The current paper establishes the computational efficiency and accuracy of the RBF-FD method for large-scale geoscience modeling with comparisons to state-of-the-art methods as high-order discontinuous Galerkin and spherical harmonics, the latter using expansions with close to 300,000 bases. The test cases are demanding fluid flow problems on the sphere that exhibit numerical challenges, such as Gibbs phenomena, sharp gradients, and complex vortical dynamics with rapid energy transfer from large to small scales over short time periods. The computations were possible as well as very competitive due to the implementation of hyperviscosity on large RBF stencil sizes (corresponding roughly to 6th to 9th order methods) with up to O(105) nodes on...
A numerical model based on radial basis functiongenerated finite differences (RBF-FD) is developed f...
Since the introduction of modern computers, numerical methods for atmospheric simulations have routi...
In this project, a proposal for a framework to use the local radial basis functions (RBFs) method to...
The current paper establishes the computational efficiency and accuracy of the RBF-FD method for lar...
The current paper establishes the computational e±ciency and accuracy of the RBF- FD method for larg...
Radial basis function-generated finite differences (RBF-FD) is a mesh-free method for numerically so...
Radial basis function generated finite differences (RBF-FD) is a mesh-free method for nu-merically s...
The paper derives the first known numerical shallow water model on the sphere using radial basis fun...
Radial Basis Functions (RBFs) are a powerful numerical methodology for solving PDEs to high accuracy...
We present three new semi-Lagrangian methods based on radial basis function (RBF) interpolation for ...
Many global climate models require efficient algorithms for solving the Stokes and Navier--Stokes eq...
The transport phenomena dominates geophysical fluid motions on all scales making the numerical solut...
RBF-generated finite differences (RBF-FD) have in the last decade emerged as a very powerful and fle...
Radial basis function-generated finite difference (RBF-FD) approximations generalize classical grid-...
The final copy of this thesis has been examined by the signatories, and we find that both the conten...
A numerical model based on radial basis functiongenerated finite differences (RBF-FD) is developed f...
Since the introduction of modern computers, numerical methods for atmospheric simulations have routi...
In this project, a proposal for a framework to use the local radial basis functions (RBFs) method to...
The current paper establishes the computational efficiency and accuracy of the RBF-FD method for lar...
The current paper establishes the computational e±ciency and accuracy of the RBF- FD method for larg...
Radial basis function-generated finite differences (RBF-FD) is a mesh-free method for numerically so...
Radial basis function generated finite differences (RBF-FD) is a mesh-free method for nu-merically s...
The paper derives the first known numerical shallow water model on the sphere using radial basis fun...
Radial Basis Functions (RBFs) are a powerful numerical methodology for solving PDEs to high accuracy...
We present three new semi-Lagrangian methods based on radial basis function (RBF) interpolation for ...
Many global climate models require efficient algorithms for solving the Stokes and Navier--Stokes eq...
The transport phenomena dominates geophysical fluid motions on all scales making the numerical solut...
RBF-generated finite differences (RBF-FD) have in the last decade emerged as a very powerful and fle...
Radial basis function-generated finite difference (RBF-FD) approximations generalize classical grid-...
The final copy of this thesis has been examined by the signatories, and we find that both the conten...
A numerical model based on radial basis functiongenerated finite differences (RBF-FD) is developed f...
Since the introduction of modern computers, numerical methods for atmospheric simulations have routi...
In this project, a proposal for a framework to use the local radial basis functions (RBFs) method to...