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<br />formed, The adjusted radar estimates associated with each pair of points in this figure reflect the <br /> <br />multiplication of the computed hourly bias estimates from the Adjustinent argorithm as shown in <br /> <br />Figs. 6a and 9a on the radar rainfall estimates exactly as would have been done if the Adjustment <br /> <br />algorithm had been executing on an hourly basis over the course of the storm event. The open <br /> <br />circles are associated with the adjusted radar estimates using the existing method to form the <br /> <br />pairs, while filled circles are associated with the adjusted radar estimates if the center bin of the <br /> <br />3x3 array was used. <br /> <br />Focusing first on the results from the existing algorithm (open circles), the storm-total <br /> <br />sample bias after adjustment is 0.615, equivalent to a 63% radar overestimation, which is not <br /> <br />very close to the ideal post-adjustment bias of 1.0 that the Adjustment algorithm strives to <br /> <br />achieve. This bias is slightly larger than the corresponding unadjusted value shown in Table I <br /> <br />(0.614) reflecting a slight reduction in the radar overestimation. Although the Adjustment <br /> <br />algorithm has successfully moved the radar estimates in the right direction, i.e., decreasing them <br /> <br />in better accordance with the gauge observations, it has not moved them far enough as there is <br /> <br />still a large overestimation even after automated bias adjustment has been applied. <br /> <br />On the other hand, the resulting adjusted storm-total sample bias associated with the new <br /> <br />methodology (filled circles) is 0.797, about 30% larger than the previous 0,615, and closer to the <br /> <br />ultimate goal of 1.0. A sample bias of 0.797 corresponds to a radar overestimation of25% <br /> <br />which, though not totally unbiased, is much better than the previous radar overestimation of <br /> <br />63%. In this case, the new methodology has moved the radar estimates much farther in the right <br /> <br />direction by reducing the overestimation and bringing the post-adjustment storm-total sample <br /> <br />bias closer to 1.0. However, since the post-adjustment bias is still less than unity, there is still <br /> <br />15 <br />