On June 15 2006, the World Wildlife Federation (WWF) released a report called 'Killing them Softly', which highlighted concern over the accumulation and toxic effects of persistent organic pollutants present in Arctic wildlife, particularly marine mammals such as the Polar Bear. The Times newspaper ran a full-page article summarising this report and detailed 'legacy' chemicals such as DDT and polychlorinated biphenyls (PCBs), as well as the rise in 'new' chemical contaminants such as brominated flame retardents and perfluorinated surfactants, which are also accumulating in arctic fauna and adding an additional toxic risk. The high levels of these contaminants are making animals like the Polar Bear less capable of surviving the harsh Arctic conditions and dealing with the impacts of climate change. The work in this proposal intends to examine how these chemicals are delivered to surface waters of the Arctic Ocean, and hence the base of the marine foodweb. Persistent organic pollutants reach the Arctic via long-range transport, primarily through the air from source regions in Europe, North America and Asia, but also with surface ocean currents. The cold conditions of the Arctic help to promote the accumulation of these chemicals in snow and surface waters and slows any breakdown and evaporative loss. However, the processes that remove these pollutants from the atmosphere, store them in snow and ice and then transfer them to the Arctic Ocean are poorly understood, and yet these processes may differ depending on the chemcial in question. For example, some chemicals are rather volatile (i.e. they have a tendency to evaporate), so while they can reach the Arctic and be deposited with snowfall they are unlikely to reach the ocean due to ltheir oss back to the atmosphere during the arctic summer. On the other hand, heavier, less volatile chemicals, become strongly bound to snow and particles and can be delivered to seawater during summer melt. Climate change and a warmer world are altering the Arctic and affecting pollutant pathways. For example, the number of ice-leads (large cracks in the sea-ice that give rise to 'lakes' of seawater) are increasing. As a result, the pathways that chemical pollutants take to reach ocean waters are changing and may actually be made shorter, posing an even greater threat to marine wildlife. During ice-free periods, the ocean surface water is in contact with the atmosphere (rather than capped with sea-ice) and airborne pollutants can dissolve directly into cold surface waters. Encouragingly, there is evidence that some of the 'legacy' pollutants are declining in the arctic atmosphere, but many 'modern' chemicals are actually increasing in arctic biota and work is required to measure their input and understand their behaviour in this unusual environment. For example, in sunlit surface snow following polar sunrise (24 h daylight), some of these compounds can degrade by absorbing the sunlight, and in some cases, this can give rise to more stable compounds that subsequently enter the foodchain. Therefore, the quantity of chemical pollutant that is deposited with snowfall and the chemical's fate during snowmelt are important processes to address, especially to understand the loading and impact of these pollutants on the marine ecosystem. This project aims to understand these processes, and to understand which type of pollutants and their quantities pose the greatest threat to wildlife.

The atmosphere changes on time scales from seconds (or less) through to years. An example of the former are leaves swirling about the ground within a dust-devil, while an example of the latter is the quasibiennial oscillation (QBO) which occurs over the equator high up in the stratosphere. The QBO is seen as a slow meander of winds: from easterly to westerly to easterly over a time scale of about 2.5 years. This 'oscillation' is quite regular and so therefore is predictable out from months through to years. These winds have also been linked with weather events in the high latitude stratosphere during winter, and also with weather regimes in the North Atlantic and Europe. It is this combination of potential predictability and the association with weather which can affect people, businesses and ultimately economies which makes knowing more about these stratospheric winds desirable. However, it has been difficult to get this phenomenon reproduced in global climate models. We know that to get these winds in models one needs a good deal of (vertical) resolution. Perhaps better than 600-800m vertical resolution is needed. In most GCMs with a QBO this is the case, but why? We also know that there needs to be waves sloshing about, either ones that can be 'seen' in the models, or wave effects which are inferred by parameterisations. Get the right mix of waves and you can get a QBO. Get the wrong mix and you don't. Again we do not know entirely why. Furthermore, we also know convection bubbling up over the tropics and the slow migration of air upwards and out to the poles also has a big impact of resolving the QBO. All of these factors need to be constrained in some way to get a QBO. The trouble is that these factors are invariably different in different climate models. It is for this reason that getting a regular QBO in a climate model is so hard. This project is interested in exploring the sensitivity of the QBO to changes in resolution, diffusion and physics processes in lots of climate models and in reanalyses (models used with observations). To achieve this, we are seeking to bring together all the main modelling centres around the world and all the main researchers interested in the QBO to explore more robust ways of modelling this phenomena and looking for commonalities and differences in reanalyses. We hope that by doing this, we may get more modelling centres interested and thereby improve the number of models which can reproduce the QBO. We also hope that we can get a better understanding of those impacts seen in the North-Atlantic and around Europe and these may affect our seasonal predictions. The primary objective of QBOnet is to facilitate major advances in our understanding and modelling of the QBO by galvanizing international collaboration amongst researchers that are actively working on the QBO. Secondary objectives include: (1) Establish the methods and experiments required to most efficiently compare dominant processes involved in maintaining the QBO in different models and how they are modified by resolution, numerical representation and physics parameterisation. (2) Facilitate (1) by way of targeted visits by the PI and researchers with project partners and through a 3-4 day Workshop (3) Setup and promote a shared computing resource for both the QBOi and S-RIP QBO projects on the JASMIN facility

The role of external drivers of climate change in mid-latitude weather events, particularly that of human influence on climate, arouses intense scientific, policy and public interest. In February 2014, the UK Prime Minister stated he "suspected a link" between the flooding at the time and anthropogenic climate change, but the scientific community was, and remains, frustratingly unable to provide a more quantitative assessment. Quantifying the role of climate change in extreme weather events has financial significance as well: at present, impact-relevant climate change will be primarily felt through changes in extreme events. While slow-onset processes can exacerbate (or ameliorate) the impact of individual weather events, any change in the probability of occurrence of these events themselves could overwhelm this effect. While this is known to be a problem, very little is known about the magnitude of such changes in occurrence probabilities, an important knowledge gap this project aims to address. The 2015 Paris Agreement of the UNFCCC has given renewed urgency to understanding relatively subtle changes in extreme weather through its call for research into the impacts of a 1.5oC versus 2oC increase in global temperatures, to contribute to an IPCC Special Report in 2018. Few, if any, mid-latitude weather events can be unambiguously attributed to external climate drivers in the sense that these events would not have happened at all without those drivers. Hence any comprehensive assessment of the cost of anthropogenic climate change and different levels of warming in the future must quantify the impact of changing risks of extreme weather, including subtle changes in the risks of relatively 'ordinary' events. The potential, and significance, of human influence on climate affecting the occupancy of the dynamical regimes that give rise to extreme weather in mid-latitudes has long been noted, but only recently have the first tentative reports of an attributable change in regime occupancy begun to emerge. A recent example is the 2014 floods in the Southern UK, which are thought to have occurred not because of individually heavy downpours, but because of a more persistent jet. Quantifying such changes presents a challenge because high atmospheric resolution is required for realistic simulation of the processes that give rise to weather regimes, while large ensembles are required to quantify subtle but potentially important changes in regime occupancy statistics and event frequency. Under this project we propose, for the first time, to apply a well-established large-ensemble methodology that allows explicit simulation of changing event probabilities to a global seasonal-forecast-resolution model. We aim to answer the following question: over Europe, does the dynamical response to human influence on climate, manifest through changing occupancy of circulation regimes and event frequency, exacerbate or counteract the thermodynamic response, which is primarily manifest through increased available moisture and energy in individual events? Our focus is on comparing present-day conditions with the counterfactual "world that might have been" without human influence on climate, and comparing 1.5 degree and 2 degree future scenarios. While higher forcing provides higher signal-to-noise, interpretation is complicated by changing drivers and the potential for a non-linear response. We compensate for a lower signal with unprecedentedly large ensembles. Event attribution has been recognised by the WCRP as a key component of any comprehensive package of climate services. NERC science has been instrumental in its development so far: this project will provide a long-overdue integration of attribution research into the broader agenda of understanding the dynamics of mid-latitude weather.

Forecasting the weather from days to two weeks in advance has typically focused on the troposphere, the layer of the atmosphere closest to the ground. A typical weather forecast first attempts to estimate what the atmosphere is like now, and then extrapolates forward in time, using a complex model of the atmosphere based on the basic physical laws of motion. Over the last 15 years, evidence has been growing that different parts of the atmosphere and Earth system can also be exploited to improve weather forecasts. One of these regions is the stratosphere, the layer directly above the troposphere. Because, temperatures increase with height in the stratosphere, winds and weather systems are quite different, and a distinct community of scientific researchers who study the stratosphere exists around the world. Through the work of this community, many weather forecasting centres have been encouraged to look to the stratosphere to improve their weather forecasts and have been modifying their weather forecasting models accordingly. What has been missing, however, is a concerted effort to understand how best to make use of the stratosphere to improve weather forecasts and to determine how much weather forecasts might benefit. This proposal will fund a new international scientific network which will bring scientists from around the world together to study the stratosphere and how it might be used to improve weather forecasts. The network is made up of scientists from universities and weather forecasting centres around the world and is supported by two other international scientific research bodies. The network will allow scientists to come together to discuss current research in this area and to plan and carry out a new experiment which will compare the stratosphere and its impact on weather forecasts in their weather forecasting models. At the end of the research project, the network members will work together to produce a report which will provide guidance to all weather forecasting centres on the use of the stratosphere for weather forecasting.

The oldest, thickest sea ice in the 'last ice area' of the Arctic - a region thought to be most resilient to climate warming - unexpectedly broke up twice in the past year. Our current theories assume that the end-of-summer ice-covered area will steadily retreat into the Central Arctic Basin as global warming accelerates over coming decades. However, the dynamic break-up events witnessed in 2018 challenge this prevailing view. Here we hypothesise that a weaker, increasingly mobile Central Arctic ice pack is now susceptible to dynamic episodes of fragmentation which can precondition the ice for rapid summer melt. This mechanism of dynamic seasonal preconditioning is unaccounted for in global climate models, so our best current projections are overlooking the possibility for rapid disintegration of the Arctic's last ice area. Our team has demonstrated that seasonal preconditioning is already responsible for the neighbouring Beaufort Sea becoming ice-free twice in the past five years. Even ten years ago this region contained thick perennial sea ice, mirroring the Central Arctic Ocean, but it has now transitioned to a marginal Arctic sea. Could the processes responsible for the decline of the Beaufort Sea ice pack start to manifest themselves in the Central Arctic? Currently, a shortfall in satellite observations of the Arctic pack ice in summer prevents us from testing our hypothesis. We desperately require pan-Arctic observations of ice melting rates, but so far satellite observations of sea ice thickness are only available during winter months. Our project will therefore deliver the first measurements of Arctic sea ice thickness during summer months, from twin satellites: ESA's Cryosat-2 & NASA's ICESat-2. We have designed a new classification algorithm for separating ice and ocean radar altimeter echoes, regardless of surface melting state, providing the breakthrough required to fill the existing summer observation 'gap'. Exploiting the recent launch of multiple SAR missions for polar reconnaissance, our project will integrate information on ice-pack ablation, motion and deformation to generate a unique year-round sea ice volume budget in the High Arctic. This record will inform high-resolution ice dynamics simulations, performed with a suite of state-of-the-art sea ice models from stand alone (CICE), ocean-sea ice (NEMO/CICE), to fully coupled regional high resolution (RASM), and global coarser resolution (HadGEM) models, all now equipped with the anisotropic (EAP) sea ice rheology developed by our team. Using the regional and stand-alone models we will analyse the role of mechanics in this keystone region north of Greenland to scrutinise the coupling and preconditioning of winter breakup events - such as those witnessed in 2018 - to summer melting rates. Using the coupled models, we will quantify the likelihood of the Arctic's last ice area breaking up much sooner than expected due to oceanic and atmospheric feedbacks and how this will affect the flushing of ice and freshwater into the North Atlantic.