Demonstration of a method for improved Doppler spectral moment estimation is presented. Time series data have been recorded using a commercial processor and digital receiver whereby the sampling frequency is several times larger than the reciprocal of the transmitted pulse. The in-phase and quadrature components of this oversampled data are used to estimate the three first spectral moments by suitably combining weighted averages in range with usual processing at a fixed range location. The weights are chosen in such a manner that the resulting signals become uncorrelated. Consequently, the variance of estimates decreases significantly. Because errors of estimates are inversely proportional to the volume scanning times, it follows that weather phenomena can be surveyed faster, while maintaining the same level of accuracy as present processing methods, or variance of estimates can be improved for the current volume scanning time.