Comments (1)
@masonwillman Take a look at the nomads class for a reference on how our wx model fetching is implemented. These archived HRRR files are at https://console.cloud.google.com/storage/browser/high-resolution-rapid-refresh. You can see attached for a python script that downloads a full file from the server.
The process we implement in WindNinja will need to clip out a small subset of the full dataset on disk based on our DEM extents using the GDAL /vsigs/ virtual file system driver. This is an example that should work from the command line (you'll need to get a free GCP API key to use and associated client email to populate in the command below in place of the XXXX's).
gdal_translate -b 697 -projwin -113.55 45.00 -112.55 44.00 -projwin_srs EPSG:4326 -of GTiff /vsigs/high-resolution-rapid-refresh/hrrr.20210525/conus/hrrr.t01z.wrfprsf00.grib2 --config GS_OAUTH2_PRIVATE_KEY_FILE XXXX --config GS_OAUTH2_CLIENT_EMAIL XXX out.tif
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Related Issues (20)
- fetch_dem_exe issue HOT 2
- Inconsistency in vtk files from cli and GUI HOT 2
- Docker Issues: `Windninja: cannot connect to X server` HOT 1
- Installing WindNinja on an AWS EC2 Ubuntu server HOT 2
- Point Initialization failing during download HOT 1
- 3.8 and 3.9 don't build HOT 3
- Using vertical levels with weather model initialization HOT 3
- Mesh/output grid resolution issue/question HOT 2
- Inconsistent output filenames in the gridded initialization method
- Implement Back and Forth Error Compensation and Correction in Semi-lagrangian solver
- LCP service is broken HOT 6
- Incorrect time zone reported in the GUI with point initialization HOT 2
- Running WindNinja through a Cloud Service? HOT 2
- Disable SRTM data sources in GUI until the data is available again HOT 1
- Add 30 m COP30 global dataset HOT 1
- update docs for new SRTM source HOT 1
- Surface data bounds check not working properly in the GUI DEM download widget
- Add instructions for compiling OpenFOAM shared library for Windows
- shift WindNinja momentum solver runs from using the kEpsilon model to using the RNG kEpsilon model
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