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wradlib Documentation, Release 0.1.1 radius model. The formula was taken from [Collier1996]. Parameters ranges : array the distances of each bin from the radar [m] elevations : array the elevation angles of each bin from the radar [degrees or radians] degrees : bool if True (the default) elevation angles are given in degrees and will be converted to radians before calculation. If False no transformation will be done and elevations has to be given in radians. re : float earth radius [m] Returns output : height of the beam [m] Notes The shape of elevations and ranges may differ in which case numpy’s broadcasting rules will apply and the shape of output will be that of the broadcast arrays. See the numpy documentation on how broadcasting works. References [Collier1996] 3.7.2 wradlib.qual.beam_height_ft_doviak wradlib.qual.beam_height_ft_doviak(ranges, elevations, degrees=True, re=6371000) Calculates the height of a radar beam above the antenna according to the 4/3 (four-thirds -> ft) effective Earth radius model. The formula was taken from [Doviak1993]. Parameters ranges : array the distances of each bin from the radar [m] elevations : array the elevation angles of each bin from the radar [degrees or radians] degrees : bool if True (the default) elevation angles are assumed to be given in degrees and will be converted to radians before calculation. If False no transformation will be done and elevations has to be given in radians. re : float earth radius [m] Returns output : height of the beam [m] 52 Chapter 3. Library Reference
wradlib Documentation, Release 0.1.1 Notes The shape of elevations and ranges may differ in which case numpy’s broadcasting rules will apply and the shape of output will be that of the broadcast arrays. See the numpy documentation on how broadcasting works. References [Doviak1993] 3.7.3 wradlib.qual.pulse_volume wradlib.qual.pulse_volume(ranges, h, theta) Calculates the sampling volume of the radar beam per bin depending on range and aperture. We assume a cone frustum which has the volume V=(pi/3)*h*(R**2 + R*r + r**2). R and r are the radii of the two frustum surface circles. Assuming that the pulse width is small compared to the range, we get R=r=tan(theta*pi/180)*range. Thus, the pulse volume simpy becomes a the volume of a cylinder with V=pi * h * range**2 * tan(theta*pi/180)**2 Parameters ranges : array h : float the distances of each bin from the radar [m] pulse width (which corresponds to the range resolution [m]) theta : float the aperture angle (beam width) of the radar beam [degree] Returns output : volume of radar bins at each range in ranges [m**3] 3.8 Composition Combine data from different radar locations on one common set of locations extract_circle togrid compose_ko compose_weighted Extract the indices of coords which fall within a circle Interpolate data from a radar location to the composite grid or set of locations Composes grids according to quality information using quality information as a knockout criterion. Composes grids according to quality information using a weighted averaging approach. 3.8.1 wradlib.comp.extract_circle wradlib.comp.extract_circle(center, radius, coords) Extract the indices of coords which fall within a circle defined by center and radius Parameters center : float radius : float coords : array of float with shape (numpoints,2) Returns output : 1-darray of integers 3.8. Composition 53
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