resebb commited on
Commit
3daec11
1 Parent(s): bd2d880

Add mean elevation data

Browse files
README.md CHANGED
@@ -21,6 +21,7 @@ The dataset consists of 3 different types of data (as illustrated above):
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  - For a given SMHI station: Historical, (relatively) low-resolution ECMWF weather forecasts from the 4 nearest ECMWF grid points
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  - **Topography/elevation data ([Copernicus DEM GLO-30](https://spacedata.copernicus.eu/collections/copernicus-digital-elevation-model))**:
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  - Topography/elevation data around a given SMHI station, grid enclosed by the 4 ECMWF points
 
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  The dataset is meant to facilitate the following modeling pipeline:
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  - 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:
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  - topography/elevation
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  ```python
 
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  import pandas as pd
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  import xarray as xr
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@@ -140,16 +142,23 @@ smhi_observation_data = pd.read_csv(
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  f'/smhi_weather_param_{weather_parameter}_station_{smhi_weather_observation_station_id}.csv',
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  sep=';',
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  )
 
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  print(smhi_observation_data)
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  ecmwf_data = xr.open_dataset(
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  './ecmwf_historical_weather_forecasts/ECMWF_HRES-reindexed.nc'
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  ).sel(station_index=smhi_weather_observation_station_index)
 
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  print(ecmwf_data)
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  topography_data = xr.open_dataset(
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  'topography/sweden_chunks_copernicus-dem-30m'
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  f'/topography_chunk_station_index-{smhi_weather_observation_station_index}.nc'
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  )
 
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  print(topography_data)
 
 
 
 
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  ```
 
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  - For a given SMHI station: Historical, (relatively) low-resolution ECMWF weather forecasts from the 4 nearest ECMWF grid points
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  - **Topography/elevation data ([Copernicus DEM GLO-30](https://spacedata.copernicus.eu/collections/copernicus-digital-elevation-model))**:
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  - Topography/elevation data around a given SMHI station, grid enclosed by the 4 ECMWF points
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+ - 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)
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  The dataset is meant to facilitate the following modeling pipeline:
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  - 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)
 
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  - topography/elevation
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  ```python
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+ import pickle
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  import pandas as pd
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  import xarray as xr
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  f'/smhi_weather_param_{weather_parameter}_station_{smhi_weather_observation_station_id}.csv',
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  sep=';',
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  )
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+ print('SMHI observation data:')
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  print(smhi_observation_data)
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  ecmwf_data = xr.open_dataset(
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  './ecmwf_historical_weather_forecasts/ECMWF_HRES-reindexed.nc'
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  ).sel(station_index=smhi_weather_observation_station_index)
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+ print('ECMWF data:')
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  print(ecmwf_data)
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  topography_data = xr.open_dataset(
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  'topography/sweden_chunks_copernicus-dem-30m'
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  f'/topography_chunk_station_index-{smhi_weather_observation_station_index}.nc'
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  )
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+ print('Topography chunk:')
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  print(topography_data)
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+
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+ mean_elevations = pickle.load(open('./topography/ecmwf_grid_mean_elevations.pkl', 'rb'))
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+ print('Mean elevation:')
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+ print(mean_elevations[0])
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  ```
topography/ecmwf_grid_mean_elevations.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:1f03796e007f0dc029590a1a0f05b534953d9803cd2eca253e0b39392ff21f88
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+ size 77510