KE shifted southward with a range of 0.5–3.5°, which depended on the longitudes. The Kuroshio Current at 6 ka became similar to that of modern day. Key Points: Ocean modeling suggests that, due to an enhanced North Equatorial Current, Kuroshio was stronger during last glacial period than at presentSouthward migration of the Kuroshio Extension during the last glacial period was between 0.5 and 3.5° depending on the longitudesModel results indicate that the vertical thermal gradient in the upper ocean is not a suitable indicator of the Kuroshio intensity [ABSTRACT FROM AUTHOR]

This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles (Goldman et al., 2021, https://doi.org/10.1002/essoar.10508554.1) in the AGU section paleoclimatology and paleoceanography (P&P), and a discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, technology transfer and application, reproducibility, and data sharing and infrastructure; (Section 3) Local knowledge, global gain: improving interactions within the scientific community and with locals, indigenous communities, stakeholders, and the public; (Section 4) Field, experimental, remote sensing, and real‐time data research and application. P&P projects can better include ICON principles by directly incorporating them into research proposals. A promising way to overcome the challenges of interdisciplinarity and integration is to foster networking, which will advance our research discipline through the application of ICON. Plain Language Summary: Paleoceanography and Paleoclimatology seeks to reveal past changes in the oceans and the climate, to help us better understand how Earth systems work. Traditionally, it has a strong focus on international networks and cooperation and we have accomplished many international projects. However, we are still facing some major challenges to achieve equity among researchers and science questions. In this article we discuss the current state, issues and solutions from three different perspectives: (a) data structure problems and data sharing issues, (b) relationships between research groups with different levels of knowledge, cultural aspects and their interaction with local communities in fieldwork, and (c) utilization of data, instrument sharing, promotion of networking, and effective communication with the public to make our research as inclusive and visible as possible. Actions aimed at ICON could be further promoted by research programs, governments, and scientists via integration of cooperation strategies into research projects. Key Points: Open science and global collaboration increase networking opportunities, data availability, and quality of scientific outcomesICON principles support inclusivity and diversity, and ultimately resulting in increased and quicker uptake of scientific outcomesICON practices are well established in large‐scale international collaborations, but coordinated data and sampling standards are needed [ABSTRACT FROM AUTHOR]

Understanding climate change impacts on top predators is fundamental to marine biodiversity conservation, due to their increasingly threatened populations and their importance in marine ecosystems. We conducted a systematic review of the effects of climate change (prolonged, directional change) and climate variability on seabirds and marine mammals. We extracted data from 484 studies (4808 published studies were reviewed), comprising 2215 observations on demography, phenology, distribution, diet, behaviour, body condition and physiology. The likelihood of concluding that climate change had an impact increased with study duration. However, the temporal thresholds for the effects of climate change to be discernibly varied from 10 to 29 years depending on the species, the biological response and the oceanic study region. Species with narrow thermal ranges and relatively long generation times were more often reported to be affected by climate change. This provides an important framework for future assessments, with guidance on response‐ and region‐specific temporal dimensions that need to be considered when reporting effects of climate change. Finally, we found that tropical regions and non‐breeding life stages were poorly covered in the literature, a concern that should be addressed to enable a better understanding of the vulnerability of marine predators to climate change. [ABSTRACT FROM AUTHOR]

Plankton communities play an important role in marine food webs, in biogeochemical cycling, and in Earth's climate; yet observations are sparse, and predictions of how they might respond to climate change vary. Correlative species distribution models (SDM's) have been applied to predicting biogeography based on relationships to observed environmental variables. To investigate sources of uncertainty, we use a correlative SDM to predict the plankton biogeography of a 21st century marine ecosystem model (Darwin). Darwin output is sampled to mimic historical ocean observations, and the SDM is trained using generalized additive models. We find that predictive skill varies across test cases, and between functional groups, with errors that are more attributable to spatiotemporal sampling bias than sample size. End‐of‐century predictions are poor, limited by changes in target‐predictor relationships over time. Our findings illustrate the fundamental challenges faced by empirical models in using limited observational data to predict complex, dynamic systems. Plain Language Summary: Marine plankton communities play a central role within Earth's climate system, with important processes often divided among different "functional groups." Changes in the relative abundance of these groups can therefore impact on ecosystem function. However, the oceans are vast, and samples are sparse, so global distributions are not well known. Statistical species distribution models (SDM's) have been developed that predict global distributions based on their relationships with observed environmental variables. They appear to perform well at summarizing present day distributions, and are increasingly being used to predict ecosystem changes throughout the 21st century. But it is not guaranteed that such models remain valid over time. Rather than wait 100 years to find out, we applied a statistical SDM to a complex virtual ocean, and trained it using virtual observations that match real‐world ocean samples. This allows us to jump forward to the end‐of‐century to test the accuracy of our predictions. The SDM performed well at qualitatively predicting "present day" plankton distributions but yielded poor end‐of‐century predictions. Our case study emphasizes both the importance of environmental variable selection, and of changes in the underlying relationships between environmental variables and plankton distributions, in terms of model validity over time. Key Points: We use a correlative species distribution model to predict the global plankton biogeography of a trait‐based ecosystem modelPredictive skill varies across test cases, with functional group, and spatiotemporally, with poor end‐of‐century performanceKey sources of uncertainty are traced to sampling biases in observations, and the temporal variability in target‐predictor relationships [ABSTRACT FROM AUTHOR]

ESA's Next Generation Gravity Mission (NGGM) is a candidate Mission of Opportunity for ESA–NASA cooperation in the frame of the Mass Change and Geosciences International Constellation (MAGIC). The mission aims at enabling long-term monitoring of the temporal variations of Earth's gravity field at relatively high temporal (down to 3 days) and increased spatial resolutions (up to 100 km) at longer time intervals. This implies also that time series of GRACE and GRACE-FO can be extended towards a climate series. Such variations carry information about mass change induced by the water cycle and the related mass exchange among atmosphere, oceans, cryosphere, land and solid Earth and will complete our picture of global and climate change. The main observable is the variation of the distance between two satellites measured by a ranging instrument. This is complemented by accelerometers that measure the nongravitational accelerations, which need to be reduced from ranging measurements to obtain the gravity signal. The preferred satellite constellation comprises one satellite pair in a near-polar and another in an inclined circular orbit. The paper focuses on the orbit selection methods for optimizing the spatial sampling for multiple temporal resolutions and then on the methodology for deriving the engineering requirements for the space segment, together with a discussion on the main mission parameters. [ABSTRACT FROM AUTHOR]