What Makes an Annular Mode “Annular”?

Annular patterns with a high degree of zonal symmetry play a prominent role in the natural variability of the atmospheric circulation and its response to external forcing. But despite their apparent importance for understanding climate variability, the processes that give rise to their marked zonally symmetric components remain largely unclear. Here the authors use simple stochastic models in conjunction with an atmospheric model and observational analyses to explore the conditions under which annular patterns arise from empirical orthogonal function (EOF) analysis of the flow. The results indicate that annular patterns arise not only from zonally coherent fluctuations in the circulation (i.e., “dynamical annularity”) but also from zonally symmetric statistics of the circulation in the absence of zonally coherent fluctuations (i.e., “statistical annularity”). It is argued that the distinction between dynamical and statistical annular patterns derived from EOF analysis can be inferred from the associated variance spectrum: larger differences in the variance explained by an annular EOF and successive EOFs generally indicate underlying dynamical annularity. The authors provide a simple recipe for assessing the conditions that give rise to annular EOFs of the circulation. When applied to numerical models, the recipe indicates dynamical annularity in parameter regimes with strong feedbacks between eddies and the mean flow. When applied to observations, the recipe indicates that annular EOFs generally derive from statistical annularity of the flow in the midlatitude troposphere but from dynamical annularity in both the stratosphere and the mid–high-latitude Southern Hemisphere troposphere.

Delay-Optimal Scheduling for Two-Hop Relay Networks with Randomly Varying Connectivity: Join the Shortest Queue-Longest Connected Queue Policy

We consider a scheduling problem for a two-hop queueing network where the queues have randomly varying connectivity. Customers arrive at the source queue and are later routed to multiple relay queues. A relay queue can be served only if it is in connected state, and the state changes randomly over time. The source queue and relay queues are served in a time-sharing manner; that is, only one customer can be served at any instant. We propose Join the Shortest Queue-Longest Connected Queue (JSQ-LCQ) policy as follows: (1) if there exist nonempty relay queues in connected state, serve the longest queue among them; (2) if there are no relay queues to serve, route a customer from the source queue to the shortest relay queue. For symmetric systems in which the connectivity has symmetric statistics across the relay queues, we show that JSQ-LCQ is strongly optimal, that is, minimizes the delay in the stochastic ordering sense. We use stochastic coupling and show that the systems under coupling exist in two distinct phases, due to dynamic interactions among source and relay queues. By careful construction of coupling in both phases, we establish the stochastic dominance in delay between JSQ-LCQ and any arbitrary policy.

Bounds on moments of symmetric statistics

In this paper we prove analogues of Khintchine, Marcinkiewicz-Zygmund and Rosenthal moment inequalities for symmetric statistics of arbitrary order in not identically distributed random variables. We also construct an example that shows the significance of each term in the obtained Rosenthal-type inequalities for symmetric statistics and obtain results concerning the rate of growth of the best constants in the inequalities.