wradlib Documentation - Bitbucket

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wradlib Documentation, Release 0.1.1 We try out what happens, if we convert the same reflectivity scan based on a ZR-relation with parameters for stratiform precipitation (below left) and look for the difference (below right) between both results: data_Rc_s = wrl.zr.z2r(data_Z, a = 256., b = 1.42) dif = data_Rc_s - data_Rc_c wrl.vis.polar_plot(data_Rc_s, title = ’Rain rate: Radarscan Feldberg 18-08-2006 02:25\nStratiform ZRunit = ’mm/h’, colormap = ’spectral’) wrl.vis.polar_plot(dif, title = ’’’Difference of convective rain transformed with convective respectively stratiform ZR-relationships’’’, unit = ’mm/h’, colormap = ’spectral’) 24 Chapter 2. Tutorials
wradlib Documentation, Release 0.1.1 At first view the results of the convective and the stratiform ZR-relationsship look very similar, but take the scalebar into account. That explains the differnce in the right image, where you can observe punctual overestimations up to 160 mm/h. That is because the reflecting signal of a rain drop with a diameter of 5mm (heavy precipitation) is equal to about 15000 raindrops (light precipitation) with a diameter of 1mm. At which the latter are weighing more than 100 times of the first one. Given that in flash flood forecasting an overestimation of convective rainstorms is more critical (false alarm) than an underestimation of light precipitation, the default is set to the convective type of rain. If we know the precipitation type exactly, the corresponding ZR-parameters should be applicated of course. Now we should examine what happens, if we convert a stratiform precipitation event with ZR-relationsships for stratiform respectively convective precipitation. In this case we use the same scale extends: data_dBZ = wrl.io.readDX(datadir + ’raa00-dx_10908-200608281420-fbg---bin’)[0] data_Z = wrl.trafo.idecibel(data_dBZ) data_Rs_s = wrl.zr.z2r(data_Z, a = 256., b = 1.42) data_Rs_c = wrl.zr.z2r(data_Z) max_data = max(data_Rs_s.max(), data_Rs_c.max()) dif = data_Rs_s - data_Rs_c wrl.vis.polar_plot(data_Rs_s, title = ’Rain rate: Radarscan Feldberg 28-08-2006 14:20\nStratiform ZRunit = ’mm/h’, colormap = ’spectral’, vmax = max_data) wrl.vis.polar_plot(data_Rs_c, title = ’Rain rate: Radarscan Feldberg 28-08-2006 14:20\nConvective ZRunit = ’mm/h’, colormap = ’spectral’, vmax = max_data) wrl.vis.polar_plot(dif, title = ’’’Difference of convective rain transformed with stratiform respectively convective ZR-relationships’’’, unit = ’mm/h’, colormap = ’spectral’) 2.4. Converting reflectivities 25
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