British Antarctic Survey

UKRI Gateway to Research · FY 2026 · 2026-06

The precipitation of charged particles into the Earth’s upper atmosphere is a key mechanism by which space weather impacts the Earth’s environment, yet big questions remain about the global process and its local variation.  Through the development of the first physics-based model of energetic electron precipitation (EEP) into the Earth’s atmosphere, this project will answer these questions while advancing our understanding of, and ability to predict, the contribution of this aspect of space weather to climate variability in the polar regions. EEP occurs when electrons with energies above about 100 keV rain down into the atmosphere from near-Earth space. Understanding when this happens is important because the electrons react with neutral atoms and molecules in the atmosphere producing odd nitrogen (NOx, i.e. N, NO, and NO2) and odd hydrogen (HOx, i.e. H, OH, and HO2) species.  These species destroy ozone in the mesosphere (50-80km altitude) and stratosphere (10-50km altitude). The extent of this destruction depends on conditions in the radiation belts and the concurrent state of the atmosphere. Reductions in ozone concentration will affect local temperatures and winds, which in turn alters the atmospheric circulation by strengthening the stratospheric polar vortex. This has been shown to affect the regional surface climate during polar winter. EEP is not well understood and significant questions about it remain, including: ·      How does it vary in time and space? ·      Which space weather conditions produce the most significant EEP? ·      How do varying levels of EEP affect NOx and HOx production and ozone loss? Simulations of climate and atmospheric chemistry need to include the effect of EEP. The Intergovernmental Panel on Climate Change (IPCC) Coupled Model Intercomparison Project (CMIP) phases 6 and 7 model recommendations include EEP as a requirement, under solar forcing of the climate system. However, current models of EEP are based on satellite observations that are unreliable due to sparce, patchy measurements, contamination by protons and uncertainty around the performance of the instruments. This project will answer the important questions about EEP and develop the first physics-based model of EEP conforming to the IPCC CMIP-6/7 recommendations. Since EEP is a loss process from the region of Earth’s radiation belts, a well-established, physics-based model (the British Antarctic Survey Radiation Belt Model) will be repurposed to calculate electron precipitation. To capture all EEP this model will be extended spatially and then used to simulate a period of 22 years. This simulation will be used to address the significant questions about EEP outlined above. It will also be used to derive the first physics-based model of EEP meeting the IPCC CMIP-6/7 requirements. This new model will be designed so it can be used for studies of past and future climate. The new model will be combined with the Whole Atmosphere Community Climate Model – with D-region ion chemistry (WACCM-D), to quantify the effect that EEP has on atmospheric chemistry, ozone loss and climate-system dynamics. This project will provide a major step forward in our understanding of EEP and the physics-based model of EEP will dramatically change the particle forcing landscape for the IPCC, allowing the main goals of the CMIP model experiments to be achieved. The 22-year simulation of EEP, the new model meeting the CMIP requirements and the results from WACCM-D simulations will be made available to the research community.

UKRI Gateway to Research · FY 2026 · 2026-03

The Earth’s upper atmosphere is a dynamic environment comprised of co-existing neutral gases and electrically charged plasma. Various processes affect the density of the more populous neutral atmosphere, including heating through friction as the plasma particles, driven by electrical forces, push past the neutral gas molecules. These electrical forces are linked to the interaction of the Earth’s plasma environment with the Solar wind that flows away from the Sun; a highly variable stream of particles that continuously blows past the Earth. Thus, the heat input to the upper atmosphere varies significantly both in time and location around the planet. The heating of the neutral atmosphere is an important pathway for energy transfer into the wider Earth environment. Understanding the overall heat budget is important for a range of questions in atmospheric science related to changes in the chemistry and dynamics, such as the influence on global atmospheric circulation. An immediate impact of this heating is the consequent atmospheric expansion, which in turn increases the drag on orbiting satellites, affecting satellite lifetimes and collision warning calculations. For example, during the geomagnetic storm in May 2024, the number of orbital manoeuvres for station keeping and collision avoidance increased by a factor of 5 due to rapid and dynamic changes in density. The challenge the science community faces is that methods of tracking this heat input on a scale useful for global calculations rely on large scale observations, these miss the significant input from smaller scale changes in the plasma motion through the neutral gases. Recent studies have shown this missing contribution can double the heating estimated from large scale observations. The aim of this project is to determine where, when and why small-scale heating occurs, thus establishing its overall importance to the upper atmosphere heat budget. We will achieve this through novel use of existing instrumentation and datasets and application of AI techniques followed by dedicated experiments with state-of-the-art instruments coming online in 2025. To capture this small-scale variation on a global scale we will use data from the Super Dual Auroral Radar Network (SuperDARN) which covers both the northern and southern hemispheres from sub-auroral latitudes to the poles. We will derive an empirical relationship between SuperDARN data and small-scale heating through co-located, fine detail auroral and plasma measurements. To enable world-leading impact in our field and beyond we will turn this new understanding into an open-source tool that can be applied to all SuperDARN data, past, present, and future. SuperDARN data is freely available, therefore this tool will have a wide range of beneficiaries, for example: atmospheric modellers (upper atmospheric heating effects influence density, chemistry and circulation patterns), national space weather services providing information to satellite operators trying to predict orbit changes that could lead to collisions in ever more congested space (e.g. the UK Met Office, NOAA space weather prediction service) and space debris tracking teams (e.g. European Space Agency).

UKRI Gateway to Research · FY 2026 · 2026-02

Overview Changes in physical processes are having profound impacts on Southern Ocean species and ecosystems. To generate accurate ecological predictions of climate impacts in the Southern Ocean, we must first understand how biological mechanisms such as species interactions and physiological traits shape climate responses. Seabirds are key consumers in the Southern Ocean whose demographic rates have been correlated with climate modes, but the mechanisms underlying these relationships are not well understood. Changes to wind patterns and Antarctic sea ice are strongly impacted by climate change and influence seabird life history. Knowledge of the mechanistic links through which wind and sea ice influence seabird population processes and species interactions can improve our predictive capacity of Southern Ocean ecosystems. This research focuses on giant petrels (Macronectes spp.), large and dominant avian predators and scavengers. Giant petrels exert considerable predation pressure on more abundant species such as penguins and albatrosses, and influence population dynamics of these species. Despite their prominent ecological role, giant petrels have received far less attention than well-studied Southern Ocean seabird species such as albatross. Giant petrels are thought to rely on dynamic soaring for flight, which allows seabirds to extract energy from the wind in order to move while expending little energy. However, to date there are no quantitative studies demonstrating how giant petrels use wind or the role that wind plays in constraining their distribution. Further, recent studies suggest that giant petrels rely regularly on sea ice for foraging, tracking seasonal changes in ice habitats. Impacts of wind and sea ice on foraging energetics could provide a mechanism explaining correlations between climate metrics and demographic rates of seabirds. Intellectual Merit This research will improve our current understanding of climate impacts on seabirds in the Southern Ocean by developing a mechanistic model linking climate-driven environmental variability in wind and sea ice with foraging energetics in giant petrels. Further, we will link environmental drivers of giant petrel foraging energetics and habitat use with predation pressure on penguins and albatrosses, and implications for population trends. This work will address key gaps in knowledge regarding the mechanistic links through which physical change influences species interactions and life history in the Southern Ocean. Our approach allows us to connect individual energetics with landscape-scale environmental variability, and will enable new insight into the role of climate change in structuring biological processes. Broader Impacts This work will provide much-needed data on climate impacts on threatened seabirds that is critical to developing effective management plans. In addition, effectively communicating science to the broader public is a major goal of this work. This project will: (1) Provide a science communication internship for a graduate student in an interdisciplinary graduate degree program; 2) Work with a science journalist to generate feature articles in popular wildlife magazines; and (3) Generate a sample dataset to be used in a graduate-level environmental modeling course. This proposal does not require USAP-supported fieldwork in the Antarctic.

UKRI Gateway to Research · FY 2025 · 2025-11

SO-SIMMER will examine and quantify the drivers and mechanisms of the observed and projected accumulation of subsurface heat below the sea-ice regions of the Southern Ocean.   Using two numerical models, in combination with observational and reanalysis datasets, it will establish how this warming has and will impact ice shelf melting, sea-ice extent and air-sea fluxes. The deep Southern Ocean transports heat south from the relatively warm subtropics to the Antarctic continental margins.  Here, a unique combination of ocean, cryosphere and atmospheric processes brings this deep warm water upwards to the mixed layer and surface.  This subsurface heat influences air-sea heat fluxes, sea-ice concentrations and extent, as well as being the major mechanism driving ice shelf melt. The deep subsurface waters have been observed to be warming in recent decades and heat is accumulating directly below the mixed layer in the upwelling regions.  Alongside atmospheric candidates, the movement of this accumulated deep heat to the surface layers was likely a major driver of the extremely anomalous low sea-ice around Antarctica that occurred in the Austral winter of 2023. While the impact of the released heat is the subject of intense scrutiny, the mechanisms driving the subsurface warming have not yet been investigated, making SO-SIMMER extremely timely.  There is significant evidence to suggest that increasing surface stratification, changed ocean poleward circulation, and increased ocean eddy mixing may be occurring in the Southern Ocean. These are all known to influence heat delivery and storage below the regions of sea-ice formation.  However, the relative contribution of each of these factors is presently unknown.  It is also unclear how changes in these processes will influence delivery of heat to ice shelves, drive changes in sea-ice and air-sea fluxes, and how this will change in the future. This study will undertake a range of well-posed experiments using two realistic state-of-the-art numerical models; one optimised to examine the drivers of heat accumulation, and the other their impacts on the cryosphere.  Both will be constrained by observations of ocean properties and surface fluxes.   They will be used to answer the following questions: How does surface stratification impact subsurface heat accumulation in the vicinity of sea-ice?  2. How does heat delivery to this subsurface region change in response to changes in the residual overturning circulation, or a warming of northern source waters? 3. How does an increase in eddy driven mixing in the Antarctic Circumpolar Current (ACC) impact poleward heat delivery? 4. How do the ocean properties of the continental shelf change in response to this subsurface heat, and what are the subsequent impacts on sea-ice, the ice shelves, and the atmosphere? 5. How do we expect the above processes to change under future climate forcing and what feedbacks do the induced cryosphere changes impose? This study will identify those processes most significant in driving subpolar subsurface warming.  It will deliver major improvements to our understanding of recent Southern Ocean change, and our ability to assess the potential for future ice shelf melt, sea-ice and air-sea heat flux change.  This will provide information necessary to assess coupled climate model projections, which typically represent historical Southern Ocean water masses and sea-ice trends very poorly.  It will also serve to constrain future projections of ocean heat change, sea-ice and ice shelf melt, as well as guide focused improvements in ocean parameterisations.

UKRI Gateway to Research · FY 2025 · 2025-09

Context - Warming in the Arctic is leading to a significant increase in glacial meltwater discharge, large alterations in major Arctic river outputs and unprecedented levels of sea-ice retreat. This introduces large amounts of extra freshwater into the Arctic ecosystem with numerous ecological impacts, both locally and globally. These impacts will vary depending on the source of this freshwater since that influences the amount, and mix, of nutrients introduced into the ocean. Arctic nutrients fuel the biological growth essential for healthy marine ecosystems, not only in the Arctic itself but in temperate and tropical regions. Therefore, tracing these sources of freshwater from land to ocean is a priority if the global consequences of Arctic change are to be understood. The different sources of freshwater inputs, from rivers, glaciers, and sea-ice, can be tracked through tracers such as the stable oxygen isotope d18O, as well as certain trace metals and Rare Earth Elements. Freshwater tracer measurements are particularly insightful when combined with accompanying temperature and salinity measurements. Challenge - The collection of freshwater tracer samples, plus accompanying temperature and salinity data, can be easily accommodated within polar field campaigns. Nevertheless, the many challenges of these campaigns, plus the required laboratory analyses, has resulted in sample coverage gaps. Furthermore, scientific programmes are often short-term and geographically focussed, leading to sample results being disparate and uncollated. Finally, ocean circulation and mixing means that there are numerous factors that complicate the interpretation of freshwater tracer data that require powerful analytical approaches. Together, these issues have resulted in the lack of a comprehensive overview of freshwater sources into and out of the Arctic Ocean. Nevertheless, such an understanding can be achieved with a thorough collation of the many sources of freshwater tracer data already available, combined with a growing suite of machine learning methods that can help interpret this data. Aims and Objectives – AISIT is a 6-month project that will enhance data accessibility and use of Arctic freshwater tracer data. The core objective is to develop a standardised and machine-readable database of freshwater tracer data combined with temperature and salinity. It will initially focus on d18O data collected from the NERC cross-centre National Capability programme BIOPOLE, which considers the complexities associated with the land-to-sea transport of nutrient-laden freshwater in polar regions. Through its own fieldwork, and in collaboration with international partners, BIOPOLE has generated, and has access to, a good amount of suitable data for this project. A follow-on objective is to collaborate with other programmes to make the database even more comprehensive in terms of coverage and incorporating other types of freshwater tracers. Throughout the database collation phase, regular interaction with the AI community will be maintained to ensure the database is fit for purpose and that an appropriate AI benchmark is established for wider community engagement. Potential applications and benefits - AISIT will further our capability to understand the wider implications of Arctic change to the Earth system as well as to the marine economy of the UK. Through our interactive approach in co-designing an AI ready database and accompanying AI-benchmark, AISIT will catalyse new downstream research opportunities to exploit sparse data more effectively and improve scientific insights using multi-modal AI to accelerate scientific discovery. Furthermore, AISIT will help further establish the UK as being a leading nation in impactful Arctic science.

UKRI Gateway to Research · FY 2025 · 2025-09

Objective: Generate an AI-ready dataset of sea ice from satellite imagery. Rationale: Understanding where sea ice is located and how it is changing over time is crucial for monitoring the effects of climate change in the polar regions, identifying suitable habitat locations for important Arctic and Antarctic wildlife, and ensuring the safe navigation of ships in areas of the ocean covered by sea ice. One powerful dataset for tracking sea ice is radar satellite imagery, captured from the Sentinel-1 satellite, which is able to ‘see’ through cloud and darkness to detect sea ice all year round and in all weather conditions. However, interpreting radar imagery is not straightforward. Unlike visible images, radar images contain a lot of noise or speckle, sometimes making it difficult to automate systems to identify where sea ice is located. To train Artificial Intelligence (AI) systems to detect sea ice, we require large, high-quality datasets where radar imagery is paired with labels that can inform the system of where sea ice is present. Currently, most labelled data is generated from manually annotating the image. This approach is time-consuming, meaning most of the labelled data is limited to very restricted parts of the Arctic and is only produced for radar images captured during particular times of the year. This limits the usefulness of this labelled data for training AI models to identify sea ice all year round and in both hemispheres. This project will develop a large, publicly available, AI-ready dataset of sea ice coverage, automatically derived from satellite images. We will identify pairs of overlapping radar and visible satellite images, captured from the MODIS satellite, that have been acquired in the same place at the same time. The visible images will be used to distinguish between ice and water in cloud-free, daylight conditions. This will produce a triplet dataset contained labelled radar and visible satellite imagery that can be used for training AI models and for other environmental and operational applications. Our project contains three main steps: ·    Match radar and optical satellite images: We will identify radar images that have been captured within one hour of a visible image from the same location. This short time window is essential due to the very dynamic nature of sea ice that can drift tens of kilometres each day. ·      Generate sea ice labels: Automated methods will be applied to the visible images to produce binary masks that clearly distinguish between ice and water in each image. These masks will be paired with the original radar and visible satellite images. ·      Build a reusable codebase for the future: We will publish an open-source codebase alongside the dataset, enabling other users to apply the same methods and generate additional data as new satellite imagery is made available.   Our initial analysis shows that in just one year (2020), over 10,000 high-quality patches of radar-optical image pairs could be identified for the Antarctic alone. Scaling this up to include data from multiple years and both polar regions could result in a dataset that is far larger and more diverse than pre-existing datasets produced through manual annotation. This will increase the range of downstream applications for this dataset from supporting AI-driven climate research, to increasing navigation safety, and improving environmental monitoring.

UKRI Gateway to Research · FY 2025 · 2025-06

As atmospheric CO2 and sea levels continue to rise, understanding the interactions among ice sheets, oceanic processes, and the atmosphere becomes increasingly critical. While current climate change is driven by human activity, understanding natural climate cycles is essential for predicting future changes. MPT-ICE will investigate the processes driving glacial-interglacial cycles spanning the Mid-Pleistocene Transition (MPT), between 700-1500 thousand years (ky) before present (BP), a period when ice sheets were smaller than today. This will be achieved by generating the first continuous record of impurities (chemical elements, organic compounds, and insoluble particulate material) spanning the full MPT from the highly anticipated Beyond EPICA Oldest Ice core (hereafter Oldest Ice). Marine records hint at the climate before the MPT, revealing ~41-ky glacial cycles and smaller Northern Hemisphere ice sheets1. Post-MPT, the shift to longer ~100-ky glacial cycles and ice sheet expansion is intriguing, as it occurred without changes in orbital patterns affecting solar insolation2. Various theories exist to explain the MPT, but evidence increasingly points to the critical role of the Southern Ocean. We hypothesize that the processes driving CO2 exchange in the Southern Ocean shifted during the MPT. MPT-ICE will test this by reconstructing atmospheric circulation, sea ice, and marine primary productivity changes over the MPT from the oldest ice core ever drilled. The EU-funded Oldest Ice project, supported by NERC logistics and scientific leadership, is on-target to retrieve a 2756 m-long ice core in Antarctica (January 2025). Radar and ice flow modelling suggest this will surpass the iconic Dome C ice core, which provided unrivalled insight into glacial cycles spanning the past 800-ky. MPT-ICE is a standalone initiative that will go beyond both the research scope and funding of the Oldest Ice project, to deliver state-of-the-art impurities analysis. It will work in partnership with the international Oldest Ice consortium, enhancing the far-reaching scientific, socio-economic, and political impacts of the research. Based on our expertise, the Oldest Ice consortium have asked the MPT-ICE team to lead the impurities analysis of this highly valued ice core. Hosting the analysis at the NERC ice core laboratories will position UK scientists at the forefront of their field and create a legacy for NERC researchers. However, immediate investment in NERC’s analytical capabilities is crucial. Otherwise, this important suite of analyses will move to another European laboratory, diminishing the UK's pivotal role. The expected small ice sample volume, with an estimated time-depth resolution of just ~20 ky m-1 during the MPT, represents a considerable analytical challenge. MPT-ICE will surpass NERC's current impurities analysis capabilities by enhancing data acquisition and temporal resolution, crucial for testing our hypothesis and maintaining leadership in ice core and environmental research. MPT-ICE objectives: Optimise the capability of NERC’s ice core laboratories to measure a comprehensive and continuous suite of impurities at sub-centimetre depth-resolution. Analyse the impurities in the Oldest Ice across the MPT, from 700-1500 -ky BP, at sub-centennial temporal-resolution. Utilize the terrestrial impurities to reconstruct changes in Southern Ocean winds and the aerial deposition of mineral dust and bioavailable nutrients. Utilize a suite of impurities of marine origin to reconstruct changes in Southern Ocean marine primary productivity and sea ice extent. Characterise the relative changes in Southern Ocean winds, sea ice and marine productivity, over the MPT, to provide a mechanistic framework to test our hypothesis.

UKRI Gateway to Research · FY 2025 · 2025-06

Jupiter sits within a giant magnetic bubble encapsulated in the flow of the Solar wind. Inside this magnetosphere, Jupiter’s magnetic field can trap energetic charged particles (electrons and ions) in radiation belts. Jupiter’s magnetosphere contains a wide variety of ions heavier than hydrogen at much greater abundance than in Earth’s magnetosphere. This is mainly due to the many moons that surround Jupiter, in particular the volcanically active moon, Io. The radiation belts of Jupiter are the most energetic and hazardous radiation belts in the Solar system. Recent analysis of NASA Galileo heavy ion data has shown that an incredibly energetic radiation belt of oxygen and sulphur ions which exists very close to Jupiter cannot be formed by the traditional method of accelerating radiation belt particles, a process called radial diffusion. The data from Galileo show that another mechanism of heating these heavy ions must be present and is accelerating the ions in-situ rather than via a transport process. One possible mechanism is the interaction of the ions with waves in the magnetosphere. This mechanism is actively employed to heat charged plasma injected into nuclear fusion reactors and is also thought to be involved in ion heating in the outer layers of the Sun. The primary aim of the project aim is to use available wave and particle data at Jupiter together with internationally respected computer simulations to assess whether ion-wave heating is responsible for this intense, heavy ion radiation belt at Jupiter. The secondary goal of this project is to investigate similar wave-heavy ion interactions that have recently been suggested to play a key part of the production of X-ray aurora at Jupiter. By tackling these two exciting and recent discoveries in Jupiter’s magnetosphere this project will significantly advance the understanding of the impact of wave-particle interactions on the dynamics of energetic heavy ions in radiation belts at Jupiter and beyond. The Project Lead has over 12 years’ experience in analysing wave-particle interactions at Jupiter and Saturn. The PDRA will be embedded in an active, internationally respected radiation belt physics group where the authors of the modelling tools for the project still work. The data is already publicly available and the work has been carefully planned to be low risk and high reward which will lead to a successful project.

UKRI Gateway to Research · FY 2025 · 2025-03

Passive microwave (PM) derived sea ice concentration (SIC) data are possibly the most utilised satellite product for the polar regions for monitoring trends in sea ice conditions. It is regularly used by scientists, local communities, policy makers, and media, as well as industries such as fishing, tourism, and shipping. Despite the fundamental importance of the PM-derived SIC products, it is widely acknowledged within the sea ice community that their present form is inadequate, due to a lack of rigour in their assessment of uncertainty on both temporal and spatial scales, and the diverse range of algorithms that can be used to derive SIC value from PM records. The fundamental difficulty derives from the coarse, 36 - 625km2, size of the PM pixels, which precludes the use of traditional ground-truthing methods as viable routes to assess the accuracy of PM measurements over a range of spatial and temporal scales. Two recent developments mean that we can now overcome these challenges. Firstly, there has been a step-change increase in the rate of satellite image acquisition with petabytes of high-resolution satellite imagery pertaining to sea ice conditions now being available to validate the accuracy of the PM SIC pixels. Secondly, advances in the capabilities of digital technologies, including machine learning (ML), means we can for the first time automate the storage, processing, and analysis of these big satellite data archives. By unifying these two developments we are able to quantify the error and uncertainty in Antarctic PM-derived SIC data at unprecedented temporal and spatial scales. The specific goal of the proposal is to use digital technologies and ML methods in satellite imagery to: SO1 Develop and enhance ML techniques to automatically generate high-resolution sea ice concentration (SIC-HR) charts from multispectral and radar satellite imagery. SO2 Develop a modular pipeline to automate the quantification of uncertainty in PM-derived SIC at unprecedented spatial and temporal scales. SO3 Quantify the spatial and temporal uncertainties associated with the calculation of Antarctic SIC derived from PM data at a decadal, pan-Antarctic scale. SO4 Refine decadal-scale time series of pan-Antarctic sea ice area via sensitivity of ice edge location. Our analyse and the generation of error and uncertainty values will be used to refine the half-centennial time-series of Antarctic sea ice extent, a crucial product recognised by the World Meteorological Organisation as a key Global Climate Indicators for describing the changing climate and an Essential Climate Variable, critical for characterising the Earth's evolving climate. When our objectives are fulfilled, our project will provide increased trust in this invaluable product and improve understanding of the sensitivity of Antarctic sea ice to a warming world.

UKRI Gateway to Research · FY 2025 · 2025-01

The challenge: The study of life's adaptation to extreme environments challenges our fundamental understanding of biological systems from molecular to whole organism levels. Proteins are key building blocks for all life on Earth with functions that are uniquely dependent on their 3-D folded state. Whilst much is known about constraints on how proteins operate at high temperatures, little knowledge exists about how biology operates at all scales of life in sub-zero conditions where proteins are less stable and oxidative damage is high. Almost 90% of the habitable biosphere is permanently below 5°C (i.e. deep sea and polar regions). Hence, we do not understand how a large proportion of global biodiversity functions at such low temperatures: A critical knowledge gap given the current climate crisis and impeding large-scale loss of the planet's colder regions and their endemic biodiversity. Aims and interdisciplinarity: Cellular proteins are adapted to function in highly crowded solutions of macromolecules, which affect protein folding, diffusion, and interactions. Temperature plays a critical role in these processes. However, there are currently no tools available that image live cells at very low temperatures. We will use the most advanced methods to adapt current state-of-the-art microscopy, and for the first time, develop fully automated microscope technology optimised for the high-resolution optical imaging of live animal cells near 0°C. This will enable us to observe the behaviour of proteins in situ and gain a deeper understanding of the behaviour of proteins near 0°C within the complex environment of the living cell. The system will be used for studies of Antarctic fish cell cultures at 0°C, our cold-adapted model organism. In particular, we will study temperature effects and cell viscosity in the context of protein folding within the cell, using a fast-folding protein, Venus, introduced into the Antarctic fish cells at 0°C and use single molecule translation imaging, developed by us, to compare the time for protein folding with temperate systems. This highly interdisciplinary project is at the very intersection of biology, physics and chemistry and involves collaboration between world-leading researchers in cutting-edge microscopy, molecular cell biology, and polar marine biology.

UKRI Gateway to Research · FY 2024 · 2024-11

The amount of plastic entering our oceans is increasing (8 million tonnes p.a.) with global implications for the health of our planet. As this plastic debris degrades in the ocean, fragmentation will shift particle size from large plastics to smaller microplastics, even in the absence of any new inputs. Thus, the problem of microplastic pollution will only increase in future years. However, the ways in which microplastics are transported to the deep ocean are still largely unknown. This limits our ability to determine the impacts of plastic debris on the ocean ecosystem and how these can be alleviated. Microplastic debris interact with highly dynamic communities of zooplankton. These small organisms, which are at the base of marine food chains, ingest microplastics and repackage them into faecal pellets which may become deposited deep in the ocean over the cycle of diel vertical migration. Microplastics may also become incorporated into zooplankton body tissue which, at the end of life, will sink as part of the carcass. I am introducing a new concept of the "Plastic Pump", to collectively describe the process of incorporation of plastics into biological processes and their subsequent movement to depth. The Plastic Pump also interacts with the biological capability of the ocean to export carbon from the surface to depth (a process known as Biological Carbon Pump, BCP). Further elucidation of the interaction between the Plastic Pump and the BCP is important since the BCP provides a critical ecosystem service in mitigating climate change through uptaking and storing anthropogenically-derived atmospheric CO2 in the deep ocean. Interference by the Plastic Pump may reduce the effectiveness of the BCP. This has yet to be determined. CUPIDO will undertake two cruise expeditions where a suite of cutting edge approaches, at the intersection of biogeochemistry, material science, and biology, will be used. These approaches include floating and moored platforms that will not only determine depth profiles of plastic concentrations over seasons, but also how plastics interact with the natural ecosystem over these depths. It will also deploy a unique device, built in-house, to evaluate how oceanic plastics alter over long time scales through incubating pre-selected meso- and microplastics in in situ conditions. CUPIDO will focus on two regions located in the Southern Ocean and the Mediterranean Sea. The contrasting conditions of the two selected regions (relatively pristine vs. highly polluted) allow for a comparative analysis of the impact of the Plastic Pump on the ocean's ability to export and sequester C within a low (Southern Ocean) and high (Mediterranean Sea) plastic input regime. My CUPIDO team will measure how the characteristics of plastics alter as a function of exposure to the marine environment; the vertical distribution and export of plastic over daily and seasonal timescales and the role of zooplankton as vectors of plastics through the water column. This wealth of novel data will be analysed and modelled to predict: (i) the accumulation of plastics in specific water layers through the water column and (ii) how the flux of plastics and C alters in regions of high and low plastic debris input. Overall, CUPIDO will address the hypothesis that zooplankton and food web associated processes play a major role in promoting the sinking of plastic through the water column. This mechanisms will decreases the ability of the marine ecosystem to transfer C from the surface to the deep ocean (resulting in a slowing of the BCP). The service provided by the BCP in lowering atmospheric CO2 levels has an economic significance to the mitigation of climate change. Through parameterising the various components of the Plastic Pump, CUPIDO will assess the economic impact of microplastic debris on the BCP and the value of combatting marine plastic pollution to restore levels of climate change mitigation.

UKRI Gateway to Research · FY 2024 · 2024-11

Mixing of the ocean around Antarctica is a key process that exerts influences over large scales and in multiple ways. By redistributing heat in the ocean, it exerts strong influences on the Antarctic Ice Sheet, with implications for sea level rise globally. Similarly, the redistribution of ocean heat affects the production of sea ice in winter and its melt in summer, with consequences for climate. Mixing also affects the distribution of nutrients in the ocean, with direct impacts on the marine ecosystem and biodiversity, and with impacts on fisheries. It was long thought that mixing of the seas close to Antarctica was predominantly caused by winds, tides, and the loss of heat from the ocean especially in winter. However, we recently discovered that when glaciers calve in Antarctica, they can trigger underwater tsunamis. These are large (multi-meter) waves that move rapidly away from the coastline, and when they break they cause sudden bursts of very intense mixing. Simple calculations indicated that the net impact of these underwater tsunamis could be as strong as winds, and much more important than tides, in driving mixing. It was also argued that they are likely to be relevant everywhere that glaciers calve into the sea, including Greenland and across the Arctic. As our ocean and atmosphere continue to heat up, it is very possible that glacier calving will become more frequent and intensify, increasing further the impact of underwater tsunamis on large-scale climate, the cryosphere, and ecosystems. This is an exciting new avenue of scientific investigation, and many key questions remain unanswered. We need to know how widespread and frequent the generation of underwater tsunamis is, how far they travel from the coastline before breaking, and how variable this is. We need to measure what impacts the extra mixing has on ocean temperature and nutrient concentrations, and to determine what this means for the cryosphere and ocean productivity. There is a pressing need to include the effects of underwater tsunamis in the computer models that are used for projecting future ocean climate and ecosystem conditions, and to determine the feedbacks between climate change and the generation of more underwater tsunamis. To answer these questions, our project will deploy innovative techniques for measuring the ocean and ice in close proximity to a calving glacier, including robotic underwater vehicles and remotely-piloted aircraft, and cutting-edge deep-learning techniques applied to satellite data. We will use advanced computer simulations to fully understand the causal mechanisms responsible for the creation and spread of the underwater tsunamis, and their impacts on ocean climate and marine productivity. We will make our developments in computer simulation available to the whole community of users, for widespread uptake and future use. This project will have significant benefits for academics seeking to predict the future of Antarctica and its impacts on the rest of the world, for Governments and intergovernmental agencies seeking to understand how best to respond to climate change, and for the curious general public wanting to learn more about the extremes of the planet and why they matter. The fieldwork will be especially photo- and video-genic, and will lead to outstanding outreach and impact opportunities, and we will work with media agencies seeking to tell compelling stories about the extremes of the Earth.

UKRI Gateway to Research · FY 2024 · 2024-11

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

UKRI Gateway to Research · FY 2024 · 2024-11

Mountains and hills (or "orography") disturb the regional and global atmospheric circulation. These disturbances affect the development of weather systems and the global atmospheric circulation. For example, they play a key role in determining the wintertime northern hemisphere circulation. Consequently, it is vital that the effects of orography are represented accurately in weather and climate models for improved predictions. This includes the Unified Model (UM) and the Momentum Unified Earth Prediction Framework (Momentum) - the current and next-generation models used by the Met Office. Orography disturbs the atmospheric circulation by exerting a frictional drag force in a variety of ways. These include drag induced by blocking of the near-surface flow by the orography. Additionally, flow that goes over the orography generates waves in the atmosphere known as orographic gravity waves (GWs). These propagate upwards until the GWs become unstable and break down, resulting in a drag at upper-levels known as orographic GW drag, as well as the cause of severe clear-air turbulence. As orography spans multiple scales, some of the smaller mountains are often smaller than the grid-spacing used by models, resulting in the drag they exert being poorly represented. These drag effects therefore have to be "parameterised" in models, i.e. represented in a simplified way in terms of the large-scale flow. However, despite the importance of orographic drag parameterisation schemes, their representation in weather and climate models is highly uncertain and a major impediment to improving the accuracy of predictions. Addressing this lack of understanding is an urgent scientific need. Tackling these problems is where our understanding of how drag is generated and partitioned over complex mountainous regions is pushed to its limits - and often falls short. For example, a major uncertainty is a lack of understanding of how the partitioning of orographic drag between its parameterised and resolved components differs between high-resolution weather models and coarse-resolution climate models. Additionally, a significant simplification made by parameterisation schemes is that they neglect the effects that changes in horizontal wind direction with height have on the breakdown of orographic GWs. This results in a misrepresentation of the altitude and magnitude of orographic GW drag. Both these deficiencies cause large and systematic errors in atmospheric circulation in weather and climate models. In TeamX-FLOW, we will provide the fundamental scientific knowledge needed to address both these critical knowledge gaps. We will deliver: A comprehensive evaluation of the representation of orographic drag (parameterised and resolved) in the UM and Momentum. Improved understanding of how changes in horizontal wind direction with altitude affect orographic GW drag, including representation of this in the UM and Momentum. To do so, we will exploit the uniquely dense and sophisticated network of measurements made as part of TEAMx over the Alps, including observations from the FAAM airborne and NCAS radiosonde campaigns. This will be supported by analysis of UM and Momentum simulations across multiple spatial scales. Our project is ideally timed to take advantage of the TEAMx observational campaign and feed into the Met Office's development of Momentum. We will work with Met Office partners to translate the results of this work to improve the representation of orographic drag in their weather and climate predictions, which are vital for public safety, agriculture, the economy, and climate adaptation plans. Our work is also important for aviation and forecasting turbulence.

UKRI Gateway to Research · FY 2024 · 2024-06

Our society is increasingly reliant upon technological infrastructure that orbits in the harsh and highly dynamic radiation environment of near-Earth space. Low-cost access to space is driving a rapid increase in the number of satellites on orbit (e.g., Starlink, Oneweb), many of which use electronics that are untested during active solar conditions, such as the upcoming solar maximum in 2024-2025. This proposal will make a significant advance in the understanding of the radiation environment in which these satellites operate. Space was a £16.5 Bn UK industry in 2019/2020 and severe space weather was added to the National Risk Register in 2011, owned by the Met Office who provide space weather services to the satellite industry. However, current forecasting models, including the BAS Radiation Belt Model (BAS-RBM) that provides forecasts to the Met Office and European Space Agency, only forecast the highest energy electrons and the associated risk of damage from internal charging. The Met Office currently has no capability to forecast the lower energy electrons that can cause surface charging damage and be energised to become so-called 'killer' electrons. The radiation environment is highly dynamic and includes several different populations of electrons, identified by their energy ranges. The lowest energy electrons form the background plasma, medium energy electrons are found in the ring current, and the highest energy electrons form the radiation belts. These have historically been studied independently but the populations are interdependent, and recent research has highlighted that they need to be studied as a single system. For example, the highest energy killer electrons are produced when lower energy electrons are energised by electromagnetic waves. These waves are generated by the medium energy electrons and the acceleration is most effective in regions with a depleted background plasma. This proposal aims to establish how the populations and their interactions contribute to the variability of the radiation environment. We will determine which solar wind conditions produce the most effective wave-electron interactions, quantify the role of realistic magnetic fields on the loss and energisation of electrons, and determine how the interactions of the different populations affect the radiation environment in key types of space weather events. This will significantly increase our understanding of the conditions that lead to radiation environments that may damage satellites. These studies require a combination of data analysis and modelling. A few models can study multiple populations, but they all initially addressed a single population using an appropriate framework for that population. Extending to include another population meant incorporating an additional framework, introducing interpolation errors and inconsistencies. For example, although these models use realistic magnetic field models for part of the calculation, they assume a dipole magnetic field to model the wave-electron interactions. Building on our BAS-RBM experience, we will adopt a novel approach using a unifying framework for all three populations that can also include realistic magnetic and electric fields. To be consistent we will also develop the first comprehensive characterisations of wave-electron interactions in realistic magnetic fields. Using observations from spacecraft such as the Van Allen Probes, together with this new modelling framework, we will address the causes of variability in the radiation environment. The model created for these studies will also be able to provide improved predictions of the conditions leading to internal charging on satellites and a new ability to address surface charging.