BACKGROUND In the last fifty years aviation has experienced very rapid development, with air traffic recording an almost 9% yearly growth rate in the first half of the period (approximately 2.5 times the average GDP growth rate) and approximately 5% yearly growth rate in the second half of the period. According to the most recent estimates, aviation climatic impact amounts to 2-8% of the global radiative forcing associated with climate change. As a result of the expected increase in air traffic in the next decades, the relative importance of air traffic on climate change is expected to increase significantly. THE NEED FOR COSIC AND AIMS One of aviation's largest effects is likely to be that due to contrails and their spreading into cirrus. This could be considerably larger than the effects of increased CO2 emissions but this contrail-cirrus remains unquantified. Previous estimates of combined aviation induced cloudiness suggest that spreading contrails could be important. However, these studies rely on correlating air traffic with cirrus coverage and have large uncertainties and methodological problems. The ultimate aim of this proposal is, for the first time, to build a physically based parameterisation of contrail-cirrus - to determine its role in climate change, testing whether it has a larger role than line-shaped contrails. To achieve this ultimate goal, observations of contrail properties and their spreading will be made with FAAM (research aircraft) flights and satellite observations. Then a hierarchy of models will be used to develop a contrail-cirrus cloud parameterisation within the Met Office Unified Model, working closely with both the Met Office and the Deutsches Zentrum für Luft- und Raumfahrt (DLR) partners, and constraining the developed parameterisations by the observations made by University of Manchester and Met Office researchers during the aircraft campaign. WORKPLAN WP1 will perform an aircraft campaign making 6 'case study' observations of spreading contrail during 2009 in an area out of the flight corridor to the southwest of the UK . We will use a novel 'figure of eight' flight pattern to make and monitor our own contrail and, in particular, track its evolution into cirrus. We will measure its radiative forcing by flying cross sections above and below and by monitoring from space using the GERB and SEVIRI geostationary instruments. We will make use of state-of-the-art observations made by the Met Office and University of Manchester groups. We will also rely on ice supersaturation forecasts supplied by the University of Reading group using European Centre forecasts. WP2 will use idealised modelling data supplied by DLR and the detailed observations made during WP1 to simulate specific case studies observed during the aircraft campaign. Particular attention will be made to the later stages of contrail lifecycle. WP3 will again make use of idealised DLR data and our own (and others) case-study data to build a prognostic contrail-cirrus scheme for the Met Office Unified Model. WP4 will employ the Unified Model with this parameterisation to predict the radiative forcing and climate impact from contrail-cirrus, comparing its climate impact to that estimated for line-shaped contrails.

This project will quantify the impacts of processes that control export of pollution from Europe on air quality, climate and ecosystems. These processes currently lack observational constraint, and our understanding is largely based on model simulations. We will conduct the first studies of European pollution export constrained by extensive aircraft and satellite observations, and quantify air quality and climate impacts. We will also quantify the role of ozone pollution from Europe in reducing CO2 uptake to European and Siberian forest, due to its harmful effects on vegetation. This will be compared with the direct climate impact of European ozone as a greenhouse gas. This will also allow quantification of a reduction in the effectiveness of CO2 emission cuts due to ozone limitation of carbon uptake to the biosphere, which is of urgent interest to policy makers and governments. Ozone is a pollutant in the lower atmosphere, which is not emitted directly, but is formed in the atmosphere by sunlight-driven chemical reactions acting on nitrogen oxides emitted from high-temperature fuel combustion (primarily motor vehicles, power plants, biomass burning) and volatile organic compounds, emitted from both man-made and natural sources. Ozone is a strong oxidant and a greenhouse gas in the lower atmosphere, and its concentrations have increased markedly since pre-industrial times. It is harmful to human health, and also damages vegetation. This leads to substantial reductions in crop yields, and also results in a reduction in the ability of vegetation to take up CO2 from the atmosphere - meaning it may result in further 'indirect' greenhouse warming. Export of pollution from the major continents in controlled by transfer of pollutants from the surface boundary layer (BL) to the overlying large-scale free troposphere (FT), where it can be transported over 1000s km. Over North America and Asia this 'venting' of the BL is controlled largely by fronts associated with low-pressure weather systems, however over central Europe these are much less frequent. Processes controlling European pollution export are much less well understood, and our lack of understanding is exacerbated by a lack of observations in regions downstream from Europe (mainly Arctic, Siberia and over the Mediterranean basin). Our approach will be to use new observations from aircraft experiments over the Arctic and Siberia, satellites and numerical models to quantify the roles of dynamic and chemical processes in controlling ozone pollution export from Europe. We will investigate how these processes determine the air quality and climate impacts of European ozone precursor emissions. In addition, we will determine how anthropogenic and natural processes interact to affect these processes, and quantify the impact of European ozone pollution on CO2 uptake to European and Siberian vegetation. We will finally quantify how these processes may change under future climate (year 2050).

This research is focused on new technology development. The NERC's Technologies Theme Action Plan, has identified the area of new numerical model development as a critical area where UK skills and expertise should be developed. An important goal of NERC-funded research is 'tackling the key issue of climate change', and as such 'identifying the limitations of a particular model is an important part of stimulating further improvements, and advancing our understanding' (http://www.nerc.ac.uk/research/issues/climatechange/predict.asp). The proposed research focuses on this goal in relation to atmospheric flows. Contemporary numerical models used in the simulation of stratified rotating atmospheric flows are predominantly based on structured computational meshes, with rigid connectivity of a Cartesian grid. For some problems (e.g., hurricanes and flows in long winding valleys), mesh adaptivity has a potential to achieve solutions not obtainable by other methods. However, existing unstructured mesh models are still in their infancy compared to both established structured-grid codes and state-of-the-art engineering advancements with unstructured meshes. Furthermore, their implementation tends to emphasize small-scale convective phenomena and emergency responses, which are relatively easy to model because of the large noise-to-signal ratio, and because of the proximity of events to the excitation region. Insofar as the full-range of wave dynamics are concerned -- including such subtleties as wave-wave and wave-mean-flow interactions, as well as large-amplitude events occurring far from the excitation region -- the potential of unstructured-mesh technology remains unknown. In order to prove the competence and competitiveness of unstructured-mesh technology for simulating all-scale flows in the atmosphere and oceans, there is a pressing need for developing an advanced, fully non-hydrostatic model for simulating accurately rotating stratified flows in a broad range of Rossby-, Froude-, and Reynolds-number regimes. In this work we propose to develop a novel code operating on hybrid (arbitrary polyhedra) meshes, for solving a number of optional forms of non-hydrostatic equations of atmospheric fluid dynamics with flexible mesh-adaptivity capabilities. The proposed model will mirror stratified, rotating turbulence-simulation capabilities of the structured-grid model EULAG (EUlerian/LAGrangian), the proven record of which includes direct and large-eddy simulations of complex fluid problems from laboratory-, to meso-, up to the planetary scale. Additionally, we shall perform rigorous studies and comparisons, by applying both the new model and EULAG to complex benchmarks and research problems combining wave dynamics and turbulence generation on scales relevant to weather, climate and extreme events. To the best of our knowledge, the proposal offers the first ever in-depth study of the relative performance of structured and unstructured/adapted meshes for stratified turbulent flows which involve practical computations of inertia-gravity-wave dynamics. Deliverables: 1) Novel technology --- a high-resolution non-hydrostatic unstructured mesh based model. 2) Method validation and first ever demonstrations of unstructured meshes on advanced test cases, which will deliver information about the applicability of such meshes to realistic atmospheric problems. 3) Quantitative study identifying performance properties of the mesh adaptivity technologies.

The grounding line of the Antarctic Ice Sheet is the point at which ice leaves the continent and enters the ocean and contributes to sea level. It is where the ocean has its greatest influence on inland flow through bottom melting of floating ice shelves. It is, in fact, a zone (the Grounding Zone) where tidal motion, basal melting and ice dynamics are all key controls on its structure. The GZ is a dynamic feature of the ice sheet and changes in its location and structure may indicate the development of an instability in ice flow or a change in ice motion that will impact sea level and the future evolution of the ice sheet. Identifying and monitoring the evolution of the GZ is important, therefore, for providing i) an early warning of changes in state of the inland ice, ii) as an input into numerical models of ice sheet flow and iii) for measuring the flux of ice leaving the ice sheet. The ice thickness at the grounding line is an essential variable for determining the flux of ice leaving the ice sheet based on observations of ice velocity. To date, there has been no satisfactory way to investigate the evolution of the GZ for the whole of Antarctica. The aim of this project is to achieve this goal using a novel approach applied to CryoSat 2 data. This satellite was launched in 2010 and has a unique instrument on board called the SIRAL, which provides, for the first time, the ability to resolve at high temporal and spatial resolution the detailed structure of the GZ. Proof of concept analyses indicate its huge potential for this but work is required to i) improve and verify the accuracy of the CryoSat 2 data and ii) fully develop the methods for studying the GZ. Once this is achieved, we intend to monitor the evolution of the GZ over at least a seven year period and hopefully extending this further into the future using the same methods. In the process, we will also address an outstanding issue related to the accuracy of the ice thickness estimates derived from surface elevation in the GZ and greatly improve the accuracy of ice thickness estimates over the freely floating shelves that fringe almost the entire coastline of Antarctica.

The motivation for this project is that aerosols have persistently been assessed by the IPCC as the largest uncertainty in the radiative forcing of climate over the industrial period. This means that our ability to understand temperature changes over the industrial period is hampered by very poorly constrained aerosol processes in models. The main uncertainty is due to the effect that aerosols have on clouds - the so-called aerosol indirect effect by which anthropogenic aerosols make clouds more reflective. In the IPCC assessment, the range of predictions of the aerosol indirect forcing lies between -0.4 to -1.8 Wm-2, a far larger range than associated with CO2 forcing (1.6-1.9 Wm-2). Thus, to improve our understanding of climate change, we need to reduce the uncertainty in the aerosol indirect effect. The controlling factor in the indirect effect is the concentration in the atmosphere of "cloud condensation nuclei" (CCN). CCN are a subset of the aerosol particles in the atmosphere, typically larger than 50 nm diameter and sufficiently water soluble to form cloud drops. Only recently, global models have been developed that are able to explicitly simulate CCN concentrations. This opens up the possibility of reducing model uncertainty by exploiting extensive measurements of CCN that have been made over many years. We propose to undertake the first ever comprehensive synthesis of global CCN and related aerosol observations within the UK aerosol-chemistry-climate model. The overall aim is to reduce uncertainty in the indirect effect by constraining modern aerosol as much as possible based on present observing systems and models. We will reduce the uncertainty by producing a global model of CCN with well defined uncertainties that are constrained by worldwide observations. We will then use the "calibrated" aerosol model to quantify the indirect radiative forcing and its uncertainty. We will also use the new and better model to understand the sources of CCN in different environments, and thereby the factors that will drive future changes in the concentration. As a spin-off of the project we will also be able to use the model and data to identify the regions or environments in which new measurements would have the greatest impact on reducing the uncertainty further. An important new aspect of the project will be the use of new uncertainty information about the global model. In most similar studies it has been possible to run the model only a few times. However, in reality the model has a wide uncertainty range due to the very large number of uncertain processes in the model. In this project we will use new information that tells us how the model behaves under all possible assumptions of uncertainty. From this collection of model runs we will be able to identify the best possible model in all parts of the world. This procedure is known as "calibration", and it has not been attempted before for a complex global model. With this approach we can be sure the model is as close to observations of CCN as can presently be achieved.