The Weather Research and Forecasting (WRF) model is a next-generation mesoscale numerical weather prediction system designed to serve both operational forecasting and atmospheric research needs. It features multiple dynamical cores, a 3-dimensional variational (3DVAR) data assimilation system, and a software architecture allowing for computational parallelism and system extensibility. WRF is suitable for a broad spectrum of applications and across scales ranging from meters to thousands of kilometres.
If you have any corrections, comments or contributions, please feel free to email us on firstname.lastname@example.org so that we can continue to update and upgrade the guides over time.
The installation (obtaining and compiling the source code) is NCI specific. The NCAR guides which we link to give instructions for compilation. DO NOT USE THOSE INSTRUCTIONS. They will not work. First, install WRF using this wiki's instructions and only follow the NCAR guides for running your simulation.
05 March 2020: ERA-Interim
Description wps-era has now been ported to Gadi for these versions. Note the code is using a new METGRID.TBL: METGRID.TBL.ERAI. This file has been corrected in WRF/WPS/metgrid.
This file is not distributed with standard WRF but is in the code base ported to Gadi.
Please clone wps-era and update your WRF code to use this capability.
Compilation No compilation is required after updating the code.
03 March 2020: Bug
Issue description: An error has been found that affect the January 2000 case from the NCAR tutorial. In order to run this case, you will now need to use the Variable Table: Vtable.GFS.tutorial for ungrib.exe.
Compilation: No compilation is required after updating the code base from Github.
For all versions, you will now find the code on Github. Please follow the instructions in the README for the branch corresponding to the version you want to use.
Please see this page to learn more about WRF performance on Gadi.
Running WRF at NCI
UPP hasn't been ported to Gadi yet.
Process for WRF porting to NCI machine