Prediction of severe tropical cyclones over the Bay of Bengal during 2007–2010 using high-resolution mesoscale model

In this paper, the performance of a high-resolution mesoscale model for the prediction of severe tropical cyclones over the Bay of Bengal during 2007?C2010 (Sidr, Nargis, Aila, and Laila) is discussed. The advanced Weather Research Forecast (WRF) modeling system (ARW core) is used with a combination of Yonsei University PBL schemes, Kain-Fritsch cumulus parameterization, and Ferrier cloud microphysics schemes for the simulations. The initial and boundary conditions for the simulations are derived from global operational analysis and forecast products of the National Center for Environmental Prediction-Global Forecast System (NCEP-GFS) available at 1°lon/lat resolution. The simulation results of the extreme weather parameters such as heavy rainfall, strong wind and track of those four severe cyclones, are critically evaluated and discussed by comparing with the Joint Typhoon Warning Center (JTWC) estimated values. The simulations of the cyclones reveal that the cyclone track, intensity, and time of landfall are reasonably well simulated by the model. The mean track error at the time of landfall of the cyclone is 98?km, in which the minimum error was found to be for the cyclone Nargis (22?km) and maximum error for the cyclone Laila (304?km). The landfall time of all the cyclones is also fairly simulated by the model. The distribution and intensity of rainfall are well simulated by the model as well and were comparable with the TRMM estimates.     

A statistical cyclone intensity prediction (SCIP) model for the Bay of Bengal

A statistical model for predicting the intensity of tropical cyclones in the Bay of Bengal has been proposed. The model is developed applying multiple linear regression technique. The model parameters are determined from the database of 62 cyclones that developed over the Bay of Bengal during the period 1981–2000. The parameters selected as predictors are: initial storm intensity, intensity changes during past 12 hours, storm motion speed, initial storm latitude position, vertical wind shear averaged along the storm track, vorticity at 850 hPa, Divergence at 200 hPa and sea surface temperature (SST). When the model is tested with the dependent samples of 62 cyclones, the forecast skill of the model for forecasts up to 72 hours is found to be reasonably good. The average absolute errors (AAE) are less than 10 knots for forecasts up to 36 hours and maximum forecast error of order 14 knots occurs at 60 hours and 72 hours. When the model is tested with the independent samples of 15 cyclones (during 2000 to 2007), the AAE is found to be less than 13 knots (ranging from 5.1 to 12.5 knots) for forecast up to 72 hours. The model is found to be superior to the empirical model proposed by Roy Bhowmik et al (2007) for the Bay of Bengal.     

Tropical cyclone prediction over Bay of Bengal: a comparison of the performance of NCEP operational HWRF, NCAR ARW, and MM5 models

Much progress has been made in the area of tropical cyclone prediction using high-resolution mesoscale models based on community models developed at National Centers for Environmental Predication (NCEP) and National Center for Atmospheric Research (NCAR). While most of these model research and development activities are focused on predicting hurricanes in the Atlantic and Eastern Pacific domains, there has been much interest in using these models for tropical cyclone prediction in the North Indian Ocean region, particularly for Bay of Bengal storms that are known historically causing severe damage to life and property. In this study, the advanced operational hurricane modeling system developed at NCEP, known as the Hurricane Weather Research and Forecast (HWRF) model, is used to simulate two recent Bay of Bengal tropical cyclones??Nargis of November 2007 and Sidr of April 2008. The advanced NCEP operational vortex initialization procedure is adapted for simulating these Bay of Bengal tropical cyclones. Two additional regional models, the NCAR Advanced Research WRF and NCAR/Penn State University Mesoscale Model version 5 (MM5) are also used in simulating these storms. Results from these experiments highlight the superior performance of HWRF model over other models in predicting the Bay of Bengal cyclones. These results also suggest the need for a sophisticated vortex initialization procedure in conjunction with a model designed exclusively for tropical cyclone prediction for operational considerations.     

Impact of initial and boundary conditions on simulations of western disturbances and associated precipitation

Western Himalayas (WH) is characterized by variable topography and heterogeneous land use. During winter, it receives enormous amount of precipitation due to eastward moving extratropical cyclones, called western disturbances (WDs), in Indian parlance. This variable altitude and orientation of orographic barriers has a complex interplay with WDs in defining precipitation over the WH. To understand such complexities, three WDs are considered to study interaction with the Himalayan orography using the advanced regional prediction system. Two simulation strategies are performed and presented??first to illustrate the impact of different initial and boundary conditions and second to illustrate the impact of different horizontal model resolution with same model configuration. In the first strategy, three different initial and boundary conditions??the National Center for Environmental Prediction?CGlobal Forecast System, USA (NCEP?CGFS) (1) analysis (2) 0000UTC forecast and the National Center for Medium Range Weather Forecast, India?CT80 spectral model (NCMRWF?CT80) (3) 0000UTC forecast??are provided to the same model configuration. In the second strategy, outputs from model simulated with NCMRWF??T80 spectral model forecast at coarser horizontal model resolution of 30?km (hereafter called Experiment I) are used as input initial and boundary conditions for simulation at finer horizontal model resolution of 10?km (hereafter called Experiment II). Though there are many other dynamical factors, but in the present study, it is shown that model-simulated precipitation is sensitive to the initial and boundary conditions. Simulations at coarse resolution could capture the weather system, but detailed spatial distribution along the orography is better illustrated at finer resolution model simulation. Also, Experiment II could simulate precipitation over different ranges of the western Himalayas depicting orographic forcings.     

A Study on the Impact of Parameterization of Physical Processes on Prediction of Tropical Cyclones over the Bay of Bengal With NCAR/PSU Mesoscale Model

Prediction of the track and intensity of tropical cyclones is one of the most challenging problems in numerical weather prediction (NWP). The chief objective of this study is to investigate the performance of different cumulus convection and planetary boundary layer (PBL) parameterization schemes in the simulation of tropical cyclones over the Bay of Bengal. For this purpose, two severe cyclonic storms are simulated with two PBL and four convection schemes using non-hydrostatic version of MM5 modeling system. Several important model simulated fields including sea level pressure, horizontal wind and precipitation are compared with the corresponding verification analysis/observation. The track of the cyclones in the simulation and analysis are compared with the best-fit track provided by India Meteorological Department (IMD). The Hong-Pan PBL scheme (as implemented in NCAR Medium Range Forecast (MRF) model) in combination with Grell (or Betts-Miller) cumulus convection scheme is found to perform better than the other combinations of schemes used in this study. Though it is expected that radiative processes may not have pronounced effect in short-range forecasts, an attempt is made to calibrate the model with respect to the two radiation parameterization schemes used in the study. And the results indicate that radiation parameterization has noticeable impact on the simulation of tropical cyclones.     

Impact of sea surface temperature in modulating movement and intensity of tropical cyclones

It is well recognized that sea surface temperature (SST) plays a dominant role in the formation and intensification of tropical cyclones. A number of observational/empirical studies were conducted at different basins to investigate the influence of SST on the intensification of tropical cyclones and in turn, modification in SST by the cyclone itself. Although a few modeling studies confirmed the sensitivity of model simulation/forecast to SST, it is not well quantified, particularly for Bay of Bengal cyclones. The present study is designed to quantify the sensitivity of SST on mesoscale simulation of an explosively deepening storm over the Bay of Bengal, i.e., Orissa super cyclone (1999). Three numerical experiments are conducted with climatological SST, NCEP (National Center for Environmental Prediction) skin temperature as SST, and observed SST (satellite derived) toward 5-day simulation of the storm using mesoscale model MM5. At model initial state, NCEP skin temperature and observed SST over the Bay of Bengal are 1–2°C warmer than climatological SST, but cooler by nearly 1°C along the coastline. Observed SST shows a number of warm patches in the Bay of Bengal compared with NCEP skin temperature. The simulation results indicate that the sea surface temperature has a significant impact on model-simulated track and intensity of the cyclonic storm. The track and intensity of the storm is better simulated with the use of satellite-observed SST.     

Numerical Modelling of Storm Surge in the Head Bay of Bengal Using Location Specific Model

The head Bay of Bengal region, which covers part of Orissa and west Bengal in India as well as Bangladesh, is one of the most vulnerable regions of extreme sea levels associated with severe tropical cyclones which cause extensive damage. There has been extensive loss of life and property due to extreme events in this region. Shallow nature of the Bay, presence of Ganga-Brahmaputra-Meghna deltaic system and high tidal range are responsible for storm surges in this region. In view of this a location specific fine resolution numerical modelis developed for the simulation of storm surges. To represent mostof the islands and rivers in this region a 3km grid resolution is adopted. Several numerical experiments are carried out to compute the storm surges using the wind stress forcings representative of 1974, 1985, 1988, 1989, 1991, 1994 and 1999 cyclones, which crossed this region. The model computed surges are in good agreement with the available observations/estimates.     

Multi-Physics ensemble prediction of tropical cyclone movement over Bay of Bengal

Ensemble prediction methodology based on variations in physical process parameterizations in tropical cyclone track prediction has been assessed. Advanced Research Weather Research and Forecasting model with 30-km resolution was used to make 5-day simulation of the movement of Orissa super cyclone (1999), one of the most intense tropical cyclones over the North Indian Ocean. Altogether 36 ensemble members with all possible combinations of three cumulus convection, two planetary boundary layer and six cloud microphysics parameterization schemes were produced. A comparison of individual members indicated that Kain–Fritsch cumulus convection scheme, Mellor–Yamada–Janjic planetary boundary layer scheme and Purdue Lin cloud microphysics scheme showed better performance. The best possible ensemble formulation is identified based on SPREAD and root mean square error (RMSE). While the individual members had track errors ranging from 96–240 km at 24 h to 50–803 km at 120 h, most of the ensemble predictions show significant betterment with mean errors less than 130 km up to 120 h. The convection ensembles had large spread of the cluster, and boundary layer ensembles had significant error disparity, indicating their important roles in the movement of tropical cyclones. Six-member ensemble predictions with cloud microphysics schemes of LIN, WSM5, and WSM6 produce the best predictions with least of RMSE, and large SPREAD indicates the need for inclusion of all possible hydrometeors in the simulation and that six-member ensemble is sufficient to produce the best ensemble prediction of tropical cyclone tracks over Bay of Bengal.     

Prediction of monsoon rainfall with a nested grid mesoscale limited area model

At the India Meteorological Department (IMD), New Delhi, a 12-level limited area model with 100 km horizontal resolution has been in use for weather forecasting. The present study uses this model together with a higher horizontal resolution (50 km) and vertical resolution (16-levels) model to examine the impact of increased resolution to simulate mesoscale features of rainfall during monsoon disturbances. The model was run for 22 days in the month of August 1997 and one week in September 1997 during three monsoon depressions and one cyclonic storm in the Bay of Bengal. The model results are compared with observations. The study shows that the model can capture mesoscale convective organization associated with monsoon depression.     

SPH-based simulation of flow process of a landslide at Hongao landfill in China

The cyclones over Bay of Bengal (BoB) have varied socio-economic impacts and meteorological importance. There are considerable uncertainties in predicting the track and intensity of cyclonic systems in the BoB. The present study examines the cyclogenesis characteristics over the BoB and addresses the regional impacts and their importance in terms of intensification of cyclones. An analysis of cyclone track data from 1971–2013 reveals that the cyclones generated in Andaman Sea (a regional sea of BoB) and propagating through central BoB sustain maximum life time. Furthermore, within the BoB, the cyclones originated from Andaman Sea are the most intensified and characterized by highest cyclogenesis potential index. Interestingly, we have found that higher value of mid-tropospheric relative humidity over Andaman Sea during the cyclone period is enhancing the cyclone’s intensity. Climatologically also the Andaman Sea is dominated by higher values of mid-tropospheric relative humidity compared to other regions of BoB. There is no significant distinction between Andaman Sea and rest of the BoB for other meteorological and oceanic parameters that supports cyclogenesis. Climatologically dominant east–west asymmetry in mid-tropospheric relative humidity is enhancing the intensity of cyclones from Andaman Sea. The results will be helpful in understanding the processes of cyclone intensification and useful in the statistical and dynamical prediction of cyclones.     

Mean monthly wind driven climatological circulation model of the Bay of Bengal

A special feature of the Bay of Bengal circulation is its seasonal variation in response to the monsoonal winds. In the case of the Bay of Bengal, observationally very little is known about the large scale circulation. Theoretically, the problem of driving the circulation in the Bay of Bengal is more complex than that in other basins because of the presence of large quantities of fresh water discharge from Ganga-Brahmaputra-Meghna river systems, and also because the atmospheric driving forces even within a season are highly variable with frequent occurrences of tropical disturbances. Exploring the nature of the circulation in the Bay of Bengal is a problem of great importance in itself as well as for the critical role this region plays in the genesis of tropical disturbances which are the main source of large scale rainfall over the northern part of the Indian subcontinent. The surface circulation of the Bay of Bengal may, therefore, help in understanding the variation of rainfall over time scales ranging from the subseasonal to the interannual. Keeping this in view, an attempt was made towards the development of an oceanic climatological circulation model for the Bay of Bengal, which explains the seasonal variability of the currents. The model is fully non-linear and vertically integrated, with realistic basin geometry. The treatment of coastal boundaries involves a procedure leading to a realistic curvilinear representation of the western and eastern sides of the Bay of Bengal. This coastal representation has the advantage of taking into account the finer resolution in the shallow regions of the northern Bay. The model is forced by the monthly mean wind stress derived from 30 years (1950–79) of Comprehensive Oceanographic Atmospheric Data Sets (COADS). Special emphasis is given to the southern open boundary condition for the model. For this purpose, sensitivity experiments have been performed with six open boundary conditions and a comparative study of the results has been made. These sensitivity tests for the open boundary condition will help the development of a suitable coupled ocean-atmosphere model for this region. The model-generated main features are in general agreement with the known climatological circulation of the Bay of Bengal.     

Operational tropical cyclone intensity prediction—an empirical technique

One very specific operational requirement of the Tropical Cyclone (TC) Programme of the Regional Specialized Meteorological Centre, New Delhi is to provide 12-hourly forecasts valid up to 48 h (preferably 72 h) on the intensity of cyclones over the southern Indian Seas. In this paper, a simple empirical model for predicting the intensity of TCs occurring in the Bay of Bengal is proposed. The model parameter has been determined from a database assembled on 30 recent cyclones, and the model itself is based on the assumption that a TC intensifies exponentially. A method for correcting the forecast during subsequent observation hours (6- or 12-h intervals) is also presented. The results show that the forecast skill for forecasts of up to 48 h is reasonably good. The absolute mean errors are less than 12 knots for 48-h forecasts, with the forecast skill decreasing with time. With the incorporation of a correction procedure based on the latest observations, some improvement in the forecast skill can be obtained. The model is expected to be useful to operational forecasters.     

Swarm intelligence and neural nets in forecasting the maximum sustained wind speed along the track of tropical cyclones over Bay of Bengal

Tropical cyclones are well-known extreme weather and the cause of considerable damages, injuries and loss of life. The assessment of the maximum sustained wind speed along the track of the tropical cyclones is very important for estimating the strength of the cyclones. The swarm intelligence in the form of ant colony optimization (ACO) technique is introduced in this study to compute the pheromone deposition along the track of tropical cyclones followed by neural nets to forecast the maximum sustained wind speed of the cyclones occurring over the Bay of Bengal of North Indian Ocean. The ACO is a nonlinear problem-based meta-heuristic optimization method for finding approximate solutions to discrete optimization problems and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. The method has shown its application potential in various fields including the prediction of monsoon rainfall. In this study, the amount of pheromone deposition during the successive stages of the cyclones has been estimated. A range of minimum central pressure (MCP), central pressure drop (PD), maximum sustained wind speed (MSWS) and intensity (T-No) associated with the cyclones of Bay of Bengal are utilized to form the input matrix of the neural nets. The neural nets are trained to forecast the maximum sustained wind speed along the track of the tropical cyclones over Bay of Bengal. The result reveals that the errors in forecasting the MSWS along the track of tropical cyclones with 6, 12, 18 and 24 h lead time are 2.6, 2.9, 3.1 and 4.8, respectively. The result is compared with the existing dynamical, statistical and adaptive models to evaluate the skill of the present model. The result is well validated with observation.     

Cyclone track prediction using INSAT data

INSAT visible and infrared imageries of three cyclones in the Bay of Bengal during the period 1984–1987 were analysed with a view to improve the cyclone track prediction in this region. It was observed that the rotation in the major structural cloud features (as seen from the cloud-top temperature maps) associated with these cyclones in the Bay of Bengal is followed with a change in direction of their movement. This method is seen to be particularly effective when the cyclone is severe and when the major cloud features persist for a reasonably longer time. In the present study, only the direction of movement is forecast assuming a uniform speed of the cyclone.     

Experimental superensemble forecasts of tropical cyclones over the Bay of Bengal

This study entails the implementation of an experimental real time forecast capability for tropical cyclones over the Bay of Bengal basin of North Indian Ocean. This work is being built on the experience gained from a number of recent studies using the concept of superensemble developed at the Florida State University (FSU). Real time hurricane forecasts are one of the major components of superensemble modeling at FSU. The superensemble approach of training followed by real time forecasts produces the best forecasts for tracks and intensity (up to 5 days) of Atlantic hurricanes and Pacific typhoons. Improvements in track forecasts of about 25–35% compared to current operational forecast models has been noted over the Atlantic Ocean basin. The intensity forecasts for hurricanes are only marginally better than the best models. In this paper, we address tropical cyclone forecasts over the Bay of Bengal for the years 1996–2000. The main result from this study is that the position and intensity errors for tropical cyclone forecasts over the Bay of Bengal from the multimodel superensemble are generally less than those of all of the participating models during 1- to 3-day forecasts. Some of the major tropical cyclones, such as the November 1996 Andhra Pradesh cyclone and October 1999 Orissa super cyclone were well handled by this superensemble approach. A conclusion from this study is that the proposed approach may be a viable way to construct improved forecasts of Bay of Bengal tropical cyclone positions and intensity.     

Impact of various synthetic vortices on cyclone track prediction

Sensitivity experiments are conducted for three cases of cyclones for investigating the impact of different vortex initialization schemes on the structure and track prediction of the cyclone using India Meteorological Department’s Limited Area Model. The surface wind and pressure profiles generated using Holland and Rankine initialization schemes differ from each other. These different generated profiles are compared with the actual data and the root mean square error (RMSE) was calculated between them. In case of the Holland vortex, ‘b’ is found to be equal to 1.5 and 2.0 respectively for two cases of very severe cyclonic storms in the Arabian Sea, namely 6–10 June 1998 and 16–20 May 1999 and 2.25 for the severe cyclonic storm in the Bay of Bengal. The ‘α’ parameter in Rankine’s scheme was found to be 0.5 for two cases and 0.4 for the third system. This shows that cyclones differ even if they attain the same intensity. The values of these parameters i.e. ‘b’ and ‘α’ are used for generating the synthetic wind data for individual cyclones and the same is used in the data assimilation system. The analysis and forecast generated for the above cases using the Holland scheme show that the simulated structure has characteristics closer to the actual storm; however, the Rankine scheme shows a weaker circulation. The mean track error for three cases in the Holland scheme is 93, 149, 257 and 307 km in 12-, 24-, 36- and 48-h forecast. The mean track errors for the Rankine scheme are 152, 274, 345 and 327 km, respectively, for the same period.     

Impact of satellite observed microwave SST on the simulation of tropical cyclones

The impact of realistic representation of sea surface temperature (SST) on the numerical simulation of track and intensity of tropical cyclones formed over the north Indian Ocean is studied using the Weather Research and Forecast (WRF) model. We have selected two intense tropical cyclones formed over the Bay of Bengal for studying the SST impact. Two different sets of SSTs were used in this study: one from TRMM Microwave Imager (TMI) satellite and other is the weekly averaged Reynold’s SST analysis from National Center for Environmental Prediction (NCEP). WRF simulations were conducted using the Reynold’s and TMI SST as model boundary condition for the two cyclone cases selected. The TMI SST which has a better temporal and spatial resolution showed sharper gradient when compared to the Reynold’s SST. The use of TMI SST improved the WRF cyclone intensity prediction when compared to that using Reynold’s SST for both the cases studied. The improvements in intensity were mainly due to the improved prediction of surface latent and sensible heat fluxes. The use of TMI SST in place of Reynold’s SST improved cyclone track prediction for Orissa super cyclone but slightly degraded track prediction for cyclone Mala. The present modeling study supports the well established notion that the horizontal SST gradient is one of the major driving forces for the intensification and movement of tropical cyclones over the Indian Ocean.     

Impact of bogus vortex for track and intensity prediction of tropical cyclone

The initialization scheme designed to improve the representation of a tropical cyclone in the initial condition is tested during Orissa super cyclone (1999) over Bay of Bengal using the fifth-generation Pennsylvania State University — National Center for Atmospheric Research (Penn State — NCAR) Mesoscale Model (MM5). A series of numerical experiments are conducted to generate initial vortices by assimilating the bogus wind information into MM5. Wind speed and location of the tropical cyclone obtained from best track data are used to define maximum wind speed, and centre of the storm respectively, in the initial vortex. The initialization scheme produced an initial vortex that was well adapted to the forecast model and was much more realistic in size and intensity than the storm structure obtained from the NCEP analysis. Using this scheme, the 24-h, 48-h, and 72-h forecast errors for this case was 63, 58, and 46 km, respectively, compared with 120, 335, and 550 km for the non-vortex initialized case starting from the NCEP global analysis. When bogus vortices are introduced into initial conditions, the significant improvements in the storm intensity predictions are also seen. The impact of the vortex size on the structure of the initial vortex is also evaluated. We found that when the radius of maximum wind (RMW) of the specified vortex is smaller than that of which can be resolved by the model, the specified vortex is not well adapted by the model. In contrast, when the vortex is sufficiently large for it to be resolved on horizontal grid, but not so large to be unrealistic, more accurate storm structure is obtained.     

Sensitivity of simulated cyclone Gonu intensity and track to variety of parameterizations: Advanced hurricane WRF model application

Domain configuration and several physical parameterization settings such as planetary boundary layer, cumulus convection, and ocean–atmosphere surface flux parameterizations can play significant roles in numerical prediction of tropical cyclones. The present study focuses to improve the prediction of the TC Gonu by investigating the sensitivity of simulations to mentioned configurations with the Advanced Hurricane WRF model. The experiments for domain design sensitivity with 27 km resolution has been shown moving the domains towards the east improve the results, due to better account for the large-scale process. The fixed and movable nests on a 9-km grid were considered separately within the coarse domain and their results showed that despite salient improvement in simulated intensity, an accuracy reduction in simulated track was observed. Increasing horizontal resolution to 3 km incredibly reduced the simulated intensity accuracy when compared to 27 km resolution. Thereafter, different initial conditions were experimented and the results have shown that the cyclone of 1000 hPa sea level pressure is the best simulation initial condition in predicting the track and intensity for cyclone Gonu. The sensitivity of simulations to ocean–atmosphere surface-flux parameterizations on a 9-km grid showed the combination of ‘Donelan scheme’ for momentum exchanges along with ‘Large and Pond scheme’ for heat and moisture exchanges provide the best prediction for cyclone Gonu intensity. The combination of YSU and MYJ PBL scheme with KF convection for prediction of track and the combination of YSU PBL scheme with KF convection for prediction of intensity are found to have better performance than the other combinations. These 22 sensitivity experiments also implicitly lead us to the conclusion that each particular forecast aspect of TC (e.g., track, intensity, etc.) will require its own special design.     

Impact of global warming on cyclonic disturbances over south Asian region

A state-of-the-art regional climate modelling system, known as PRECIS (Providing REgional Climates for Impacts Studies) developed by the Hadley Centre for Climate Prediction and Research, UK is applied over the Indian domain to investigate the impact of global warming on the cyclonic disturbances such as depressions and storms. The PRECIS simulations at 50 × 50 km horizontal resolution are made for two time slices, present (1961–1990) and the future (2071–2100), for two socioeconomic scenarios A2 and B2. The model simulations under the scenarios of increasing greenhouse gas concentrations and sulphate aerosols are analysed to study the likely changes in the frequency, intensity and the tracks of cyclonic disturbances forming over north Indian Ocean (Bay of Bengal and Arabian Sea) and the Indian landmass during monsoon season. The model overestimates the frequency of cyclonic disturbances over the Indian subcontinent in baseline simulations (1961–1990). The change is evaluated towards the end of present century (2071–2100) with respect to the baseline climate. The present study indicates that the storm tracks simulated by the model are southwards as compared to the observed tracks during the monsoon season, especially for the two main monsoon months, viz., July and August. The analysis suggests that the frequency of cyclonic disturbances forming over north Indian Ocean is likely to reduce by 9% towards the end of the present century in response to the global warming. However, the intensity of cyclonic disturbances is likely to increase by about 11% compared to the present.