Study of Weak Intensity Cyclones Over Bay of Bengal Using WRF Model
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Internal Displacement in Pakistan
REASSESSING INTERNAL DISPLACEMENT IN SOUTH ASIA REASSESSING INTERNAL DISPLACEMENT IN SOUTH ASIA ii Reassessing Internal Displacement in South Asia The views and opinions entailed in the papers presented at the conference are not essentially of South Asians for Human Rights (SAHR). Published by: South Asians for Human Rights (SAHR) 345/18 Kuruppu Road, (17/7 Kuruppu Lane) Colombo 08, Sri Lanka Telephone: +94 11 5549183 Tel/Fax: +94 11 2695910 Email: [email protected] Website: www.southasianrights.org Printed and Published in 2013 All rights reserved. This material is copyright and not for resale, but may be reproduced by any method for teaching purposes. For copying in other circumstances for re-use in other publications or for translation, prior written permission must be obtained from the copyright owner. ISBN: 978-955-1489-15-1 Cover Photograph: Dilshy Banu Printed and bound in Sri Lanka by Wits Originals Reassessing Internal Displacement in South Asia iii Table of Contents Acknowledgements xi Abbreviations xii Introduction 1 AFGHANISTAN 17 Report on the SAHR Afghanistan National Consultation 19 on IDPs Introduction 19 Main Discussion Points 20 General Discussion 25 Recommendations 25 Annexure 27 List of Participants 27 BANGLADESH 31 Background Report - The Internally Displaced People of 33 Bangladesh Introduction 33 Bangladesh and the Internally Displaced People 35 Section I: Climate IDPs 38 Section II: Conflict IDPs 42 Displacement in the CHT Region 42 Displacement of Religious Minorities 51 Section III: The Eviction of Slum-Dwellers and Sex 54 Workers Concluding Remarks 57 iv Reassessing Internal Displacement in South Asia Report on the SAHR Bangladesh National Consultation on 59 IDPs 1. -
Model for Simulating Typhoons
Nat. Hazards Earth Syst. Sci., 14, 2179–2187, 2014 www.nat-hazards-earth-syst-sci.net/14/2179/2014/ doi:10.5194/nhess-14-2179-2014 © Author(s) 2014. CC Attribution 3.0 License. The efficiency of the Weather Research and Forecasting (WRF) model for simulating typhoons T. Haghroosta1, W. R. Ismail2,3, P. Ghafarian4, and S. M. Barekati5 1Center for Marine and Coastal Studies (CEMACS), Universiti Sains Malaysia, 11800 Minden, Pulau Pinang, Malaysia 2Section of Geography, School of Humanities, Universiti Sains Malaysia, 11800 Minden, Pulau Pinang, Malaysia 3Centre for Global Sustainability Studies, Universiti Sains Malaysia, 11800 Minden, Pulau Pinang, Malaysia 4Iranian National Institute for Oceanography and Atmospheric Science, Tehran, Iran 5Iran Meteorological Organization, Tehran, Iran Correspondence to: T. Haghroosta ([email protected]) Received: 18 December 2013 – Published in Nat. Hazards Earth Syst. Sci. Discuss.: 14 January 2014 Revised: – – Accepted: 29 July 2014 – Published: 26 August 2014 Abstract. The Weather Research and Forecasting (WRF) 1 Introduction model includes various configuration options related to physics parameters, which can affect the performance of the model. In this study, numerical experiments were con- Numerical weather forecasting models have several configu- ducted to determine the best combination of physics param- ration options relating to physical and dynamical parameter- eterization schemes for the simulation of sea surface tem- ization; the more complex the model, the greater variety of peratures, latent heat flux, sensible heat flux, precipitation physical processes involved. For this reason, there are several rate, and wind speed that characterized typhoons. Through different physical and dynamical schemes which can be uti- these experiments, several physics parameterization options lized in simulations. -
Prediction of Landfalling Tropical Cyclones Over East Coast of India in the Global Warming Era
Prediction of Landfalling Tropical Cyclones over East Coast of India in the Global Warming Era U. C. Mohanty School of Earth, Ocean and Climate Sciences Indian Institute of Technology Bhubaneswar Outline of Presentation • Introduction • Mesoscale modeling of TCs with MM5, ARW, NMM and HWRF systems • Conclusions and Future Directions Natural disasters Hydrometeorologi- Geophysical cal Disasters: Disasters: Earthquakes Cyclones Avalanches Flood Land slides Drought Volcanic eruption Tornadoes Dust storms Heat waves Cold waves Warmest 12 years: 1998,2005,2003,2002,2004,2006, 2001,1997,1995,1999,1990,2000 Global warming Period Rate 25 0.1770.052 50 0.1280.026 100 0.0740.018 150 0.0450.012 Years /decade IPCC Introduction • Climate models are becoming most important tools for its increasing efficiency and reliability to capture past climate more realistically with time and capability to provide future climate projections. • Observations of land based weather stations in global network confirm that Earth surface air temperature has risen more than 0.7 ºC since the late 1800s to till date. This warming of average temperature around the globe has been especially sharp since 1970s. • The IPCC predicted that probable range of increasing temperature between 1.4 - 5.8 ºC over 1990 levels by the year 2100. Contd…… • The warming in the past century is mainly due to the increase of green house gases and most of the climate scientists have agreed with IPCC report that the Earth will warm along with increasing green house gases. • In warming environment, weather extremes such as heavy rainfall (flood), deficit rainfall (drought), heat/cold wave, storm etc will occur more frequent with higher intensity. -
Climate Chage – Impact of Different Cyclones * Dr. P. Subramanyachary
Volume : 2 | Issue : 1 | January 2013 ISSN - 2250-1991 Research Paper Engineering Climate Chage – Impact of Different Cyclones * Dr. P. Subramanyachary ** Dr. S. SiddiRaju * Associate Professor, Dept of MBA, Siddhrath Institute of Engineering and Tech, Puttur, Chittoor, Andhrapradesh ** Associate Professor, Dept of Civil Eng., Siddhrath Institute of Engineering and Tech, Puttur, Chittoor, Andhrapradesh ABSTRACT Climate is a complex and interactive system. Climate is the long-term average of a region's weather events, thus the phrase ‘climate change’ represents a change in these long-term weather patterns. With the advent of the stability and statistics era, Climate data series started working as powerful basis for risk management. The system post-1970s was revolutionized with the arrival of Satellites which boosted the science of “climate system” and global monitoring. Another important issue Global Warming refers to an average increase in the Earth's temperature, which in turn causes changes in climate patterns. By continuing research and development the climate change has to be estimated and also measures to be taken for reducing damage of assets and human lives and protection of environment. Keywords: Climate Change, Global Warming, Sustainable Development INTRODUCTION: 5. Industrial revolution Climate is a complex and interactive system. It consists of 6. Green House gases the atmosphere, land surface, snow and ice, oceans and 7. Vehicles other water bodies, and living beings. Among these, the 8. Large scale of wastages first component, atmosphere characterizes climate. Climate 9. Deforestation is the long-term average of a region’s weather events, thus 10. Exploitation of Natural resources the phrase ‘climate change’ represents a change in these long-term weather patterns. -
Monsoon Cyclones. 52
STUDY ON VERTICAL STRUCTURE OF TROPICAL CYCLONES FORMED IN THE BAY OF BENGAL DURING 2007-2016 A dissertation submitted to the Department of Physics, Bangladesh University of Engineering and Technology (BUET), Dhaka in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN PHYSICS Submitted by SHAIYADATUL MUSLIMA Roll No.: 0416142506F Session: April/2016 DEPARTMENT OF PHYSICS BANGLADESH UNIVERSITY OF ENGINEERING AND TECHNOLOGY (BUET), DHAKA-1000, BANGLADESH April, 2019 i CANDIDATE'S DECLARATION It is hereby declared that this thesis or any part of it has not been submitted elsewhere for the award of any degree or diploma. Signature of the Candidate ---------------------------------------------------- SHAIYADATUL MUSLIMA Roll No.: 0416142506F Session: April/2016 ii iii Dedicated To My Beloved Parents iv CONTENTS Page No. List of Table viii List of Figures ix Abbreviations xv Acknowledgement xvi Abstract xvii Chapter No. Page No. CHAPTER 1: INTRODUCTION 1 1 1.1 prelude 1.2 objectives of the research 2 CHPATER 2: LITERATURE REVIEW 2.1 previous work 4 2.2 Overview of the study 6 2.2.1 Cyclone 6 2.2.2 Detail of tropical cyclone 6 2.2.3 Cyclone season 7 2.2.4 Tropical cyclone basins 8 2.2.5 Bay of Bengal 9 2.2.6 Classifications of tropical cyclone intensity 10 2.2.7 Physical structure of tropical cyclone 11 2.2.8 Environmental parameters related to cyclone 13 2.2.8.1Wind 13 2.2.8.2 Wind shear 14 2.2.8.3 Temperature 15 2.2.8.4 Vorticity 16 2.2.8.5 Equivalent potential temperature 18 2.2.8.6 Relative humidity 18 CHAPTER -
Measurement of Total Ozone, D-UV Radiation, Sulphur Dioxide And
MAUSAM, 72, 1 (January 2021), 35-56 551.515.2 : 551.509 (267) Evolution of IMD’s operational extended range forecast system of tropical cyclogenesis over North Indian Ocean during 2010-2020 D. R. PATTANAIK and M. MOHAPATRA India Meteorological Department, Ministry of Earth Sciences, Lodi Road, New Delhi – 110 003, India e mail : [email protected] सार — मॉनसूनोर ऋतु (अटूबर-दसंबर; OND) को उर हंद महासागर (NIO) और वशेष प से बगं ाल क खाड़ (BoB) म अिधक तीता के उणकटबधं ीय चवात (TCs) क उप के िलए जाना जाता है। 2010 से 2020 के दौरान गितकय मॉडल पर आधारत चवातजनन क संभावना के चालनामक वतारत अविध पवू ान मु ान (ERF) वकिसत करने पर चचा क गई है। ECMWF तथा CFSv1 गितकय मॉडल पर आधारत चवातजनन क संभावना के चालनामक वतारत अविध पवू ान मु ान (ERF) का आरंभ वष 2010 म नवबं र के थम साह के दौरान बने चडं चवाती तूफान ‘जल’ के युसगं त िनपादन के साथ हुआ था। वष 2015 क सय अरब सागर और िनय बगं ाल क खाड़ सहत चवात ऋतु म भी भली भाँित वातवक समय ERF िनपादत कए गए थे। भारत मौसम वान वभाग ारा 2017 म चालनामक ERF के िलए CFSv2 युमत मॉडल लाग ू कया गया और इसके आधार पर चार साह के िलए गितकय परवत जसै े िमलता, अपसारता, ऊवाधर पवन अपपण तथा मय-तर सापेक आता के मायम से जने ेिसस पोटिशयल परै ामीटर (GPP) क गणना क जाती है तथा 24-30 नवबं र, 2017 के ‘ओखी’ चवात हेत ु इसका परण कया गया था। ‘ओखी’ चवात के मामले म केवल एक साह के लीड समय के साथ ERF म GPP का भली भािँ त पवू ान मु ान कया गया। उनत GPP (IGPP) का उपयोग वष 2019 से कया जा रहा है, जसे महासागर और भूिम दोन े म योग कया जा सकता है। IGPP के मामले म GPP क िमलता तथा मय ोभमंडलीय आता क श दावली को यथावत रखा गया है, परंतु तापगितक क श दावली को मापन तथा 1000 और 500 hPa के मय औसत समक वभव तापमान (θe) के प म संशोिधत कया गया। येक िड बदं ु के िलए 850 और 200 hPa के बीच ऊवाधर अपपण को 100 और 200 क.मी. -
Draft Code of Conduct for the Sustainable Management of Mangrove Ecosystems
A draft code of conduct for the sustainable management of mangrove ecosystems DRAFT CODE OF CONDUCT FOR THE SUSTAINABLE MANAGEMENT OF MANGROVE ECOSYSTEMS A draft code of conduct for the sustainable management of mangrove ecosystems World Bank, ISME, cenTER Aarhus (2003). Draft Code of Conduct for the Sustainable Management of Mangrove Ecosystems. Prepared by: Professor Donald J. Macintosh Centre for Tropical Ecosystems Research (cenTER Aarhus) E-mail: [email protected] and Dr. Elizabeth C. Ashton Centre for Tropical Ecosystems Research (cenTER Aarhus) E-mail: [email protected] Front Cover Pristine Mangrove, Sematan, Sarawak, Degraded mangrove, Ca Mau Province, Lower Eastern Malaysia. Photo by: Donald J. Mekong Delta, Vietnam. Photo by: Thomas Macintosh, cenTER Aarhus Nielsen, cenTER Aarhus Woman carrying mangrove fuelwood in A coastal shrimp farm in Ceará, Brazil. Photo Ghana. Photo by: Donald J. Macintosh, by: Donald J. Macintosh, cenTER Aarhus cenTER Aarhus * WORK IN PROGRESS PLEASE REFER TO THE AUTHORS WITH COMMENTS OR FOR INFORMATION Based on consultations in South and Southeast Asia (21-23 October, 2002), Africa (17-19 February, 2003) and Central and South America (17-19 March, 2003). - 1 - A draft code of conduct for the sustainable management of mangrove ecosystems TABLE OF CONTENTS TABLE OF CONTENTS ......................................................................................................................................1 PREFACE ..............................................................................................................................................2 -
Determining the Sensitive Parameters of WRF Model for the Prediction of Tropical Cyclones in Bay of Bengal Using Global Sensitivity Analysis and Machine Learning
Determining the sensitive parameters of WRF model for the prediction of Tropical cyclones in Bay of Bengal using Global sensitivity analysis and Machine learning Harish Bakia, Sandeep Chintaa, C.Balajia,∗, Balaji Srinivasana aIndian Institute of Technology Madras, Chennai 600036, India Abstract The present study focuses on identifying the parameters from the Weather Research and Forecasting (WRF) model that strongly influence the prediction of tropical cyclones over the Bay of Bengal (BoB) region. Three global sensitivity analysis (SA) methods namely the Morris One-at-A-Time (MOAT), Multivariate Adaptive Regression Splines (MARS), and surrogate-based Sobol' are employed to identify the most sensitive parameters out of 24 tunable parameters corresponding to seven parameterization schemes of the WRF model. Ten tropical cyclones across different categories, such as cyclonic storms, severe cyclonic storms, and very severe cyclonic storms over BoB between 2011 and 2018, are selected in this study. The sensitivity scores of 24 parameters are evaluated for eight meteorological variables. The parameter sensitivity results are consistent across three SA methods for all the variables, and 8 out of the 24 parameters contribute 80% − 90% to the overall sensitivity scores. It is found that the Sobol' method with Gaussian progress regression as a surrogate model can produce reliable sensitivity results when the available samples exceed 200. The parameters with which the model simulations have the least RMSE values when compared with the observations are considered as the optimal parameters. Comparing observations and model simulations with the default and optimal parameters shows that predictions with the optimal set of parameters yield a 19.65% improvement in surface wind, 6.5% in surface temperature, and 13.2% in precipitation predictions, compared to the default set of parameters. -
Laboratory for Atmospheres 2010 Technical Highlights
NASA/TM—2011–215877 Laboratory for Atmospheres 2010 Technical Highlights July 2011 Cover Photo Captions: Top Left: Scott Janz with the ACAM Instrument prior to the GloPac mission. ACAM is one of 11 science instruments that were carried by the remotely operated high-altitude aircraft during the 2010 NASA GloPac mission. Top Center: Matt McGill and Robert Rivera prepare the CPL Instrument for the GloPac mission. CPL is one of 11 science instruments that were carried by the remotely operated high-altitude aircraft during the 2010 NASA GloPac mission. Top Right: Gerry Heymsfield with Matt McLinden and Lihua Li installing the HIWRAP instrument for the GRIP mission. HIWRAP is one of four science instruments that were carried by the remotely operated high-altitude aircraft during the 2010 NASA GRIP hurricane study. Background: NASA’s AV-6 Global Hawk cruises over the NASA Dryden Flight Research Center. The AV-6 carried the GloPac mission payload. Bottom Left: Forecaster Leslie Lait (foreground) and Lenny Pfister (background) supported the GloPac mission using products supplied by the GMAO to plan Global Hawk flights. Bottom Center: Time Warner Cable SoCal News’’ Cody Urban and Keli Moore interview NASA atmospheric physicist Paul Newman, co-mission scientist for the GloPac environmental science mission, beside a NASA Global Hawk aircraft at NASA’s Dryden Flight Research Center. NASA Photo / Tom Tschida Bottom Right: Lihua Li prepares to install the HIWRAP, on the underside of a NASA Global Hawk. NASA/TM—2011–215877 Laboratory for Atmospheres 2010 Technical Highlights National Aeronautics and Space Administration Goddard Space Flight Center Greenbelt, Maryland 20771 July 2011 The NASA STI Program Offi ce … in Profi le Since its founding, NASA has been ded i cated to the • CONFERENCE PUBLICATION. -
Is Cyclone JAL Stimulated Chlorophyll-A Enhancement Increased Over the Bay of Bengal?
Mini Review Oceanogr Fish Open Access J Volume 10 Issue 5 - October 2019 Copyright © All rights are reserved by K Muni Krishna DOI: 10.19080/OFOAJ.2019.10.555800 Is Cyclone JAL Stimulated Chlorophyll-A Enhancement Increased Over the Bay of Bengal? Muni Krishna K1* and Manjunatha B2 1Department of Meteorology and Oceanography, Andhra University, India 2Department of Marine Geology, Mangalore University, India Submission: September 09, 2019; Published: October 18, 2019 Corresponding author: K Muni Krishna, Department of Meteorology and Oceanography, Andhra University, Visakhapatnam, India Abstract Tropical cyclone JAL developed in the south Bay of Bengal and worn south coastal Andhra Pradesh on November 7, 2010. The main objective of this study was to investigate the ocean’s response before and after the passage of cyclone in the southern Bay by utilizing the multi-satellite approach. For this study, I used Sea Surface Temperature (SST), Chlorophyll-a (Chl-a), and Sea Surface Height (SSH) data production from different remote sensing satellites. JAL induced large scale of upwelling within large cooling of sea surface (~ 1.2°C), enhancement of Chl-a ~ 0.4 mg/m3 in the open ocean and 2-3mg/m3 along the coast, and decrease of SSH (~15cm) in the southeast Bay of Bengal after its passage. After the JAL, the upwelling area expanded rapidly on the shelf break. Chl-a images also revealed high values (~3.3mg/m3) appeared in the shelf region, where the high Chl-a patterns matched the upwelling in terms of location and time. Large offshore surface cooling was also observed mainly to Bay of Bengal.