Rainfall distributions from rain gages are typically estimated by assuming a spatial geometry tied to point rain gage observations using, for example, Thiessen polygons, inverse distance squared weighting, or statistical Kriging techniques. Unfortunately, the spatial distributions inferred by these approaches have little connection with how rain actually falls. Since the release of the WSR-88D (NEXRAD) radar in the early 1990s, many hydrologists and engineers have begun using gage-adjusted

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... rainfall estimates for hydrologic and water resource modeling. Over large areas under multiple NEXRAD radar coverages, the quality of radar rainfall estimates can vary significantly from one location to another. Visible discontinuities can develop at the limits of coverage of a single NEXRAD site because of slightly different performance or calibration techniques used at the different radar sites. Using a variety of GIS procedures for this study, these discontinuities were eliminated and locations of ground clutter were suppressed, yielding a seamless map of unadjusted radar rainfall estimates. These data were adjusted with over 400 rain gages located throughout the state using a modified spatial adjustment technique originally developed by Brandes at the National Severe Storms Lab in the mid-1970s. This approach was able to retain the volumetric rainfall estimates from the gages while maintaining the spatial signature of the rainfall. Use of this technique greatly improves gage-adjusted radar rainfall estimates.