STUDIES ON THE CHARACTERISTICS OF TROPOSPHERE AND LOWER STRATOSPHERE ASSOCIATED WITH THE PASSAGE OF TROPICAL CYCLONES

In the present thesis, an attempt has been made to study the characteristics of troposphere and lower stratosphere during the passage of tropical cyclones from a tropical station in India using MST radar. MST radar is an excellent tool for studying various features of the atmosphere from ground to mesospheric heights, as it can be operated continuously with good time and altitude resolution. The major objectives are to identify the multiple layers of reflectivity observed in the atmosphere during cyclones, to study the troposphere characteristics during these cyclones and its dependence on cyclone position and intensity, to detect the waves present in the atmosphere, to study the transport of momentum fluxes and to understand stratosphere. The winds in the troposphere and lower stratosphere are greatly affected by the passage of cyclones; the presence of high reflectivity layers below the tropopause suggests the passage of severe weather systems etc. are some of the major findings of the study. The study can be extended further to understand the circulation and dynamics of the atmosphere associated with the passage of tropical cyclones. The gravity wave generation and its characteristics during the passage of storms is another important aspect to be studied in detail.

Studies on the paratial and temporal distribution of surface meteorological parameters over Indian subcontinent

The intention of the present thesis work is to understand the physical processes responsible for climatic variability and predictability of the Indian subcontinent. The study is expected to delineate and emphasize the various boundaries and areas of transition and bring out the regional and temporal characteristics of the meteorological distribution of the country. The results obtained from the study is expected to provide a better understanding the physics of Indian cl imate, which can be incorporated for numerical weather prediction. The results obtained from the present study can be incorporated for climate modelling and long-term prediction of the meteorological parameters over Indian subcontinent

Characteristics of SST over the Arabian Sea and Bay of Bengal

Evolution of mini warm pool in the Arabian Sea just before the onset of southwest monsoon and behavior of SST in the vicinity of weather systems formed during the premonsoon, southwest monsoon and post monsoon seasons were studied using TMI SST data. The Arabian Sea mini warm pool is formed about three weeks ahead of onset of southwest monsoon. Maximum SST is found about one week ahead of monsoon onset and then the warm pool gradually dissipated. Generally, a low-pressure system is formed when the SST exceeds a certain threshold value for the formation of the system. Daily SST values are examined both in Arabian sea and Bay of Bengal to bring out the quantity of increase in SST just before the formation of the system, quantity of rapid decrease in SST during the formation of the system and the number of days required for returning to normal SST. Many cases were examined for pre-monsoon, southwest monsoon and post monsoon seasons to understand the behavior of SST pattern. It is found that the SST increases about 3° C just before the formation of the system and decreases about 4° C during the formation within 2 to 3 days and takes about 4 to 6 days to return to normal SST pattern. However, the SST pattern depends on the weather system

Impact of Western Ghats Orography on the Weather and Climate over Southern Peninsular India-A Mesoscale Modelling Study

The thesis gives a general introduction about the topic include India, the spatial and temporal variation of the surface meteorological parameters are dealt in detail. The general pattern of the winds over the region in different seasons and the generation and movements of the thermally and dynamically originated local wind systems of Western Ghats region has been studied. The modification of the prevailing winds over region by the Palghat Gap and its effect on the mouth regions pf the gap is analysed in great depth. The thesis gives the information of climatic elements of the mountain region such as energy budgets, rainfall studies, evaporation and condensation and the variation in the heat fluxes over the region. The impact of orography is studied in a different approach. The type of hypothetical study gives more insight into the control of mountain on the distribution of meteorological parameter over the study region and helps to quantify the impact of the mountain in varying the weather climate of region. The detailed study of the hydro-meteorological aspects of the main river basins of the region also should be included to the climatic studies for the total understanding of the weather and climate over the region.

Design and Development of Instrumentation Systems to determine the Dry Rubber Content in Natural Rubber Latex

Hevea latex is a natural biological liquid of very complex composition .Besides rubber hydrocarbons,it contains many proteinous and resinous substances,carbohydrates,inorganic matter,water,and others.The Dry Rubber Content (DRC) of latex varies according to season, tapping system,weather,soil conditions ,clone,age of the tree etc. The true DRC of the latex must be determined to ensure fair prices for the latex during commercial exchange.The DRC of Hevea latex is a very familiar term to all in the rubber industry.It has been the basis for incentive payments to tappers who bring in more than the daily agreed poundage of latex.It is an important parameter for rubber and latex processing industries for automation and verious decesion making processes.This thesis embodies the efforts made by me to determine the DRC of rubber latex following different analytical tools such as MIR absorption,thermal analysis.dielectric spectroscopy and NIR reflectance.The rubber industry is still Looking for a compact instrument that is accurate economical,easy to use and environment friendly.I hope the results presented in this thesis will help to realise this goal in the near future.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.