Mean vertical velocities and their variations observed with Indian mesosphere-stratosphere-troposphere (MST) radar located at Gadanki (13.5degreesN, 79.2degreesE), a tropical station in India, are presented. In this study, a comparison has been made between Indian MST radar-measured vertical velocities and those computed by radiosonde data using kinematic and adiabatic methods. From this study, it is observed that the signs of vertical motion estimated by the kinematic method agree well with MST-radar values, although the magnitudes differ, except in a small region where radar vertical velocity changes in sign from negative to positive in the lower troposphere during monsoon months. This upward motion in this season is attributed to horizontal convergence due to change in wind direction that is not observed in radiosonde data when averaged, because of poor height resolution of the radiosonde (500 m or more varying with height) as compared with the radar range resolution (150 m). Profiles of vertical velocities computed using the kinematic method tend to approach the shape of radar vertical velocity profiles as the separation of the radiosonde network decreases. The vertical velocities computed using the adiabatic method are found to be small and are attributed to a small tilt in isentropic surfaces caused by small latitudinal temperature gradients commonly observed in the Tropics; they also may be partly due to neglect of diabatic heating. The bias between radar and radiosonde vertical velocities tends to decrease when the time used for averaging of MST radar data is approximately 6 h (before and after 3-h average).

Simultaneous observations of Indian Mesosphere-Stratosphere-Troposphere (MST) radar, Lower Atmospheric Wind Profiler (LAWP) and disdrometer, located at Gadanki (13.5°N, 79.2°E), over two seasons are used to derive the Z-R relationships, of the form Z = ARb, for different types of precipitation and for different seasons. Disdrometer data are classified into three types, convection, transition, and stratiform, based on the variation of the median volume diameter D0 with the rain rate R. The disdrometer classification is verified by comparing with the profilers classification, based on reflectivity (in terms of range corrected signal-to-noise ratio), Doppler velocity, spectral width, and vertical air velocity. Overall agreement between the two classification schemes is found to be reasonable. The variations in the coefficient A and the exponent b in the Z-R relation for the case studies presented here are explained with the help of variations in drop size distribution parameters. From the total data the percentage occurrence of precipitation is found to be 55% stratiform, 9% convective, and 36% transition, whereas the total rainfall is 12, 54, and 34%, respectively. Interestingly, the exponent b (coefficient A) is found to be smaller (larger) in the case of stratiform (convective) precipitation than that in convective (stratiform) precipitation, in contrast to the earlier results. The values of A and b are also derived for different monsoon seasons.

Retrieval of vertical profiles of temperature and humidity parameters using a VHF radar is described in this paper. For this, Indian MST radar located at Gadanki (13.5° N, 79.2° E) has been operated in a special mode. First, vertical velocities are collected continuously using the radar and are subjected to Fast Fourier Transform (FFT) analysis to obtain Brunt-Väisälä oscillations. From the measured Brunt-Väisälä oscillations, temperature profile is obtained from the radar observations following Revathy et al. (1996). The various terms required for the retrieval of vertical profiles of humidity are the eddy dissipation rate, ε, the volume reflectivity, η, and the potential refractive index gradient, M. The eddy dissipation rate, ε, is calculated from the spectral width after removing the effects due to non-turbulence. The volume reflectivity, η, of the turbulence scattering is calculated using the signal-to-noise ratio as a function of height. The potential refractive index gradient, M, is evaluated using the measured Brunt-Väisälä oscillations, the eddy dissipation rate and the volume reflectivity, η. Vertical profiles of humidity are retrieved following Tsuda (1997) using the radar derived temperature as well as the balloon measured temperature and are compared with the humidity as measured by the radiosonde. The sign of the potential refractive index gradient, M, is taken from the simultaneous measurements of balloon soundings. The retrieved vertical profiles of temperature and humidity have been compared with the radiosonde data, which are released simultaneously with the radar observations at the radar site. A fairly good comparison is seen between the two measurements on some days and there are some discrepancies on some other days. The strengths and limitations in estimating the vertical profiles of temperature and humidity from the radar observations are discussed.Key words. Atmospheric composition and structure (pressure, density and temperature; enhancements and techniques)