This includes scripts for processing high-resolution DEM data to get the required subgrid information. To use these scripts, a lot of GIS libraries are required. For more details, you can refer to how to install Python + GIS
High-resolution DEM data are required for getting the subgrid information. Generally, DEM can be downloaded from https://www.usgs.gov/core-science-systems/ngp/tnm-delivery/.
Calculate slope and aspect of the study domain from the DEM, and then their Trigonometry functions SIN and COS. Then A1, A2, and A3. The results are saved in output_dir. The script for doing such job is subgrid_info_calulate.py.
The high-resolution information has been calculated in the previous step. In this step, we need to calculate mean, variance, and covariance of A1, A2, and A3 for coarse resolution. This is similar as upscale high-resolution data into coarse-resolution. The script for doing this job is subgrid_info_extract.py.
In this script, input_lat and input_lon are ASCII files that include latitudes (corner, XLAT_V in HRRR) and longitudes (corner, XLONG_V in HRRR) of all the grid cells at coarse-resolution. The final output of this script is a shapefile that inlcudes all the required information for each grid cell.
Step 3 can be very time consume, if there are a lot of grid cells.
More details on the subgrid information can refer to He et al. (2019).
He, S., Smirnova, T. G., & Benjamin, S. G. (2019). A scale-aware parameterization for estimating subgrid variability of downward solar radiation using high-resolution digital elevation model data. Journal of Geophysical Research: Atmospheres, 124, 13680-13692. https://doi.org/10.1029/2019JD031563
For any questions, you can reach me with siwei.he@noaa.gov or hesiweide@gmail.com.