USING SPECTRAL MOMENT DATA FROM NOAAS 404-MHZ RADAR WIND PROFILERS TOOBSERVE PRECIPITATION

A brief description is given of NOAA's 404-MHz Wind Profiler Demonstra tion Network (WPDN), including the radar configuration, sampling strat egy, site locations and characteristics, and a discussion of the Doppl er power spectrum and its first three spectral moments: signal power ( S), radial velocity (V-r), and velocity variance (sigma(2)). Evidence is presented showing that g-min time resolution spectral moment data f rom the vertically pointing beam of a WPDN wind profiler can be used t o identify when precipitation is present above the profiler. Signature s of snow, light and moderate stratiform rain, heavy convective rain, freezing rain, and snow within jet stream cirrus are illustrated and s ummarized. Although radar reflectivity factor (Z) cannot be determined from WPDN wind profilers, the precipitation rates and fall speeds sho wn to be observable in the cases documented here are roughly consisten t with earlier studies suggesting that precipitation with Z > 0-15 dBZ should typically be observable at 404 MHz, and that precipitation or clouds with Z < 0 dBZ should not be readily distinguishable from clear -air echoes. General signatures common to most precipitation, and char acteristics in the data that allow different types of precipitation to be distinguished from one another, are revealed from three case studi es. The most useful indicators of stratiform rain are downward V-r > 3 -5 m s(-1) and sigma(2) > 1.0 m(2) s(-2). Snow is indicated by 2 m s(- 1) > V-r > 0.5-0.9 m s(-1) and sigma(2) < 1.0 m(2) s(-2). Evidence of a melting level in S, Vr, and sigma(2) is a very good indicator of str atiform precipitation, and when absent helps identify precipitation as convective when S and sigma(2) are large. Because the spectral moment data are regularly archived, this information can be examined in real time and compared with simultaneously measured wind profiles. Such in formation should be useful in both research and operational meteorolog y. The ability to infer relationships between precipitation and kinema tic features evident in the observed winds is also illustrated.