The role of oscillating modes on the climate system
Supervisors: Dr Adrian Matthews and Dr Manoj Joshi.
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 with further impacts on the extratropics (Matthews et
al., 2004), to the El Nino-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
system1 and by designing and running numerical
experiments with a global climate model2. A framework
will be developed to objectively quantify the impact that
individual modes such as El Nino 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 Nino (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 North America 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 Nino in the climate model led to an error in the mean climate
such that the mean temperature over AAA was BBB degrees Celsius
colder.' Such statements can then be used to guide improvements
of climate model formulation.
1ERA-Interim atmospheric reanalysis, ECCO ocean
reanalysis, satellite precipitation and sea surface temperature
data sets, etc.
2Intermediate General Circulation Model (IGCM), a
fast, stripped-down climate model that is well designed for
carrying out numerical experiments (Forster et al., 2000).
Requirements, training and opportunites: 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. This project will
suit an applicant intending to start a scientific career in
meteorology, oceanography or climate science.
Bell CJ, Gray LJ, Charlton-Perez AJ, Joshi MM, Scaife AA,
Stratospheric communication of El Nino teleconnections to European winter.
J. Climate, 22, 4083-4096.
Forster PMde~F, Blackburn M, Glover R, Shine KP,
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,
The global response to tropical heating in the Madden-Julian Oscillation during northern winter.
Quart. J. Roy. Meteorol. Soc., 130, 1991-2011.
Rev. Geophys., 43, RG2003, doi: 10.1029/2004RG000158.
The animation shows the cycle
of the Madden-Julian Oscillation (MJO), with global maps of
cloudiness/rainfall anomalies every day through its 48-day period.
Blue colours correspond to regions where there is more precipitation
than usual, red colours to where it is drier than usual. The way this
particular version of the MJO life cycle has been mathematically
constructed means that if you sum the cloudiness/rainfall anomalies
over the entire MJO cycle, the positive values exactly cancel the
negative values, and the net result is zero. Hence this type of
analysis gives no information on the effect of the MJO on to the mean
climate. Though, of course, it gives very useful information on to
which regions may expect wet or dry conditions over the next few
weeks. The aim of this PhD project is to move beyond 'linear'
representations as shown in this animation, and to look at the
nonlinear interactions that do not cancel out, whereby the MJO (and
other oscillating modes such as the NAO, ENSO etc.) do have an effect
on the mean climate.