wradlib Documentation - Bitbucket

More documents

Recommendations

Info

$LaTeX-Tutorium III - Bitbucket$

wradlib Documentation, Release 0.1.1 Consistently the conversion image with the wrongly supposed convective ZR-parameters (upper right) underestimates the supposeable more precisely conversion with stratiform ZR-parameters (upper left). But the underestimation isn’t exceeding values of more than 4.2 mm/h, which is quite acceptable. 26 Chapter 2. Tutorials
wradlib Documentation, Release 0.1.1 All raw data is provided by DWD 2.5 Integration of precipitation rates (Accumulation) 2.5.1 Integrating precipitation rate of one radar scan over its corresponding time interval For many purposes in hydrology you need data of precipitation depth. For that reason we have to integrate the precipitation rate over the interval of the corresponding radar scan. In case of the radar stations of the German Weather Service the precipitation scan is repeated at intervals of 5 minutes (300 seconds): import wradlib as wrl # set the location of your data datadir = ’D:/THIS/IS/MY/DATA/DIRECTORY/’ data_dBZ = wrl.io.readDX(datadir + ’raa00-dx_10908-200608180005-fbg---bin’)[0] data_R_rate = wrl.zr.z2r(wrl.trafo.idecibel(data_dBZ)) # in mm/h!!! data_R_depth = wrl.trafo.r2depth(data_R_rate, 300.) # in mm!!! wrl.vis.polar_plot(data_R_depth, title = ’Precipitation height 18.8.2006, 00:00 - 00:05 (Radarstation unit = ’mm’, colormap = ’spectral’) 2.5. Integration of precipitation rates (Accumulation) 27
Page 1: wradlib Documentation Release 0.1.1
Page 4 and 5: 5.3 Users . . . . . . . . . . . . .
Page 6 and 7: wradlib Documentation, Release 0.1.
Page 80 and 81:
wradlib Documentation, Release 0.1.
Page 82 and 83:
Page 84 and 85:
Page 86 and 87:
Page 88 and 89:
Page 90 and 91:
Page 92 and 93:
Page 94 and 95:
Page 96 and 97:
Page 98 and 99:
Page 100 and 101:
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
show all

wradlib Documentation - Bitbucket

Create successful ePaper yourself

Delete template?

Save as template?