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Our current understanding of the Earth's climate is largely based on the predictions of numerical models that simulate the behaviour of, and interaction between, the atmosphere and the ocean. These models are crucially limited in their resolution, however, such that processes within the ocean that have horizontal scales of less than approximately 10 km cannot be explicitly represented and need to be parameterised for their effects to be included within the models. The purpose of this project, Surface Mixed Evolution at Submesoscales (SMILES), is to identify the potentially crucial role played by one variety of these unresolved processes, referred to as submesoscales, in influencing the structure and properties of the upper ocean, and thereby the transformation of surface water masses, within the Southern Ocean. Submesoscales are flows with spatial scales of 1-10 km that occur within the upper ocean where communication and exchange between the ocean and the atmosphere occurs. Previously considered unimportant to climate-scale studies due to their small scale and the presumed insignificance of their dynamics, recent evidence from high resolution regional models and observational studies is now emerging which suggests that submesoscales are actually widespread throughout the upper ocean and play a key role within climate dynamics due to their ability to rapidly restratify the upper ocean and reduce buoyancy loss from the ocean to the atmosphere. The impact of such a process is particularly important to the surface transformation of water masses such as Subantarctic Mode Water (SAMW), which is an important component of the Meridional Overturning Circulation (MOC) that redistributes heat, freshwater and tracers around the globe. Within the MOC, dense water masses such as SAMW are formed and transformed at high latitudes by surface processes before being subducted into the ocean interior. The properties of the subducted water masses and the tracers and dissolved gases such as carbon dioxide contained within them are vitally important to the global climate and geochemical cycles as these water masses remain out of contact with the surface over decennial to centennial timescales. In the light of the recent discoveries concerning the ability of submesoscales to substantially influence the properties of the upper ocean, we will directly study the impacts of submesoscales on SAMW properties within the Scotia Sea. Using an integrated approach, we will both observe and simulate submesoscales within the upper ocean at a range of spatial and temporal scales, spanning from turbulence up to mode water formation. The principal goal of the study is the diagnosis of the role played by submesoscales in water mass transformation so that we can accurately incorporate these effects into climate-scale models which cannot explicitly resolve them. Our methods will entail a cruise approximately 200 miles south of the Falklands Islands at the Subantarctic Front (SAF), to the north of which SAMW is transformed, and a concurrent modelling study using a state-of-the-art global circulation model. During the cruise, we will use towed instruments to measure the length scales of variability in the temperature, salinity and related fields throughout the upper 300 m of the ocean. The data will enable us to identify the intensity and distribution of submesoscales within the vicinity of the SAF, and to ascertain the forcing mechanisms that generate them. In conjunction with the modelling component of the project, which will include both high resolution and coarse-scale simulations with the MITgcm and large eddy simulations (LES), we will assess how submesoscales ultimately impact on the properties of SAMW within the region and the ultimate effect this has on the formation of SAMW.

Copepod species of the genus Calanus (Calanus hereafter) are rice grain-sized crustaceans, distant relatives of crabs and lobsters, that occur throughout the Arctic Ocean consuming enormous quantities of microscopic algae (phytoplankton). These tiny animals represent the primary food source for many Arctic fish, seabirds and whales. During early spring they gorge on extensive seasonal blooms of diatoms, fat-rich phytoplankton that proliferate both beneath the sea ice and in the open ocean. This allows Calanus to rapidly obtain sufficient fat to survive during the many months of food scarcity during the Arctic winter. Diatoms also produce one of the main marine omega-3 polyunsaturated fatty acids that Calanus require to successfully survive and reproduce in the frozen Arctic waters. Calanus seasonally migrate into deeper waters to save energy and reduce their losses to predation in an overwintering process called diapause that is fuelled entirely by carbon-rich fat (lipids). This vertical 'lipid pump' transfers vast quantities of carbon into the ocean's interior and ultimately represents the draw-down of atmospheric carbon dioxide (CO2), an important process within the global carbon cycle. Continued global warming throughout the 21st century is expected to exert a strong influence on the timing, magnitude and spatial distribution of diatom productivity in the Arctic Ocean. Little is known about how Calanus will respond to these changes, making it difficult to understand how the wider Arctic ecosystem and its biogeochemistry will be affected by climate change. The overarching goal of this proposal is to develop a predictive understanding of how Calanus in the Arctic will be affected by future climate change. We will achieve this goal through five main areas of research: We will synthesise past datasets of Calanus in the Arctic alongside satellite-derived data on primary production. This undertaking will examine whether smaller, more temperate species have been increasingly colonising of Arctic. Furthermore, it will consider how the timing of life-cycle events may have changed over past decades and between different Arctic regions. The resulting data will be used to validate modelling efforts. We will conduct field based experiments to examine how climate-driven changes in the quantity and omega-3 content of phytoplankton will affect crucial features of the Calanus life-cycle, including reproduction and lipid storage for diapause. Cutting-edge techniques will investigate how and why Calanus use stored fats to reproduce in the absence of food. The new understanding gained will be used to produce numerical models of Calanus' life cycle for future forecasting. The research programme will develop life-cycle models of Calanus and simulate present day distribution patterns, the timing of life-cycle events, and the quantities of stored lipid (body condition), over large areas of the Arctic. These projections will be compared to historical data. We will investigate how the omega-3 fatty acid content of Calanus is affected by the food environment and in turn dictates patterns of their diapause- and reproductive success. Reproductive strategies differ between the different species of Calanus and this approach provides a powerful means by which to predict how each species will be impacted, allowing us to identify the winners and losers under various scenarios of future environmental changes. The project synthesis will draw upon previous all elements of the proposal to generate new numerical models of Calanus and how the food environment influences their reproductive strategy and hence capacity for survival in a changing Arctic Ocean. This will allow us to explore how the productivity and biogeochemistry of the Arctic Ocean will change in the future. These models will be interfaced with the UK's Earth System Model that directly feeds into international efforts to understand global feedbacks to climate change.

Shelf seas are of major societal importance providing a diverse range of goods (e.g. fisheries, renewable energy, transport) and services (e.g. carbon and nutrient cycling and biodiversity). Managing UK seas to maintain clean, healthy, safe, productive and biologically diverse oceans and seas is a key governmental objective, as evidenced by the obligations to obtain Good Environmental Status (GES) under the UK Marine Strategy Framework, the Convention on Biological Diversity and ratification of the Oslo-Paris Convention (OSPAR) .. The delivery of these obligations requires comprehensive information about the state of our seas which in turn requires a combination of numerical models and observational programs. Computer modelling of marine ecosystems allows us to explore the recent past and predict future states of physical, chemical and biological properties of the sea, and how they vary in 3D space and time. In an analogous manner to the weather forecast, the Met Office runs a marine operational forecast system providing both short term forecast and multi-decadal historical data products. The quality of these forecasts is improved by using data assimilation; the process of predicting the most accurate ocean state using observations to nudge model simulations, producing a combined observation and model product. Marine autonomous vehicles (MAVs) are a rapidly maturing technology and are now routinely deployed both in support of research and as a component of an ocean observing system. When used in conjunction with fixed point observatories, ships of opportunity and satellite remote sensing, the strategic deployment of MAVs offers the prospect of substantial improvement in our observing network. Marine Gliders in particular have the capability to provide depth resolved data sets of high resolution from deployments that can endure several months and cover 100s kms, allowing the collection of sufficient information to be useful for assimilation into models. We will improve the exchange of data between model systems and observational networks to inform an improved strategy for the deployment of the UK's high-cost marine observing capability. In particular we will utilise mathematical and statistical models to develop and test "smart" autonomy - autonomous systems that are enabled to selectively search and monitor explicit features within the marine system. By developing data assimilation techniques to utilise autonomous data, our model systems will be able to better characterise episodic events such as the spring bloom, harmful algal blooms and oxygen depletion, which are currently not well captured and are key to understanding ecosystem variability and therefore quantifying GES. In doing so CAMPUS will provide a step change in the combined use of observation and modelling technologies, delivered through a combination of autonomous technologies (gliders), other observations and shelf-wide numerical models. This will provide improved analysis of key ocean variables, better predictions of episodic events, and 'smart' observing systems in order to improve the evidence base for compliance with European directives and support the UK industrial strategy.