DPhil (PhD) Projects in Climate Physics 2020

If you are interested in any of the following research areas, we encourage you to contact the relevant supervisor directly. They will be happy to have a dialogue with you.

See also the DTP's Physical Climate System page for key areas covered by this stream. Click here for details of other DTP CASE studentships.

Project examples:

The following projects are posted to give overseas candidates an idea of possible options. (Home/EU candidates who we ask to apply through the DTP will be encouraged to propose their own projects in liaison with supervisors during their first term in Oxford.)

Revisiting atmospheric timescales

Supervisor: Tim Woollings (AOPP)

Weather patterns are generally unpredictable beyond a week or so due to the chaotic nature of the atmospheric fluid dynamics. This is the well-known butterfly effect. However, this is an average picture; some events are clearly more predictable and others less so.

This project will revisit the issue of predictability and timescales in the atmosphere using long modern datasets. New methods will be developed to characterise the memory of the atmosphere and these will be used to determine not only the average predictability but also the range of behaviour.

We rely on complex numerical models for predictions of the weather and climate next week, next summer and the next century. A key aim of this project is to assess the memory timescales in current models when compared to observations. Are models under- or over-confident and how much should we trust their projections of future change?

This project requires a strong first degree in either Physics, Mathematics, Engineering, or Earth Science, with a particular emphasis on skills in mathematical methods or computational modelling.

Using Trace Gas Measurements to Infer Aerosol Type

Supervisors: Don Grainger (AOPP), Anu Dudhia (AOPP)

Scientific Background
The effect of atmospheric aerosols is the most poorly quantified element of the Earth's radiative budget (see Figure 1). Aerosols act directly by reflecting or absorbing solar radiation, or indirectly by altering cloud properties. This project focuses on understanding the direct effect of aerosols. Ground and aircraft based instruments can be used to measure aerosol properties locally whereas satellite measurements provide a global perspective. Progress has been made in using satellite instruments to quantify aerosol optical depth and particle size (using, for example, NASA's Moderate Resolution Imaging Spectrometer, MODIS, or ESA's Advanced Along Track Scanning Radiometer, ATSR) but much uncertainty remains in the type of aerosol being observed. Understanding the type of aerosol is critical as measurements from a thin layer of highly reflective aerosol can be indistinguishable from a thicker layer of strongly absorbing aerosol. Without knowledge of aerosol type it is not possible to tell if solar radiation has been reflected harmlessly back to space or absorbed into the atmosphere, further heating the Earth-atmosphere system.

The aim of this project is to quantify aerosol absorption (as opposed to scattering) over an annual cycle, globally.

The Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm is open source software developed by EODG in conjunction with scientists at the Rutherford Appleton Laboratory. The code is used to infer aerosol (and cloud) properties from radiometer imagers such as MODIS, the Sea and Land Surface Temperature Radiometer (SLSTR) and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). Currently ORAC uses a combination of spectral signature augmented by geographic location to select a most probable aerosol type. This is not always successful. In this project additional measurements of aerosol-forming gases will be used to construct a prior probability of aerosol type. This will be used within ORAC to create a best guess of aerosol type.
The Infrared Atmospheric Sounding Interferometer (IASI) is a nadir-viewing Fourier transform spectrometer carried on the MetOp series of satellites (October 2006 - ~2030). Work within EODG has shown IASI can provide information on gases that form aerosol (e.g. SO2 or NH3) or gases associated with industrial pollution or biomass burning (e.g. CO or HCN). The goal of this project is to use the IASI gas measurements to improve ORAC's prediction of aerosol type. For example an enhanced value in the linear flag of SO2 will be used to increase the likelihood of the ORAC algorithm selecting sulphate aerosol. Much of the work will involve optimising the choice of aerosol given the values of the gas measurements. Once the method is finalised the algorithm will be applied to at least a year of data and the results analysed to give a measure of absorbing versus non-absorbing aerosol. If time permits further investigations could include fire emission indices, aerosol-formation mass budgets or aerosol composition climatologies.

Skills that would be helpful: Computing, atmospheric radiative transfer, remote sensing, chemistry.

Full details can be found here.

Observing the Origins of Tropical Cyclones

Supervisors: Anu Dudhia (AOPP); Tony McNally (ECWMF, Reading)

Scientific Motivation
Tropical cyclones are potentially devastating weather systems for which accurate early warning is critical. However, their origins and behaviour often depend on rather small scale atmospheric structures which are not well-resolved in global numerical weather prediction models. The aim of this project is to explore if key features signalling the genesis, or sudden intensification, of tropical cyclones can be observed in infrared spectra from a 12km footprint measured by the IASI instrument on the MetOp satellites. Such features include warm Sea Surface Temperatures (SSTs), high levels of mid-tropospheric humidity (fuel) and cloud top temperatures. The work would combine the IASI expertise in AOPP with the forecast modelling and data assimilation at ECMWF.

The conclusions from this project will be relevant for improving the use of data from current satellite instruments in operational tropical cyclone prediction. In addition this study will help pave the way for the successful exploitation of future satellite instruments. The next generation geostationary Meteosat sounders (2023 onwards) will observe the genesis of Atlantic tropical cyclones with high temporal resolution (up to every 15 minutes) and IASI-NG instruments (2021 onwards) will provide enhanced information about the vertical structure of these storms.

Relevant Skills: Computing, atmospheric radiative transfer and thermodynamics.

Full details can be found here.

Satellite Remote Sensing of Volcanic Plumes

Supervisors: Don Grainger (AOPP), Isabelle Taylor (AOPP), Tamsin Mather (Earth Sciences)

Plumes of ash and gas are one of the far-reaching hazards associated with volcanic eruptions. Monitoring them helps to mitigate their effects, understand the impacts they have on the environment and climate, and interpret volcanic activity. Satellite remote sensing offers a cost-effective solution to some of the limitations of ground-based monitoring and can be used to study the propagation of these plumes as they move across the globe and interact with different weather systems. The IASI instrument is an infrared hyperspectral sensor on-board three of EUMETSAT’s meteorological satellites, with each obtaining global coverage twice a day. IASI can be used to obtain the mass and height of both ash and SO2 and previous studies have demonstrated its capability for studying the plumes from large explosive eruptions and also continuous degassing.

To explore some of the ways in which the IASI instruments (and future generations of this instrument) can be used to study volcanic plumes of ash and gas.

This project will build on the previous research in Oxford using IASI to study volcanic plumes. The focus of the PhD can be tailored to the student’s strengths and interests. A student from a physics or more technical background may wish to work on the further development of retrievals for IASI or other hyperspectral satellites; while a student with an Earth Sciences or Geography background may wish to explore how this data may be used to understand volcanic activity. Students may be interested to explore the impacts of these plumes on atmospheric dynamics. Opportunities may arise during the PhD to study recent eruptions.

Skills that would be helpful: Programming (IDL, python), experience with remote sensing, experienced with multi-disciplinary work.

Retrieval of aerosol from single-view imagery

Supervisors: Don Grainger (AOPP), Adam Povey (AOPP)

Scientific Background
Atmospheric aerosols and cloud influence the climate by scattering and absorbing light. The most recent IPCC report labelled these interactions the most uncertain aspect of our understanding of the Earth's radiation budget. An accurate and long-term record of aerosol properties is essential to understanding the mechanics of our atmosphere, monitoring the effects of wildfires, and adapting to the growing problem of air pollution. As part of a European Space Agency project, researchers at Oxford helped produce a 30+ year record of cloud properties from satellite observations. A successful DPhil candidate will join that team and devise a means to extend our aerosol record to cover the same period. The method could be adapted to the next generation of geostationary imagery, providing near-real-time observations of aerosol and cloud of unrivaled detail and duration.

This project aims to produce an accurate retrieval of aerosol properties from single-view satellite imagery.

The Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm is open-source implementation of optimal estimation retrieval developed by EODG in conjunction with scientists at the Rutherford Appleton Laboratory. The code is used to infer aerosol (and cloud) properties from radiometer imagers, such as MODIS, the Sea and Land Surface Temperature Radiometer (SLSTR) and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). Currently, ORAC requires two views of the atmosphere to produce an aerosol retrieval. This limits us to observations since 1995 despite acceptable satellite records beginning in 1978. This also excludes observations from the SEVIRI geostationary imagers, which provide planetary-scale imagery every 15-minutes. Aerosol retrievals at such resolution are necessary to evaluate some of the most uncertain processes.
This project will determine the best means to produce aerosol retrievals from single-view imagery. This is expected to involve constraining the surface reflectance, through some combination of theoretical modelling and independent observations. Various single-view aerosol retrievals exist, such as NASA's Deep Blue, that are expected to provide a starting point.
Depending on the student's interest, there is scope to manage and operate remote sensing instruments in Oxford to generate data that can be compared to the new retrievals for validation. Products can also be intercompared to trace gas and volcanic products generated within the group.

Skills that would be helpful: Computing, statistics, atmospheric radiative transfer, remote sensing (especially of the surface).

Full details can be found here.

Satellite Observations of Air Quality

Supervisors: Anu Dudhia (AOPP); Brian Kerridge (Remote Sensing Group, RAL Space)

Ammonia (NH3) and carbon monoxide (CO) are important atmospheric pollutants, contributing to the production of ozone and particulates, which are important to air quality and also to climate change. Ammonia is generated from agricultural processes and carbon monoxide from fossil fuel combustion, but both are also products of biomass burning.
Concentrations of these (and many other molecules) can be retrieved from their infrared signatures in the spectra taken by the current generation of polar-orbiting interferometers, such as the IASI instrument on the MetOp satellites.

Aims of the Project
Both RAL (CO) and Oxford (NH3) have developed retrieval algorithms for IASI and the first part of the project will be to compare these results with other sources, eg other IASI retrievals, other satellite instruments, models, and surface measurements.

The second part of the project involves the adaptation of these algorithms for two new satellite instruments:
IASI-NG, the next generation IASI instruments, the first of which will be launched in 2021 and should provide data in the time-frame of the DPhil. This will have improved spectral resolution, allowing more species to be retrieved and with greater accuracy.

MTG-S, the third generation of the Meteosat geostationary satellite which will carry an interferometer viewing the entire earth's disk every hour. The first of these is due for launch in 2023. Unlike the IASI instruments which are on polar-orbiters and hence view each location only every 12 hours, the MTG-S will allow the full diurnal cycle to be observed.

Relevant Skills: Ability to write computer code in Fortran, C, IDL or Python, basic knowledge of radiative transfer and inverse methods.

Full details can be found here.

Studying weather and climate predictability with crowd computing

Supervisors: Tim Palmer (AOPP); Antje Weisheimer (AOPP); and Peter Dueben (ECMWF)

In this project we will use the newly developed infrastructure of openIFS@home to enable tens of thousands of simulations on private computers to improve our understanding of the predictability of weather and climate. OpenIFS is based on the weather forecast model of the world-leading numerical weather prediction producing centre ECMWF (European Centre for Medium-rRange Weather Forecasts, based in Reading, UK). The project seeks to probe the chaotic phase space of weather and climate models and to improve the efficiency of weather and climate simulations. If successful, this project has the potential to make weather and climate simulations more affordable in terms of running costs and provide a better representation of uncertainties in weather forecasts. This will help to improve predictions of weather and climate models in the future.

Required skills: Good mathematical knowledge and basic programming skills

Eddy-mean flow interactions in the ocean over sloping bottom topography

Supervisors: David Marshall (AOPP)

The ocean is populated by a vigorous mesoscale eddy field on scales of 10-100 km which is either unresolved or only partially resolved by state-of-the-art ocean climate models. Recently, we have developed a new parameterisation of mesoscale eddies – “GEOMETRIC” – based on the fundamental conservation laws of momentum and energy. We have shown that GEOMETRIC leads to many enhancements in our ability to represent the physics of unresolved mesoscale eddies in coarse-resolution ocean climate models, and physical understanding of previously unexplained phenomena. However, a key outstanding issue is how to represent interactions between eddies and the mean flow in the presence of sloping bottom topography. This problem is important because current eddy parameterisations drive the ocean towards a resting state whereas eddies are known to drive rectified mean currents along the topographic contours – sometimes described as an “entropic force”. The fundamental idea underpinning this project is that eddies mix potential vorticity, a dynamical tracer that is concserved by fluid parcels in the absence of forcing and dissipation, along density surfaces, subject to the constraints of energy and momentum conservation. The GEOMETRIC framework is the ideal tool with which to tackle this problem with the conservation laws of momentum and energy built in from the outset. The project is likely to involve a combination of theoretical work and numerical modelling.

This is a blue skies project that will suit a student with an interest in fluid dynamics, numerical modelling and with strong physical/mathematical skills.

Idealized models of polar climate in warm and cold climates

Supervisor: Raymond Pierrehumbert (AOPP)

Recent research has shown that polar climate is strongly influenced by incursions of outbreaks of warm, moist air from lower latitudes. In cold climates this process affects the growth and decay of sea ice, and in warm climates such as the Eocene this determines the ability of polar continents (e.g. Antarctica) to avoid hard freezes in the winter. This project will explore idealized models of the response of polar climates to stochastic intrusions, with a particular eye to understanding the seasonal cycle, the extent of fluctuations about it, the influence of clouds and the way the seasonal cycle is affected by precessional variations in insolation.

This project requires a thorough understanding of fundamental physics, including thermodynamics, mechanics and electromagnetic radiation, as well as a facility with analysis of mathematical models. Familiarity with physical chemistry is also desirable. Hence, a first degree in Physics, Mathematics or a related discipline is required. The project involves considerable use of computational techniques, so basic familiarity with numerical analysis and familiarity with programming techniques in some computer language is required. The main programming languages used are Python and Fortran, but prior experience with these specific languages, while desirable, is not required.

Nonlinearity, climate sensitivity and bifurcations in the climate system

Supervisor: Raymond Pierrehumbert (AOPP)

Much current analysis of the problem of climate sensitivity is based on linearization of the Earth's energy balance about its pre-industrial state. However, our work has shown that the high-sensitivity "fat tail" of the distribution, which poses the greatest risk, is generically indicative of the climate system being near a bifurcation or tipping point. Analyses of climate sensitivity that ignore the presence of a nearby bifurcation risk missing important features of climate change. We are working on a variety of means to detect and explore tipping points in multiphysics model ensembles. We are also examining idealized mathematical models which have a dense set of bifurcations, so that climate is nowhere differentiable with regard to its parameters. Why is such exotic behavior not seen in general circulation models? Or is it just that we haven't looked hard enough?

What ended the boring billion?

Supervisor: Raymond Pierrehumbert (AOPP)

The “boring billion” is the period of Earth history roughly bookended at one end by the Great Oxygenation Event and Makganyene Snowball at the dawn of the Proterozoic, and the Cryogeneian glaciations of the Neoproterozoic (about 700 million years ago) at the other. During this period, there are few major carbon isotope excursions, and there is no evidence of major glaciations. The termination of this period of relative stasis is a key event in Earth history, as it was followed not long afterwards by the first multicellular life (the Ediacarans) and somewhat later the Cambrian Explosion which marks the dawn of the modern world of the Phanerozoic. The question of what terminated the Boring Billion is closely associated with the more specific question of how Snowball Earth events (global glaciations) are initiated, and involves consideration of the physical climate system as well as biogeochemistry. This project involves wide-ranging research aimed at understanding Proterozoic climate evolution, from a standpoint of climate dynamics, atmospheric chemistry and biogeochemistry. General circulation models, as well as a hierarchy of simpler process models, are all employed in the work. A typical DPhil research project in this area would not involve the problem as a whole, but rather some specific aspect such as the effect of ocean/atmosphere dynamics on the greenhouse gas threshold for global glaciation, or the nature of carbon cycle fluctuations that could draw down CO2 while being compatible with the proxy record of carbon isotope excursions.

This project requires a thorough understanding of fundamental physics, including thermodynamics, mechanics and electromagnetic radiation, as well as a facility with analysis of mathematical models. Familiarity with physical chemistry is also desirable. Hence, a first degree in Physics, Mathematics or a related discipline is required. The project involves considerable use of computational techniques, so basic familiarity with numerical analysis and familiarity with programming techniques in some computer language is required. The main programming languages used are Python and Fortran, but prior experience with these specific languages, while desirable, is not required.

Nonlinear dynamics of the Quasi-Biennial Oscillation in laboratory and theoretical models

Supervisor: Peter Read (AOPP)

The Quasi-Biennial Oscillation (QBO) dominates the climate of the tropical stratosphere, influencing the long range transport of momentum, heat and chemical constituents. It is also thought to play an important role in influencing the predictability of various features, such as the Madden-Julian Oscillation (MJO) and other phenomena in the troposphere. So understanding what determines its variability in space and time is important for a range of problems in seasonal climate prediction. Although the basic nonlinear wave-driven mechanisms that drive the QBO are reasonably well understood, its detailed variability is complex, chaotic and much less well understood. The phenomenon is notoriously difficult to capture realistically in global climate models. The likely impact of future global climate change on the QBO is also quite controversial and uncertain.

In this project, we propose to study a number of mechanisms that might influence the behavior of the QBO, using a combination of numerical models and a laboratory analogue of the QBO, in which factors such as the wave forcing and other parameters and feedbacks can be closely controlled and varied. In the laboratory experiment, internal waves are launched into a salt-stratified fluid in an annular channel by oscillating flexible membranes in the bottom of the tank. Each segment of the membrane in the new experiment can be separately controlled by computer (a uniquely novel aspect) to enable varying spectra of internal waves to be excited and for the amplitude of the waves to be varied in time (thereby emulating the seasonal cycle and other modulations). The response of the fluid to this forcing in the form of time varying velocity fields will then be measured by optical particle imaging techniques, while conductivity probes will measure the stratification. The experiments will be complemented by a series of numerical model simulations (a) to achieve direct numerical simulation of some of the laboratory flows themselves for comparison with and validation against experimental measurements, and (b) to explore idealized simulations of QBO-like phenomena in global atmospheric circulation models. The numerical models will make use of Met Office codes such as ENDGAME to maximize opportunities to transfer benefits of this research directly to Met Office researchers.

This is a blue skies project that will suit a student with an interest in fluid dynamics, numerical modelling and with strong physical/mathematical skills. The project will involve collaboration with the Department of Engineering Science on experimental aspects, and with the Met Office on numerical modeling (for which additional funding may be available).

The global impacts of El Niño

Supervisor: Hannah Christensen (AOPP)

One of the largest sources of information on seasonal timescales is the El Niño-Southern Oscillation (ENSO). ENSO consists of an irregular cycle in sea surface temperature in the Tropical Pacific, with associated changes in the atmospheric circulation. During a warm ‘El Niño’ event, SST anomalies in the central and eastern Tropical Pacific reach two to three degrees above average, while during a cold ‘La Niña’ event, SST anomalies reach two to three degrees below average. A strong El Niño or La Niña event substantially increases the likelihood of extreme weather events both near and far. For example, locally it leads to heavy rain and flooding in Peru and drought in Indonesia. Further afield, there is evidence to suggest it affects the intensity of precipitation in the Indian Monsoon, the likelihood of drought in the American mid-west, and even European weather patterns.

Quantifying these so-called ‘teleconnections’, whereby ENSO impacts extreme weather around the globe, is important to understand sources of skill in seasonal forecasts. If we know a strong El Niño is on the way, we would like to quantify the resultant chance of severe flood or drought events, months in advance. But it is difficult to quantify these changes in probability of extreme events due to the short observational record.

In this project, we will produce simulations using world-leading climate models to quantify the impact that ENSO has on extreme weather around the globe. This will provide an important source of information on seasonal timescales, enabling industry, policy makers, and the humanitarian sector to quantify the risks of natural hazards, and act accordingly.

Required skills: Good mathematical knowledge and basic programming skills