The UK's Net Zero strategy is for all sectors of the economy to meet the Net Zero target by 2050. Similar long-term aims to move towards Net Zero emissions on the same timescales exist in other countries, including the USA. High-performance computing (HPC) is not exempt from needing to adapt to these strategic challenges, and pushing HPC towards sustainability and Net Zero is crucial if the scientific community is to keep justifying the use and cost of large-scale HPC resources in the face of climate change. Electricity consumption of data centres and systems is by far the largest contributor to the carbon footprint of operational HPC and minimising the energy that is consumed, and reducing/reusing waste, is therefore key in achieving Net Zero. The International Collaboration Towards Net Zero Computational Modelling and Simulation (CONTINENTS) project will build on the expertise of EPCC, the supercomputing centre at the University of Edinburgh, the National Centre for Atmospheric Science in the UK and the National Centre for Atmospheric Research in the USA to transform the state-of-the-art in sustainability and power/energy efficiency of computational modelling and simulation through an ambitious programme of research that will drive innovations in: data centre and HPC system operation; optimal use of hardware; machine learning applied to data analysis and numerical modelling; and software design and development strategies. As a specific use case, CONTINENTS will focus the application of its research on weather and climate modelling. These are both scientifically and computationally challenging, and compute resource intensive, domains that are vital to furthering our understanding of climate change and the factors that influence it. CONTINENTS is a unique interdisciplinary collaboration between leading centres of HPC research and service provision, atmospheric science experts, and numerical and machine learning application developers, providing a comprehensive approach to addressing the Net Zero challenge from the data centre all the way through to individual applications using both computational and climate science expertise. The projects objectives include: establishing a long-term collaboration between leading supercomputing researchers and centres in the UK and USA; pushing the boundaries of sustainable operation of data centres; exploring the use of novel and specialised hardware; developing new methods for performance, power and energy efficient software development and deployment; minimising the resources needed for moving, processing, analysing and storing data; and creating a collaborative research environment that encourages sharing of expertise and knowledge.

Dimethyl sulphide (DMS) is a trace gas produced in marine environments that gives the ocean the typical 'smell of the sea'. Its concentrations in seawater and in air samples have been monitored for many years, since research demonstrated that DMS is responsible for making clouds in the remote marine atmosphere. Of course, this is important for our understanding of climate and future global change. In contrast to this global significance, we know very little about how, when and why DMS is produced. Most of the DMS is enzymatically cleaved from dimethylsulphoniopropionate (DMSP), a compound that many algae use as an osmolyte to survive in high salt environments. Conventional methodology (purge-and-trap coupled to gas chromatography) to quantify DMS in seawater and air is laborious and time-consuming. As a result, we currently lack high-resolution data on the production of DMS in algal cultures. We hypothesise that DMS production is variable over the day and sensitive to environmental stress such as high light conditions. Methodology using chemiluminescence detection of DMS for high resolution measurements in air exists but this technology has not been used to address physiological aspects of DMS production in water. We conducted DMS measurements in the water and in the waste air from aerated chemostat cultures of the globally important and DMS-producing alga Emiliania huxleyi. The aeration efficiently purges most of the DMS out of the water and transfers this gas into the air stream. As a result, the DMS concentrations in the waste air provide an accurate measurement of DMS production. Since the DMS concentrations in the waste air are relatively high (2 to 40 parts per million) and other trace gases occur at relatively low concentrations, it is possible to use the ozone-induced chemiluminescence of DMS to continuously monitor the concentration of this compound. We already tested a commercially available chemiluminescence detector (Fast Isoprene Sensor) for DMS and found a linear response to DMS in the parts per billion to parts per million concentration range. This is encouraging and suggests that this instrument could be readily used for our application. We propose to optimise and test the Fast Isoprene Sensor for our DMS measurements. A series of experiments using chemostats with continuous cultures of E. huxleyi will be used to address DMS production under steady-state conditions before perturbing the system with short periods of increased light intensity (in the visible and ultraviolet spectrum). Light has been shown to affect DMS production in E. huxleyi, and it is thought that DMS functions as an antioxidant and assists with the removal of harmful reactive oxygen species that are produced under high light conditions. However, the dynamics of DMS production under such stressful conditions are unknown. Our project will deliver new information on DMS production in E. huxleyi. It will further test an online chemiluminescence detector for inexpensive continuous monitoring of DMS-production in algal cultures. We envisage that this high-resolution methodology will be used in future grant applications that will address DMS-production from various organisms including other phytoplankton species, macroalgae, fungi and bacteria.

The AMOC is a large-scale ocean circulation system composed of currents that carry warm, shallow water northwards and return cold, deeper water southwards. The AMOC is crucial in maintaining the relatively mild winter climate of Northwest Europe. A shutdown of the AMOC would strongly impact European temperature and precipitation variability. Because of the AMOC's role in regulating the global climate system, several direct ocean observing programmes have been put in place to monitor the AMOC. In the North Atlantic, the two main observing arrays are the Rapid Climate Change Program (RAPID) and the Overturning in the Subpolar North Atlantic Program (OSNAP) at 26N and 50-60N, respectively. While these programmes have transformed our understanding of changes in the AMOC, they are limited to single lines of latitude and have relatively short lifespans (two decades at most). These constraints prevent us from being able to understand changes on long (decadal to centennial) timescales or understand how the AMOC is connected across the latitudes where we don't have direct measurements. Further, the maintenance of the observing arrays is costly and there is no backup system in place in the event of instrumentation failure or loss. To overcome the limitations of the RAPID and OSNAP observing arrays, the oceanographic community has sought alternative solutions for monitoring the AMOC using cost-effective observing systems, like existing satellite and autonomous ocean robot data that have high spatial and temporal coverage. These alternative solutions for monitoring the AMOC have recently been trialled at a few places in the North Atlantic. At the same time, advances in machine learning and modelling methods are starting to prove useful for monitoring the AMOC from indirect measurements. The AMOC monitoring at RAPID and OSNAP will soon achieve 20- and 10- years worth of continuous measurements, respectively. The combination of these AMOC records with the recent developments in alternative AMOC monitoring methods means that the oceanographic community now has the tools in place to dramatically improve our ability to understand the AMOC across the North Atlantic Ocean over long time periods. Thus, MEZCAL will combine computational advances with the recent proven alternative methods for monitoring the AMOC to extend the coverage of AMOC observations across the North Atlantic and deliver a new framework that will make a step change in our understanding of AMOC variability. This project will also provide recommendations for how to build a sustainable AMOC monitoring system moving forward.

The Antarctic Peninsula is currently one of the most rapidly warming regions on Earth. Large environmental changes have occurred as a result of this warming, most notably the retreat and rapid disintegration of some of the floating ice shelves that fringe the Peninsula. Subsequent to the loss of ice shelves, glaciers draining the Peninsula ice sheet have accelerated, contributing to global sea level rise. The forces driving this rapid regional warming are not fully understood, but analysis of limited climatiological data from the region suggests a link between rapid summer warming on the eastern side of the Peninsula and an increase in the strength of the prevailing westerly winds. The strengthening of the westerlies has already been attributed, with some degree of confidence, to atmospheric circulation changes associated with anthropogenic forcing, particularly stratospheric ozone depletion and increases in greenhouse gases. It is thus highly probable that anthropogenic forcing is contributing to the rapid warming of the Peninsula. We propose an integrated programme of field observations, analysis and modelling aimed at understanding of how the westerly winds interact with the mountains of the Antarctic Peninsula and how these interactions control the climate of the eastern side of the Peninsula. Our field observations will be concentrated into a one-month (January 2011) intensive field campaign. During this period, atmospheric flow along a transect across the Antarctic Peninsula mountains at around 67 degrees south will be observed using an instrumented aircraft and four automatic weather stations along the line of the transect. Atmospheric conditions on the upwind (western) and downwind (eastern) sides of the mountains will be measured using balloon-borne radiosondes while the fluxes of energy (solar and terrestrial radiation, turbulent heat fluxes) that drive surface melting will be monitored at a camp on the Larsen Ice Shelf to the east of the Peninsula. In order to obtain a more complete picture of the flow across the Peninsula, we will use these observations in conjunction with the results of high-resolution atmospheric model simulations. Observations and model results will, together, provide new insight into the links between atmospheric flow, orography and surface climate in this region. Having established these links, we will use our new understanding of the controls on regional climate to develop soundly-based future (next 100 years) climate scenarios for this region, using predictions of the changes in large-scale atmospheric flow from the 4th Assessment Report of the Intergovernmental Panel on Climate Change. The results of our work will be of value to many groups of scientists working on environmental change in the Antarctic Peninsula and its wider impacts, including glaciologists, oceanographers and marine and terrestrial biologists. The proposal will also contribute to improving the performance of numerical weather prediction and climate models in mountainous areas generally.

The Arctic is a region experiencing rapid climate changes. APPOSITE is a proposed three year research programme focusing on improving our ability to forecast the climate of the Arctic on seasonal to inter-annual timescales. Arctic predictions would be of great value to both the people that live and work in the Arctic regions and also for informing important policy decisions about the region. Additionally, the Arctic region exerts an influence on the climate outside the Arctic. Hence improved forecasts of Arctic climate may increase our ability to forecast climate in mid-latitude regions, such as Europe, on similar seasonal to inter-annual timescales. Building such Arctic forecast systems will be a complex task, involving the construction of a detailed observation system to monitor Arctic climate, and sophisticated forecast models that can use these observations to enhance predictive capabilities. An important first step before committing to such a programme, is to assess the likely benefits that such a system may bring. APPOSITE is specifically designed to provide this assessment by answering four key questions: 1) What aspects of Arctic climate can we predict? 2) How far in advance can we predict these aspects? Does this depend on the season? 3) What physical processes and mechanisms are responsible for this predictability? 4) What aspects of forecast models should be prioritised for development? APPOSITE will use state-of-the art climate models to answer these questions. The answers to these questions will form a key part of the future development of seasonal to inter-annual Arctic forecasting systems nationally and internationally.