Abstract
The algorithms used to estimate rainfall from polarimetric radar variables show significant variance in error characteristics over the range of naturally occurring rain rates. As a consequence, to improve rainfall estimation accuracy using polarimetric radar, it is necessary to optimally combine a number of different algorithms. In this study, a new composite method is proposed that weights the algorithms by the inverse of their theoretical error. A number of approaches are discussed and are investigated using simulated radar data calculated from disdrometer measurements. The resultant algorithms show modest improvement over composite methods based on decision-tree logic-in particular, at rain rates above 20 mm h-1.
Original language | English |
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Pages (from-to) | 2092-2103 |
Number of pages | 12 |
Journal | Journal of Applied Meteorology and Climatology |
Volume | 50 |
Issue number | 10 |
DOIs | |
Publication status | Published - 2011 |