We formulate and study a low-order nonlinear coupled ocean-atmosphere model with an emphasis on the impact of radiative and heat fluxes and of the frictional coupling between the two components. This model version extends a previous 24-variable versi
on by adding a dynamical equation for the passive advection of temperature in the ocean, together with an energy balance model. The bifurcation analysis and the numerical integration of the model reveal the presence of low-frequency variability (LFV) concentrated on and near a long-periodic, attracting orbit. This orbit combines atmospheric and oceanic modes, and it arises for large values of the meridional gradient of radiative input and of frictional coupling. Chaotic behavior develops around this orbit as it loses its stability; this behavior is still dominated by the LFV on decadal and multi-decadal time scales that is typical of oceanic processes. Atmospheric diagnostics also reveals the presence of predominant low- and high-pressure zones, as well as of a subtropical jet; these features recall realistic climatological properties of the oceanic atmosphere. Finally, a predictability analysis is performed. Once the decadal-scale periodic orbits develop, the coupled systems short-term instabilities --- as measured by its Lyapunov exponents --- are drastically reduced, indicating the oceans stabilizing role on the atmospheric dynamics. On decadal time scales, the recurrence of the solution in a certain region of the invariant subspace associated with slow modes displays some extended predictability, as reflected by the oscillatory behavior of the error for the atmospheric variables at long lead times.
A Bayesian analysis of the worlds p(gamma,K^+)Lambda data is presented. From the proposed selection of 11 resonances, we find that the following nucleon resonances have the highest probability of contributing to the reaction: S11(1535), S11(1650), F1
5(1680), P13(1720), D13(1900), P13(1900), P11(1900), and F15(2000). We adopt a Regge-plus-resonance framework featuring consistent couplings for nucleon resonances up to spin J=5/2. We evaluate all possible combinations of 11 candidate resonances. The best model is selected from the 2048 model variants by calculating the Bayesian evidence values against the worlds p(gamma,K^+)Lambda data.
We present the results of a Bayesian analysis of a Regge model for K+ Lambda photoproduction. The model is based on the exchange of K+(494) and K*+(892) trajectories in the t-channel. For different prior widths, we find decisive Bayesian evidence (De
lta ln Z ~ 24) for a K+ Lambda photoproduction Regge model with a positive vector coupling and a negative tensor coupling constant for the K+(892) trajectory, and a rotating phase factor for both trajectories. Using the chi^2 minimization method, one could not draw this conclusion from the same dataset.
We present the results of a Bayesian analysis of a Regge model to describe the background contribution for K+ Lambda and K+ Sigma0 photoproduction. The model is based on the exchange of K+(494) and K*+(892) trajectories in the t-channel. We utilise t
he Bayesian evidence Z to determine the best model variant for each channel. The Bayesian evidence integrals were calculated using the Nested Sampling algorithm. For different prior widths, we find decisive Bayesian evidence (Delta ln Z ~ 24) for a K+ Lambda photoproduction Regge model with a positive vector coupling and a negative tensor coupling constant for the K*+(892) trajectory, and a rotating phase factor for both trajectories. Using the chi^2 minimisation method, one could not draw this conclusion from the same dataset. For the K+ Sigma0 photoproduction Regge model, on the other hand, the difference between the evidence integrals is insufficient to pinpoint one model variant.
