Tim Palmer

Abstract:

Stochastic parametrization provides a methodology for representing model uncertainty in ensemble forecasts. Here we study the impact of three existing stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean where ensemble spread is increased. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.

Abstract:

Given their increasing relevance for society, I suggest that the climate science community itself does not treat the development of error-free ab initio models of the climate system with sufficient urgency. With increasing levels of difficulty, I discuss a number of proposals for speeding up such development. Firstly, I believe that climate science should make better use of the pool of post-PhD talent in mathematics and physics, for developing next-generation climate models. Secondly, I believe there is more scope for the development of modelling systems which link weather and climate prediction more seamlessly. Finally, here in Europe, I call for a new European Programme on Extreme Computing and Climate to advance our ability to simulate climate extremes, and understand the drivers of such extremes. A key goal for such a programme is the development of a 1 km global climate system model to run on the first exascale supercomputers in the early 2020s.

Abstract:

In the 2013/14 winter, the eastern USA was exceptionally cold, the Bering Strait region was exceptionally warm, California was in the midst of drought and the UK suffered severe flooding. It has been suggested that elevated SSTs in the tropical West Pacific (TWPAC) were partly to blame due to their producing a Rossby wavetrain that propagated into the extratropics. We find that seasonal forecasts with the tropical atmosphere relaxed towards a reanalysis give 2013/14 winter-mean anomalies with strong similarities to those observed in the Northern Hemisphere, indicating that low-latitude anomalies had a role in the development of the extremes. Relaxing just the TWPAC produces a strong wavetrain over the North Pacific and North America in January, but not in the winter-mean. This suggests that anomalies in this region alone had a large influence, but cannot explain the extremes through the whole winter. We also examine the response to applying the observed TWPAC SST anomalies in two atmospheric general circulation models. We find that this does produce winter-mean anomalies in the North Pacific and North America resembling those observed, but that the tropical forcing of Rossby waves due to the applied SST anomalies appears stronger than that in reanalysis, except in January. Therefore both experiments indicate that the TWPAC influence was important, but the true strength of the TWPAC influence is uncertain. None of the experiments indicate a strong systematic impact of the TWPAC anomalies on Europe.