Classification of Tropical Precipitating Systems Using Wind Profiler Spectral Moments. Part I: Algorithm Description and Validation

Abstract

The lower atmospheric wind profiler (LAWP) measurements made at Gadanki, India, have been used to develop an objective algorithm to classify the tropical precipitating systems. A detailed investigation on the existing classification scheme reveals major shortcomings in the scheme. In the present study, it is shown with examples that the Doppler velocity gradient (DVG) criterion is a necessary but certainly not a sufficient condition to identify the radar bright band. Such gradients in Doppler velocity can exist in other types of rain systems, for example, in convection, due to the modulation of Doppler velocity of hydrometeors by vertical air motion. The approach of the new classification scheme deviates considerably from that of existing algorithms. For instance, the new algorithm, in contrast to identifying the stratiform rain and assuming the remaining rain as convection, identifies first convection and later stratiform precipitation based on their specific characteristics. The other interesting feature in this algorithm is that it was built on the strengths of other potential classification schemes and theoretically accepted thresholds for classification of the precipitation. The performance of the new algorithm has been verified with the help of time-height maps of profiler moments and corresponding surface rainfall patterns.

Differences in raindrop size distribution from southwest monsoon to northeast monsoon at Gadanki

“…Therefore, if the height of melting level is different in these seasons, it may cause some differences in rain DSD at the surface. However, Rao et al (2008) found no significant difference in the height of the melting level from SW to NE monsoon at Chennai (120 km away from Gadanki). But the surface temperature and convective activity are different in these seasons.…”

A comprehensive investigation on afternoon transition of the atmospheric boundary layer over a tropical rural site

“…Though Gadanki receives 55 % of the annual rainfall in the southwest monsoon, raising instantaneous soil moisture levels, the high insolation and temperatures immediately consume the soil moisture for latent heating. On the other hand, this region also gets a good amount of rainfall during the cool northeast monsoon (Rao et al, 2009). The soil moisture levels, therefore, remain high in this season.…”

“…This site is located ∼ 375 m above the mean sea level in a rural area in southeastern peninsular India and is surrounded by hillocks (300-800 m within a 10 km region) distributed in a complex fashion. The rainfall in this region is influenced primarily by two monsoons, southwest (June-September) and northeast (OctoberDecember) (Rao et al, 2009). Summer and winter are the other two seasons, covering the months of March-May and January-February, respectively.…”

“…Omitting the days with large data gaps and rain/dense clouds, 423 days of surface data were available for further analysis from 3 years of MBLM measurements. The range-time plots of spectral moments (SNR, vertical velocity (w) and σ ) from sodar and the wind profiler are examined for the clear growth and decay of ABL and convection/precipitation contamination (Grimsdell et al, 2002;Rao et al, 2008). Based on the above criteria, a total of 530 and 482 clear-sky days of sodar and profiler, respectively, were only selected (from data set 1) for further analysis.…”

Relationship between stable isotope ratios and drop size distribution in tropical rainfall

“…The stratiform and convective rain can be distinguished by using Z or R values or by combining any of these parameters (see Rao et al 2008b for various classification schemes). For the present study, a reflectivity threshold of 40 dBZ (same as that used by ground-and space-borne radars) is employed to delineate stratiform and convective rain regimes.…”