Feedbacks from the climate to other components of the coupled human-Earth system are expected to strongly influence the co-evolution of human society and its environment. Representing these feedback loops between climate and society, via the Earth system's response to human activities and the subsequent effect back onto social systems, is essential in order to fully explore the dynamics of the coupled system. However, focus on these feedbacks has traditionally been limited, or excluded, in prior Integrated Assessment Models (IAMs) and IAM-based modelling protocols. This limits the understanding of the effects of climate change and the response of the overall system to future emissions scenarios and policies. The new IAM Feedback-based knowledge Repository for IntegrateD Assessments version 2.1 (FRIDAv2.1), documented and explored within this paper collection, seeks to address this by internalising the feedbacks between subcomponents of the human-Earth system. Within this new IAM, these connections are therefore a key part of the structure, and are documented and discussed here. FRIDA represents these climate-to-society feedbacks, conceptualised as climate impacts, through global impact functions. Where possible, they are based on estimates from existing literature, reframed as functions of global climate variables to facilitate their representation within FRIDA. Other impact channels, with insufficient background literature to inform their structure and parameter values, are incorporated via the internal calibration of the IAM. Since the systematic representation of climate damages within an IAM is a relatively novel endeavour, the approach is constrained by literature limitations and necessary simplifications. In addition, the high level of abstraction of the FRIDA model imposes limits on the set of impacts which can reasonably be implemented, and the level of process detail amongst those included. Nevertheless, FRIDA's endogenous representation of climate feedbacks to human and natural systems enables valuable insights and intuition building on an underexplored topic. The general nature of the climate damage functions aggregated and documented here allows for their incorporation within other models and frameworks.

The new global Feedback-based knowledge Repository for IntegrateD Assessments version 2.1 (FRIDAv2.1) Integrated Assessment Model (IAM) seeks to study the dynamics of the coupled human-Earth system. Connecting anthropogenic emissions to the resultant climate response is one part of the two-way feedback within this system, with the resultant climate impacts the other. This paper documents both the Climate Module within FRIDAv2.1, and the modified version separately simulated as a standalone simple climate model termed FRIDA-Clim version 1.0.1. This approach, based loosely on the existing FaIR simple climate model, simulates the key radiative forcings and the resultant temperature response, with process-based representations of the carbon cycle across the ocean, land, and atmosphere. When connected within the FRIDA IAM, it features deep connections to the other modules, being affected by processes such as water use for irrigation and land use change. In both uses, i.e. with the climate response interactively connected to the upstream human drivers and downstream climate impacts within the FRIDA IAM (coupled) and when ran separately as FRIDA-Clim driven by exogenous forcings (uncoupled), its climate drivers are simplified as compared to FaIR. This is to allow for this reduced set of key drivers to be interactively simulated within FRIDA, tightly coupling the evolution of the social and climate systems within the full model. Both the Climate Module and FRIDA-Clim are fully calibrated to accurately reproduce observations of key climate variables, with a systematic exploration of the uncertainty in the climate response. Together with the rest of the FRIDA model, this module is used to incorporate climate change systematically in the FRIDA System Dynamics IAM. As a standalone climate model, FRIDA-Clim comprises a simple climate model, enabling fast calculation of the global climate response to forcing; to explore this, the response of the model to both idealised CO2 emissions experiments and plausible future scenarios is also presented here. This setup will allow FRIDA-Clim to contribute to inter-model simple climate modelling initiatives, helping to explore the structural uncertainty in this modelling domain.

Future climate scenario projections are usually run with prescribed atmospheric CO2 concentrations. However, by not allowing the carbon cycle to interactively respond to emissions in Earth System models, the role of carbon cycle feedbacks on contributions to differences in climate model projections may be undersampled. Here, we present the main findings of two Earth System Models (MPI-ESM1.2-LR and NorESM2-LM) run with CO2 emissions to 2300 for three scenarios, two of which are climate overshoot scenarios, that were part of the Coupled Model Intercomparison Project Phase 6 (CMIP6). These experiments serve three important purposes: (i) an increasing focus on emissions driven runs, supplementing scenarios produced for the Coupled Climate-Carbon Cycle (C4MIP) and Carbon Dioxide Removal (CDRMIP) contributions to CMIP6; (ii) a focus on overshoot scenarios; and (iii) an extension of results beyond 2100, the timescales at which some of the most significant differences play out. Of the two models, NorESM2-LM shows more asymmetry in its climate response at the same global mean temperature levels before and after peak warming, particularly in terms of its regional pattern of warming and Atlantic Meridional Overturning Circulation (AMOC) response, with a substantially weakened AMOC persisting for decades after peak warming that takes more than a century to recover. In contrast, MPI-ESM1.2-LR shows reversibility with AMOC strength and regional warming more closely following surface temperature, but with some climate signals such as sea-level rise and ocean deoxygenation essentially irreversible. This diversity in model responses highlights the need for further research with a larger model ensemble that focuses on long-term emissions-driven model runs, particularly for overshoot scenarios, for CMIP7.

The current crop of models assessed by the Intergovernmental Panel on Climate Change (IPCC) to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, especially beyond the purely economic consequences of climate change. These climate-driven changes in human activities are critical to understanding the co-evolution of the climate and human systems. Earth System Models (ESMs) that represent the climate system and Integrated Assessment Models (IAMs) that represent the human system are typically separate, with assumptions that create coherency coordinated through RCPs and SSPs in ScenarioMIP, the core scenario analysis protocol. This divide limits understanding of climate-human feedback. An alternative aggregated approach, which couples human and natural systems (CHANS) such as the one used to build the Feedback-based knowledge Repository for IntegrateD Assessments “FRIDA” v2.1 IAM documented here, integrates climate and human systems into a unified global model, prioritizing feedback dynamics while maintaining interpretability. FRIDA represents the Earth's radiation balance, carbon cycle, and relevant portions of the water cycle alongside human demographics, economics, agriculture, and human energy use. Built using the System Dynamics method, it contains seven interconnected modules. Each subsystem is calibrated to data and validated to ensure structurally appropriate behaviour representation. FRIDA demonstrates that an aggregate, feedback-driven modelling approach, capturing CHANS interconnections with rigorous measurements of uncertainty, is possible. It complements conventional IAMs by highlighting missing feedback structures that affect future projections. Our work with FRIDA suggests SSP1-Baseline, SSP2-Baseline, and SSP5-Baseline are all overly optimistic on the prospects for future economic growth due to these feedbacks, while SSP3-Baseline and SSP4-Baseline, the SSPs with the highest challenges to adaptation, align more closely with our results. Future work will further refine climate impact representations, energy modelling, policy scenario creation, and stakeholder engagement for informed policymaking.

Storm surges can give rise to extreme floods in coastal areas. The Norwegian Meteorological Institute (MET Norway) produces 120 h regional operational storm surge forecasts along the coast of Norway based on the Regional Ocean Modeling System (ROMS), using a model setup called Nordic4-SS. Despite advances in the development of models and computational capabilities, forecast errors remain large enough to impact response measures and issued alerts, in particular, during the strongest storm events. Reducing these errors will positively impact the efficiency of the warning systems while minimizing efforts and resources. Here, we investigate how forecasts can be improved with residual learning, i.e., training data -driven models to predict the residuals in forecasts from Nordic4-SS. A simple error mapping technique and a more sophisticated Neural Network (NN) method are tested. The simple error mapping technique provides a reduction in the Root Mean Square Error (RMSE) of less than 4%. Using the NN residual correction method, the RMSE in the Oslo Fjord is reduced by 36% for lead times of one hour, 9% for 24 h, and 5% for 60 h. Therefore, the residual NN method is a promising direction for correcting storm surge forecasts, especially on short timescales. Moreover, it is well adapted to being deployed operationally, as (i) the correction is applied on top of the existing model and requires no changes to it, (ii) all predictors used for NN inference are already available operationally, (iii) prediction by the NNs is very fast, typically a few seconds per station, and (iv) the NN correction can be provided to a human expert who may inspect it, compare it with the model output, and see how much correction is brought by the NN, allowing to capitalize on human expertise as a quality validation of the NN output. While no changes to the hydrodynamic model are necessary to calibrate the neural networks, they are specific to a given model and must be recalibrated when the numerical models are updated.

The Barents Sea is one of the Polar regions where current climate and ecosystem change is most pronounced. Here we review the current state of knowledge of the physical, chemical and biological systems in the Barents Sea. Physical conditions in this area are characterized by large seasonal contrasts between partial sea-ice cover in winter and spring versus predominantly open water in summer and autumn. Observations over recent decades show that surface air and ocean temperatures have increased, sea-ice extent has decreased, ocean stratification has weakened, and water chemistry and ecosystem components have changed, the latter in a direction often described as “Atlantification” or “borealisation,” with a less “Arctic” appearance. Temporal and spatial changes in the Barents Sea have a wider relevance, both in the context of large-scale climatic (air, water mass and sea-ice) transport processes and in comparison to other Arctic regions. These observed changes also have socioeconomic consequences, including for fisheries and other human activities. While several of the ongoing changes are monitored and quantified, observation and knowledge gaps remain, especially for winter months when field observations and sample collections are still sparse. Knowledge of the interplay of physical and biogeochemical drivers and ecosystem responses, including complex feedback processes, needs further development.

This paper reviews physical mechanisms, observation techniques and modelling approaches dealing with surface currents on short time scales (hours to days) relevant for operational oceanography. Key motivations for this article include fundamental difficulties in reliable measurements and the persistent lack of a widely held consensus on the definition of surface currents. These problems are augmented by the fact that various methods to observe and model ocean currents yield very different representations of a surface current. We distinguish between four applicable definitions for surface currents; (i) the interfacial surface current, (ii) the direct wind-driven surface current, (iii) the surface boundary layer current, and (iv) an effective drift current. Finally, we discuss challenges in synthesising various data sources of surface currents - i.e. observational and modelling - and take a view on the predictability of surface currents concluding with arguments that parts of the surface circulation exhibit predictability useful in an operational context.

We explore drivers of variability in the Norwegian Atlantic Slope Current, which carries relatively warm Atlantic Water toward the Barents Sea and Arctic Ocean, using Copernicus Marine Environment Monitoring Service (CMEMS) satellite altimetry data and TOPAZ4 ocean reanalysis data. Previous studies have pointed to a variety of causes, on a variety of time scales. We use data with daily resolution to investigate day-to-day changes in ocean transport across three sections crossing the shelf-slope of Norway (Svinoy, Gimsoy, and the Barents Sea Opening). The highest (lowest) extremes in transport at all sections develop over two days as a cyclonic (anticyclonic) atmospheric pressure system approaches from the southwest, piling up (extracting) water at the coast of Norway. The actual peak is reached when the pressure system passes the site of measurement, and the transport then relaxes for the next two days as the system continues northward along the coast. Other sources of short-term variability, such as propagating continental shelf waves and baroclinic instability, are unlikely to yield covariability over large separations. Monthly variability in the current can also be explained by passing weather systems since their numbers and intensity vary greatly from month to month. Many studies of longer-term variability, especially in the Barents Sea Opening, have pointed to the North Atlantic Oscillation (NAO) as the main cause of variability. Our results show that passing weather systems offer a better explanation of month-to-month variability.

Although great progress has been made to advance the scientific understanding of oil spills, tools for integrated assessment modeling of the long-term impacts on ecosystems, socioeconomics and human health are lacking. The objective of this study was to develop a conceptual framework that could be used to answer stakeholder questions about oil spill impacts and to identify knowledge gaps and future integration priorities. The framework was initially separated into four knowledge domains (ocean environment, biological ecosystems, socioeconomics, and human health) whose interactions were explored by gathering stakeholder questions through public engagement, assimilating expert input about existing models, and consolidating information through a system dynamics approach. This synthesis resulted in a causal loop diagram from which the interconnectivity of the system could be visualized. Results of this analysis indicate that the system naturally separates into two tiers, ocean environment and biological ecosystems versus socioeconomics and human health. As a result, ocean environment and ecosystem models could be used to provide input to explore human health and socioeconomic variables in hypothetical scenarios. At decadal-plus time scales, the analysis emphasized that human domains influence the natural domains through changes in oil-spill related laws and regulations. Although data gaps were identified in all four model domains, the socioeconomics and human health domains are the least established. Considerable future work is needed to address research gaps and to create fully coupled quantitative integrative assessment models that can be used in strategic decision-making that will optimize recoveries from future large oil spills.

Since the 2010 Deepwater Horizon (DWH) oil spill, the Gulf of Mexico Research Initiative (GOMRI) has studied the oil spill from the perspectives of ocean environment, ecosystems, socioeconomics and human health. As GOMRI sunsets in its tenth year after the DWH oil spill, synthesis efforts recently took place to assess the accomplishments of the program. In this paper, we report on DWH modeling as part of GOMRI's Synthesis and Legacy effort. We compile a list of 330 published applications by GOMRI, the Natural Resource Damage Assessment (NRDA), and others studying the DWH oil spill and look at a wide range of subjects, tools, achievements, and integration with field research. We offer highlights and synthesis based on discussions and public webinars held in 2019 and 2020. We synthesize the significant achievements and advancements that have been made in integrating the various disciplines and domains from a modeling perspective. There was a large diversity of tools used, including at least 74 unique modeling systems. Most studies employed circulation models. These hydrodynamic models were often coupled to wave, river, and atmosphere models, as well as representations of high pressure physics and oil chemistry. Several research groups used Lagrangian transport models and statistical inference to track subsurface oil. Some coupled biophysical models were also employed to study oil fate and weathering, larval transport, biological effects, and population dynamics. In a few cases, such biophysical models were linked to marine populations and to humans through socioeconomics effects and ecosystem services. We consider models made for response planning and remediation, damage assessment, and restoration planning. There are relatively few socioeconomic or human health models, although those few examples make good use of biophysical modeling products. Our conclusions offer some insights on how the development of new tools has better prepared us for studying environmental management challenges in the Gulf of Mexico.

Plastic litter is accumulating on pristine northern European beaches, including the European Arctic, and questions remain about the exact origins and sources. Here we investigate plausible fishery and consumer-related sources of beach littering, using a combination of information from expert stakeholder discussions, litter observations and a quantitative tool - a drift model - for forecasting and backtracking likely pathways of pollution. The numerical experiments were co-designed together with practice experts. The drift model itself was forced by operational ocean current, wave and weather forecasts. The model results were compared to a database of marine litter on beaches, collected every year according to the standardized monitoring program of the Oslo/Paris Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR). By comparing the heterogeneous beach observations to the model simulations, we are able to highlight probable sources. Two types of plastic are considered in the simulations: floating plastic litter and submerged, buoyant microplastics. We find that the model simulations are plausible in terms of the potential sources and the observed plastic litter. Our analysis results in identifiable sources of plastic waste found on each beach, providing a basis for stakeholder actions.

Marine litter has been systematically registered at selected beaching sites within a framework of the OSPAR commission. We select a number of sites in the North Sea, Norwegian Sea and the Barents Sea to investigate where marine litter at these site could come from. Using results from hydrodynamic ocean models, wave models and atmospheric forecasts we backtrace litter from the beaching sites to possible origins within a limited time frame at the order of years. While the identified sources are hypothetical at first, we compare the types of registered plastic litter with reasonable sources in the regions identified as possible origins from the model. Thereby we distinguish between fishery related litter, industrial litter and litter from personal consumption, as the composition between these types differ between the OSPAR sites. Our modeling experiments are designed in co-production with stakeholders for planning strategies to address and reduce marine litter.

Climate model projections are used to investigate the potential impacts of climate change on future weather, agriculture, water resources, human health, the global economy, etc. However, climate projections have a broad range of associated uncertainties, and it is a challenge to take account of these uncertainties in impact studies and risk assessments. Knowing which uncertainties matter and which may be reduced via scientific research or political decisions can help policy-makers in making informed decisions, scientists in focusing their resources, and businesses in building resilience to uncertainties that cannot be avoided. On the global scale, the present political resistance or ability to move from agreements to significant action provides the largest uncertainty in climate projections, followed by the uncertainty associated with climate modelling itself. Here, we show that climate sensitivity is a very important source of model uncertainty over large parts of the globe not only for temperature, but also for precipitation and wind projections. Because 'climate sensitivity' is a collective term that encompasses a wide range of feedback mechanisms in the climate system, we may not know for a long time whether models with high or low climate sensitivities are more relevant for the twenty-first century projections. Nevertheless, investigations of climate impacts cannot wait. Here we argue that it is physically and statistically unsound to mix climate model with high and low climate sensitivities, and that the subset chosen for any impact study should depend on the question one is trying to answer.

Transports of total volume and water masses obtained from a mooring array in the East Greenland Current (EGC) in Fram Strait are presented for the period 1997–2009. The array in the EGC was moved along isobaths from 79°N to 78°50′N in 2002 to line up with moorings in the eastern Fram Strait. Analysis of the time series at the two latitudes shows that associated with the southward move, the annual mean volume transport of the EGC increased from 5.8±1.8Sv to 8.7±2.5Sv, mostly related with an increase in barotropic flow. This suggests a recirculation of close to 3Sv at 78°50′N as a consequence of the large-scale wind-driven cyclonic gyre in the Nordic Seas. In addition, the volume transport at 78°50′N showed a clear seasonal cycle which was absent at 79°N. Estimates of the wind-driven Sverdrup transport at two different latitudes show that the difference in total volume transport and seasonality can largely be explained by the wind-stress curl. However, weak transport in 2003 was only partially related with weak Sverdrup transport and coincided also with anomalously weak northerly winds. The stronger recirculation at 78°50′N has also consequences for the observed Atlantic Water: there is significantly more Atlantic derived water present at the southerly latitude. In addition, the warm anomaly in Fram Strait between 2005 and 2007 doubled the amount of Recirculated Atlantic Water temporarily. Finally, we estimate that close to 2.7Sv, or 50%, of Atlantic derived water recirculates in Fram Strait.

Following indications of recent warming trends in the Nordic Seas, we have studied the hydrography of these marginal seas from the summer of 2007 until the fall of 2008, using observations gathered by instrumented seals and Argo floats. The combined dataset shows that the upper ocean was indeed both warmer and saltier over much of the Nordic Seas in 2007–2008 compared to the average ocean state for the period 1956–2006 (based on the World Ocean Atlas 2009). There are also indications that the surface Polar Waters of the East Greenland Current were colder and fresher than the climatology, though the quality of the climatology is questionable for this region given the low number of historical observations. Dynamic height calculations suggest that the observed hydrographic changes were associated with enhanced northward upper-ocean thermal wind transport in the east and possibly also enhanced southward transport in the west.

Observations made during the 1990s and 2000s indicate that the Arctic physical environment and associated ecosystem are undergoing remarkable changes. The observed reduction in Arctic sea ice extent is arguably the strongest, most powerful visual symbol of climate change. The Arctic Ocean is changing as well. Here we discuss, from an observational point of view, the present understanding of the circulation, water masses, and stratification of the Arctic Ocean, highlighting the changes that have taken place during the past few decades. Many of these ocean signals evolve rapidly, making it essential that the state of the Arctic/Subarctic is observed continually, using all the recent advances that have been made in high-latitude monitoring and in Earth System understanding. Taking recent investigations of the Arctic atmosphere and sea ice as guides, we deem it likely that signatures of anthropogenic climate change in the Arctic/Subarctic Seas will begin to emerge above the high level of natural variability within the next decade.

The northernmost limb of the Atlantic Meridional Overturning Circulation (AMOC), so relevant for understanding decadal climate variability, enters the Nordic Seas as the Norwegian Atlantic Current and continues on to recirculate in the Arctic Ocean. The strength of the Eastern Branch of the Norwegian Atlantic Current has been systematically monitored for over 15 years at the Svinøy section off southern Norway, whereas the strength of the Western Branch has not. We therefore used autonomous gliders to monitor and quantify the strength of this broader branch at the Svinøy section, located 500 km downstream from the Iceland–Scotland Ridge, and at the Station Mike section 300 km further downstream. The gliders' diving depth is 1000 m, spanning the warm Atlantic Water. The current encompasses more than warm Atlantic Water; we find that the transport peaks in two distinct temperature ranges, one around 7.5–8 °C (Atlantic Water, carrying 7 Sv (1×106 m3/s)) and another around −0.5 °C (Norwegian Sea Deep Water, carrying 12 Sv). Contrary to earlier expectations, our results indicate that the Western Branch carries as much water of Atlantic origin (temperature>7.5 °C) as the Eastern Branch. It should therefore be included in future monitoring plans for this region.