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Computational Models for the Prediction of Severe Thunderstorms Over East Indian Region

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Computational Models for the Prediction of Severe Thunderstorms Over East Indian Region COMPUTATIONAL MODELS FOR THE PREDICTION OF SEVERE THUNDERSTORMS OVER EAST INDIAN REGION Thesis submitted by LITTA A J in partial fulfilment of the requirements for the award of the degree of DOCTOR OF PHILOSOPHY Under the Faculty of Technology DEPARTMENT OF COMPUTER SCIENCE Cochin University of Science and Technology Cochin - 682 022, Kerala, India November 2013 COMPUTATIONAL MODELS FOR THE PREDICTION OF SEVERE THUNDERSTORMS OVER EAST INDIAN REGION Ph.D Thesis Author: Litta A J Department of Computer Science Cochin University of Science and Technology Cochin - 682 022, Kerala, India [email protected] Supervisor: Dr. Sumam Mary Idicula Professor and Head Department of Computer Science Cochin University of Science and Technology Cochin - 682 022, Kerala, India [email protected] November 2013 CERTIFICATE This is to certify that the work presented in this thesis entitled “Computational Models for the Prediction of Severe Thunderstorms over East Indian Region” submitted to Cochin University of Science and Technology, in partial fulfilment of the requirements for the award of the Degree of Doctor of Philosophy in Computer Science is a bonafide record of research work done by Litta A. J. in the Department of Computer Science, Cochin University of Science and Technology, under my supervision and guidance and the work has not been included in any other thesis submitted previously for the award of any degree. Kochi Dr. Sumam Mary Idicula November 2013 (Supervising Guide) Declaration I hereby declare that the work presented in this thesis entitled “Computational Models for the Prediction of Severe Thunderstorms over East Indian Region” submitted to Cochin University of Science and Technology, in partial fulfilment of the requirements for the award of the Degree of Doctor of Philosophy in Computer Science is a record of original and independent research work done by me under the supervision and guidance of Dr. Sumam Mary Idicula, Professor and Head, Department of Computer Science, Cochin University of Science and Technology. The results presented in this thesis have not been included in any other thesis submitted previously for the award of any degree. Kochi Litta A. J. November 2013 The research work leading to PhD is a very intense process, which produced challenging, and interesting moments and experiences in my life. On those moments it was great to have the help of many people, who have strongly supported me in each phase of the thesis work. It is now my turn to express my gratitude to all of them. First and foremost thanks and supreme glory to the God Almighty for providing me the health and wisdom towards the completion of this research work. I would like to express my immense gratitude to Dr. Sumam Mary Idicula, Professor and Head, Department of Computer Science, Cochin University of Science and Technology for her guidance throughout the thesis work. I thank her for providing me an opportunity to do research under her supervision. Her knowledge, invaluable comments, caring and supportive attitude etc. were the main driving forces of my work. I am grateful to Dr. K. Poulose Jacob, Professor, Department of Computer Science and Pro-Vice Chancellor, Cochin University of Science and Technology for providing constant encouragement, support and scholarly advice throughout my research period. I would like to thank Dr. U. C. Mohanty, Professor, Centre for Atmospheric Sciences, Indian Institute of Technology (IIT), Delhi for providing guidance and necessary computer facilities to carry out the Numerical Weather Prediction (NWP) modeling part of the thesis. His constant encouragement and valuable suggestions could help me in undertaking this observational and NWP modeling work. Special thanks must also go to Dr. Someshwar Das, Scientist, National Centre for Medium Range Weather Forecasting, Noida, Dr. Ajith Abraham, Machine Intelligence Research Labs, Washington, Dr. K. Mohankumar, Dr. P. V. Joseph and Mr. B. Chakrapani, Department of Atmospheric Sciences, Cochin University of Science and Technology for their valuable suggestions and comments which have indeed helped me to improve my works. Thanks are due to the data providers specially India Meteorological Department (IMD). I extent my sincere thanks to Dr. David Peter S, Ms. Sonia Sunny, all teaching and non-teaching staff and research scholars of my department for their cordial relation and help. I am thankful to all my teachers throughout my education for making me what I am today. I owe heartfelt thanks to my parents, Mr. A. U. John and Mrs. Rosy A. A, whose encouragement and support always kept me overcoming hard times during this work. I extend my gratitude to my husband Mr. C. Naveen Francis, who has always been a constant source of energy, support and encouragement during the difficult situations. Thanks to all my relatives, friends and well-wishers for their good wishes, love and support at various stages of my study. Litta A. J. Preface Thunderstorm is one of the most spectacular weather phenomena in the atmosphere. Many parts over the Indian region experience thunderstorms at higher frequency during pre-monsoon months (March- May), when the atmosphere is highly unstable because of high temperatures prevailing at lower levels. Most dominant feature of the weather during the pre-monsoon season over the eastern Indo-Gangetic plain and northeast India is the outburst of severe local convective storms, commonly known as ‘Nor’wester’ or ‘Kalbaishakhi’. The severe thunderstorms associated with thunder, squall line, lightning and hail cause extensive losses in agriculture, damage to structure and also loss of life. The casualty due to lightning associated with thunderstorms in this region is the highest in the world. The highest numbers of aviation hazards are reported during occurrence of these thunderstorms. In India, 72% of tornadoes are associated with this thunderstorm. The severe thunderstorms have significant socio-economic impact over eastern and northeastern parts of India. An accurate location specific and timely prediction is required to avoid loss of lives and property due to strong winds and heavy precipitation associated with these storms. Forecasting thunderstorms is one of the most difficult tasks, due to their rather small spatial and temporal extension and the inherent non-linearity of their dynamics and physics. The improvement in prediction of these important weather phenomena is highly handicapped due to lack of observations and insufficient understanding. Realizing the importance of improved understanding and prediction of this weather event, an attempt is made to study severe thunderstorms during the pre- monsoon season of 2006, 2007 and 2009. The improvement in the prediction of this severe weather phenomenon has been done in this work using empirical and dynamical approaches. The most widely used empirical approach for weather prediction is artificial neural network (ANN). ANN based approach can be used to model complex relationships between inputs and outputs or to find patterns in data. The recent advances in neural network methodology for modeling nonlinear, dynamical phenomena along with the impressive successes in a wide range of applications, motivated to investigate the application of ANNs for the prediction of thunderstorms. The second approach is based upon equations and forward simulations of the atmosphere, and is often referred to as computer modeling (Numerical Weather Prediction (NWP)). These models are computer programs that take the analysis as the starting point and evolve the state of the atmosphere forward in time using the understanding of physics and fluid dynamics. The complicated equations which govern how the state of a fluid changes with time require high performance computers to solve them. The output from the model provides the basis of the thunderstorm forecast. Accurate prediction requires knowledge about “where” and “when” storms will develop and how they will evolve. NWP models can allow forecasters to anticipate not only, whether or not thunderstorms will develop in an environment, but also such things as thunderstorm movement, type, severity and longevity. In India, studies related to modeling of clouds are very scarce, particularly in intense thunderstorm events. Understanding the importance of these weather events and their socio-economic impact, this research has been initiated for analyzing and predicting severe thunderstorm events over east Indian region with most commonly known NWP models namely Non- hydrostatic Mesoscale Model (NMM) and Advanced Research WRF (ARW) model core of Weather Research and Forecasting (WRF) system. The thesis, presented in seven chapters deals with the work carried out in designing and developing computational models for the prediction of severe thunderstorms over east Indian region. Chapter 1 introduces the severity of thunderstorms over Indian region and its social impact and prediction challenges. Chapter 2 provides a brief description about computational models used for the prediction of thunderstorms over Indian region. It gives the introduction to ANN and NWP modeling. In this chapter, the definition of neural network, a brief history, the architecture of neural networks, the various activation functions used, the different learning processes, and the various learning algorithms are dealt with. This chapter also gives a brief introduction of numerical modeling and its governing equations, grid structure, boundary conditions and parameterization. The details of WRF modeling system and
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