Tropical Cyclones in the Bay of Bengal region have caused severe loss of lives, economic loss and storm surge inundation associated with maximum wind speeds, though the frequency of tropical cyclone is lower in this region. An accurate track of such cyclones is therefore crucial for decisionmakers to better prepare before disaster strikes. In order to accurately predict, and keep track of storms, regional dynamics must be understood, and precise dynamics options must be implemented to state-of-the-art Weather Research and Forecast (WRF) model. Also, there is need to predict precise storm surge inundation forecast map to prevent loss of lives in that region. This study aims to understand the efficacy of high-resolution model to predict cyclone track and intensity over BoB region using the WRF model and also aims to grasp the Impact of Land Practices over tropical cyclone storm surge using MIKE and ADCIRC models. This study also investigates the future cyclone changes and associated surge inundation levels.
Accuracy in predicting tropical storms over low-lying coastal regions is pivotal for understanding storm tracks and their subsequent impacts. The present study highlights the challenges in predicting the Bay of Bengal (BOB) cyclone “AILA” (during 23rd to 25th May 2009) using the Weather Research and Forecast model, Advanced research core module (WRF-ARW). The model configuration uses a two-way interactive nested domain with 10 km resolution over BOB. Its initial and boundary conditions are driven from the NCEP FNL operational global analysis data at every 6 hours. Many studies test the same parameters without an objective method. Often, the same parameters are tested for different datasets. A total of 74 sensitivity experiments were conducted to test the following factors and levels: a) parameterization schemes: two microphysics and two cumulus physics schemes used to select appropriate combination over study region, b) model domain: including/excluding Himalayas, c) vertical resolution: eight various increasing/decreasing vertical levels have been carried out to evaluate the storm track dependencies on these factors, d) domain size: and increasing (decreasing) the grid points of model domain in east-west direction shows that approximately 50-100 km track difference for every two points. Our results show that, the experiments including the Himalayas provide a better representation of cyclone track and speed. In order to reduce the computational time required to do such tremendous amount of experiment, we hypothesize to use statistical tools of experimental design that can involve all the factors that determine the cyclone tracks. A proper experimental design might provide unbiased results and also we might need less number of experiments.
In order to reduce the computational time required to do such a tremendous amount of experiments with including many parameters influence on track prediction capabilities. In this chapter statistical tool of the experimental design proposed to reduce the number of experiments with all the factors that determine the cyclone track and provide individual influence on track forecast. A proper experimental design might provide unbiased results and also can reduce the number of experiments. The present study considers 9 factors in Design of experiment (DoE) to assess the sensitivity of WRF model prediction for cyclone track and intensity. Those factors are: 1) SST update 2) Microphysics 3) Cumulus Physics 4) Vertical levels 5) West-East grid points 6) Domain Size 7) North-South grid points 8) Resolution and 9) Ocean Model inclusion. Using these factors, a partial design of experiment method was used (R-package) to generate 64 random experiments to study the influence of each factor in cyclone prediction. The model was also forced with two different reanalysis products (Era-Interim and FNL) in order to understand the initial and boundary condition sensitivity on track prediction. The analysis suggests a relatively small error in FNL cyclone track forecast compared to ERA simulations. The range of FNL track error compared to observed track in one of the simulations starts at 63 km away and the highest error record was 438 km. ERA simulations, on the other hand, have errors larger than the FNL simulations, with errors ranging from 233 to 740. The experiments also suggest that ERA has lesser errors in prediction of cyclone intensity, and cycle duration. Also, provided ERA lateral boundary conditions into the WRF model simulations, and these are clustered together in Taylor analysis when compared to FNL boundary conditions. FNL simulations show scattered results, and this triggers the model sensitivity towards boundary conditions.
The depth-integrated hydrodynamic models have wide application in coastal management. These models have been extensively used in modelling storm surges and related inundation, coastal engineering, tidal forecasting and vulnerability assessments over continental selves across the world. However, there is a general paucity in storm surge modelling studies where an integration of distributed land use information with depth-integrated hydrodynamic models had been tested. The landuse plays a vital role as far as the overland flow is concerned as it determines the flow velocity and travel time vis-à-vis the extent and depth. Therefore, it is essential to test the storm surge inundation models with inclusion of distributed land use land cover. In order to understand the impact of land use land cover inclusion in the storm surge model, a severe cyclone AILA is considered in this study for the assessment over the Bay of Bengal of North Indian Ocean region. Four decades of land use information are fed in the model to test the impact in storm surge inundation extent and depth. The results suggest a significant change in water depth and inundation extent when distributed land use information is included in the simulation. Five landuse scenarios were tested in the model to examine which land use class has the maximum and minimum reduction potential for storm surge inundation. The results provide valuable information for land use based coastal flood management as well as will be useful in enhancing the skill of storm surge forecast.
Evaluation of storm surge model sensitivity with observed tide and climate change projection of surge events over coastal region of West Bengal (WB). Numerical prediction of storm surges improves our understanding of the occurrence of surge heights and also provides us regions where the storm surges are frequent and how much they may impact a region. In the present study, the two-dimensional depth integrated hydrodynamic model ADCIRC (ADvance CIRCulation) has been evaluated over the deltaic coastal plains of WB and changes in surge height under a climate change scenario has been estimated. An assessment has been carried out to evaluate the ADCIRC tidal model performance over the WB coast using the past-observed tidal records at four stations over Hooghly River. The tidal model results show that the tidal wave heights are better approximated with observed wave heights and sensitive to bottom friction coefficient, which is mainly due to bathymetry in the WB coast being less than 25m for a substantial region away from the coast. Regional Climate model projections of storm surges over the Bay of Bengal region shows that the average surge heights does not vary much from baseline to future, however the individual surge heights varies depending on the occurrence of the storm. The extreme wind speeds and surge heights are found to be increasing in the future as compared to the baseline and the return period probabilities of the wind speed are also higher for the future compared to the baseline.