Inverse centrifugal effect induced by collective motion of vortices in rotating turbulent convection

ArXiv 2010.15384 (2020)

Authors:

Shan-Shan Ding, Kai Leong Chong, Jun-Qiang Shi, Guang-Yu Ding, Hao-Yuan Lu, Ke-Qing Xia, Jin-Qiang Zhong

Tidally induced stellar oscillations: converting modelled oscillations excited by hot Jupiters into observables

(2020)

Authors:

Andrew Bunting, Caroline Terquem

Exoplanets and the Sun

(2020)

Authors:

JY-K Cho, H Th Thrastarson, TT Koskinen, PL Read, SM Tobias, W Moon, JW Skinner

Continuous structural parameterization: a proposed method for representing different model parameterizations within one structure demonstrated for atmospheric convection

Journal of Advances in Modeling Earth Systems American Geophysical Union 12:8 (2020) e2020MS002085

Authors:

Fh Lambert, Pg Challenor, Neil Lewis, Dj McNeall, N Owen, Ia Boutle, Hm Christensen, Rj Keane, Nj Mayne, A Stirling, Mj Webb

Abstract:

Continuous structural parameterization (CSP) is a proposed method for approximating different numerical model parameterizations of the same process as functions of the same grid‐scale variables. This allows systematic comparison of parameterizations with each other and observations or resolved simulations of the same process. Using the example of two convection schemes running in the Met Office Unified Model (UM), we show that a CSP is able to capture concisely the broad behavior of the two schemes, and differences between the parameterizations and resolved convection simulated by a high resolution simulation. When the original convection schemes are replaced with their CSP emulators within the UM, basic features of the original model climate and some features of climate change are reproduced, demonstrating that CSP can capture much of the important behavior of the schemes. Our results open the possibility that future work will estimate uncertainty in model projections of climate change from estimates of uncertainty in simulation of the relevant physical processes.

Vortices as Brownian particles in turbulent flows.

Science advances 6:34 (2020) eaaz1110

Authors:

Kai Leong Chong, Jun-Qiang Shi, Guang-Yu Ding, Shan-Shan Ding, Hao-Yuan Lu, Jin-Qiang Zhong, Ke-Qing Xia

Abstract:

Brownian motion of particles in fluid is the most common form of collective behavior in physical and biological systems. Here, we demonstrate through both experiment and numerical simulation that the movement of vortices in a rotating turbulent convective flow resembles that of inertial Brownian particles, i.e., they initially move ballistically and then diffusively after certain critical time. Moreover, the transition from ballistic to diffusive behaviors is direct, as predicted by Langevin, without first going through the hydrodynamic memory regime. The transitional timescale and the diffusivity of the vortices can be collapsed excellently onto a master curve for all explored parameters. In the spatial domain, however, the vortices exhibit organized structures, as if they are performing tethered random motion. Our results imply that the convective vortices have inertia-induced memory such that their short-term movement can be predicted and their motion can be well described in the framework of Brownian motions.