Sweep Interpolation: A Fourth-Order Accurate Cost Effective Scheme in the Global Environmental Multiscale Model

Abstract

Abstract. The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach for solving advection which is commonly used in numerical weather prediction (NWP) models. It has a significant impact on the accuracy of the solution and can potentially be the most expensive part of model integration. The sweep algorithm, which was first described by Mortezazadeh and Wang (2017), performs SL interpolation with the same computational cost as a third order polynomial scheme but with the accuracy of a fourth order interpolation scheme. This improvement is achieved by using two 3rd-order backward and forward polynomial interpolation schemes in two consecutive time steps. In this paper, we present a new application of the sweep algorithm within the context of global forecasts produced with Environment Climate Change Canada’s Global Environmental Multiscale (GEM) model. Results show that the sweep interpolation scheme is computationally more efficient compared to a conventional fourth order polynomial scheme, especially evident for increasing number of several advected several passive tracers. An additional advantage of this new approach is that its implementation in a chemical and weather forecast models requires minimum modifications of the interpolation weighting coefficients. An analysis of the computational performance for a set of theoretical benchmarks as well as a global ozone forecast experiment show that up to 15 % reduction in total wall clock time is achieved. Forecasting experiments using the global version of the GEM model and the new interpolation show that the sweep interpolation can perform very well in predicting ozone distribution, especially in the tropopause region where transport processes play a significant role.