Neil Davis

Sure, everything is possible. I have reached out to via DM to see if this is something we could collaborate on.

Thank you for your suggestion, we have not seen academic torrents before. However, I am not sure that it would be a good set for the New European Wind Atlas dataset. Our dataset would almost double the amount of data available via that platform. It is also unclear to me how users would be able to subset the data so they could get what they are interested in and not the full dataset. We are almost finished repackaging the data into a format that should allow users to download around 10 years of data for a single point. We are doing performance testing to determine the new limits for this repackaged data. It should launch early next year.

Are you still having this issue? I am not able to replicate it. If I select say downloading 2005-01-01 for Wind Speed at a point near Copenhagen, I get the NetCDF file for that point.

We have released new versions of PyWAsP and Windkit. Windkit has a number of deprecations, please pay attention if you are using these. We aren't sure how long we should keep deprecations around, please let us know if you have thoughts on this. PyWAsP has a number of breaking changes, we are closing in on a more stable API, but still expect a few more breaking changes. The highlights of Windkit include a new Long Term Correct module, an improved WindTurbines class, better integration with GeoPanandas, Improvements to downloading of raster and vector maps, and a new function to implement cross prediction. Full release notes can be found at: https://docs.wasp.dk/windkit/release_notes.html#id1 For PyWAsP the main highlight is the new climate extrapolation functions. These functions allow the prediction of either binned or weibull wind climates without creating a generalized wind climate lookup table, reducing interpolation errors. The binned wind climate to binned wind climate approach was presented at the Wind Europe Technical Workshop for Resource Assessment. In addition, new BWC resampling functions have been added, we have included support for custom root CA certificates, and have been able to improve performance for a number of functions. Full release notes are found at: https://docs.wasp.dk/pywasp/release_notes.html#id1

The issue is that the time-series data is a raster in the projected space, but not in the lat/lon space. Therefore, the XLAT/XLON have to be two-dimensional, as the values at each point depends on both the x and y dimensions. The approach from David above will give you a non-raster dataset in the new projection. If you want to get a raster back in the new projection, you can use the Windkit tool we have developed, which will "warp" the data from one projection to another, keeping the grid spacing approximately the same. When warping, you will be performing an interpolation, nearest neighbor by default. import windkit as wk import xarray as xr ds = xr.open_dataset("mesotimeseries-Area 2.nc") ds ds_warped = wk.spatial.warp(ds, 3035) ds_warped

The timeseries data is defined on a lambert conformal grid. The WKT of the grid can be found in the crs_wkt attribute of the crs variable of the downloaded NetCDF file. It doesn't have an EPSG as it is a custom projection defined specifcally for the NEWA mesoscale simulations.

The timezone is UTC, so it is the same everywhere.

We have released new versions of PyWAsP and Windkit. Both versions include breaking changes, but only a small number. The highlights of Windkit include improved interpolation routines, several improvements to the map conversion tools to create polygon data from your roughness line maps, and additional derived fields for weibull wind climates. Full release notes can be found at: https://docs.wasp.dk/windkit/release_notes.html#id1 For PyWAsP the hightlights include a bugfix to the license manager on Windows, so now this should work correctly. We have also updated the dependencies, and aim to follow the SPEC-0 versions of our Scientific Python dependencies. This means that Python 3.10 is the oldest version of Python supported with this release. You can now use WAsP CFD results files for estimating your predicted wind climate, and we have improved the performance of the AEP calculator. Full release notes are found at: https://docs.wasp.dk/pywasp/release_notes.html#id1

I think the issue is that the library you are using is quite old and only supports TLSv1. We have recently disabled TLSv1 and TLSv2. There is also a space between 2018 and -12 in the dt_stop variable of the URL you pasted above. Here is a script using python3 that I used to download and save the file to a named temporary file. from urllib.request import urlopen from shutil import copyfileobj from tempfile import NamedTemporaryFile url = 'https://wps.neweuropeanwindatlas.eu/api/mesoscale-ts/v1/get-data-point?latitude=53.800651&longitude=3.955078&variable=WD10&variable=WS10&dt_start=2018-12-20T00:00:00&dt_stop=2018-12-31T23:30:00' with urlopen(url) as fsrc, NamedTemporaryFile(delete=False) as fdst: copyfileobj(fsrc, fdst)

What is the URL you are trying to access? The OpenDap service has been removed, about a year ago, after we restructured our data on the backend. You should now use the daTap interfaces explained in the forum post below for accessing the data.

Hi Gyeongil, Sorry for the confusion. The answer is that technically both are correct and neither is correct. Both the GWA and GASP were run on UTM projections with a 250m grid spacing. However, to make the global map, these were interpolated to a lat/lon map projection with a grid spacing of 0.0025 grid spacing. This has then often been presented as a 250m grid spacing, using the approximation of 100 km per degree. However, for the GASP paper it was decided to use the more accurate 111 km per degree, which would then come to 277.5m, which we rounded to 275. Of course, both the 275 and 250m resolutions only apply to longitude near the equator. Hope this helps.

We have released new versions of PyWAsP and Windkit. The highlights of Windkit include further improvment to the writing of wrg/rsf files, the ability to read polygon based landcover features, and enhanced the bounding box object. Full release notes can be found at: https://docs.wasp.dk/windkit/release_notes.html#id1 For PyWAsP the hightlights include a bugfix to the gross_aep calculator, where previously all turbines were assumed to be stall regulated when performing air density adjustments. Now you need to define a variable `regulation_type` on you wind turbine variables, which ensure the correct air density adjustment is applied. Full release notes are found at: https://docs.wasp.dk/pywasp/release_notes.html#id1

We have released windkit 0.6.2 which includes a few new functions for reading time-series data and cfdres files into Windkit. We also fixed an issue with writing RSF and WRG files from PyWAsP downscale output. Full release notes can be found at: https://docs.wasp.dk/windkit/release_notes.html#id1

Sorry for the long delay. We have fixed the issue in an updated release of Windkit 0.6.2. You should be able to install it from both pip and mamba now.

Hi, Sorry for this error. The issue is that by default elevation is not included in the result from `get_wasp_down`, but is required for creating the RSF. The easiest fix would be to set the argument `return_site_factors` to `True` in the call to `get_wasp_down`, this will include all of the site effects in the `pwc_rsf` variable. Alternatively, you could just copy the elevation like `pwc_rsf["elevation"] = site_effects["elevation"]`