Predictability of weather and climate

Abstract:

In the tropical stratosphere, deep layers of eastward and westward winds encircle the globe and descend regularly from the upper stratosphere to the tropical tropopause. With a complete cycle typically lasting almost 2.5 years, this quasi-biennial oscillation (QBO) is arguably the most predictable mode of atmospheric variability that is not linked to the changing seasons. The QBO affects climate phenomena outside the tropical stratosphere, including ozone transport, the North Atlantic Oscillation and the Madden–Julian Oscillation, and its high predictability could enable better forecasts of these phenomena if models can accurately represent the coupling processes. Climate and forecasting models are increasingly able to simulate stratospheric oscillations resembling the QBO, but exhibit common systematic errors such as weak amplitude in the lowermost tropical stratosphere. Uncertainties about the waves that force the oscillation, particularly the momentum fluxes from small-scale gravity waves excited by deep convection, make its simulation challenging. Improved representation of the processes governing the QBO is expected to lead to better forecasts of the oscillation and its impacts, increased understanding of unusual events such as the two QBO disruptions observed since 2016, and more reliable future projections of QBO behaviour under climate change.

Abstract:

The influence of the quasi-biennial oscillation (QBO) on tropical climate is demonstrated using 500-year pre-industrial control simulations from the Met Office Hadley Centre model. Robust precipitation responses to the phase of the QBO are diagnosed in the model, which show zonally asymmetric patterns that resemble the El Niño–Southern Oscillation (ENSO) impacts. These patterns are found because the frequency of ENSO events for each QBO phase is significantly different in these simulations, with more El Niño events found under the westerly phase of the QBO (QBOW) and more La Niña events for the easterly phase (QBOE). The QBO–ENSO relationship is non-stationary and subject to decadal variability in both models and observations. In addition, regression analysis shows that there is a QBO signal in precipitation that is independent of ENSO. No evidence is found to suggest that these QBO–ENSO relationships are caused by ENSO modulating the QBO in the simulations. A relationship between the QBO and a dipole of precipitation in the Indian Ocean is also found in models and observations in boreal fall, characterised by a wetter western Indian Ocean and drier conditions in the eastern part for QBOW and the opposite under QBOE conditions. The Walker circulation is significantly weaker during QBOW compared to QBOE, which could explain the observed and simulated zonally asymmetric precipitation responses at equatorial latitudes, as well as the more frequent El Niño events during QBOW. Further work, including targeted model experiments, is required to better understand the mechanisms causing these relationships between the QBO and tropical convection.

Abstract:

It has long been suggested that the mid-latitude atmospheric circulation possesses what has come to be known as ‘weather regimes’, loosely categorised as regions of phase space with above-average density and/or extended persistence. Their existence and behaviour has been extensively studied in meteorology and climate science, due to their potential for drastically simplifying the complex and chaotic mid-latitude dynamics. Several well-known, simple non-linear dynamical systems have been used as toy-models of the atmosphere in order to understand and exemplify such regime behaviour. Nevertheless, no agreed-upon and clear-cut definition of a ‘regime’ exists in the literature, and unambiguously detecting their existence in the atmospheric circulation is stymied by the high dimensionality of the system. We argue here for an approach which equates the existence of regimes in a dynamical system with the existence of non-trivial topological structure of the system’s attractor. We show using persistent homology, an algorithmic tool in topological data analysis, that this approach is computationally tractable, practically informative, and identifies the relevant regime structure across a range of examples.