Detecting low-altitude wind shear in support of aviation safety and efficiency is the primary mission of the Terminal Doppler Weather Radar (TDWR). The wind-shear detection performance depends directly on the quality of the data produced by the TDWR. At times the data quality suffers from the presence of clutter. Al-though stationary ground clutter signals can be removed by a high-pass filter, moving clutter such as birds and roadway traffic cannot be attenuated using the same technique because their signal power can exist any-where in the Doppler velocity spectrum. Furthermore, because the TDWR is a single-polarization radar, polarimetry cannot be used to discriminate these types of clutter from atmospheric signals. The moving clutter problem is exacerbated at Western sites with dry microbursts, because their low signal-to-noise ratios (SNRs) are more easily masked by un-wanted moving clutter. For Las Vegas (LAS), Nevada, the offending clutter is traffic on roads that are oriented along the radar line of sight near the airport. The radar is located at a significantly higher altitude than the town, improving the visibility to the roads, and giving LAS the worst road clutter problem of all TDWR sites. The Salt Lake City (SLC), Utah, airport is located near the Great Salt Lake, which is the biggest inland staging area for migrating seabirds in the country. It, therefore, suffers from bird clutter, which not only can obscure wind shear signatures but can also mimic them to trigger false alarms. The TDWR "dry" site issues are discussed in more detail by Cho (2008). In order to mitigate these problems, we developed a moving clutter spectral filter (MCSF). In this paper we describe the algorithm and present preliminary test results.