Add mean elevation data

README.md

@@ -21,6 +21,7 @@ The dataset consists of 3 different types of data (as illustrated above):
   - For a given SMHI station: Historical, (relatively) low-resolution ECMWF weather forecasts from the 4 nearest ECMWF grid points
 - **Topography/elevation data ([Copernicus DEM GLO-30](https://spacedata.copernicus.eu/collections/copernicus-digital-elevation-model))**:
   - Topography/elevation data around a given SMHI station, grid enclosed by the 4 ECMWF points
+  - Mean elevation around each of the nearest 4 ECMWF grid points for a given SMHI station (mean over +/-0.05 arc degree in each direction from the grid point center)
 
 The dataset is meant to facilitate the following modeling pipeline:
 - Weather forecasts for a set of 4 neighboring ECMWF points are combined with topography/elevation data and turned into higher resolution forecasts grid (corresponding to the resolution of the topography data)
@@ -122,6 +123,7 @@ Below, for a given SMHI weather observation station, we read the following data:
 - topography/elevation
 
 ```python
+import pickle
 import pandas as pd
 import xarray as xr
 
@@ -140,16 +142,23 @@ smhi_observation_data = pd.read_csv(
     f'/smhi_weather_param_{weather_parameter}_station_{smhi_weather_observation_station_id}.csv',
     sep=';',
 )
+print('SMHI observation data:')
 print(smhi_observation_data)
 
 ecmwf_data = xr.open_dataset(
     './ecmwf_historical_weather_forecasts/ECMWF_HRES-reindexed.nc'
 ).sel(station_index=smhi_weather_observation_station_index)
+print('ECMWF data:')
 print(ecmwf_data)
 
 topography_data = xr.open_dataset(
     'topography/sweden_chunks_copernicus-dem-30m'
     f'/topography_chunk_station_index-{smhi_weather_observation_station_index}.nc'
 )
+print('Topography chunk:')
 print(topography_data)
+
+mean_elevations = pickle.load(open('./topography/ecmwf_grid_mean_elevations.pkl', 'rb'))
+print('Mean elevation:')
+print(mean_elevations[0])
 ```

topography/ecmwf_grid_mean_elevations.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1f03796e007f0dc029590a1a0f05b534953d9803cd2eca253e0b39392ff21f88
+size 77510