International Journal of Geosciences, 2012, 3, 44-49 http://dx.doi.org/10.4236/ijg.2012.31006 Published Online February 2012 (http://www.SciRP.org/journal/ijg) A Comparative Study of Cloud Liquid Water Content from Radiosonde Data at a Tropical Location Swastika Chakraborty 1 , Animesh Maitra 2 1 Department of ECE, JIS College of Engineering, Kalyani, India 2 S. K. Mitra Centre for Research in Space Environment, Institute of Radiophysics and Electronics, University of Calcutta, Kolkata, India Email: swas_jis@yahoo.com, animesh.maitra@gmail.com Received June 10, 2011; revised August 16, 2011; accepted October 25, 2011 ABSTRACT In this paper, some features of cloud liquid water content with respect to rain and water vapor are presented. Cloud liq- uid water density profile is obtained from radiosonde observation with Salonen’s model and Karsten’s model at Kolkata, a tropical location in the Indian region. Cloud liquid water contents (LWC) are obtained from these profiles which show a prominent seasonal variation. The monsoon months exhibit much higher values of LWC than in other months. How- ever Salonen’s model yields higher LWC values than that obtained with Karsten’s model. The variation of daily total rainfall with LWC shows a positive relationship indicating the role of LWC in controlling the rainfall. Also the varia- tion pattern of LWC with integrated water vapor (IWV) content of the atmosphere indicates that a threshold value of water vapor is required for cloud to form and once cloud is formed LWC increases with IWV. Keywords: Cloud Liquid Water Contents (LWC); Integrated Water Vapor (IWV) 1. Introduction The study of cloud properties is increasingly important in the context of climate research of troposphere. One of the sources of global warming is the cloud feedback and wa- ter vapour feedback. Again as relative humidity has a greater impact on cloud formation, knowledge of mois- ture distribution of troposphere is necessary to know the cloud process [1]. Parameterization of cloud component is very much necessary as cloud plays a dual role in af- fecting outgoing long wave radiation (OLR) as well as reflecting incoming solar radiation [2]. Cloud Liquid water content (LWC) plays also a dominant role in att- enuating electromagnetic signal [3]. Stability of air is another important matter of concern as cloud develop- ment is associated with it. As air parcel is very large, it is realistically considered that it does not exchange any heat with surrounding as it rises and due to the expansion in volume it cools at a relatively constant rate. Depending on whether the air is saturated or unsaturated, the impor- tant parameter of cloud formation i.e. moist adiabatic lapse rate (MALR) or dry adiabatic lapse rate (DALR) comes into the picture. To know the profile of liquid wa- ter content and thereby total liquid water content for a particular day and also the amount of water vapour in the atmosphere the knowledge of humidity profile is also important. Water vapour can be related to low level hu- midity and low atmospheric humidity can be obtained as a function of surface temperature [4]. Retrieval of water vapour by Special Sensor Microwave Imager (SSMI) shows the dependence of water vapour is not only on humidity but also on atmospheric circulation [5]. Over the past two decades many retrieval methods have been obtained for water vapour and cloud LWC. In case of water vapour no method is identified as the most accurate as there is a mismatch between satellite footprint and in situ measurement. In addition, for LWC cloud shape and structure causes the unreliability of the measured data. Retrieval of the profile of cloud LWC by Radiometer shows the result in clear and cloudy condition. A com- parison of radiometric profile is done with sounding from super cooled cloud liquid sensor carried by radiosonde. But not more than 50% agreement was observed between the two processes [6]. Though the profile of temperature and water vapour can be given by Laser radar (Lidar) and Fourier Transform Infrared Spectrometer (FTIR), but in presence of cloud neither the Lidar nor the FTIR will work. In a different approach, as cloud reflectivity is proportional to cloud drop radius and as cloud LWC is proportional to the volume of the cloud drops, LWC can be derived from reflectivity factor. But an error more than one order of magnitude of actual value is obtained as the relation is not linear. There are some other meth- ods also for retrieving cloud LWC. For the methods us- Copyright © 2012 SciRes. IJG