Abstract
In a low-order chaotic model of global atmospheric circulation the effects of driving, i.e., time-dependent (periodic, chaotic, and noisy) forcing, are investigated, with particular interest in extremal behavior. An approach based on snapshot attractors formed by a trajectory ensemble is applied to represent the time-dependent likelihood of extreme events in terms of a physical observable. A single trajectory-based framework, on the other hand, is used to determine the maximal value and the kurtosis of the distribution of the same observable. We find the most significant effect of the driving on the magnitude, relative frequency, and variability of extreme events when its characteristic time scale becomes comparable to that of the model climate. Extreme value statistics is pursued by the method of block maxima, and found to follow Weibull distributions. Deterministic drivings result in shape parameters larger in modulus than stochastic drivings, but otherwise strongly dependent on the particular type of driving. The maximal effects of deterministic drivings are found to be more pronounced, both in magnitude and variability of the extremes, than white noise, and the latter has a stronger effect than red noise.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.