Sujata Pattanayak

Simulation of Bay of Bengal Tropical Cyclones with WRF Model: Impact of Initial and Boundary Conditions

An attempt is made to delineate the relative performances and credentials of GFS, FNL, and NCMRWF global analyses/forecast products as initial and boundary conditions (IBCs) to the WRF-ARW model in the simulation of four Bay of Bengal tropical cyclones (TCs). The results suggest that FNL could simulate horizontal advection of vorticity maxima at 850 hPa; hence, the tracks are more realistic with least errors as compared to GFS and NCMRWF. The mean landfall errors for 24-, 48-, and 72-hour forecasts are 73, 41, and 72 km, respectively. The TC intensity is well captured by NCMRWF IBCs, as it could predict 850 hPa vorticity maxima. The 24-hour accumulated rainfall is well simulated with FNL, and equitable threat score is more than 0.2 up to 100 mm with minimum bias.

Impact of Parameterization of Physical Processes on Simulation of Track and Intensity of Tropical Cyclone Nargis (2008) with WRF-NMM Model

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.

An observational perspective on tropical cyclone activity over Indian seas in a warming environment

The genesis of tropical cyclones (TCs) over Indian seas comprising of Bay of Bengal (BoB) and Arabian Sea (AS) is highly seasonal with primary maximum in postmonsoon season (mid-September to December) and secondary maximum during premonsoon season (April and May). The present study is focused to demonstrate changes in genesis and intensity of TCs over Indian seas in warming environment. For this purpose, observational data of TCs, obtained from the India Meteorological Department (IMD), are analyzed. The sea surface temperature (SST), surface wind speed, and potential evaporation factor (PEF), obtained from the International Comprehensive Ocean Atmosphere Data Set (ICOADS), are also analyzed to examine the possible linkage with variations in TC activities over Indian seas. The study period has been divided into two epochs: past cooling period (PCP, period up to 1950) and current warming period (CWP, period after 1950) based on SST anomaly (became positive from 1950) over the BoB and AS. The study reveals that the number of severe cyclones (SCS) increases significantly (statistically significant at 99% confidence level) by about 41% during CWP though no such significant change is observed in cyclonic disturbances (CDs) and cyclones (CS) over Indian seas. It is also observed that the rate of dissipation of CS and SCS over Indian seas has been decreasing considerably by about 63 and 71%, respectively, during CWP. The analysis shows that the BoB contributes about 75% in each category of TCs and remaining 25% by the AS towards total of Indian seas. A detailed examination on genesis and intensity of TC over both the basins and the seasons illustrates that significant enhancement of SCS by about 65% during CWP is confined to the postmonsoon season of the BoB. Further, the BoB is sub-divided into northern, central, and southern sectors and the AS into western and eastern sectors based on genesis of TCs and SST gradient. Results show that in postmonsoon season during CWP, the number of SCS increases significantly by about 71% in southern BoB and 300% over western AS.

A Great Escape from the Bay of Bengal ''Super Sapphire-Phailin'' Tropical Cyclone: A Case of Improved Weather Forecast and Societal Response for Disaster Mitigation

AbstractThe very severe cyclonic storm (VSCS) “Phailin (2013)” was the strongest cyclone that hit the eastern coast of the India Odisha state since the supercyclone of 1999. But the same story of casualties was not repeated as that of 1999 where approximately 10 000 fatalities were reported. In the case of Phailin, a record 1 million people were evacuated across 18 000 villages in both the Odisha and Andhra Pradesh states to coastal shelters following the improved operational forecast guidance that benefited from highly skillful and accurate numerical model guidance for the movement, intensity, rainfall, and storm surge. Thus, the property damage and death toll were minimized through the proactive involvement of three-tier disaster management agencies at central, state, and district levels.

Simulation of Track and Intensity of Gonu and Sidr with WRF-NMM Modeling System

Tropical cyclones are organized convective activities, developed over warm tropical oceans. The Indian region is unique in nature than any other region of the world, as far as the genesis and death toll due to tropical cyclone is concerned. The tropical cyclones affect this region in two seasons: Pre-monsoon (April-May) and Post-monsoon (October-December). The peak frequency is found to be in the months of May and November. Though considered to be much weaker in intensity and smaller in size as compared to the cyclones of other regions, the Bay of Bengal storms are exceptionally devastating, especially when they cross the land. This is mainly due to shallow bathymetry, nearly funnel shape of the coastline, and the long stretch of the low-lying delta region entrenched with large number of river systems leading to high storm surges and coastal inundations. The Bay of Bengal contributes about 5% of the global annual tropical storms. At the same time, Arabian Sea contributes 1-2% of the global annual tropical storms. Therefore, reasonably accurate prediction of these storms has great importance to reduce the loss of valuable lives.

Simulation of Storm Surges in the Bay of Bengal Using One-Way Coupling Between NMM-WRF and IITD Storm Surge Model

ABSTRACT The storm surge associated with severe tropical cyclones (TCs) in the Bay of Bengal (BoB) is a serious concern along the coastal regions of India, Bangladesh, Myanmar, and Sri Lanka. It is one of the most hazardous elements associated with landfalling TCs other than strong winds and heavy precipitation and about 75% of the casualities in this region are attributed to storm surges. Therefore, it is highly essential to predict the storm surges with greater accuracy at least 2 days in advance for effective evacuation. In the present study, an attempt is made to simulate the storm surges associated with severe TCs in the BoB using one-way coupling of the Non-hydrostatic Mesoscale Model core of Weather Research and Forecasting (NMM-WRF) system with the two-dimensional finite-difference storm surge model developed at the Indian Institute of Technology Delhi (IITD). The NMM-WRF model simulated track, pressure drop, and radius of maximum wind are used to calculate the wind-stress through Jelesnianski wind formulation. The results are compared with the observed/estimated values as provided by the operational/meteorological agencies of India, Bangladesh, and Myanmar. This study suggests that using simulated surface meteorological fields of a high-resolution mesoscale model, the storm surge can be predicted at least 2 days in advance of the actual landfall of TCs with reasonable accuracy. This approach will be helpful in providing disastrous storm warning well in advance in a coastal region, which will help with rapid evacuation from the vulnerable coastal region, relocation as well as protection of valuables, disaster mitigation, and coastal zone management.

Mesoscale Modelling for Tropical Cyclone Forecasting over the North Indian Ocean

The coastal regions of Bay of Bengal (BoB) and Arabian Sea (AS) experience severe damage due to landfalling tropical cyclones (TCs). The synoptic and statistical methods have limitations in predicting the track and intensity beyond 24 hours (Mohanty and Gupta, 1997). However, the numerical forecast using dynamical models can provide better forecast guidance for genesis, intensity and movement of TCs up to 72 hours (Rao and Bhaskar Rao, 2003; Mandal et al., 2004; Osuri et al., 2012a) and helps in the disaster mitigation planning. Hence, it is necessary to evaluate the comprehensive performance of such dynamical models in track and intensity forecasts of TCs. Davis et al. (2008) and Osuri et al. (2012a) showed that real-time TC forecast of ARW (Advanced Research Weather Research and Forecasting) model is generally competitive with, and occasionally superior to, other operational forecasts for track and intensity of landfalling TCs over Atlantic and BoB respectively. Wang et al. (2006) demonstrated that error growth in ARW model forecasts is noticeably slow as the forecast length increases.

Improvement in Track and Intensity Prediction of Indian Seas Tropical Cyclones with Vortex Assimilation

Tropical cyclone is one of the most hazardous weather events over data sparse warm tropical ocean. It is the most deadly weather system that causes destructive winds, heavy rainfall, high storm surges and coastal inundation, usually resulting in serious property damage and loss of life in costal belts of India and hence strong impact on the socio-economic conditions of the countries surrounding the Bay of Bengal, especially India, Bangladesh and Myanmar. The Bay of Bengal contributes about 5% of the global annual total number of tropical storms (Mohanty, 1994). Moreover, the Bay of Bengal storms are exceptionally devastating, especially when they cross the land (De Angelis, 1976). So the Bay of Bengal tropical cyclone disaster is the costliest and deadliest natural hazard in the Indian sub-continent.