https://github.com/bnb32/wrf_aws
https://github.com/bnb32/wrf_aws
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/bnb32/wrf_aws
- Owner: bnb32
- Created: 2021-03-06T12:29:03.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2021-09-19T14:59:55.000Z (over 3 years ago)
- Last Synced: 2025-01-22T18:51:21.630Z (4 months ago)
- Language: Python
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# README #
This repo is for setting up wrf on AWS.
**RUNNING WRF**
1. Create new cloud9 instance:
- select Ubuntu under "Platform"
- select vpc-00177ee82dc8fe654 under "Network Settings"
2. Add default security group to your cloud9 instance
- Go to AWS console
- Click on running instances
- Click on your instance in the list
- Click on actions, networking, change security groups
- Select default group and assign group
3. Clone wrf_aws repo to your cloud9 instance
4. Run the following commands to install packages and mount storage
`$ cd wrf_aws`
`$ ./go`
5. To run wrf first edit namelist files for your own application
`$ cd forecast/templates`
`$ vim namelist.wps`
`$ vim namelist.input`
6. Then edit the runwrf script to select length of simulation
`$ cd forecast`
`$ vim runwrf`
7. Edit `N_DAYS` and `USERNAME` variables in `runwrf`
7. Finally run wrf
`$ ./runwrf`
8. wrf output will be in `'/data//wrfout'`
**POST-PROCESSING**
1. For post-processing login to your workspace
2. Open a terminal and clone wrf_aws
3. again run the following commands
`$ cd wrf_aws`
`$ ./go`
4. This will setup a python conda environment
- to run conda open another terminal
- run the following command
`$ conda activate ecrl`