Vertical extrapolation

Example of using PyWAsP to perform vertical extrapolation.

Prepare TopographyMap

First, we need to prepare the topography map. This is done by reading the elevation and roughness maps and creating a TopographyMap object.

[1]:

import numpy as np
import windkit as wk
import pywasp as pw

bwc = wk.read_bwc(
    "../../../modules/examples/tutorial_4/data/SerraSantaLuzia.omwc", crs="EPSG:4326"
)
bwc = wk.spatial.reproject(bwc, to_crs="EPSG:32629")

elev_map = wk.read_vector_map(
    "../../../modules/examples/tutorial_4/data/SerraSantaLuzia.map",
    map_type="elevation",
    crs="EPSG:32629",
)

lc_map, lc_tbl = wk.read_vector_map(
    "../../../modules/examples/tutorial_4/data/SerraSantaLuzia.map",
    map_type="roughness",
    crs="EPSG:32629",
)

topo_map = pw.wasp.TopographyMap(elev_map, lc_map, lc_tbl)

Define output locations

Second, we need to define the output locations. This is done by creating a dataset with the coordinates of the output locations.

[2]:

output_locs = wk.create_dataset(
    west_east=bwc.west_east.values,
    south_north=bwc.south_north.values,
    height=np.linspace(10.0, 100.0, 10),
    crs="EPSG:32629",
    struct="stacked_point",
)
print(output_locs)

<xarray.Dataset>
Dimensions:      (height: 10, stacked_point: 1)
Coordinates:
  * height       (height) float64 10.0 20.0 30.0 40.0 ... 70.0 80.0 90.0 100.0
    south_north  (stacked_point) float64 4.621e+06
    west_east    (stacked_point) float64 5.147e+05
    crs          int8 0
Dimensions without coordinates: stacked_point
Data variables:
    output       (height, stacked_point) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0
Attributes:
    Conventions:  CF-1.8
    history:      2024-02-16T10:48:47:\twindkit==0.7.1.dev17+ga2ef68d\twk.cre...

Calculate resource grid

Finally, we can calculate the resource grid. This is done by calling the generalize_and_downscale function. This function takes the output locations, the boundary conditions, and the topography map as input. The output is a predicted wind climate dataset

[3]:

# pwc = pw.wasp.generalize_and_downscale(output_locs, bwc, topo_map)

Plot the mean wind speed

We can plot the mean wind speed to see the result.

[4]:

# pwc["wspd"].plot.line(y="height")