Time Series Wind Climate (TSWC)#

The time series wind climate contains a time series of wind_speed and wind_direction. It is the most basic wind climate from which all others can be derived, retaining all original information.

Data Structure#

TSWC objects are xarray.Dataset with the following schema:

Dimensions:  (time, ...)
Variables:
    wind_speed      (time, ...)  - wind speed in m/s
    wind_direction  (time, ...)  - wind direction in degrees

In addition to the core coordinates, TSWC objects contain the time dimension.

I/O#

Format

Read

write

Description

.csv

yes

no

Comma-separated values

.nc

yes

via .to_netcdf()

NetCDF format

Reading:

windkit.read_tswc() reads time series wind climates:

# Read from NetCDF
tswc = wk.read_tswc("wind_data.nc")

# Read from CSV
tswc = wk.read_tswc("wind_data.csv", crs="EPSG:4326")

Writing:

TSWC can be written to NetCDF using xarray’s built-in method:

tswc.to_netcdf("output.nc")

Creating from Arrays#

tswc = xr.Dataset(
    data_vars=dict(
        wind_speed = xr.DataArray(np.random.rand(100, 3)*10, dims=['time', 'height']),
        wind_direction = xr.DataArray(np.random.rand(100, 3)*360, dims=['time', 'height']),
    ),
    coords=dict(
        time = (("time",), pd.date_range('2020-01-01', periods=100, freq='h')),
        height = (("height"), [10, 50, 100]),
    )
)
print(tswc)

<xarray.Dataset> Size: 6kB
Dimensions:         (time: 100, height: 3)
Coordinates:
  * time            (time) datetime64[us] 800B 2020-01-01 ... 2020-01-05T03:0...
  * height          (height) int64 24B 10 50 100
Data variables:
    wind_speed      (time, height) float64 2kB 8.118 7.161 9.722 ... 2.419 9.152
    wind_direction  (time, height) float64 2kB 229.9 312.5 149.4 ... 141.5 313.0

To add spatial information:

tswc = (
    tswc
    .expand_dims("stacked_point")
    .assign_coords(
        west_east = (("stacked_point",), [10.0]),
        south_north = (("stacked_point",), [56.0]),
    )
)

tswc = wk.spatial.set_crs(tswc, crs=4326)
tswc

<xarray.Dataset> Size: 6kB
Dimensions:         (time: 100, height: 3, stacked_point: 1)
Coordinates:
  * time            (time) datetime64[us] 800B 2020-01-01 ... 2020-01-05T03:0...
  * height          (height) int64 24B 10 50 100
    west_east       (stacked_point) float64 8B 10.0
    south_north     (stacked_point) float64 8B 56.0
    crs             int8 1B 0
Dimensions without coordinates: stacked_point
Data variables:
    wind_speed      (stacked_point, time, height) float64 2kB 8.118 ... 9.152
    wind_direction  (stacked_point, time, height) float64 2kB 229.9 ... 313.0

Creating from DataFrame#

windkit.tswc_from_dataframe() creates TSWC from pandas DataFrames:

data = {
    "wind_speed_10m": np.random.rand(100)*10,
    "wind_speed_50m": np.random.rand(100)*10,
    "wind_direction_10m": np.random.rand(100)*360,
    "wind_direction_50m": np.random.rand(100)*360,
}

df = pd.DataFrame(
    data,
    index=pd.date_range('2020-01-01', periods=100, freq='h'),
)

height_to_columns = {
    10: ("wind_speed_10m", "wind_direction_10m"),
    50: ("wind_speed_50m", "wind_direction_50m"),
}

tswc = wk.tswc_from_dataframe(
    df,
    west_east=10.0,
    south_north=56.0,
    crs=4326,
    height_to_columns=height_to_columns,
)
tswc

<xarray.Dataset> Size: 4kB
Dimensions:         (time: 100, height: 2, stacked_point: 1)
Coordinates:
  * time            (time) datetime64[us] 800B 2020-01-01 ... 2020-01-05T03:0...
  * height          (height) int64 16B 10 50
    west_east       (stacked_point) float64 8B 10.0
    south_north     (stacked_point) float64 8B 56.0
    crs             int8 1B 0
Dimensions without coordinates: stacked_point
Data variables:
    wind_speed      (time, height, stacked_point) float64 2kB 2.475 ... 1.269
    wind_direction  (time, height, stacked_point) float64 2kB 334.4 ... 287.0
Attributes:
    history:          2026-01-29T09:30:18+00:00:\twindkit==2.0.1\twk.tswc_fro...
    Conventions:      CF-1.8
    Package name:     windkit
    Package version:  2.0.1
    Creation date:    2026-01-29T09:30:18+00:00
    Object type:      Time Series Wind Climate
    author:           Default User
    author_email:     default_email@example.com
    institution:      Default Institution

Validation#