Predictability of weather and climate

Abstract:

A new 46-year hindcast dataset for seasonal-to-annual ensemble predictions has been created using a multi-model ensemble of 5 state-of-the-art coupled atmosphere-ocean circulation models. The multi-model outperforms any of the single-models in forecasting tropical Pacific SSTs because of reduced RMS errors and enhanced ensemble dispersion at all lead-times. Systematic errors are considerably reduced over the previous generation (DEMETER). Probabilistic skill scores show higher skill for the new multi-model ensemble than for DEMETER in the 4-6 month forecast range. However, substantially improved models would be required to achieve strongly statistical significant skill increases. The combination of ENSEMBLES and DEMETER into a grand multi-model ensemble does not improve the forecast skill further. Annual-range hindcasts show anomaly correlation skill of ∼0.5 up to 14 months ahead. A wide range of output from the multi-model simulations is becoming publicly available and the international community is invited to explore the full scientific potential of these data. Copyright 2009 by the American Geophysical Union.

Abstract:

Observed since the 1950's, the seasonal effect on underground muons is a well studied phenomenon. The interaction height of incident cosmic rays changes as the temperature of the atmosphere changes, which affects the production height of mesons (mostly pions and kaons). The decay of these mesons produces muons that can be detected underground. The production of muons is dominated by pion decay, and previous work did not include the effect of kaons. In this work, the methods of Barrett and MACRO are extended to include the effect of kaons. These efforts give rise to a new method to measure the atmospheric K/$\pi$ ratio at energies beyond the reach of current fixed target experiments. These methods were applied to data from the MINOS far detector. A method is developed for making these measurements at other underground detectors, including OPERA, Super-K, IceCube, Baksan and the MINOS near detector.

Abstract:

There is a growing interest in using stochastic parametrizations in numerical weather and climate prediction models. Previously, Palmer (2001) outlined the issues that give rise to the need for a stochastic parametrization and the forms such a parametrization could take. In this article a method is presented that uses a comparison between a standard-resolution version and a high-resolution version of the same model to gain information relevant for a stochastic parametrization in that model. A correction term that could be used in a stochastic parametrization is derived from the thermodynamic equations of both models. The origin of the components of this term is discussed. It is found that the component related to unresolved wave-wave interactions is important and can act to compensate for large parametrized tendencies. The correction term is not proportional to the parametrized tendency. Finally, it is explained how the correction term could be used to give information about the shape of the random distribution to be used in a stochastic parametrization. © 2009 Royal Meteorological Society.