Hello everyone,
Recently, I have been learning how to run regional simulations with MPAS following the official tutorial. In the tutorial, the lateral boundary condition (LBC) files are generated using CFSv2 analysis data together with the MPAS preprocessing tools. From my understanding, this approach essentially performs a regional simulation that is continuously constrained by reanalysis data.
However, when reading the paper “ Limited-Area Atmospheric Modeling Using an Unstructured Mesh” that Skamarock wrote, I noticed that a different strategy is sometimes adopted. Instead of using reanalysis data as the lateral boundary conditions, the author performed a global MPAS simulation (for example, at about 15-km resolution) and then used the output from this global run to provide the lateral boundary conditions for a nested regional MPAS simulation.
My understanding is that this approach allows the regional simulation to evolve more consistently with the model dynamics, since the lateral boundaries come from a global MPAS forecast rather than from reanalysis fields. This seems particularly important for tropical cyclone studies, because if reanalysis data are used as the LBC, the large-scale environment is continuously imposed at the boundaries, which may limit the ability to evaluate the intrinsic forecast performance of the model.
I am therefore wondering how this type of MPAS-to-MPAS nesting is typically implemented in practice. In particular, I would like to know how the lateral boundary condition files for the regional MPAS run can be generated from the output of a global MPAS simulation.
If anyone has experience with this type of setup or could point me to relevant documentation or examples, I would greatly appreciate the advice. Thanks！
Recently, I have been learning how to run regional simulations with MPAS following the official tutorial. In the tutorial, the lateral boundary condition (LBC) files are generated using CFSv2 analysis data together with the MPAS preprocessing tools. From my understanding, this approach essentially performs a regional simulation that is continuously constrained by reanalysis data.
However, when reading the paper “ Limited-Area Atmospheric Modeling Using an Unstructured Mesh” that Skamarock wrote, I noticed that a different strategy is sometimes adopted. Instead of using reanalysis data as the lateral boundary conditions, the author performed a global MPAS simulation (for example, at about 15-km resolution) and then used the output from this global run to provide the lateral boundary conditions for a nested regional MPAS simulation.
My understanding is that this approach allows the regional simulation to evolve more consistently with the model dynamics, since the lateral boundaries come from a global MPAS forecast rather than from reanalysis fields. This seems particularly important for tropical cyclone studies, because if reanalysis data are used as the LBC, the large-scale environment is continuously imposed at the boundaries, which may limit the ability to evaluate the intrinsic forecast performance of the model.
I am therefore wondering how this type of MPAS-to-MPAS nesting is typically implemented in practice. In particular, I would like to know how the lateral boundary condition files for the regional MPAS run can be generated from the output of a global MPAS simulation.
If anyone has experience with this type of setup or could point me to relevant documentation or examples, I would greatly appreciate the advice. Thanks！
