Ozone in the stratosphere protects life on Earth from harmful ultraviolet radiation. In the troposphere, however, it is a harmful pollutant, increasing the incidence of lung disease and decreasing the productivity of crops. Human activities do not emit much ozone directly. However, they do emit many molecules which participate in chemical reactions which form ozone. So, before we can control the levels of ozone, we need to understand where these other molecules come from and how they cause ozone to form. A major source of ozone precursor molecules is the burning of biomass: this also contributes to poor air quality in other ways. Pollution from biomass burning spreads around the globe, affecting areas at great distances from its sources. The chemistry of the troposphere is complex, requiring detailed computer models in order to simulate its behaviour. Because some of the ozone in the troposphere comes from the stratosphere, it is advantageous to use a single model that simulates both regions and the transport of air between them. The TOMCAT/SLIMCAT three-diemnsional model is a state-of-the-art model of this type. Satellites have made global measurements of trace chemicals in the stratosphere for several decades. To do the same for the troposphere is much more difficult. Aura is a satellite, launched in July 2004, which carries out this mission. Four instruments fly on Aura of which three make measurements of tropospheric chemistry. These three instruments operate in different ways and have very different strengths and weaknesses. The purpose of this proposal is to gain an improved understanding of the processes that produce tropospheric ozone. To achieve this, we will combine data from Aura with the TOMCAT/SLIMCAT model. It will first be necessary to assess the degree to which the model agrees with the measurements. In order for this comparison to be made, it is necessary to extract data from the model at the same times and places and in the same manner as the measurements are made. With this assessment done, we then intend to work backwards from the measurements, in order to estimate how much of various pollutant molecules are being emitted and hence how much biomass is being burned. We will also estimate how much of the ozone in the troposphere comes from the stratosphere.

There is a pressing need to quantify the exchange of mass between the world's oceans and polar ice caps, and this can only be achieved by measuring how their volumes are changing. Currently circa 50% of the observed sea level rise of 1.8 mm yr-1 cannot be explained. The required measurements can only be made effectively from space using satellites, and several missions are either in space now, or are about to be deployed to attack this problem. In simple terms the sea and ice topography, and how it changes, can be inferred by measuring ranges from the satellites to the surface, and then subtracting the ranges from the position of the satellites in a geocentric reference frame. The satellite position is calculated by the process of orbit determination, which requires mathematical modelling of the forces acting on the satellites. Errors in the satellite orbit map directly into errors in the inferred topography. Both the orbit determination process and the modelling of the time evolution of the sea and ice changes rely upon a 'reference frame' - put simply this is a list of coordinates and velocities of the tracking stations used to observe how the satellites move in space. Velocities are needed because the tracking stations are sited on tectonic plates, all of which are in continuous motion. As these kind of analyses model geophysical effects that last decades this motion of the tracking stations must be known accurately. In turn, the methods used to calculate the station positions (coordinates) and velocities are linked to the orbit determination process - so once again, errors in the orbit estimates create problems. Orbital accuracy in the satellite radial direction of around 1 cm is required to reduce the uncertainty in the target geophysical parameters. We believe this can be achieved by accurate modelling of the satellite forces. The principal problems here are satellite surface forces caused by solar radiation pressure, thermal effects and forces caused by radiation reflected and emitted by the Earth (termed albedo effects), as well as atmospheric drag effects. These forces, particularly the earth radiation effects, have very strong seasonal and latitudinal characteristics which, if not modelled appropriately, appear as seasonal and latitudinal variations in the inferred sea and ice topography. The PI and his group have developed a suite of software utilities to attack these force modelling problems that are recognised as the leading techniques in the world for dealing with complex, realistic models of the spacecraft response to its environment. The group has been invited to participate in several international experiments that involve modelling complexity that has never been attempted before, and this proposal seeks to extend the group's techniques and apply them to current missions to achieve the 1 cm goal. Failure to address this problem of systematic biases in the satellite orbits would seriously undermine any attempt to constrain climate change models on the basis of the estimated mass exchanges.

The substorm is a repeatable earthquake-like disturbance to near-Earth Space, which, apparently unpredictably, recurs after anything from 2 hours to a day or more and dumps typically one thousand million million Joules of energy into the upper atmosphere equivalent to ten Oklahoma tornados or the largest nuclear weapon in the US arsenal. The substorm's intermittency and variable size makes it arguably the greatest source of uncertainty in predicting the state of the upper atmosphere. Its most obvious effect is the aurora, which would be nice to know when its happening so that we could plan our Arctic holidays, but substorm prediction is also important for mitigating the effects of natural changes in the upper atmosphere on geostationary satellite communications and navigation, low-altitude satellite orbits and remote sensing, electricity power grids, and oil and mineral prospecting. Prediction is also the ultimate test for our scientific understanding. Progress requires measuring and analysing substorm variability in order to test and develop models based on maths and physics. We already know the statistics of substorm timing and have explained this with a simple mathematical model (that has also been used for understanding neuron firing in the brain!). However, knowing and understanding the variability of substorm size is much harder because it requires to measure simultaneously over large regions of the polar upper atmosphere and out into Space. In this project, we propose to attempt this by examining lots of substorms over more than a decade using spacecraft together with networks of magnetometers (sophisticated scientific compasses) and radars in both the Arctic and Antarctic. The resulting stats will be compared with what we already know from much more limited observations and with the predictions of new and existing substorm theories and models. The outcomes will be knowing things like how likely a really big substorm is that could mess things up, as well as models to explain why and hopefully when that might occur.

Billions of years ago the young planet Earth was much different from the one we inhabit today, with wildly fluctuating temperatures and an atmosphere filled with toxic gases. Understanding how we got from that inhospitable place to the world of today, dominated by mild climates and large oxygen-based life forms, is a fundamental question in Earth sciences. One important transition occurred approximately 2.5 billion years ago (Ga), called the Great Oxidation Event (GOE), when the oxygen concentrations in Earth's atmosphere first increased from near zero to a fraction of modern levels. A major focus of research in natural science is determining how the Earth system (including life) has acted to produce such monumental changes in the environment; however, exactly how and why the GOE occurred remains a mystery. Integral to understanding the transition to an oxygenated environment on the early Earth are quantitative estimates of the composition of the ancient atmosphere. These estimates are difficult to make using most geochemical tools, which tend to reflect processes that occurred in the marine environment instead. This study proposes to link the four stable isotopes of sulfur, which directly reflect chemical reactions that occurred in the atmosphere, with numerical models tying these geochemical signatures to atmospheric compositions. An additional set of geochemical analyses will allow us to determine the chemistry of the oceans and how the biosphere was acting at the same time. This study is unique in its combination of these multiple techniques, which we will apply to well-preserved sediments deposited directly before the GOE, to determine how the Earth's atmosphere developed during this time, and how the oceans and biosphere both contributed and responded. Understanding the interactions between the atmosphere, oceans, and life is particularly crucial during this time period, as it represents an Earth system poised at the edge of a major transition in global surface chemistry. We have performed a preliminary set of similar analyses on ~2.65-2.5 Ga sediments that paint a tantalizing picture of an unusual Earth environment directly before the GOE. These analyses point to an atmosphere that was not only very low in oxygen, but was also periodically dominated by a layer of organic particles (termed "haze") produced at high methane levels, similar to that seen on Saturn's moon Titan. We will expand upon the hypotheses developed from these preliminary analyses and explore their significance for the development of Earth surface chemistry and the evolution of life during this critical period in Earth history.

A substantial reduction in the amount of solar radiation reaching the Earth's surface, due to the presence of urban aerosol, has been reported for a variety of global locations. In the long-wave, the aerosol impact is more uncertain, however, a number of modeling and measurement studies suggest that the presence of urban aerosol can act to enhance downwelling fluxes to the surface significantly. Even more intriguingly, recent work has indicated that information contained in the spectrum of downwelling long-wave radiation at the surface can be employed to diagnose an aerosol effect on cloud microphysics: an indirect impact which would be expected to substantially modify both short-wave and long-wave cloudy-sky surface fluxes. Here, through ALERT, we propose to simultaneously measure, for the first time, the short-wave and long-wave urban aerosol radiative effect on the urban environment. Through a unique combination of observational and modeling tools, focused on central London, we will examine two principal hypotheses: Hypothesis 1: There is a measurable urban clear-sky long-wave and short-wave direct radiative effect at the surface due to aerosols. Hypothesis 2: There is an indirect aerosol radiative effect on urban short-wave and long-wave surface fluxes due to measurable shifts in cloud effective radius