Fractal rain distributions and chaotic advection
Ronald Dickman
Abstract
Localized rain events have been found to follow power-law distributions over several decades, suggesting parallels between precipitation and seismic activity [O. Peters et al., PRL 88, 018701 (2002)]. Similar power laws can be generated by treating raindrops as passive tracers advected by the velocity field of a two-dimensional system of point vortices [R. Dickman, PRL 90, 108701 (2003)]. Here I review observational and theoretical aspects of fractal rain distributions and chaotic advection, and present new results on tracer distributions in the vortex model.
Create a lesson
Related papers
Evaluating the prediction of subgrid eddy kinetic energy from a machine learning model
Thomas Wilder, Ranjini Swaminathan, David Storkey et al.
Shifts in Rossby wave regimes via the change of group velocity with zonal jets
Zhixiang Li, Jianhua Lu, Yimin Liu et al.
Distinguishing Initial-Condition and Model Error Using Machine-Learning Weather Models
P. Trent Vonich, Gregory J. Hakim
A Multidimensional Evaluation Framework for Artificial Intelligence-Based Ocean State Forecasts
Ziqing Zu, Ye Yuan, Tiejun Ling et al.
RadarFill: Observation-Constrained Gap Filling of Systematic Blind Zones in 3-D Weather Radar Reflectivity Mosaics
Xin Huang, Haofei Sun, Wei Han et al.
Machine learning emulators of dynamic global vegetation models for fast gridded carbon budget predictions
Piyu Ke, Xiaofan Gui, Stephen Sitch et al.