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Study on the Genesis of Low Intensity Tropical Cyclones in the Bay of Bengal Using WRF Model

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Study on the genesis of low intensity tropical cyclones in the Bay of Bengal using WRF Model M. Sc. Thesis BY DEVBROTA KUMAR BISWAS DEPARTMENT OF PHYSICS KHULNA UNIVERSITY OF ENGINEERING & TECHNOLOGY KHULNA-9203, BANGLADESH March-2018 i Study on the genesis of low intensity tropical cyclones in the Bay of Bengal using WRF Model M. Sc. Thesis BY DEVBROTA KUMAR BISWAS ROLL NO: 1655503 SESSION: January-2016 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Physics, Khulna University of Engineering & Technology, Khulna-9203 DEPARTMENT OF PHYSICS KHULNA UNIVERSITY OF ENGINEERING & TECHNOLOGY KHULNA-9203, BANGLADESH March-2018 i DECLARATION This is to certify that the thesis work entitled “Study on the genesis of low intensity tropical cyclones in the Bay Bengal using WRF model” has been carried out by DEVBROTA KUMAR BISWAS in the Department of Physics, Khulna University of Engineering & Technology, Khulna, Bangladesh. The above thesis work or any part of this work has not been submitted anywhere for the award of any degree or diploma. Signature of Supervisor Signature of Candidate (PROFESSOR DR. MD. ABDULLAH ELIAS AKHTER) (DEVBROTA KUMAR BISWAS) ii DEDICATED TO MY PARENTS iii ACKNOWLEDGEMENT With my great manner it is a pleasure for me to express my deepest sense of gratitude and indebtedness to my reverend supervisor Dr. Md. Abdullah Elias Akhter, Professor, Department of Physics, Khulna University of Engineering & Technology, Khulna, for his kind guidance and supervision and for his constant encouragement throughout the research work. His inspiration and friendly cooperation has accelerated my works. I am indebted to Professor Dr. Shibendra Shekher Sikder, Head, Department of Physics, Khulna University of Engineering & Technology for his strong support in various ways during the entire period of my study in this department. I express my heartfelt gratitude and thanks to Professor Dr. Md. Mahbub Alam Department of Physics, Khulna University of Engineering & Technology. Many thanks for their inspiration and advices from the beginning of my study. I gratefully acknowledge Mr. Md. Kamrul Hasan Reza, Associate Professors, Department of Physics, KUET for his cooperation during my theatrical study. I also gratefully acknowledge Mr. Sujit Kumar Shil, Md. Alamgir Hossain, Assistant Professors, Department of Physics, KUET for their cooperation regarding writing the thesis. My personal thankful greetings are to my good friends and well wishers for their help and cooperation. There are numerous people who could not be mentioned individually but their interesting discussions have prompted much thought on various aspects, I would also like to thank them. I would like to express my heart full thanks to my parents for their inspiration, encouragement and multifaceted supports to carry out this thesis work. I am grateful to the KUET authority for approval of the project in the 43rd meeting of CASR, agenda no. 43/23/1 and providing me the relevant facilities to complete this research work. The Author is grateful to National Centre for Atmospheric Research (NCAR), USA for making the WRF (WRF- ARW) model available to modeling community. I am grateful to the authors of the Grid Analysis and Display System software (GrADS) which is used for analytical purposes and displaying Figures. India Meteorological Department (IMD) is acknowledged for providing necessary data over India. Finally, I want to express my gratitude to almighty Creator for his mercy. Devbrota Kumar Biswas iv CONTENTS Page No. Title Page i Declaration Page iii Acknowledgement v Contents vi List of Figures ix List of Tables xiii Nomenclature xiv Abstract xvi Chapter I: Introduction 1 1.1 Introduction 1 1.2 Objective and Scope of the Research Work 6 1.3 Social and Economic Benefit of the Research Work 6 1.4 Structure of the Thesis 7 Chapter II: Literature Review 8 2.1 Overview of the Cyclone 8 2.1.1 Tropical Cyclone Basins 8 2.1.1.1 North Indian Ocean 9 2.1.1.1.1 Bay of Bengal 9 2.1.1.1.2 Arabian Sea 10 2.1.2 Classification of Tropical Cyclones 10 2.1.3 Life Cycle of Tropical Cyclones 11 2.1.4 Physical Structure of Tropical Cyclone 12 2.1.4.1 Wind Field 12 2.1.4.2 Eye and Center 13 2.1.5 Formation Process of Cyclone 15 2.1.5.1 Secondary Circulation 15 2.1.5.2 Primary Circulation 16 2.1.6 Climatologically Conditions for Tropical Cyclone Formation 18 2.1.7 Large Scale Conditions Associated with Tropical Cyclone Formation 19 2.2 Parameter of Tropical Cyclone 20 2.2.1 Dynamic Parameters 20 2.2.1.1 Wind Speed 20 2.2.1.2 Wind Speed at 10m 21 2.2.1.3 Vertical Wind Shear (VWS) 21 v 2.2.1.4 Relative Vorticity 21 2.2.2 Thermodynamic Parameters 22 2.2.2.1 Sea Surface Temperature 22 2.2.2.2 Sea Level Pressure (SLP) 23 2.2.2.3 Relative Humidity 24 2.2.2.4 Convective Available Potential Energy (CAPE) 25 2.2.2.5 Convective Inhibition (CIN) 25 2.3 Weather Research & Forecasting Model 27 2.3.1 Microphysics Schemes in WRF-ARW Model 27 2.3.1.1 WSM 6-class Scheme 28 2.3.2 Cumulus Parameterization 28 2.3.2.1 Kain-Fritsch Scheme 29 2.3.3 Planetary Boundary Layer (PBL) 29 2.3.3.1 Yonsei University (YSU) Scheme 30 2.3.4 Radiation schemes 30 2.3.4.1 Long Wave Radiation 31 2.3.4.2 Short Wave Radiation 31 2.3.5 Map Projection 31 2.3.5.12.3.5.1 Mercator Projection 31 2.3.6 Arakawa Staggered C-grids for Computation Method 32 Chapter III: Model Description and Methodology 33 3.1 Model Domain and Configuration 33 3.2 Description of the Case Study and Methodology 34 Chapter IV: Results and Discussion 39 4.1 Synoptic Situation of the Tropical Cyclone 40 4.1.1 Description of Tropical Cyclone Rashmi 40 4.1.2 Description of Tropical Cyclone Nisha 40 4.1.3 Description of Tropical Cyclone Bijli 41 4.1.4 Description of Tropical Cyclone Viyaru 42 4.2 Dynamic Parameters 44 4.2.1 Wind Speed 10 (m/s) 44 4.2.2 Vertical Wind Shear 50 4.2.3 Vertical Profile of Horizontal Wind 53 4.2.4 Vertical Profile of Vertical Wind 56 4.2.5 Relative Vorticity at 850 hPa 60 4.3 Thermodynamical Parameters 65 4.3.1 Sea Surface Temperature (SST) 65 vi 4.3.2 Mean Sea Level Pressure (MSLP): 70 4.3.3 Vertical Profile of Relative Humidity 79 4.3.4 Convective Available Potential Energy (CAPE): 82 4.3.5 Convective Inhibition (CIN) 88 Chapter V: Conclusions 95 References 98 vii List of Figures Figure. No. Description Page Figure. 2.1: Tropical Cyclone basins 9 Figure. 2.2: Location of Indian Ocean 9 Figure. 2.3: (a) Tropical cyclone formation over the Bay of Bengal 10 (b) Annual cyclone occurrence frequency Figure. 2.4: Schematic view of a typical tropical cyclone 13 Figure. 2.5: A cross section diagram of a mature tropical cyclone 14 Figure. 2.6: Overturning circulation of tropical cyclone 16 Figure. 2.7: Vorticity ≠ 0 Vorticity ≠ 0 Vorticity = 0 22 Figure. 2.8: Cyclonic and anticyclonic phase of vorticity 22 Figure. 3.1: The WRF-ARW domain set up for the study. 33 Figure. 4.1: Cyclone Rashmi, Nisha, Bijli and Viyaru as a cyclone storm 43 Figure. 4.2(a-d): Variation of model simulated wind speed (ms-1) of Normal (2008), 44 Normal (2010), Normal (2011) and Normal (2012) with time. Figure. 4.2(e-h): Variation of observed and model simulated wind speed (ms-1) of TC 45 Rashmi (2008), Nisha (2008), Bijly (2009) and Viyaru (2013) with time. Figure. 4.2(i-l): Variation of observed and model simulated wind speed (ms-1) of TC 46 Rashmi (2008), Nisha (2008), Bijly (2009) and Viyaru (2013) with time. Figure. 4.3(a-d): The spatial distribution of wind speed with the forecast hours 96, 72, 48 47 and 24 hours for 4 normal cases. Figure. 4.3(e-h): The spatial distribution of wind speed with the forecast hours 96, 72, 48 48 and 24 hours for 4 cyclones. Figure. 4.3(i): The spatial distribution of wind speed with the forecast time for 4 49 cyclones. Figure. 4.4(a-d): The spatial distribution of vertical wind shear with the forecast hours 51 96, 72, 48 and 24 hours for 4 normal cases. Figure. 4.4(e-h): The spatial distribution of vertical wind shear with the forecast hours 52 96, 72, 48 and 24 hours for 4 cyclones. Figure. 4.4(i): The spatial distribution of vertical wind shear with the forecast time for 53 4 cyclones. viii Figure. 4.5(a-d): The spatial distribution of horizontal wind with the forecast hours 96, 54 72, 48 and 24 hours for 4 normal cases Figure. 4.5(e-h): The spatial distribution of horizontal wind with the forecast hours 96, 55 72, 48 and 24 hours for 4 cyclones. Figure. 4.5(i): The spatial distribution of horizontal wind with the forecast time for 4 56 cyclones. Figure. 4.6(a-d): The spatial distribution of vertical profile of vertical wind with the 57 forecast hours 96, 72, 48 and 24 hours for 4 normal cases. Figure. 4.6(e-h): The spatial distribution of vertical wind with the forecast hours 96, 72, 58 48 and 24 hours for 4 cyclones. Figure. 4.6(i): The spatial distribution of vertical wind with the forecast time for 4 59 cyclones.
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  • Forecasting of Cyclone Viyaru and Phailin by NWP-Based Cyclone Prediction System (CPS) of IMD – an Evaluation

    Forecasting of Cyclone Viyaru and Phailin by NWP-Based Cyclone Prediction System (CPS) of IMD – an Evaluation

    Forecasting of cyclone Viyaru and Phailin by NWP-based cyclone prediction system (CPS) of IMD – an evaluation SDKotal1, S K Bhattacharya1,∗, SKRoyBhowmik1 and P K Kundu2 1India Meteorological Department, NWP Division, New Delhi 110 003, India. 2Department of Mathematics, Jadavpur University, Kolkata 700 032, India. ∗Corresponding author. e-mail: [email protected] An objective NWP-based cyclone prediction system (CPS) was implemented for the operational cyclone forecasting work over the Indian seas. The method comprises of five forecast components, namely (a) Cyclone Genesis Potential Parameter (GPP), (b) Multi-Model Ensemble (MME) technique for cyclone track prediction, (c) cyclone intensity prediction, (d) rapid intensification, and (e) predicting decaying intensity after the landfall. GPP is derived based on dynamical and thermodynamical parameters from the model output of IMD operational Global Forecast System. The MME technique for the cyclone track prediction is based on multiple linear regression technique. The predictor selected for the MME are forecast latitude and longitude positions of cyclone at 12-hr intervals up to 120 hours forecasts from five NWP models namely, IMD-GFS, IMD-WRF, NCEP-GFS, UKMO, and JMA. A statistical cyclone intensity prediction (SCIP) model for predicting 12 hourly cyclone intensity (up to 72 hours) is developed applying multiple linear regression technique. Various dynamical and thermodynamical parameters as predictors are derived from the model outputs of IMD operational Global Forecast System and these parameters are also used for the prediction of rapid intensification. For forecast of inland wind after the landfall of a cyclone, an empirical technique is developed. This paper briefly describes the forecast system CPS and evaluates the performance skill for two recent cyclones Viyaru (non-intensifying) and Phailin (rapid intensifying), converse in nature in terms of track and intensity formed over Bay of Bengal in 2013.