swirlspy.blending package

Blending data / nowcast.

swirlspy.blending.comp_qpe(grid_steps: Tuple[float, float], area: Tuple[float, float, float, float], datas: List[swirlspy.blending._comp_qpe.Raw], zero_value: float = 13, method: str = 'pdf', method_args: dict = None, apply_smoothing: bool = False) → xarray.core.dataarray.DataArray

Calculate composite QPE from multiple data sources. Assume all data is lay on same grid.

grid_steps: (axis 1’s step size, axis 2’s step size)
step size of grid on both axis, e.g. (y, x), (northing, easting)
area: (axis 1’s start, axis 1’s end, axis 2’s start, axis 2’s end)
boundary of output area
datas: list of (Raw)
Data sources with necessary data, see {Raw} for details.
composite_data {xarray.DataArray}
The composite data calculated from given data sources.
class swirlspy.blending.Raw

Bases: tuple

Raw data and it’s required information for composite QPE

data : xarray.DataArray
raw data
sites : list of (axis 1, axis 2, radius), Default is None
a list radar information, point of center (axis 1, axis 2) and effectivity area’s radius
weight : float, Default is 0.1
weighting of data in the output data

Alias for field number 0


Alias for field number 1


Alias for field number 2

swirlspy.blending.rains(nwp: xarray.core.dataarray.DataArray, nowcast: xarray.core.dataarray.DataArray) → xarray.core.dataarray.DataArray

Calculate blending numerical weather prediction and nowcast result with RaINS. Assume all data is lay on same time grid.

nwp: (xarray.DataArray)
Numerical weather prediction
nowcast: (xarray.DataArray)
Nowcast result data.
blended_data {xarray.DataArray}
The blended nowcast data.
swirlspy.blending.nwp_bias_correction(radar: xarray.core.dataarray.DataArray, nwp: xarray.core.dataarray.DataArray, proj4_str: str = None, quantiles: list = [100, 95, 90, 85, 80, 75, 70, 65, 60, 55, 50, 45, 40, 35, 30, 25, 20, 15, 10, 5, 0]) → xarray.core.dataarray.DataArray

Bias correction of numerical weather prediction data. The objective of bias correction is to match the nwp percentile to the radar percentile This is also known as frequency matching.

radar: (xarray.DataArray)
Radar data
nwp: (xarray.DataArray)
Numerical weather prediction
quantiles: list of (int)
Probability quantiles to caculate the percentiles of NWP and radar.
nwp_corrected {xarray.DataArray}
Corrected NWP data.