Bjarke Tobias Olsen

Hi David, The projection, given as a proj4 string, is: '+proj=lcc +lat_1=30.0 +lat_2=60.0 +lat_0=54.0 +lon_0=15.0 +a=6370000 +b=6370000 +no_defs'

Hi Feng, You can use a resource grid calculated by WAsP or PyWAsP with PyWake by using the `from_pwc` method of the `XRSite` class. This is the way we (on the PyWAsP team) pass wind climate data to PyWake, not via the `WaspGridSite` object. If you have .rsf or .wrg files with predicted wind climates from WAsP you can use WindKit to read the files and pass those to PyWake for wind farm modeling. See e.g. https://docs.wasp.dk/windkit/io/wc_autogen/windkit.weibull_wind_climate.read_wrgfile.html#windkit.weibull_wind_climate.read_wrgfile Read more about how to install WindKit here: https://docs.wasp.dk/windkit/installation.html As an example, if you have a .wrg file from WAsP you would do something like: import windkit as wk import py_wake pwc = wk.read_wrgfile(path_to_wrgfile) site = py_wake.site.xrsite.XRSite.from_pwc(pwc) You will now be able to use `site` in your PyWake modeling. One thing to consider when you do this is how you want to handle the spatial inhomogeneity. The way we do it in WAsP is to calculate speed-ups sector-wise using the point of highest wind speed as the reference. This corresponds to the default `method_speedup="park"` option in `from_pwc`. Best regards Bjarke (PyWAsP developer)