By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. Computer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients. The aim of this project is to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions. We will gather information on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites have been chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. Using 28 radiometers, and moving them several times during the course of each experiment, will allow us to measure the highly variable patterns of radiation at the snow surface in forests. Information from the field experiments will be used in developing and testing a range of models. To reach the scales of interest, we will begin with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective is a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. We will work in close consultation with project partners at climate modelling and forecasting centres to ensure that our activities are directed towards outcomes that will meet their requirements.

There is a large and convincing body of epidemiological evidence linking short term exposure to outdoor air pollutants to adverse health effects. However, most of this evidence is derived from studies that have linked single pollutants to health in urban environments. There is increasing recognition that greater protection against the adverse health effects of air pollution could be achieved by focusing research and policy not on individual pollutants, but by a multi-pollutant approach. Furthermore, the spatial variation in pollutant concentrations and their health impacts, especially in rural areas and areas outside the larger cities where much of the UK population reside, are not-well established. Socio-economic impacts (and related issues of environmental justice) and other geographically-determined factors, including housing characteristics (indoor pollution), are also potential modifiers of exposure to outdoor air pollution. The increasing complexity of the scientific inquiry is matched by the difficulties of formulating, proving and implementing appropriate regulatory policy. This proposal builds upon an existing collaboration between researchers in the environmental and health disciplines, with the addition of investigators and practitioners from the policy and social science fields. Our proposal aims to provide new epidemiological evidence on the health impacts of exposure to multiple pollutants; to examine the implications of such evidence for regulation and control of air quality; and to assess how uncertainties in evidence affect its translation into actionable evidence-based policies and the evaluation of their costs and benefits. There are several unique innovations in our study: 1) the development of long series of high resolution (5 km) datasets for daily concentrations of a range of pollutants and weather data, linked to geo-referenced health data including daily mortality, hospital admissions and data on heart attacks; 2) an examination of the contribution of the indoor environment as a modifier of exposure to outdoor pollutants to provide an integrated assessment of the risks to health of short term exposure to air pollution; 3) an integrated assessment of the health effects of various near-term future air quality and climate policies in 2030 as well as selected emissions reduction policies for the UK; 4) the development of a 'decision analysis' tool that includes assessment of uncertainties and can be used to infer the likely outcomes of these various policy choices.

We propose a network to stimulate new international collaboration in measuring and understanding the surface temperatures of Earth. This will involve experts specialising in different types of measurement of surface temperature, who do not usually meet. Our motivation is the need for better understanding of in situ measurements and satellite observations to quantify surface temperature as it changes from day to day, month to month. Knowing about surface temperature variations matters because these affect ecosystems and human life, and the interactions of the surface and the atmosphere. Surface temperature (ST) is also the main indicator of "global warming". Knowledge of ST for >150 years has been derived from in situ meteorological and oceanographic measurements. These have been fundamental to weather forecasting, to environmental sciences, and to detection and attribution of climate change. Thermal remote sensing of ST from space has a ~30 year history, including operational exploitation. Observations of high accuracy and stability come from the 20-year record of Along Track Scanning Radiometers (ATSRs) . ATSR-class capability will shortly become operational in the space segment of Global Monitoring for Environment and Security (GMES), and will continue until at least 2030. The best insight into ST variability and change through the 21st century will come from jointly using in situ and multi-platform satellite observations. There is a clear need and appetite to improve the interaction of scientists across the in-situ/satellite 'divide' and across all domains of Earth's surface. This will accelerate progress in improving the quality of individual observations and the mutual exploitation of different observing systems over a range of applications. Now is a critical time to initiate this research network. First, the network will link closely to a major new initiative to improve quantification of ST from surface meteorological stations (surfacetemperatures.org). Second, there are areas of acute need to improve understanding of ST: e.g., across regions of Africa, where in situ measurements are very sparse; and across the Arctic, where the evolving seasonal sea ice extent challenges the current practices for quantifying ST variability and change. Third, it is timely to share experience between remote sensing communities. All these motivations are present against a backdrop where ST is, in relation to climate change, of current public interest & relevance to policy. This network will increase the international impact of UK science. UK investigators are involved across the full scope of the proposed ST network, and have leading international roles in several areas. The network will ensure UK participation at the highest level across all domains of ST research. In this proposal, key world-class organisations overseas have roles in steering and/or hosting network activities. The network will welcome participation of others not contacted in preparation of this proposal. Permission will be sought from the originators of all data used for case studies to make the data set freely available. The network will be organised around three themes over three years: Year 1. In situ and satellite ST observations: challenges across Earth's domains Year 2: Quantifying surface temperature across Arctic Year 3: Joint exploitation of in situ and satellite surface temperatures in key land regions. The first theme is an inclusive question, designed to bring together research communities and develop a full picture of common research needs and aspirations. The second theme is a pressing research question to which the network will co-ordinate a useful and unique contribution. The third theme is one of long-term interest and importance in the strengthening of the observational foundations for climate change monitoring and diagnosis.

Anthropogenic emissions that affect climate are not just confined to greenhouse gases. Sulfur dioxide (SO2) and other pollutants form atmospheric aerosols that scatter and absorb sunlight, and influence the properties of clouds, modulating the Earth-atmosphere energy balance. Anthropogenic emissions of aerosols exert a significant, but poorly quantified, cooling of climate that acts to counterbalance the global warming from anthropogenic emissions of greenhouse gases. Uncertainties in aerosol-climate impacts are dominated by uncertainties in aerosol-cloud interactions (ACI) which operates through aerosols acting as cloud-condensation nuclei (CCN) which increases the cloud droplet number concentration (CDNC) while reducing the size of cloud droplets and subsequently impact rain formation which may change the overall physical properties of clouds. This consequently impacts the uncertainty in climate sensitivity (the climate response per unit climate forcing) because climate models with a strong/weak aerosol cooling effect and a high/low climate sensitivity respectively are both able to represent the historic record of global mean temperatures. On a global mean basis, the most significant anthropogenic aerosol by mass and number is sulphate aerosol resulting from the ~100Tg per year emissions of sulphur dioxide from burning of fossil fuels, but these plumes are emitted quasi-continuously owing to the nature of industrial processes, meaning that there is no simple 'control' state of the climate where sulphur dioxide is not present. On/off perturbation/control observations have, to date, been limited to observations of ship tracks but the spatial scales of such features are far less than the resolution of the weather forecast models or of the climate models that are used in future climate projections. This situation changed dramatically in 2014 with the occurrence of the huge fissure eruption at Holuhraun in 2014-2015 in Iceland, which was the largest effusive degassing event from Iceland since the eruption of Laki in 1783-17849. The eruption at Holuhraun emitted sulphur dioxide at a peak rate of up to 1/3 of global emissions, creating a massive plume of sulphur dioxide and sulphate aerosols across the entire North Atlantic. In effect, Iceland became a significant global/regional pollution source in an otherwise unpolluted environment where clouds should be most susceptible to aerosol emissions. Thus, the eruption at Holuhraun created an excellent analogy for studying the impacts of anthropogenic emissions of sulphur dioxide and the resulting sulphate aerosol on ACI. Our research will comprehensively evaluate impacts of the Holuhraun aerosol plume on clouds, precipitation, the energy balance, and key weather and climate variables. Observational analysis will be extended beyond that of our pilot study to include high quality surface sites. Two different climate models will be used; HadGEM3, which is the most up to date version of the Met Office Unified model and ECHAM6-HAM, developed by MPI Hamburg. These models are chosen because they produce radically different responses in terms of ACI; ECHAM6-HAM produces far stronger ACI impacts overall than HadGEM3. Additionally, the UK Met Office Unified Model framework means that the underlying physics is essentially identical in low-resolution climate models and high-resolution numerical weather predication models, a feature that is unique in weather/climate research. In the high resolution numerical weather prediction version, parameterisations of convection can be turned off and sub-gridscale processes can be explicitly represented. Thus the impacts of choices of parameterisation schemes and discrete values of variables within the schemes may be evaluated. The research promises new insights into ACI and climate sensitivity promising us great strides improving weather and climate models and simulations of the future.

In 2006 scientists from the UK's National Oceanography Centre, Southampton (NOCS) installed additional sensors to measure the rate at which the atmosphere and ocean exchange heat, CO2 and momentum. The behaviour of theses exchanges or 'fluxes' is complicated and is affected by many other processes. For example, the CO2 flux may depend on wind speed, air temperature and humidity, sea temperature, sea state, wave breaking, whitecap coverage, CO2 concentration of the water and CO2 concentration in the atmosphere. All these processes need to be measured as well, so that the behaviour of the flux can be understood. The Polarfront was already equipped with a ship borne wave recorder (SBWR) which makes direct measurements of the wave heights, but this system does not measure the direction of the waves. As part of the NOCS project a wave radar system (WAVEX) was also installed to provide wave direction. The WAVEX does not make direct height measurements, but combining its directional data with the height data from the SBWR gives a very detailed description of the sea state - the Polarfront is the only ship in the world to have both systems. NOCS added digital cameras to the ship's bridge to obtain whitecap fraction and sea spikes in the wave radar data will be used to obtained wave breaking statistics. The fluxes are very difficult to measure directly and such measurements are usually only made from research ships, during short cruises of only a few weeks. To date very few measurements have been made of the CO2 flux and none have been made over the open ocean for winds of more than 15 m/s. In contrast, the NOCS systems on the Polarfront have operated continuously since they were installed in September 2006 and measurements in mean wind speeds of more than 25 m/s have already been made. Obtaining high wind speed data is important because the fluxes increase rapidly with increasing wind speed. The Polarfront was chosen for the project since it is dedicated to meteorological observations, unlike any other ship in the world. It also occupies a location where high wind speeds and therefore large fluxes often occur. To understand the interaction between the various forcing process requires a large data set obtained under as wide a range of conditions as possible. Extending the measurement program from 2 years to 3 years (as originally planned) would significantly increase the data available for analysis and would only increase the cost of the project by 12%.