Nazrui Islam's "Study of the Formal/on and Evolution of Tropical Cyclone over Bengal Bay of Weather Research & Forecasting (WRF) Model" has been accepted by the Examination Board in partial fulfillment of the requirements for the degree of Master of Philosophy in the Department of Physics of the University of Engineering and of Technology Khulna, Khulna, Bangladesh, 29 November 2013. Therefore, the model has great potential to predict the formation, development, intensity, track and landfall of tropical cyclones in the Bay of Bengal.
General Introduction
Moreover, high values of cyclone heat potential (CHP> 16 kcal/cm2) are found in the Bay of Bengal regions with high frequency of tropical cyclone formation. Accurate prediction of landfall and tropical cyclone intensity is of great importance in taking proactive mitigation measures to reduce damage to life and property in the vulnerable region. The present study was conducted using Numerical Weather Prediction (NWP).
Adjoining land masses and Geophysical location of the Bay of Bengal
In the Bay of Bengal, tidal currents develop particularly in estuaries such as the Hooghly and Meghna ([29]). Weather conditions are often brutal in the Bay of Bengal as the area is hit by heavy monsoon rains.
Objectives and Scope of the Research Work
Soclo-Economic Benefit of the Research Work
In addition to the prediction of tropical cyclones using NWP models, it is possible to conduct studies to gain in-depth knowledge and insight into their formation, evolution and structural features. A better understanding of tropical cyclones will lead to the development of more advanced and realistic NWP models for the Bay of Bengal.
Layout of the research work
Thus, the improved forecasting of NWP models will provide advance information for cyclone preparedness and rescue operations that can save valuable lives and properties. Moreover, the knowledge gained through this research will create new avenues for further studies for improving the NWP models useful for the Bay of Bengal region.
Chapter-I!: Literature Preview
Tropical Cyclone
- Definition of Tropical cyclone
- Classifications of Tropical Cyclone
- Naming of Tropical Cyclones
Tropical cyclone is warm-core system (relatively warmer than the environment at the same pressure level) while extra-tropical cyclones and polar lows are cold-core frontal systems [11]. The name of the tropical cyclone is well remembered by millions of people as it is.
Onil Ogni Gin
- Life cycle, Structure and Configuration of Tropical Cyclone
- The life cycle of tropical cyclone
- Structure of Tropical cyclone
- Cyclogenesis
- Formation of Tropical Cyclone
- Formation Areas
- Times of Occurrence
- Movement observation and Forecasting of Tropical Cyclone .1 Movement of Tropical Cyclone
- Storm Surges
- Vulnerability of the Bay of Bengal region due to Tropical Cyclones
- Observation
- Number Cl-Number
- Forecasting
- Earlier studies and Chronological improvement of Prediction Models .1 Earlier studies of Tropical Cyclone
- The Weather Research and Forecasting (WRF) Model
- Advanced Research of ARW Model
- Initial Conditions
Analyzing the passage of tropical cyclones across different coastal boundaries of the Bay of Bengal in different seasons discussed the vulnerability of different coasts in different seasons. Intensity is a vital factor of tropical cyclone. Therefore, the filters in ARW DFI are digital low-pass filters, which are applied to the time series of the model fields; the state of the initialized model is the output of the filter at a given time, eg, the analysis time.
IIIH::II
- Cumulus parameterization
- Surface Layer
- Land-Surface Model
- Specified Lower Boundary Conditions
- Planetary Boundary Layer
The surface layer schemes calculate friction velocities and exchange coefficients that enable the calculation of surface heat and moisture fluxes through the land surface models and surface tensions in the planetary boundary layer scheme. These fluxes provide a lower bound condition for the vertical transport performed in the PBL schemes (or the vertical diffusion scheme in the case where a PBL scheme is not nm, such as in the large eddy mode). Note that the large eddy mode with interactive surface fluxes is not yet available in the ARW, but is planned for the near future.] The land surface models have varying degrees of sophistication in dealing with thermal and moisture fluxes in multiple layers of the soil and can also handle with vegetation, root and canopy effects and prediction of surface snow cover.
CAM3 scheme: A spectral-band scheme used in the NCAR Community Atmosphere Model (CAM 3.0) for climate simulations, [173]. CAM3 Schme: A spectral banding scheme used in the NCAR Community Atmosphere Model (CAM 3.0) for climate simulations, [173].
Chapter-Ill
Preface
It is evident that the mortality associated with tropical cyclones is quite high, especially in the Bay of Bengal region, mainly due to poverty. In the present study, an investigation on the formation and evolution of Bay of Bengal tropical cyclones is carried out. It integrates the incompressible, non-hydrostatic Euler equation, which has been introduced into the flow by [31] with the vertical mass coordinates behind the terrain [32]. In the present study three tropical cyclones of different intensity that formed in the Bay of Bengal are selected.
It developed over Bay of Bengal and crossed northern Tamil Nadu and Puducherry Coast between Puducherry and Cuddalore during 0630-0730 hrs 1ST 0001h. Finally, the model output is compared to the Joint Typhoon Warning Center (JTWC) best track data [25], to demonstrate the performance of the modeling exercise.
Model setup for the Bay of Bengal .1 Domain selection
Grid Analysis and Display System (GrADS) and Win Surfer software have been used for visualization of model output. In the present modeling exercise, the Kain–Fritch (KF) cumulus parameterization scheme and the WRF single moment (WSM) 3-class microphysics scheme (simple ice and snow scheme) have been chosen to simulate all events. Long and short wave radiation have been treated with the Rapid Radiative Transfer Model (RRTM) and Dudhia schemes, respectively.
The integration time step was set to 120 seconds to maintain computational stability as the model uses the third-order Runga-Kutta time integration scheme. Land surface model Noah 4-layer Land Surface Model (LSM) planetary boundary layer physics YonseiUniversity scheme.
Life History of Selected Tropical Cyclones
- Very Severy Cyclonic Storm Nargis (2008)
- Very Severy Cyclonic Storm Thane (2011)
- Cyclonic Storm Mahasen (2013)
In association with an active ITCZ, a cyclonic circulation formed over the southeastern Bay of Bengal on 23 December 2011. Gradually, the convective clusters deepened and moved closer to each other, and a low pressure area with T1.0 formed over the southeastern Bay of Bengal on the morning of the 24th. The thermal energy of the ocean was about 50-80 KJ/cm over the southeast Bay of Bengal and its surroundings.
The Madden Julian Oscillation (MJO) Index over phase 5 witch is favorable for cyclogenesis over the Bay of Bengal. Associated intense to very intense convection lies over the Bay of Bengal, south of lat.
Chapter-IV
A STUDY ON THE FORMATION AND EVOLUTION OF TROPICAL CYCLONE OVER BAY OF BENGAL USING
Prediction of Formation
To study the formation of selected tropical cyclones, forecast experiments were performed up to 96 h using the initial field prior to system formation. Such experiments were conducted to test whether the model was capable of capturing the process of cyclonic system formation. Since Cyclone Nargis started in the southeastern Bay of Bengal on 26 April as a well-marked low, the forecast was carried out with the initial field of 0000 UTC 24 April 2008 to capture the formation of the system.
But the center of the observed system at 11.5°N/87.2°E, which is close to the predicted center. Therefore, it is noted that in this case, like the case of the model, was able to predict the first formation of the low pressure system 36 hours in advance, which intensifies into a depression during the next 24 hours of driving.
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Very Severy Cyclonic Storm Thane (2011)
Continuing to move north-northwestward, the deep depression intensified into Cyclonic Storm Thane (2011) at 1800 UTC on the 26th. It then moved west-northwestward and strengthened into a severe cyclonic storm over the southwestern and adjacent southeastern Bay of Bengal at 1800 UTC On December 27, near the After landfall, the system moved westward and weakened into a severe cyclonic storm at 0300 UTC 30 December 2011 over the north coast of Tamil Nadu.
The cyclonic storm was moving very fast (about 40-50 km per hour on the day of landfall ie due to the faster movement, adverse weather due to the cyclonic storm was relatively less.
Evolution of Minimum Sea level Pressure (MSLP)
Sv'svukstgd SLP, WRF_TC_FCr9iS FCST VALID FOR IBZ2IAPR2008 Atmospheric Fhys(co Laboratooy, K(JET. 5imuia,ci SLP, WRF_TC_Na,91,s FCST VALID FOR o8ZO1MAyaOO6' 4Snoshe,-ic Phystcs Laboratoiij. Sftnulate4 Sea Level Pressure, rfRF _rc_Thane DAY FCST VALID FOR 06ZS6DSCS010 Almopheri.c Physics LaborQlory.KIIET.
Simulated Sea Level Pressure, WRFj'C_Thane Simulated Sea Level Pressure, WRF_TC_Thai'ee DAY FCST VALID FOR OOZZEDECSOI1 DAY FCST VALID FOR I8ZZ9DSCSOI. Simulated Sea Level Pressure, WRF_TC_Thane DAY FCST APPLIES TO 0OZ30DSC2011 Atmospheric Physics Lccboratory, KUSr.
Evolution of Pressure Drop (Ap)
Evolution of Maximum Wind Speed (MWS)
IIRF_TC_Nsi-gis DAY 0 FCST VALID FOR 18ZO1MAYOO8 A1ev.osphscic Phcjoct £ oi.s1oiy Ill/FT. WRF_TD_Thne C DAY FCST VALID FOR QOZZ8DRUZ0II Atoo.ferric physics Looratoy Kr/Fr. The analysis reveals that there is a sharp increase in the value of vorticity in the first 48 hours of small fluctuation model integration for very strong cyclonic storm Nargis (2008), very strong cyclonic storm Thane (2011) and severe cyclonic storm Mahasen (2013).
Sima11acI Voificity, WRF_TC_Tho,tE FCS'T VALID FOR 00Z31DEC20II Sinauaed Voricity, WRF_TC,Th,zna. It can be seen from the figure that the RMW of the simulated model gradually decreases with the intensification of the cyclonic system which reflects the real situation.
Relations among Different Parameters of Tropical Cyclones derived from Model Results
From these discussions of sub-section 4.2.2, it can be concluded that the ARW model used in this study generates more or less realistic tropical cyclone intensification. This may be due to the poor representation of the system in the initial field of FNL. Prasad [107] showed that the incorporation of an idealized vortex in the initial field improves the ability of the QLM model to maintain the intensity of the cyclonic system and to provide a forecast to a satisfactory degree of accuracy.
Another reason could be in the parameterization schemes used in this study (Kain-Fritch cumulus parameterization scheme, Yonsei University PBLand WSM 3-class simple ice. In this study, the horizontal grid resolution is used as 24 km with 27 eta levels in the vertical direction.
Evolution of Track's Movement of Tropical Cyclones
- Very Severe Cyclonic Storm Nargis (2008)
- Cyclonic Storm Mahasen (2013)
- Errors in Track Forecasting
However, the 24-hour and 48-hour forecasts show a better representation of the route and landing to within 50 km. This experiment is performed with an initial field of 0000UTC on 12 May to capture track curvature. Mathur and Ruess in evaluating QLM's track management at NMC Washington.
It is interesting to note that the mean position errors of Cyclone Nargis are lower than other two selected tropical cyclones and that of Mahasen is higher than other two selected tropical cyclones. This is due to the fact that the simulated rate of translation for Thane and Mahasen was lower than the observed one.
Chapter- V
A study on Bay of Bengal tropical cyclone forecasting using the Numerical Weather Prediction (NWP) model has been conducted. The Advanced Research WRF (ARW) version 3, a more advanced NWP model, was used for the present tropical cyclone forecast study. The model generates a realistic tropical cyclone structure with high spatial detail without the use of any idealized eddies at the outset.
Finally, it can be concluded that the high-resolution ARW model used in this study has great potential for predicting the formation and development of tropical cyclones in the Bay of Bengal. Impact of Tropical Cyclones on Coastal Regions of SAARC Countries and Their Impact in the Region, Report No.
Appendices
Physical Constants
