Diurnal variability of stability indices observed using radiosonde observations over a tropical station: Comparison with microwave radiometer measurements

Convection plays an important role in maintaining the thermodynamic structure of the atmosphere particularly in the tropical regions and it is often associated with clouds and precipitation. In the present study we report the diurnal variation of various stability indices observed using intensive radiosonde observations made during October 2010 to October 2011 over Indian tropical region, Gadanki (13.5°N, 79.2°E). Simultaneous co-located microwave radiometer (MWR) observations collected during April–October 2011 are used for comparison. Detailed comparison between these two independent techniques has been made which will be very much useful in assessing the data from MWR for Nowcasting. In general, MWR observations show warm (cold) bias in the temperature, except at 0.5 km, when compared to radiosonde observations below (above) 3–4 km, assuming latter as a standard technique. In case of water vapor, MWR observations show wet (dry) bias below (above) 2–3 km depending on the time. Nevertheless, very good comparison in several convection indices is noticed between the two different techniques, particularly in the trends though some differences are noticed in the amplitudes. For about 25% of time MWR is unable to estimate the Convective Available Potential Energy (CAPE) as equilibrium level is above the altitude that MWR can detect. Strong diurnal variation in CAPE and other thermodynamic parameters is noticed with maximum in the afternoon and minimum in the early morning hours in all the seasons except in winter over this tropical station.

► Diurnal variation of various stability indices observed using intensive GPS radiosonde observations are reported.
► They are compared with simultaneous MWR observations.
► Very good comparison in several convection indices is noticed between the two different techniques.
► This study will be very much useful in assessing the data from MWR for Nowcasting.