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dependency on the rain rate threshold as indicated in Table I, and indeed this is the case as shown in Fig, 13, As the rain rate threshold increases from 49 (paner a) to 53 dBl (panel c), the bias estimates decrease only slightly. They never approach the much smaller sample bias values of 0.5-0.7 in Table I. The less-than-optimal method of fonning the gauge-radar pairs is causing this insensitivity, not any deficiencies in the Adjustment algorithm's Kalman filtering procedure. As previously mentioned, it turns out that the radar estimate over the town of Buffalo Creek (the top row of symbols in Fig. 12) was very close to the actual rain gauge measurement for the case when the default value of 51 dBl was used as a rain rate threshold. The rain gauge measured 2.68 inches while the PPS estimated 2.51 inches which is only a 6% underestimate. The range of PPS estimates for the nine surrounding polar bins ranges from 1.41 to 2.81 inches (Table 3). The largest stonn-total PPS rainfall estimate at any location affected by the flood- producing storm was 2.85 inches, only two polar grid boxes away from the town of Buffalo Creek, at an azimuth of 232,5 deg and range of 77 km. Both the town and this largest rainfall estimate are located within the Buffalo Creek basin and just a short distance upstream of its outlet where it empties into the North Fork of the South Platte River. 7. Other possible error sources The integrity of PPS rainfall estimates may be affected by other meteorological and/or algorithmic factors besides the rain rate threshold adaptable parameter setting. It is possible that some or all of the radar overestimation bias for this case may be best corrected by using different l-R parameters that produce lower rainfall accumulations instead of decreasing the rain rate threshold. Changing the maximum rain rate threshold will only have an impact on the radar 19