FLOOD03496 - Laserfiche WebLink

Home Browse Search

some residual radar overestimation that the Adjustment algorithm could not totally correct. There is one last important point worthy of notice from Fig, J I. Despite the new Adjustment algorithm's reduction of the radar-wide rainfall overestimation, it has inadvertently reduced the storm-total radar estimate over the tOml of Buffalo Creek that had previously been a relativdy good estimate when using the old methodology as well as when no automated bias correction had been performed at all. The radar estimate in the bin over the tOml of Buffalo Creek was reduced from 63,8 mm to 43.2 mm using the new formulation, a 32% decrease (see the top pair of points in Fig, II), Since the rain gauge observation at this location was 68.1 mm, the net result is that for the gauge-radar pair over Buffalo Creek the radar estimates would have been degraded by the inclusion of real-time gauge data in the PPS algorithm. This is an unavoidable dilemma that may sometimes occur when estimating spatially uniforrll biases as in the current design of the Adjustment algorithm. If the PPS perfonnance for this case is judged based only on radar-wide gauge-radar comparisons (e.g., sample biases computed from all available gauge data) as opposed to point-specific gauge-radar comparisons, then the Adjustment algoritlun would have improved the rainfall estimates relative to fb.e case if the Adjustment algorithm had not been run at all. In this case, the total water volume over the entire radar umbrella has been better estimated (i.e., the radar overestimation has been decreased), and hydrologists who use these adjusted rainfall estimates as input to hydrologic models would be happier, On the other hand, if one judges the performance of the Adjustment algorithm based only on individual point-by-point comparisons of gauge and radar, then it is unavoidable that there will some locations where the adjusted radar estimates will be locally degraded relativle to the 16