swirlspy.blending package¶
Blending data / nowcast.¶
-
class
swirlspy.blending.
Raw
(data: xarray.core.dataarray.DataArray, sites: Optional[List[Tuple[float, float, float]]] = None, weight: float = 0.1)¶ Bases:
tuple
Raw data and it’s required information for composite QPE
- dataxarray.DataArray
raw data
- siteslist 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
- weightfloat, Default is 0.1
weighting of data in the output data
-
property
data
¶ Alias for field number 0
-
property
sites
¶ Alias for field number 1
-
property
weight
¶ Alias for field number 2
-
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: Optional[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.
-
swirlspy.blending.
nwp_bias_correction
(radar: xarray.core.dataarray.DataArray, nwp: xarray.core.dataarray.DataArray, proj4_str: Optional[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.
-
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.