Gianluca Meneghello

Observations of Seasonal Upwelling and Downwelling in the Beaufort Sea Mediated by Sea Ice

AbstractWe present observational estimates of Ekman pumping in the Beaufort Gyre region. Averaged over the Canada Basin, the results show a 2003–14 average of 2.3 m yr−1 downward with strong seasonal and interannual variability superimposed: monthly and yearly means range from 30 m yr−1 downward to 10 m yr−1 upward. A clear, seasonal cycle is evident with intense downwelling in autumn and upwelling during the winter months, despite the wind forcing being downwelling favorable year-round. Wintertime upwelling is associated with friction between the large-scale Beaufort Gyre ocean circulation and the surface ice pack and contrasts with previous estimates of yearlong downwelling; as a consequence, the yearly cumulative Ekman pumping over the gyre is significantly reduced. The spatial distribution of Ekman pumping is also modified, with the Beaufort Gyre region showing alternating, moderate upwelling and downwelling, while a more intense, yearlong downwelling averaging 18 m yr−1 is identified in the northern ...

Observational Inferences of Lateral Eddy Diffusivity in the Halocline of the Beaufort Gyre

Using Ekman pumping rates mediated by sea ice in the Arctic Ocean’s Beaufort Gyre (BG), the magnitude of lateral eddy diffusivities required to balance downward pumping is inferred. In this limit—that of vanishing residual-mean circulation—eddy-induced upwelling exactly balances downward pumping. The implied eddy diffusivity varies spatially and decays with depth, with values of 50–400 m2/s. Eddy diffusivity estimated using mixing length theory applied to BG mooring data exhibits a similar decay with depth and range of values from 100 m2/s to more than 600 m2/s. We conclude that eddy diffusivities in the BG are likely large enough to balance downward Ekman pumping, arresting the deepening of the gyre and suggesting that eddies play a zero-order role in buoyancy and freshwater budgets of the BG.

Delaunay-based optimization in CFD leveraging multivariate adaptive polyharmonic splines (MAPS)

Delaunay-based derivative-free optimization leveraging global surrogates (∆-DOGS) is a recentlydeveloped optimization algorithm designed for nonsmooth functions in a handful of adjustable parameters. The first implementation of the original ∆-DOGS algorithm used polyharmonic splines to develop an inexpensive interpolating “surrogate” of the (expensive) function of interest. The behavior of this surrogate was found to be irregular in cases for which the function of interest turned out to be much more strongly dependent on some of the adjustable parameters than others. This irregularity of the surrogate led to the optimization algorithm requiring many more function evaluations than might have otherwise been necessary. In the present work, a modified interpolation strategy, dubbed multivariate adaptive polyharmonic splines (MAPS), is proposed to mitigate this irregular behavior, thereby accelerating the convergence of ∆-DOGS. The MAPS approach modifies the natural polyharmonic spline (NPS) approach by rescaling the parameters according to their significance in the optimization problem based on the data available at each iteration. This regularization of the NPS approach ultimately reduces the number of function evaluations required by ∆-DOGS to achieve a specified level of convergence in optimization problems characterized by parameters of varying degrees of significance. The importance of this rescaling of the parameters during the interpolation step is problem specific. To quantify its beneficial impact on a practical problem, we compare ∆-DOGS with MAPS to ∆-DOGS with NPS on an application related to hydrofoil shape optimization in seven parameters; results indicate a notable acceleration of convergence leveraging the MAPS approach.

A probabilistic framework for the control of systems with discrete states and stochastic excitation

Abstract A probabilistic framework is proposed for the optimization of efficient switched control strategies for physical systems dominated by stochastic excitation. In this framework, the equation for the state trajectory is replaced with an equivalent equation for its probability distribution function in the constrained optimization setting. This allows for a large class of control rules to be considered, including hysteresis and a mix of continuous and discrete random variables. The problem of steering atmospheric balloons within a stratified flowfield is a motivating application; the same approach can be extended to a variety of mixed-variable stochastic systems and to new classes of control rules.

A coordinated balloon observation system for sustained in-situ measurements of hurricanes

In this paper, a low-cost balloon observation system is proposed for sustained (week-long), broadly distributed, in-situ measurements of hurricane development. The high-quality, high-density (in both space and time) measurements to be made available by such a system should be instrumental in significantly improving our ability to forecast such extreme and dangerous atmospheric events. The present paper focuses specifically on developing the overall requirements and specifications of the balloons making up such a system, including a rough budget of the mass, energy, and cost of the key components of each balloon. A brief review of the specific balloon technology and control strategies to be used in the system is also included; both of these topics are discussed much further in our companion publications included in the references.