The problem: The Earth's climate system contains many oscillating phenomena, usually called "modes of variability". Examples of these are the North Atlantic Oscillation (NAO), which influences day-to-day weather in Europe, or the Madden-Julian Oscillation (MJO; Zhang, 2005), which modulates tropical weather systems over timescales of a few weeks  (Matthews et al., 2004), to the El Niño-Southern Oscillation (ENSO), which can affect climate globally over months to years.

The conventional way of defining oscillating modes and their impacts is in terms of anomalies or perturbations from a climatological average. In this framework a single cycle has a positive phase and a negative phase, rather like a sine wave, so by definition, an average over one (or many) cycle(s) is zero, implying that these modes do not alter the long-term average climate. However, in a more complete framework, non-linear interactions can cause even oscillating modes to have an effect on climate when averaged in time; these oscillatory modes can then become integral to defining the mean climate.

The research: This project will address potentially important non-linear contributions of oscillatory modes to the mean climate. The analysis will be carried out using global observational data sets of the atmosphere-ocean system and by designing and running numerical experiments with a global climate model. A framework will be developed to objectively quantify the impact that individual modes such as El Niño have on the mean climate system. This framework will then be used to attribute errors in mean climate simulation to errors in simulating specific weather/climate modes or phenomena such as El Niño (Bell et al., 2009) or the MJO.  For example, the framework will allow us to make statements such as "If there was no MJO, the jet stream over the North Pacific would be XXX m s-1 weaker, with YYY consequences for weather over North America and Europe" (where XXX and YYY are not "zero"!), or "The error in simulating El Niño in the climate model led to an error in the mean climate such that the mean temperature over AAA was BBB ºC colder."  Such statements can then be used to guide improvements of climate model formulation

Requirements, training and opportunities: We seek an enthusiastic, pro-active student with strong scientific interests and self-motivation. They will have at least a 2.1 honours degree in physics, mathematics, meteorology or oceanography or another branch of environmental science with good numerical ability.  Experience of a programming language such as python, FORTRAN or matlab will be advantageous.  They will be trained in meteorological, oceanographical and climate theory, and in the theoretical and practical aspects of computer modelling.  The student will have the opportunity to present their work at an international conference. 

Bell CJ, Gray LJ, Charlton-Perez AJ, Joshi MM, Scaife AA, 2009: Stratospheric communication of El Nino teleconnections to European winter. J. Climate, 22, 4083-4096.

Forster PMde~F, Blackburn M, Glover R, Shine KP, 2000: An examination of climate sensitivity for idealised climate change experiments in an intermediate general circulation model. Climate Dyn., 16, 833-849.

Matthews AJ, Hoskins BJ, Masutani M, 2004: The global response to tropical heating in the Madden-Julian Oscillation during northern winter. Quart. J. Roy. Meteorol. Soc., 130, 1991-2011.

Zhang C, 2005: Madden-Julian Oscillation. Rev. Geophys., 43, RG2003, doi: 10.1029/2004RG000158.