ACS  Vol.4 No.1 , January 2014
Assessment of Convective Activity Using Stability Indices as Inferred from Radiosonde and MODIS Data

The combined use of both radiosonde data and three-dimensional satellite derived data over ocean and land is useful for a better understanding of atmospheric thermodynamics. Here, an attempt is made to study the thermodynamic structure of convective atmosphere during pre-monsoon season over southwest peninsular India utilizing satellite derived data and radiosonde data. The stability indices were computed for the selected stations over southwest peninsular India viz: Thiruvananthapuram and Cochin, using the radiosonde data for five premonsoon seasons. The stability indices studied for the region are Showalter Index (SI), K Index (KI), Lifted Index (LI), Total Totals Index (TTI), Humidity Index (HI), Deep Convective Index (DCI) and thermodynamic parameters such as Convective Available Potential Energy (CAPE) and Convective Inhibition Energy (CINE). The traditional Showalter Index has been modified to incorporate the thermodynamics over tropical region. MODIS data over South Peninsular India are also used for the study. When there is a convective system over south peninsular India, the value of LI over the region is less than ?4. On the other hand, the region where LI is more than 2 is comparatively stable without any convection. Similarly, when KI values are in the range 35 to 40, there is a possibility for convection. The threshold value for TTI is found to be between 50 and 55. Further, we found that prior to convection, dry bulb temperature at 1000, 850, 700 and 500 hPa is minimum and the dew point temperature is a maximum, which leads to increase in relative humidity. The total column water vapor is maximum in the convective region and minimum in the stable region. The threshold values for the different stability indices are found to agree with that reported in literature.

Cite this paper
P. Jayakrishnan and C. Babu, "Assessment of Convective Activity Using Stability Indices as Inferred from Radiosonde and MODIS Data," Atmospheric and Climate Sciences, Vol. 4 No. 1, 2014, pp. 122-130. doi: 10.4236/acs.2014.41014.
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