2006 PSL Seminars
Are there distinct metastable atmospheric regimes despite nearly Gaussian statistics?
In this study we analyze data from three geophysical models in order to objectively identify atmospheric flow regimes despite nearly Gaussian statistics of the planetary waves in these models. We use a hierarchy of models which describe the atmospheric circulation with increasing complexity. To objectively identify atmospheric regimes we utilize Hidden Markov Models (HMM). A Hidden Markov Model is designed to describe the situation in which part of the information of the system is unknown or hidden and another part is observed. Therefore, HMMs are a powerful tool to systematically identify metastable states in phase space despite nearly Gaussian statistics of the planetary waves. These metastable states are identified as atmospheric regimes. The concept of metastability assumes a separation of time scales in the Markov chain.
We first apply the HMM procedure to a 57 mode model of barotropic flow over topography with a large scale mean flow. This model exhibits metastable regime behavior of its large-scale mean flow for sufficiently high topography. In the case of high topography three regime states have been found; two of those correspond to zonal flow and the third to blocking.
Next a three-layer quasi-geostrophic model as a prototype atmospheric General Circulation Model (GCM) is used. Its first Empirical Orthogonal Function (EOF) is similar to the Arctic Oscillation (AO) and exhibits metastability. For this model two regime states are found; one corresponding to the positive phase of the AO with large amplitude and decreased variability of the streamfunction field, whereas, the other regime corresponds to the negative AO phase with small amplitude and increased variability. Finally, we investigate a comprehensive GCM. This model shows no signs of metastable behavior in the subspace of its first 4 EOFs. Our results suggest that the observed small skewness of planetary wave PDFs is an imprint of blocked circulation states.
2:00 PM (Refreshments at 1:50 pm)
PSL-South Conference Room (1D403)