Dear all
I modified the albedo to characterize photovoltaic (PV) power plants using WRFv4.5. The specific operation steps are as follows:
During the WPS phase, I used Python code to change the land use type of Barren or Sparsely Vegetated(category 16) to PV power plants (category 22, since the original land use types only included 21 categories) in the geo_em.d0*.nc files generated by geogrid.exe.
In the WRF phase (adopting the Noah land surface model), before running real.exe, I referred to the module_sf_noahlsm.F file and modified the MODIFIED_IGBP_MODIS_NOAH section in the VEGPARM.TBL file: I added category 22 as 'PV Power Plant' along with its corresponding parameter indicators.
My objective is to maintain the albedo of PV power plants (category 22) at 0.16; however, the albedo values obtained through the above methods did not meet my requirements and showed significant fluctuations.
Below are the Python code I used, the modified VEGPARM.TBL file, and the namelist.input file for your reference. Thank you all.
I modified the albedo to characterize photovoltaic (PV) power plants using WRFv4.5. The specific operation steps are as follows:
During the WPS phase, I used Python code to change the land use type of Barren or Sparsely Vegetated(category 16) to PV power plants (category 22, since the original land use types only included 21 categories) in the geo_em.d0*.nc files generated by geogrid.exe.
In the WRF phase (adopting the Noah land surface model), before running real.exe, I referred to the module_sf_noahlsm.F file and modified the MODIFIED_IGBP_MODIS_NOAH section in the VEGPARM.TBL file: I added category 22 as 'PV Power Plant' along with its corresponding parameter indicators.
My objective is to maintain the albedo of PV power plants (category 22) at 0.16; however, the albedo values obtained through the above methods did not meet my requirements and showed significant fluctuations.
Below are the Python code I used, the modified VEGPARM.TBL file, and the namelist.input file for your reference. Thank you all.