A class of modular high order forward semi-Lagrangian (FSL) schemes with a number of advantages (outlined below) for linear advection equations is extended to have high resolution, in the sense that sharp gradients can be captured without loss of accuracy, by means of weighted essentially non-oscillatory derivative (DWENO) calculations based on finite differences. Principally, our approach (the convected scheme, CS) differs from conventional high order FSL schemes in the means by which it reaches higher order accuracy. The high order CS progressed in this work reserves use of a low order histogram representation of the solution and a mass-conservative volume-weighted projection operator which ordinarily produces a second order accurate solution. A higher order version is obtained by compensating for the amount by which the CS solution and the exact solution disagree at every order in a Taylor series sense. Instead of including these error terms algebraically, which changes the projection operator itself, the novel idea of the CS is to incorporate this information geometrically as a commensurate adjustment to the volume-weighted proportion assigned to each cell. We leverage DWENO approximations to compute these Taylor series error terms more sensitively, and show the corresponding WENO convected schemes (WENO-CS) achieve the desired dual high order and high resolution behavior. Fifth, seventh, and ninth order WENO-CS base solvers are presented for the 1D constant speed advection equation prototype, and are employed in a Strang splitting approach for the numerical solution of linear and nonlinear two-dimensional hyperbolic equations. Results are showcased for 2D linear transport and rigid body rotation, as well as for classic benchmark problems for the (1+1)-dimensional Vlasov–Poisson system including Landau damping, and the two-stream instability. The schemes enjoy the usual benefits of semi-Lagrangian schemes (e.g. no CFL time step restriction) while further claiming distinct advantages afforded to forward schemes including automatic mass conservation, compact support, and therefore straightforward parallelization.
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