Fractional Stochastic Partial Differential Equation for Random Tangent Fields on the Sphere

TL;DR

This paper introduces a fractional SPDE model for random tangent fields on the sphere, capturing complex spatial-temporal behaviors using fractional operators and vector spherical harmonics, with analysis of approximation convergence.

Contribution

It develops a novel fractional SPDE framework for tangent fields on the sphere, incorporating Lévy-type jumps, long-range dependence, and provides solution representations and convergence analysis.

Findings

Solution expressed via vector spherical harmonics.

Covariance as Legendre tensor kernel expansion.

Convergence rates depend on spectral decay and Brownian motion variances.

Abstract

This paper develops a fractional stochastic partial differential equation (SPDE) to model the evolution of a random tangent vector field on the unit sphere. The SPDE is governed by a fractional diffusion operator to model the L\'{e}vy-type behaviour of the spatial solution, a fractional derivative in time to depict the intermittency of its temporal solution, and is driven by vector-valued fractional Brownian motion on the unit sphere to characterize its temporal long-range dependence. The solution to the SPDE is presented in the form of the Karhunen-Lo\`{e}ve expansion in terms of vector spherical harmonics. Its covariance matrix function is established as a tensor field on the unit sphere that is an expansion of Legendre tensor kernels. Approximations to the solutions are studied and convergence rates of the approximation errors are given. It is demonstrated how these convergence rates depend on the decay of the power spectrum and variances of the fractional Brownian motion.