pysteps.feature.tstorm.detection¶

pysteps.feature.tstorm.detection(input_image, max_num_features=None, minref=35, maxref=48, mindiff=6, minsize=50, minmax=41, mindis=10, output_feat=False, time='000000000')¶

This function detects thunderstorms using a multi-threshold approach. It is recommended to use a 2-D Cartesian maximum reflectivity composite, however the function will process any 2-D array. The thunderstorm cell detection requires both scikit-image and pandas.

Parameters

input_image: array-like: Array of shape (m,n) containing input image, usually maximum reflectivity in dBZ with a resolution of 1 km. Nan values are ignored.
max_num_featuresint, optional: The maximum number of cells to detect. Set to None for no restriction. If specified, the most significant cells are chosen based on their area.
minref: float, optional: Lower threshold for object detection. Lower values will be set to NaN. The default is 35 dBZ.
maxref: float, optional: Upper threshold for object detection. Higher values will be set to this value. The default is 48 dBZ.
mindiff: float, optional: Minimal difference between two identified maxima within same area to split area into two objects. The default is 6 dBZ.
minsize: float, optional: Minimal area for possible detected object. The default is 50 pixels.
minmax: float, optional: Minimum value of maximum in identified objects. Objects with a maximum lower than this will be discarded. The default is 41 dBZ.
mindis: float, optional: Minimum distance between two maxima of identified objects. Objects with a smaller distance will be merged. The default is 10 km.
output_feat: bool, optional: Set to True to return only the cell coordinates.
time: string, optional: Date and time as string. Used to label time in the resulting dataframe. The default is ‘000000000’.

Returns

cells_id: pandas dataframe: Pandas dataframe containing all detected cells and their respective properties corresponding to the input image. Columns of dataframe: ID - cell ID, time - time stamp, x - array of all x-coordinates of cell, y - array of all y-coordinates of cell, cen_x - x-coordinate of cell centroid, cen_y - y-coordinate of cell centroid, max_ref - maximum (reflectivity) value of cell, cont - cell contours
labels: array-like: Array of shape (m,n), grid of labelled cells.