This study investigates seasonal changes in near-surface wind speeds in the Arctic using the regional climate model (RCM) simulations with RCA4 driven by four global climate models (GCMs) CMIP5 under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. In addition, the RCM RCA-GUESS (RCA4 with interactive vegetation dynamics) is used to investigate the role of biogeophysical feedbacks in modulating near-surface wind speeds under different RCP scenarios. Our results show that the reduction in ocean surface roughness induced by sea-ice reduction leads to a projected increase in near-surface wind speeds over the Arctic Ocean, with the most pronounced effects occurring in autumn and winter. Overall, the projected changes in near-surface wind speeds from the RCM are consistent with the changes from the forcing GCMs though the RCM simulations show larger amplitude changes compared to the GCMs. The expansion of vegetation on land increases surface roughness and alters atmospheric circulation by modifying static stability and the land-sea temperature contrast, leading to changes in near-surface wind speeds. Specifically, wind speeds decrease over continental regions but increase over parts of the Arctic Ocean. This study emphasizes that interactive vegetation dynamics significantly influence changes in land surface properties and near-surface wind speeds. These processes should be incorporated into Earth system models to enhance the accuracy of future climate projections.

We review how the international modelling community, encompassing integrated assessment models, global and regional Earth system and climate models, and impact models, has worked together over the past few decades to advance understanding of Earth system change and its impacts on society and the environment and thereby support international climate policy. We go on to recommend a number of priority research areas for the coming decade, a timescale that encompasses a number of newly starting international modelling activities, as well as the IPCC Seventh Assessment Report (AR7) and the second UNFCCC Global Stocktake. Progress in these priority areas will significantly advance our understanding of Earth system change and its impacts, increasing the quality and utility of science support to climate policy.We emphasize the need for continued improvement in our understanding of, and ability to simulate, the coupled Earth system and the impacts of Earth system change. There is an urgent need to investigate plausible pathways and emission scenarios that realize the Paris climate targets - for example, pathways that overshoot 1.5 or 2 degrees C global warming, before returning to these levels at some later date. Earth system models need to be capable of thoroughly assessing such warming overshoots - in particular, the efficacy of mitigation measures, such as negative CO2 emissions, in reducing atmospheric CO2 and driving global cooling. An improved assessment of the long-term consequences of stabilizing climate at 1.5 or 2 degrees C above pre-industrial temperatures is also required. We recommend Earth system models run overshoot scenarios in CO2-emission mode to more fully represent coupled climate-carbon-cycle feedbacks and, wherever possible, interactively simulate other key Earth system phenomena at risk of rapid change during overshoot. Regional downscaling and impact models should use forcing data from these simulations, so impact and regional climate projections cover a more complete range of potential responses to a warming overshoot. An accurate simulation of the observed, historical record remains a fundamental requirement of models, as does accurate simulation of key metrics, such as the effective climate sensitivity and the transient climate response to cumulative carbon emissions. For adaptation, a key demand is improved guidance on potential changes in climate extremes and the modes of variability these extremes develop within. Such improvements will most likely be realized through a combination of increased model resolution, improvement of key model parameterizations, and enhanced representation of important Earth system processes, combined with targeted use of new artificial intelligence (AI) and machine learning (ML) techniques. We propose a deeper collaboration across such efforts over the coming decade.With respect to sampling future uncertainty, increased collaboration between approaches that emphasize large model ensembles and those focussed on statistical emulation is required. We recommend an increased focus on high-impact-low-likelihood (HILL) outcomes - in particular, the risk and consequences of exceeding critical tipping points during a warming overshoot and the potential impacts arising from this. For a comprehensive assessment of the impacts of Earth system change, including impacts arising directly as a result of climate mitigation actions, it is important that spatially detailed, disaggregated information used to generate future scenarios in integrated assessment models be available for use in impact models. Conversely, there is a need to develop methods that enable potential societal responses to projected Earth system change to be incorporated into scenario development.The new models, simulations, data, and scientific advances proposed in this article will not be possible without long-term development and maintenance of a robust, globally connected infrastructure ecosystem. This system must be easily accessible and useable by modelling communities across the world, allowing the global research community to be fully engaged in developing and delivering new scientific knowledge to support international climate policy.

The Arctic has warmed more than twice the rate of the entire globe. To quantify possible climate change effects, we calculate wind energy potentials from a multi-model ensemble of Arctic-CORDEX. For this, we analyze future changes of wind power density (WPD) using an eleven-member multi-model ensemble. Impacts are estimated for two periods (2020-2049 and 2070-2099) of the 21st century under a high emission scenario (RCP8.5). The multi-model mean reveals an increase of seasonal WPD over the Arctic in the future decades. WPD variability across a range of temporal scales is projected to increase over the Arctic. The signal amplifies by the end of 21st century. Future changes in the frequency of wind speeds at 100 m not useable for wind energy production (wind speeds below 4 m/s or above 25 m/s) has been analyzed. The RCM ensemble simulates a more frequent occurrence of 100 m non-usable wind speeds for the wind-turbines over Scandinavia and selected land areas in Alaska, northern Russia and Canada. In contrast, non-usable wind speeds decrease over large parts of Eastern Siberia and in northern Alaska. Thus, our results indicate increased potential of the Arctic for the development and production of wind energy. Bias corrected and not corrected near-surface wind speed and WPD changes have been compared with each other. It has been found that both show the same sign of future change, but differ in magnitude of these changes. The role of sea-ice retreat and vegetation expansion in the Arctic in future on near-surface wind speed variability has been also assessed. Surface roughness through sea-ice and vegetation changes may significantly impact on WPD variability in the Arctic.

Ocean deoxygenation due to anthropogenic warming represents a major threat to marine ecosystems and fisheries. Challenges remain in simulating the modern observed changes in the dissolved oxygen (O₂). Here, we present an analysis of upper ocean (0-700m) deoxygenation in recent decades from a suite of the Coupled Model Intercomparison Project phase 6 (CMIP6) ocean biogeochemical simulations. The physics and biogeochemical simulations include both ocean-only (the Ocean Model Intercomparison Project Phase 1 and 2, OMIP1 and OMIP2) and coupled Earth system (CMIP6 Historical) configurations. We examine simulated changes in the O₂ inventory and ocean heat content (OHC) over the past 5 decades across models. The models simulate spatially divergent evolution of O₂ trends over the past 5 decades. The trend (multi-model mean and spread) for upper ocean global O₂ inventory for each of the MIP simulations over the past 5 decades is 0.03 ± 0.39×1014 [mol/decade] for OMIP1, −0.37 ± 0.15×10¹⁴ [mol/decade] for OMIP2, and −1.06 ± 0.68×10¹⁴ [mol/decade] for CMIP6 Historical, respectively. The trend in the upper ocean global O₂ inventory for the latest observations based on the World Ocean Database 2018 is −0.98×10¹⁴ [mol/decade], in line with the CMIP6 Historical multi-model mean, though this recent observations-based trend estimate is weaker than previously reported trends. A comparison across ocean-only simulations from OMIP1 and OMIP2 suggests that differences in atmospheric forcing such as surface wind explain the simulated divergence across configurations in O₂ inventory changes. Additionally, a comparison of coupled model simulations from the CMIP6 Historical configuration indicates that differences in background mean states due to differences in spin-up duration and equilibrium states result in substantial differences in the climate change response of O₂. Finally, we discuss gaps and uncertainties in both ocean biogeochemical simulations and observations and explore possible future coordinated ocean biogeochemistry simulations to fill in gaps and unravel the mechanisms controlling the O₂ changes.

The variability of September Arctic sea ice at interannual to multidecadal time scales in the midst of anthropogenically forced sea ice decline is not fully understood. Understanding Arctic sea ice variability at different time scales is crucial for better predicting future sea ice conditions and separating the externally forced signal from internal variability. Here, we study modes of variability, extreme events and trend in September Arctic sea ice in 100–150 year datasets by using time-frequency analysis. We extract the non-linear trend for sea ice area and provide an estimate for the sea ice loss driven by anthropogenic warming with a rate of ∼−0.25 million km² per decade in the 1980s and accelerating to ∼−0.47 million km² per decade in 2010s. Assuming the same accelerating rate for sea ice loss in the future and excluding the contributions of internal variability and feedbacks, a September ice-free Arctic could occur around 2060. Results also show that changes in sea ice due to internal variability can be almost as large as forced changes. We find dominant modes of sea ice variability with approximated periods of around 3, 6, 18, 27 and 55 years and show their contributions to sea ice variability and extremes. The main atmospheric and oceanic drivers of sea ice modes include the Arctic Oscillation and Arctic dipole anomaly for the 3 year mode, variability of sea surface temperature (SST) in the Gulf Stream region for the 6-year mode, decadal SST variability in the northern North Atlantic Ocean for the 18-year mode, Pacific Decadal Oscillation for the 27 year mode, and Atlantic Multidecadal Oscillation for the 55 year mode. Finally, our analysis suggests that over 70% of the sea ice area loss between the two extreme cases of 1996 (extreme high) and 2007 (extreme low) is caused by internal variability, with half of this variability being related to interdecadal modes.

We use an ensemble of models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) to analyse the number of days with extreme winter precipitation over Northern Europe and its relationship to the North Atlantic Oscillation (NAO), for the historical period 1950-2014 and two future 21st-century scenarios. Here we find that over Northern Europe, the models project twice more extreme precipitation days by the end of the 21st century under the high-emission scenario compared to the historical period. We also find a weakening of the NAO variability in the second half of the 21st century in the high greenhouse gas emission scenario compared to the historical period, as well as an increasing correlation between extreme winter precipitation events and the NAO index in both future scenarios. Models with a projected decrease in the NAO variability across the 21st century show a positive trend in the number of days with extreme winter precipitation over Northern Europe. These results highlight the role played by NAO in modulating extreme winter precipitation events.

We investigate the uncertainty (i.e., inter-model spread) in future projections of the boreal winter climate, based on the forced response of ten models from the CMIP5 following the RCP8.5 scenario. The uncertainty in the forced response of sea level pressure (SLP) is large in the North Pacific, the North Atlantic, and the Arctic. A major part of these uncertainties (31%) is marked by a pattern with a center in the northeastern Pacific and a dipole over the northeastern Atlantic that we label as the Pacific–Atlantic SLP uncertainty pattern (PA_∆SLP). The PA_∆SLP is associated with distinct global sea surface temperature (SST) and Arctic sea ice cover (SIC) perturbation patterns. To better understand the nature of the PA_∆SLP, these SST and SIC perturbation patterns are prescribed in experiments with two atmospheric models (AGCMs): CAM4 and IFS. The AGCM responses suggest that the SST uncertainty contributes to the North Pacific SLP uncertainty in CMIP5 models, through tropical–midlatitude interactions and a forced Rossby wavetrain. The North Atlantic SLP uncertainty in CMIP5 models is better explained by the combined effect of SST and SIC uncertainties, partly related to a Rossby wavetrain from the Pacific and air-sea interaction over the North Atlantic. Major discrepancies between the CMIP5 and AGCM forced responses over northern high-latitudes and continental regions are indicative of uncertainties arising from the AGCMs. We analyze the possible dynamic mechanisms of these responses, and discuss the limitations of this work.

The paper presents a synthesis of some of the interdisciplinary work from the ARCPATH project that focuses on the effects of climate change on Arctic social-ecological systems. It does so through the prism of whales and their recreational ecosystem services (ES). Whales present a group of species that are vulnerable to climate change and, at the same time, are central to the economies, cultures, and identities of many Arctic coastal communities. One such community is the town of Húsavík in Skjálfandi Bay, Iceland. The paper conducts an initial literature review to examine the effects of climate change on whales, globally, before using these findings and site-specific data from climate change modelling, whale observations from whale watching boats and whale watching trip records to investigate possible future impacts on whale watching in Skjálfandi Bay. The literature review identifies three categories of impacts on whales due to climate change, which concern changing distributions and migration, prey availability, and sea-ice and ocean temperature. Linear regression models identify statistically significant relationships between sea-surface temperatures (SST) and cetacean sightings for minke whales, blue whales and white-beaked-dolphins over the period 1995 to 2017. These species appear to have changed their usual feeding areas, and the results imply that further increases in SST are likely to further affect whale distributions. Future climate scenarios indicate that at least 2 °C of SST warming in Skjálfandi Bay up to 2050 might be inevitable regardless of the future emissions scenario, which implies nearly certain change that would require adaptation. The reliance of the local tourism sector on whale watching makes Húsavík vulnerable to the effects of climate change on whales. The results of this interdisciplinary inquiry emphasize the interconnectedness of different components of social-ecological systems and calls for adaptation planning that would enhance the resilience of local community to climate change and conservation measures that could enhance the protection of whales beyond the scope of the current whale sanctuary in Skjálfandi Bay.

The influence of Rossby waves emitted in the northeastern Pacific Ocean on the Northern Hemisphere’s atmosphere during summer is analysed using ERA5 reanalysis and a new large ensemble performed with the EC-Earth3 model. The Rossby Wave Sources (RWS) trigger wave-like patterns arising from the upper troposphere of the north-eastern Pacific region, causing a response around the Northern Hemisphere with alternating regions of positive and negative correlation values between RWS and geopotential height at 500 hPa. Increased RWS intensity during summer is related to negative temperature anomalies over western North America, and positive temperature anomalies over eastern North America, concurrently with increased precipitation over the western subtropical Atlantic and Northern Europe during summer. Colder than normal conditions on the North Pacific Ocean intensify the RWS and its impact on the global atmospheric circulation. Different warm or cold states in the Pacific and Atlantic Oceans modify the atmospheric response to RWS, showing a change in the middle troposphere (500 hPa) towards a more-wavy structure with cold Pacific conditions, and towards a less-wavy structure with a warm Pacific Ocean. Furthermore, the North Atlantic plays a very important role in hindering (in the case of warm water) or permitting (cold water) that Rossby waves generated in the Pacific modulate the atmospheric conditions over Europe.

Quantitative estimates of changes in wind energy resources in the Arctic were obtained using the RCA4 regional climate model under the RCP4.5 and RCP8.5 climate change scenarios for 2006–2099. The wind power density proportional to cubic wind speed was analyzed. The procedure for the model near-surface wind speed bias correction using ERA5 data as a reference with subsequent extrapolation of wind speed to the turbine height was applied to estimate the wind power density (WPD). According to the RCA4 simulations for the 21st century under both anthropogenic forcing scenarios, a noticeable increase in the WPD was noted, in particular, over the Barents, Kara, and Chukchi seas in winter. In summer, a general increase in the WPD is manifested over the Arctic Ocean. The changes are more significant under the RCP8.5 scenario with high anthropogenic forcing for the 21st century. According to model projections, an increase in the interdaily WPD variations does not generally lead to the deviations of wind speed to the values at which the operation of wind generators is unfeasible.