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BackgroundIt is well-established that what is good for the heart is good for the brain. Vascular factors such as hypertension, diabetes, and high cholesterol, and genetic factors such as the apolipoprotein E4 allele increase the risk of developing both cardiovascular disease and dementia. However, the mechanisms underlying the heart–brain association remain unclear. Recent evidence suggests that impairments in vascular phenotypes and cerebrovascular reactivity (CVR) may play an important role in cognitive decline. The Heart and Brain Study combines state-of-the-art vascular ultrasound, cerebrovascular magnetic resonance imaging (MRI) and cognitive testing in participants of the long-running Whitehall II Imaging cohort to examine these processes together. This paper describes the study protocol, data pre-processing and overarching objectives.Methods and DesignThe 775 participants of the Whitehall II Imaging cohort, aged 65 years or older in 2019, have received clinical and vascular risk assessments at 5-year-intervals since 1985, as well as a 3T brain MRI scan and neuropsychological tests between 2012 and 2016 (Whitehall II Wave MRI-1). Approximately 25% of this cohort are selected for the Heart and Brain Study, which involves a single testing session at the University of Oxford (Wave MRI-2). Between 2019 and 2023, participants will undergo ultrasound scans of the ascending aorta and common carotid arteries, measures of central and peripheral blood pressure, and 3T MRI scans to measure CVR in response to 5% carbon dioxide in air, vessel-selective cerebral blood flow (CBF), and cerebrovascular lesions. The structural and diffusion MRI scans and neuropsychological battery conducted at Wave MRI-1 will also be repeated. Using this extensive life-course data, the Heart and Brain Study will examine how 30-year trajectories of vascular risk throughout midlife (40–70 years) affect vascular phenotypes, cerebrovascular health, longitudinal brain atrophy and cognitive decline at older ages.DiscussionThe study will generate one of the most comprehensive datasets to examine the longitudinal determinants of the heart–brain association. It will evaluate novel physiological processes in order to describe the optimal window for managing vascular risk in order to delay cognitive decline. Ultimately, the Heart and Brain Study will inform strategies to identify at-risk individuals for targeted interventions to prevent or delay dementia.

The Armenian highlands encompasses rugged and environmentally diverse landscapes and is characterized by a mosaic of distinct ecological niches and large temperature gradients. Strong seasonal fluctuations in resource availability along topographic gradients likely prompted Pleistocene hominin groups to adapt by adjusting their mobility strategies. However, the role that elevated landscapes played in hunter-gatherer settlement systems during the Late Pleistocene (Middle Palaeolithic [MP]) remains poorly understood. At 1640 m above sea level, the MP site of Kalavan 2 (Armenia) is ideally positioned for testing hypotheses involving elevation-dependent seasonal mobility and subsistence strategies. Renewed excavations at Kalavan 2 exposed three main occupation horizons and ten additional low densities lithic and faunal assemblages. The results provide a new chronological, stratigraphical, and paleoenvironmental framework for hominin behaviors between ca. 60 to 45 ka. The evidence presented suggests that the stratified occupations at Kalavan 2 locale were repeated ephemerally most likely related to hunting in a high-elevation within the mountainous steppe landscape.

Abstract Volcanoes in the East Asian/Pacific region have been the source of some of the largest magnitude eruptions during the Late Quaternary, and accurately evaluating their eruptive histories is essential for hazard assessments. To overcome difficulties in resolving and precisely dating eruptions in the near‐source realm, the high‐resolution (varved) sediments of Lake Suigetsu (central Honshu, Japan) were examined for the presence of non‐visible (cryptotephra) layers from 50 ka up until the 30 ka Aira‐Tanzawa (AT) caldera‐forming event of Aira volcano. Cryptotephra layers are four times more frequently preserved than visible markers in the Suigetsu sediments, meaning that this archive provides a unique and unprecedented record of eruptions that were dispersed over the densely populated regions of central Honshu. Major and trace element volcanic glass chemistry is used to fingerprint the ash layers and pinpoint their volcanic origin. Tephras are found throughout the investigated sediments, but the highest abundance of ash fall events are recorded between 39 and 30 ka, capturing a period of intense volcanism at calderas on Kyushu Island (Japan). The augmented Suigetsu tephrostratigraphy records at least seven eruptions from Aso caldera (southern Kyushu) that post‐date the widespread ACP‐4 Plinian eruption (ca. 50 ka) and four explosive events from Aira (central Kyushu) that occurred leading up to the catastrophic caldera‐forming AT eruption (ca. 30 ka).

Abstract We describe and evaluate historical simulations which use the third Hadley Centre Global Environment Model in the Global Coupled configuration 3.1 (HadGEM3‐GC3.1) and which form part of the UK's contribution to the sixth Coupled Model Intercomparison Project, CMIP6. These simulations, run at two resolutions, respond to historically evolving forcings such as greenhouse gases, aerosols, solar irradiance, volcanic aerosols, land use, and ozone concentrations. We assess the response of the simulations to these historical forcings and compare against the observational record. This includes the evolution of global mean surface temperature, ocean heat content, sea ice extent, ice sheet mass balance, permafrost extent, snow cover, North Atlantic sea surface temperature and circulation, and decadal precipitation. We find that the simulated time evolution of global mean surface temperature broadly follows the observed record but with important quantitative differences which we find are most likely attributable to strong effective radiative forcing from anthropogenic aerosols and a weak pattern of sea surface temperature response in the low to middle latitudes to volcanic eruptions. We also find evidence that anthropogenic aerosol forcings play a role in driving the Atlantic Multidecadal Variability and the Atlantic Meridional Overturning Circulation, which are key features of the North Atlantic ocean. Overall, the model historical simulations show many features in common with the observed record over the period 1850–2014 and so provide a basis for future in‐depth study of recent climate change.

An assessment of the risks of a seasonally ice-free Arctic at 1.5 and 2.0 °C global warming above pre-industrial levels is undertaken using model simulations with solar radiation management to achieve the desired temperatures. An ensemble of the CMIP5 model HadGEM2-ES uses solar radiation management (SRM) to achieve the desired global mean temperatures. It is found that the risk for a seasonally ice-free Arctic is reduced for a target temperature for global warming of 1.5 °C (0.1 %) compared to 2.0 °C (42 %), in general agreement with other methodologies. The SRM produced more ice loss, for a specified global temperature, than for CO2 mitigation scenarios, as SRM produces a higher polar amplification.

Interest in seasonal predictions of Arctic sea ice has been increasing in recent years owing, primarily, to the sharp reduction in Arctic sea-ice cover observed over the last few decades, a decline that is projected to continue. The prospect of increased human industrial activity in the region, as well as scientific interest in the predictability of sea ice, provides important motivation for understanding, and improving, the skill of Arctic predictions. Several operational forecasting centres now routinely produce seasonal predictions of sea-ice cover using coupled atmosphere–ocean–sea-ice models. Although assimilation of sea-ice concentration into these systems is commonplace, sea-ice thickness observations, being much less mature, are typically not assimilated. However, many studies suggest that initialization of winter sea-ice thickness could lead to improved prediction of Arctic summer sea ice. Here, for the first time, we directly assess the impact of winter sea-ice thickness initialization on the skill of summer seasonal predictions by assimilating CryoSat-2 thickness data into the Met Office's coupled seasonal prediction system (GloSea). We show a significant improvement in predictive skill of Arctic sea-ice extent and ice-edge location for forecasts of September Arctic sea ice made from the beginning of the melt season. The improvements in sea-ice cover lead to further improvement of near-surface air temperature and pressure fields across the region. A clear relationship between modelled winter thickness biases and summer extent errors is identified which supports the theory that Arctic winter thickness provides some predictive capability for summer ice extent, and further highlights the importance that modelled winter thickness biases can have on the evolution of forecast errors through the melt season.

We present a method for analysing changes in the modelled volume budget of the Arctic sea ice as the ice declines during the 21st century. We apply the method to the CMIP5 global coupled model HadGEM2-ES to evaluate how the budget components evolve under a range of different forcing scenarios. As the climate warms and the ice cover declines, the sea ice processes that change the most in HadGEM2-ES are summer melting at the top surface of the ice due to increased net downward radiation and basal melting due to extra heat from the warming ocean. There is also extra basal ice formation due to the thinning ice. However, the impact of these changes on the volume budget is affected by the declining ice cover. For example, as the autumn ice cover declines the volume of ice formed by basal growth declines as there is a reduced area over which this ice growth can occur. As a result, the biggest contribution to Arctic ice decline in HadGEM2-ES is the reduction in the total amount of basal ice growth during the autumn and early winter.Changes in the volume budget during the 21st century have a distinctive seasonal cycle, with processes contributing to ice decline occurring in May–June and September to November. During July and August the total amount of sea ice melt decreases, again due to the reducing ice cover.The choice of forcing scenario affects the rate of ice decline and the timing and magnitude of changes in the volume budget components. For the HadGEM2-ES model and for the range of scenarios considered for CMIP5, the mean changes in the volume budget depend strongly on the evolving ice area and are independent of the speed at which the ice cover declines.

Abstract The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Among other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific descriptions of these components are in companion papers) and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present‐day forcing. The suitability of the configuration for predictability on shorter time scales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2‐AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however, there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2‐AO, many aspects of the present‐day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extratropical variability and top‐of‐atmosphere and surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking.

A new sea ice configuration, GSI8.1, is implemented in the Met Office global coupled configuration HadGEM3-GC3.1 which will be used for all CMIP6 (Coupled Model Intercomparison Project Phase 6) simulations. The inclusion of multi-layer thermodynamics has required a semi-implicit coupling scheme between atmosphere and sea ice to ensure the stability of the solver. Here we describe the sea ice model component and show that the Arctic thickness and extent compare well with observationally based data.

This paper presents an investigation of the robustness of correlations between characteristics of Arctic summer cyclones and September Arctic sea ice extent. A cyclone identification and tracking algorithm is run for output from 100-year coupled climate model simulations at two resolutions and for 30 years of reanalysis data, using two different tracking variables (mean sea-level pressure, MSLP; and 850 hPa vorticity) for identification of the cyclones. The influence of the tracking variable, the spatial resolution of the model, and spatial and temporal sampling on the correlations is then explored. We conclude that the correlations obtained depend on all of these factors and that care should be taken when interpreting the results of such analyses. Previous studies of this type have used around 30 years of reanalysis and observational data, analysed with a single tracking variable. Our results therefore cast some doubt on the conclusions drawn in those studies.