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Cyclone induced storm surge and flood forecasting in the northern Bay of Bengal
Abstract
A cyclone induced storm surge and flood forecasting system that has been developed for the northern Bay of Bengal is presented. The developed system includes a cyclone forecasting model that uses statistical models for forecasting of the cyclone track and maximum wind speed, and an analytical cyclone model for generation of cyclone wind and pressure fields. A data assimilation system has been developed that allows updating of the cyclone parameters based on air pressure and wind speed observations from surface meteorological stations. The forecasted air pressure and wind fields are used as input in a 2D hydrodynamic model for forecasting storm surge levels and associated flooding. An efficient uncertainty prediction procedure based on Harr's point estimation method has been implemented as part of the forecasting system for prediction of the uncertainties of the forecasted storm surge levels and inundation areas caused by the uncertainties in the cyclone track and wind speed forecasts. The developed system is applied on a severe cyclone that hit Bangladesh in April 1991. The simulated storm surge and associated flooding are highly sensitive to the cyclone data. The cyclone data assimilation system provides a more accurate cyclone track when the cyclone approaches the coastline, which results in a significant improvement of the storm surge and flood predictions. Application of the uncertainty prediction procedure shows that the large uncertainties of the cyclone track and intensity forecasts result in large uncertainties of the forecasted storm surge levels and flood extend. The forecasting system shows very good forecasting capabilities up to 24 h before the actual landfall.
... Η έρευνα των τελευταίων δεκαετιών επικεντρώνεται στη διαχείριση των καταιγίδων (Hissel et al., 2014;Spencer et al., 2015), στις προβλέψεις ακραίων γεγονότων (Madsen and Jakobsen, 2004;Lowe and Gregory, 2005;McInnes et al., 2007;Mattocks and Forbes, 2008;Rego and Li, 2009;Izaguirre et al., 2013) και στην εφαρμογή συστημάτων έγκαιρης προειδοποίησης (Ciavola et al., 2011b(Ciavola et al., , 2011aGall et al., 2013;Jones et al., 2017). Η διερεύνηση των καταιγίδων έχει εφαρμογή στην ολοκληρωμένη διαχείριση της παράκτιας ζώνης (Curtis, 2013;De la Torre et al., 2013;Hallegatte et al., 2013;Chadenas et al., 2014;Musereau and Regnauld, 2014;Jaranovic et al., 2017), και στο σχεδιασμό λιμενικών και παράκτιων έργων (Phan and Simiu, 2011;McCullough et al., 2013;Takahashi et al., 2014;Altomare et al., 2015;Burmeister et al., 2015;Basco, 2016;Do et al., 2016;Hatzikyriakou and Lin, 2017;Mooyaart and Jonkman, 2017;Mohd Anuar et al., 2018). ...
... Several researchers have published their work concerning the accurate prediction of extreme storm events (Ferreira and Guedes Soares, 1998;Lowe and Gregory, 2005;McInnes et al., 2007;Izaguirre et al., 2013), the storm forecasting (Madsen and Jakobsen, 2004;Verlaan et al., 2005;Mattocks and Forbes, 2008;Rego and Li, 2009), and early warning techniques (Ciavola et al., 2011b(Ciavola et al., , 2011aGall et al., 2013;Jones et al., 2017). In general, the nexus of extreme events and human preparation against their impacts attracts diachronically the research interest since the storm research provides information that improves not only the understanding of these extreme events but also the risk analysis of the related hazards. ...
The sea-level rise and the increase of storms severity are the major effects of climate change in coastal areas. Their impacts are of great importance for millions of people who live and work in coastal communities, also affecting the ports functionality and many other economic activities. In conjunction with the sea level, the astronomical and the meteorological tide, coastal storms cause extreme wave runup and overtopping phenomena in ports and coastal structures. Consequently, coastal storms threaten the reliability of infrastructure, the urban areas with coastal flooding, and the coasts from erosion. The above reasons depict the importance of coastal storms analysis and its necessity before any technical study in coastal engineering. Such analyses provide valuable information for risk reduction, coastal management, harbour and coastal structures design. Coastal storms as multivariate extreme events require a detailed multivariate analysis of many variables. A coastal storm analysis is accomplished by studying the wave height, the wave period, the duration, the calm period, and the storm energy, which are considered “coastal storm parameters” since they define a coastal storm event. The range of coastal storm parameters and how they are interrelated draw a rough outline of wave climate during coastal storm events. The analysis of these parameters is used to understand the coastal storm characteristics, their severity and improve their modelling. The theory of copulas can be applied for coastal storm modelling, as it has already been implemented for other multivariate events in hydrology and finance. This thesis focuses on the modelling of coastal storms through copulas, and secondly, in order to apply the proposed methodology, analyses 4008 coastal storms in the Mediterranean Sea, studying the activity of coastal storms in the last decades. More specifically, this thesis: a) describes the dependency of wave height (H) and the wave period (T) during a coastal storm investigating the best fit bivariate copulas, b) simulates the coastal storms in a given location applying a five-dimensional C-Vine copula, and c) estimates the return periods of coastal storms by using two- to five-dimensional copulas. In addition, for the description of energy, a comparison of coastal storm energy with energy flux is accomplished and the shape of coastal storms is also investigated. The dependency of H and T is investigated among 40 copula families for 4008 coastal storms, presenting the two best-selected copulas and their properties. Three algorithms based on works of De Michele et al. (2007), Aas et al. (2009), and Stöber and Czado (2017) developed into five dimensions and compared for their efficiency in coastal storms simulation. To estimate the return periods, up to five-dimensional copulas are used for any combination of important coastal storm parameters. Moreover, the thresholds of coastal storm parameters, their identification, the frequency of their occurrence and the description of their characteristics are presented. The Tawn and the Joe copulas are the most frequent best-selected bivariate copulas for modelling H and T during a coastal storm. The C-Vine copulas can be used to simulate the coastal storms efficiently and estimate high-dimensional return periods with extreme characteristics. The flexibility of C-Vines to describe better the tail dependencies makes this class of copulas an effective tool for coastal storm modelling. In addition, it can be said that Mediterranean coasts face around 10-14 coastal storms per year, with most of them occurring in winter. Their average duration is shorter than 30 hours, and 25% of them are consecutive events that hit twice a location in less than a day. Furthermore, the wave period and the main direction present no remarkable fluctuations during a coastal storm. The sharpness of coastal storms is not related to the wave period or the direction and they are not reaching their peak faster than they decay. This thesis describes the use of copulas for the modelling of coastal storms. Besides, through a thorough analysis of Mediterranean coastal storms, a deeper understanding of coastal storm severity is pursued, gaining knowledge about their past activity in order to be prepared in the future and protect the coastal areas. Consequently, all this information is helpful for their application in harbours and coastal structures design.
... It is very important to carry out storm surge research along the coast of the BoB. The generation and propagation of storm surges and flooding in coastal regions have been extensively investigated since the 1970s (Dube et al., 1985(Dube et al., , 2004Madsen et al., 2004;Lewis et al., 2013b). Because the BoB is sufficiently large and full of islands, this study involves large calculations using a uniform grid, especially for the high-resolution storm surge numerical model. ...
... It was one of the deadliest cyclones in human history, causing approximately 138,000 deaths. The simulated wind speed and atmospheric pressure agreed well with the observed data from Madsen (2004) (Fig. 9). Fig. 10 shows the distribution of the maximum storm surge during "TC02B" in 1991. ...
The coastal region of the Bay of Bengal (BoB) is one of the most vulnerable areas to storm surges caused by tropical cyclones (TCs). Historical data indicate that the BoB experiences two seasons in the annual cycle of TC formation, namely, the pre-monsoon season (April to May) and the post-monsoon season (October–December). The frequency of post-monsoon cyclones is significantly higher than that of pre-monsoon cyclones. Very severe cyclonic storms and stronger-intensity storms can cause disastrous storm surges. Based on the accuracy of current forecasts of the path, intensity and radius of maximum wind of TCs in the BoB, a total of 153 ensemble members are automatically generated according to the subjective deterministic forecast results of the TCs, basically covering all possible TCs. A graphics processing unit (GPU)-based parallel storm surge forecast model is established and validated for the coastal areas of the BoB. The speedup ratio of the model can exceed 300, which can meet the computational time requirements of large-scale ensemble numerical forecasts. For the 2020 Amphan cyclone, the costliest cyclone ever recorded in the North Indian Ocean (NIO), the numerical ensemble forecast model can provide rapid and accurate storm surge ensemble and numerical probability forecast products for the BoB. The probability of coastal flooding risk can be evaluated for the coastal areas of the BoB, enabling reasonable and valuable recommendations to be made to evacuate people and protect property near dangerous areas.
... Most of these models have successfully predicted the storm surge; however, their predictions were limited to forecasting the peak surge height along the coastline. The later models (Flather, 1994;Rao et al., 1997;Madsen and Jakobsen, 2004;Karim and Mimura, 2008) focused on improving the surge forecast height along the coastline and estimated the surge-induced inundation over the coastal regions of Bangladesh. For operational purposes, the Bangladesh Meteorological Department (BMD) used a numerical storm surge model (the IIT model) and regression models (STP and STEEPER) (Debsarma, 2009;Debsarma et al., 2014) to predict the maximum surge height and cyclone track information, respectively. ...
... Thus, IMD track data are used for simulating a total of 31 TCs to develop the storm surge inundation database. Madsen and Jakobsen (Madsen and Jakobsen, 2004) both track data for modeling the 1991 cyclone and presented that the JTWC tracks predicted a higher maximum wind speed than the one used by the BMD. ...
Bangladesh's vulnerability to storm surge and success in reducing their impacts on the coastal communities are well-known. However, global warming is expected to increase both the frequency and the intensity of tropical cyclones. Also, the country still lacks in good quality data and information that can offer enhanced services to effectively design coastal defense systems and adapt to climate changes. This study developed a storm surge inundation model and database using the available tropical cyclones' database and simulated inundation for the past 31 cyclones in the Bay of Bengal, near the coastal regions of Bangladesh. The model uses a suite of Delft3D hydrodynamic and Delft Dashboard cyclone models. The model was calibrated and validated for two major cyclones, namely Sidr and Aila, using the available data for different bed roughness, track sources, and wind drag coefficient conditions. The results suggested that spatially varying bed roughness and wind varying drag conditions provide a more reliable prediction of inundation over the coast. The results also show that historical track data from Indian Meteorological Department optimize the model performances. The inundation database indicates that depending on the intensity and location, tropical cyclones can cause the maximum inundation of 1–5 m in the coastal lands of Bangladesh. More than 70% of the storms lead to the maximum inundation of more than 2 m, and about 25 and 7% of the storms can cause the maximum inundation of more than 3 and 4 m, respectively. The study also discusses the potential applications and shares insights on the implications of the inundation database that can offer improved information for enhanced climate services in Bangladesh. The database can be advanced with information about sectoral loss and damage as well as citizen science that will not only provide necessary information to design coastal protection structures and emergency measurements but also contribute to build long-term climate adaptation plans in the data-scarce region.
... Several studies (Adnan et al., 2019;Bhuiyan and Dutta, 2012;Carvalho and Wang, 2019;Choudhury et al., 2004;Condon and Sheng, 2012;Hasan et al., 2020;Islam et al., 2019;Karim and Mimura, 2008;Madsen and Jakobsen, 2004;Warner et al., 2018) can be found in the literature related to flooding and inundation of the coastal zone of the Ganges delta particularly on the coastal zone of Bangladesh. These studies were on the evaluation and analysis of flood vulnerability and coastal inundation (Bhuiyan and Dutta, 2012;Condon and Sheng, 2012), flood risk assessment and flood dynamics (Adnan et al., 2019;Choudhury et al., 2004;Islam et al., 2019;Warner et al., 2018) and on the uncertainties due to future climate change (Carvalho and Wang, 2019;Hasan et al., 2020;Karim and Mimura, 2008;Madsen and Jakobsen, 2004). ...
... Several studies (Adnan et al., 2019;Bhuiyan and Dutta, 2012;Carvalho and Wang, 2019;Choudhury et al., 2004;Condon and Sheng, 2012;Hasan et al., 2020;Islam et al., 2019;Karim and Mimura, 2008;Madsen and Jakobsen, 2004;Warner et al., 2018) can be found in the literature related to flooding and inundation of the coastal zone of the Ganges delta particularly on the coastal zone of Bangladesh. These studies were on the evaluation and analysis of flood vulnerability and coastal inundation (Bhuiyan and Dutta, 2012;Condon and Sheng, 2012), flood risk assessment and flood dynamics (Adnan et al., 2019;Choudhury et al., 2004;Islam et al., 2019;Warner et al., 2018) and on the uncertainties due to future climate change (Carvalho and Wang, 2019;Hasan et al., 2020;Karim and Mimura, 2008;Madsen and Jakobsen, 2004). Similarly, a body of literature can be found on disaster risk and reduction Saha, 2015;Sattar and Cheung, 2019) and adaptation and recovery Sadik et al., 2018;Uddin et al., 2020) for the communities living in this zone. ...
Inundation by sea water in coastal areas can devastate cropping; recovery from the impacts can be slow. We used a water and salt balance model of polders to investigate the impacts of and recovery from flood inundation by sea water. We applied the model to three polders in the Ganges delta: Amtali, with high rainfall and low salinity; Dacope with intermediate rainfall and salinity; and Gosaba, with lower rainfall and higher salinity. Dacope and Gosaba were inundated a few years prior to our study, and the model calibration is pertinent to the recovery period. The calculated evapotranspiration from the polder (indicating crop growth) was dramatically reduced following inundation, and the calculated salt concentration in the soil water and shallow groundwater greatly increased. The model simulations showed that recovery depends on several factors, in particular how well the soil in the polder is drained and therefore how well salt is flushed out. Our simulations suggest that with sound maintenance of infrastructure and sound management, particularly of soil drainage, the polders and islands of the Ganges delta could recover fairly quickly from inundation events.
... This restricts their application and hinders their capability to generate rapid simulations used for real-time flood prediction and fine risk analysis. Among all 2D models, MIKE 21 is the most well-accepted software for assessing flood hazards in coastal areas [22][23][24], and it is a powerful tool developed by Danish Hydraulic Institute (DHI). However, it requires a lot of manual work to adjust the computing mesh for 2D modeling of flows. ...
... The hydraulic model used for comparison in this article is the HD module in MIKE 21, which is the most well-accepted software for assessing flood hazards in coastal areas [22][23][24]. It uses a two-dimensional hydrodynamic numerical model with an average vertical velocity assumption, for the changes of hydraulic elements such as water depth and flow velocity in the vertical direction are much smaller than the changes in the horizontal direction during the flooding process. ...
The evaluation of storm surge flood risk is vital to disaster management and planning at national, regional and local levels, particularly in coastal areas that are affected more severely by storm surges. The purpose of this paper is to propose a new method that includes two modules for the simulation modeling and risk assessment of coastal flooding. One is a hydrodynamic module for simulating the process of the flood inundation coastal inundation arising from storm surge, which is based on a cellular automata (CA) model. The other is a risk assessment module for quantitatively estimating the economic loss by using the inundation data and land use data. The coastal areas of Pearl River estuary in China were taken as a case study. Simulation results are compared to experimental results from MIKE 21 and depth data from a social-media-based dataset, which demonstrates the effectiveness of the CA model. By analyzing flood risk, the flood area and the direct economic losses predicted are close to the actual case incurred, further demonstrating the computational reliability of the proposed method. Additionally, an automatic risk assessment platform is designed by integrating the two modules in a Geographic Information System (GIS) framework, facilitating a more efficient and faster simulation of coastal flooding. The platform can provide the governments as well as citizens of coastal areas with user-friendly, real-time graphics for coastal flood disaster preparation, warning, response and recovery.
... The results with possible values of k 1 were found to be in general agreement with the ones presented in the study through graphical outputs in the respective cases. It is significant to point out here that some recent investigations are carried out applying wetting and drying scheme to include these effects (e.g., Madsen and Jakobsen 2004;Mashriqui et al. 2005). Since the highest resolution of the grids of the models used in the study is 0.6847 km (see Table 1), it cannot be capable of handling effectively the wetting and drying features in the area of interest. ...
... The results in this case also generally agreed the graphical outputs presented in our study. Uncertainty in simulated storm surge magnitude can arise from cyclone position, maximum sustained wind speed, and the radius of the maximum wind (Madsen and Jakobsen 2004;Lewis et al. 2014). Uncertainties in each of the parameters mentioned have been estimated with freely available data sources keeping the other parameters at a fixed value. ...
In this paper, a two-dimensional, vertically integrated hydrodynamic model is developed taking into account entrained air bubbles during storm surges as well as incorporating inverted barometer, and river and land dynamics. The model is specifically designed for the coastal region of Bangladesh. A nested scheme method with a fine mesh scheme (FMS), capable of incorporating the complex coastline and all major offshore islands accurately, nested into a coarse mesh scheme (CMS) covering up to 15° N latitude in the Bay of Bengal is used. To incorporate the small and big offshore islands in the Meghna estuarine region with its complex coastline accurately, a very fine mesh scheme (VFMS) is again nested into the FMS. Along the northeast corner of the VFMS, the Meghna river discharge is taken into account. The coastal and island boundaries are approximated through proper stair steps. The model equations are solved by a semi-implicit finite difference technique using a staggered C-grid. A stable appropriate tidal condition over the model domain is generated by applying tidal forcing with the four major tidal constituents M
2, S
2, K
1, and O
1 along the southern open boundary of the CMS. This tidal regime is introduced as the initial state of the sea for nonlinear interaction of tide and surge. The model is applied to simulate water levels due to the interaction of tide and surge associated with the cyclones April 1991 and Aila at different coastal and island locations along the coast of Bangladesh. The results are found to be quite satisfactory with root mean square error of ∼0.50 m as calculated for both the storm events. Tests of sensitivities on water levels are carried out for air bubbles, offshore islands, river discharge, inverse barometer, and grid resolution. The presence of air bubbles increases simulated water levels a little bit in our model, and the contribution of air bubbles in increasing water level is found around 2 %. Further, water levels are found to be influenced by offshore islands, river discharge, inverse barometer as well as grid resolution.
... The prediction accuracy of model usually depends on various input parameters i.e., tides, cyclone model, improved bathymetry and representation of the coastal geometry. To date, a number of models have already established to simulate cyclonic storms induced storm surge, making landfall on the northern Bay of Bengal coast (Deb and Ferreira, 2016;Dube et al., 2009;Krien et al., 2016;Madsen and Jakobsen, 2004;Murty et al., 2016). These storm surge models were 2D depth averaged models based on shallow water continuity equations. ...
... The nonlinearity is the driver of the interaction that caused the tide level amplification and wave height reduction (Poulose et al., 2017). Bottom friction is responsible for wave energy dissipation in shallow coast (Madsen and Jakobsen, 2004). Due to cyclone movement over the ocean a significant part concentrated surrounding the cyclone wind field. ...
Storm surge modeling in the Northern Bay of Bengal still remain challenging due to complex tidal nature and poor observational coverage. In this study, using satellite information a coupled modeling system was developed which comprises of Delft3D-FLOW and SWAN to simulate storm surge associated with cyclone Mora 2017. To improve the present state of storm surge prediction in this region, hydrodynamic model was developed with improved bathymetric datasets and model parameterization was done followed by parameters sensitivity test on bathymetry, bottom roughness coefficient, wind model, and bottom friction formulation. The wind-pressure parametric Holland model was parameterized and validated using ASCAT MetOp B Level 2 wind speed. The significant wave height (SWH) was validated with CryoSat-2 and AltiKa derived sea surface altimetry. The coupled model provides a realistic interpretation of storm surge. The tide-surge interaction in surge generation largely dominated with shallow bathymetry and tide phase. The improved bathymetry and satellite wind information provide supportive information for explaining the surge clustering and external surge phenomena of tide-surge interaction. The computed peak storm surge height was 3-3.5 m along the landfall location i.e., Chittagong-Cox's Bazar coast and the maximum SWH of 4.2-5.3 m, formed surrounding the cyclone eye. The predicted surge height exhibits a reasonable match with observed measurement and the obtained coefficient of determination is 0.87-0.91. Therefore, the developed storm surge model with satellite derived information is envisaged to support storm surge modeling in data scarce region.
... Past experiences have shown that extreme disasters have resulted in significant economic losses and tragic casualties to coastal nations, as exemplified by the Bangladesh storm surge in 1970, which claimed 300 000 lives. 1 Hurricane Katrina occurred in the United States in 2005 and was one of the costliest storms, both in fatalities and damage, leaving more than 204 000 homes destroyed. 2,3 In recent years, the adoption of hard protection measures, which include seawalls, breakwaters, and revetments, has made significant progress contributing to the resilience and protection of coastal cities against marine hazards. ...
Coastal cities at low-lying elevations face extensive inundation risks when attacked by extreme storm surges or tsunamis. Efficient and accurate modeling of flooding is critical for reducing losses in economic and lives. Therefore, the paradox arises that the computational cost is usually too high for rapid forecasts when considering the complex topography and buildings. The present contribution presents a subgrid-based approach, which combines the subgrid model and a drag force module, to realize efficient modeling of urban flooding at a high resolution. The volume-occupation effects of buildings are incorporated naturally in the subgrid treatment, and the blockage, sheltering, and frictional effects of buildings acting on the flows are considered through a simple, bulk parameterization in the form of drag forces. The model is validated with a laboratory experiment and then applied to an ideal numerical model at a real city scale. The proposed model is compared to three other models using coarse grids, with high-resolution simulation results serving as the benchmark for evaluation. The results demonstrate that the presence of buildings induces noticeable alterations in the distribution of water level and velocity fields within the urban area. The proposed model yields comparable predictions to the benchmark in terms of inundation extent, elevation, and velocity. Furthermore, the model exhibits minor sensitivity to grid size, allowing for a significant reduction in computational time compared to high-resolution simulations. The model achieves a well-balanced combination of high resolution, accuracy, and efficiency for large-scale simulations of coastal urban flooding.
... Thus, taking into account the development in depth-averaged hydrodynamic models which solve shallow water equation, there have been considerable improvisation over time to predict the storm surge. Apart from model development and improvisation, a number of studies have carried out with different sensitive experimentations with movable coastal boundary representing both storm surge generation and inundation, wetting and drying conditions (Madsen and Jakobsen 2004). Also, to observe the impact of the strength and size of the storm on surge, idealized cyclone model outputs in terms of track, central pressure, wind, radius of maximum wind have been incorporated (Jelenianski and Taylor 1973;Holland 1980). ...
The Bay of Bengal (BoB) basin is regarded as one of the most cataclysmic basins in the world from a tropical cyclone (TC) destruction point of view. The major part of the devastation is attributed to seawater inundation over several kilometers inland due to storm surge. Thus, storm surge prediction with advanced lead time can contribute to minimizing damage and loss. Therefore, an attempt has been made to improve the storm surge prediction with a longer lead time using the high-resolution mesoscale model outputs. Weather Research Forecasting (WRF) and Hurricane WRF (HWRF) have been used to simulate 8 TCs over BoB and the model track and intensity both in terms of pressure drop and 10 m maximum wind speed have been provided as input to produce surge height using IIT Delhi dynamical storm surge model. The models’ reliability has been verified by analyzing different initial condition simulations of all TCs selected. 96–24 h forecast length with 12 h interval, prior to landfall have been used in this study. HWRF shows better overall predictability for the track, intensity as well as landfall; however, both models are capable of producing reliable results with 3–4 days of lead time. Using these model outputs in the surge model, the predicted surges for each TC are presented. The statistical analysis of the surge predictions using different intensity inputs shows that both models can generate reliable surge prediction when compared to the Indian National Centre for Ocean Information Services observed surge heights. The skill of the models in predicting storm surge shows that the HWRF wind input has the highest skill followed by ARW wind, HWRF pressure drop, and ARW pressure drop. Thus, this study suggests that the early warning of TCs by IMD should include the surge prediction from these highly reliable mesoscale model products with 96–72 h lead time in order to mitigate catastrophic loss associated with storm surge.
... Uncertainties can be present in our simulated results, originating from various factors including the position of the cyclone, MSWS, and the RMW. Madsen and Jakobsen [32] and Lewis et al. [33] have identified these parameters as significant sources of uncertainty. To evaluate these uncertainties, each parameter was individually modified while keeping the other parameters constant, utilizing freely available data sources. ...
In this study, water levels resulting from the dynamic interaction of tide and surge are estimated by solving a 2-D vertically integrated shallow water equations numerically. To solve the equations on the specific 2-D grid, the explicit Leapfrog scheme is implemented, adopting a staggered Arakawa C-grid. The domain's complex land-sea interface is approximated through the stair-step method in order to employ the finite difference technique. To incorporate the complexity of the domain with a considerably high accuracy and to reduce computational cost, one-way nested grid models are embraced. The Meghna River freshwater discharge is incorporated into the innermost child model. A stable tidal regime over the region of interest is generated by applying the four vital tidal constituents, namely M2 (principal lunar semidiurnal), S2 (principal solar semidiurnal), O1 (principal lunar diurnal) and K1 (luni-solar diurnal) in the southern open boundary of the outermost model. This previously effectuated tidal regime is used as the initial state of the sea in getting total water levels due to the dynamic interaction of tide and surge. Numerical experiments are performed with the storm AILA that hit the coast of Bangladesh on May 25, 2009. The simulated results are found to closely match observed and reported data.
... Tropical cyclones (TCs) also known as hurricanes and typhoons are increasingly affecting the lives and livelihoods of biological communities that inhabit within and beside coastal-marine ecosystems such as estuaries (Paerl et al. 2001;Phlips et al. 2020;Paul et al. 2020aPaul et al. , 2020b. With the advances in weather forecasting, tracking TCs before their landfall has become more predictable than was possible in the 20th century (Madsen and Jakobsen 2004;Mohanty et al. 2019); therefore, the estuarine scientific community is able to conduct assessment of disruptions caused by a TC or successive TCs (Steinke and Ward 1989;Paerl et al. 2001;Mukherjee et al. 2012;Beyrend-Dur et al. 2013;Bhattacharya et al. 2014;Kumar et al. 2017;Paul et al. 2020a). The impacts of TCs that hit the eastern coasts of North America have received significant attention in the estuarine literature because biogeochemical cycles and ecological communities of a few estuaries there are regularly monitored (Gong et al. 2007;Wetz and Paerl 2008;Paerl et al. 2018;Phlips et al. 2020;Wachnicka et al. 2020). ...
Tropical cyclones are increasingly affecting estuarine communities. The effects of category-5 tropical cyclone Amphan (landfall on 20 May 2020 near the Ganges estuary mouth) on the copepod community of the Ganges estuary were studied. Copepod assemblages were sampled before (February–December 2019), shortly after (31 May–12 June 2020) and post-(September–November 2020) Amphan periods. It was hypothesized that shortly after Amphan a relatively homogeneous community consisting of a few estuarine specialists would succeed but that would soon be replaced by a heterogeneous one; however, those specialists would continue their dominance. Shortly after Amphan species richness declined but the recovery process was completed within months, led by Paracalanus parvus, Bestiolina similis, Acartia spinicauda, Acartiella tortaniformis and Oithona brevicornis. Spatial homogeneity of the community that prevailed in pre- and shortly after Amphan was lost in post-Amphan. The unilateral dominance of B. similis observed in the pre-Amphan period was challenged by P. parvus, A. spinicauda, A. tortaniformis and O. brevicornis after Amphan. Shortly after Amphan A. spinicauda proliferated and co-dominated the estuary with A. tortaniformis but the latter replaced the former within a few months. The copepod community experienced rearrangements in species composition, abundance and dominance hierarchy; therefore, its regular monitoring is recommended.
... On the one hand, the strong winds of TCs can induce huge waves and storm surges in the nearshore region, which in turn threaten coastal communities and infrastructure, and arouse seawater encroachment to affect ecology (Kundu et al. 2001;Bhaskaran et al. 2020). On the other hand, TCs can directly destroy buildings with their strong wind, bring a heavy precipitation in a short time, and further cause flooding on the land (Chittibabu et al. 2004;Madsen and Jakobsen 2004;Chauhan et al. 2021a). In the Ganges Delta, which has a long and complex coastline with many estuary islands, dense river network, high tidal range, and other adverse factors (Paul et al. 2016), the impact of TC is particularly pronounced in Bangladesh, since its large population density makes it especially vulnerable to high rates of mortality. ...
In May 2020, a category-5 tropical cyclone (TC) Amphan formed in the Bay of Bengal and struck the coasts of India and Bangladesh. In this study, the relevant dynamic characteristics and aftermaths of Amphan are documented. Through detailed investigation of the reanalysis and observation data, spatiotemporal varying characteristics of the atmospheric and oceanic parameters during the Amphan propagation process were analyzed. Due to a wide range of high sea surface temperature anomaly, Amphan developed rapidly and ultimately led to the local heavy precipitation and strong winds in the coastal areas during its passage. It is also noted that the recorded wave height, wave period, and current speed all amplified when Amphan passed by and the characteristics of wave and current directions are also consistent with the temporal variation of the corresponding wind field. Meanwhile, Amphan occurred in accompany with the ongoing COVID-19 pandemic. In Khulna Division of Bangladesh, the number of newly confirmed COVID-19 cases increased rapidly after Amphan landing, which however was almost nil before the event, indicating there might exist a possible correlation between Amphan and the intensive outbreak of the local COVID-19, and particular attentions should be paid to deal with the multi-type, coexisting disasters if different or even conflicting measures are required.
... It is important to perform studies at the local scale in order to provide effective information about storm surge impacts and flooding in coastal areas. To avoid unacceptable future risks, due to storm hazards, it is essential that this information is required for implementing sustainable coastal planning or management strategies with the help of appropriate tools for planning and sustainable management of natural and anthropogenic hazards impacts on coastal zones [18], [20], [35]. Over the past years, many studies have employed various logistical, numerical and machine learning methods to improve flood risk assessment. ...
Coastal cities are growing at a very rapid pace, in terms of both population and physical assets, and great uncertainty surrounds the future evolution of flood due to storm surge and sea-level rise. Storms are a major cause of loss of human life and property in many coastal cities around the world. It is therefore essential to accurately predict the impact of storm surges to assess an area’s flood risk and plan to minimize it. Historical records of storms are too short and too sparse to support reliable statistical predictions of storm surge levels; thus, numerical analysis is used for simulating and predicting flooding in coastal areas. In recent years, improvements in the understanding of the physics of storm surge processes have led to the development of computationally intense hydrodynamic models capable of estimating storm surge elevations. In this study, an attempt is made to assess the impact of storm surges in the coastal region by integrating numerical hydrodynamic and wave model with GIS. The study concentrated on the coastal panchayats of Alappuzha district namely, Arattupuzha, Thrikkunnapuzha, Purakkadu and Ambalapuzha south. A numerical model using MIKE21 was developed for the study area to simulate storm surges by integrating hydrodynamic and wave model. The coupled model is calibrated by optimizing the parameters and validated based on observed data. The performance of the model is assessed using RMSE, RRMSE and MRE where the developed model and the model results were found to be in good agreement with the observed data. The developed model was then used to simulate storm surge and wave condition for five different storm scenarios. From the results of the simulations, it is found that the surge heights are dependent of high wind speed and astronomical tide elevation during the period of occurrence. The high intensity rainfall has also an effect on the water level rise during the storm surges. The coastal inundation extent under different storm scenarios were also mapped using the results from the storm surge simulations and the severity of coastal inundation during storm surges were also assessed.
... Meanwhile, the flood level and flood inundation extent are also the keys to flood risk assessment in coastal areas (Dawson et al. 2003). With the development of computer science, numerical models have been widely used in the field of water conservancy engineering (Brett et al. 2010;Henrik and Flemming 2004;Panayiotis et al. 2016). The main idea of the numerical models is to simulate the complex physical movement of the water body by calculating the physical equations. ...
In the context of climate change and urbanization, flood becomes one of the most important threats to human life, health, and property. Coastal areas gathering large numbers of population, capital, and industries are vulnerable to suffering from the compound floods caused by hydrological and oceanic processes. The disaster mechanisms of compound floods are more complex, and the consequences are even more serious. Based on the existing research results, this article sorts out the main disaster mechanisms of compound floods in coastal areas and explains the main methods, including using statistical models to study the dependence between flood drivers or joint probability and numerical models to simulate compound flood inundation, and presents the characteristics of different methods. We also discuss the advantages and disadvantages of different models and analyze their uncertainties. Current research seldom considers the rainfall-runoff-storm surge compound flood and the effect of climate change. In addition, there are only a few kinds of literature that integrate statistical models and numerical models to investigate compound flood hazard. Uncertainties in compound flood study methods are also less considered. Future investigation should focus on the characteristics and uncertainties of different models and consider the impact of climate change on compound floods. These will help to fully understand compound floods, research models, and provide effective opinions for flood management in coastal areas.
... The north Indian Ocean accounts for only 6% of the global annual cyclone frequency (Singh and Roxy, 2022). Despite the fewer number of cyclones as compared to other basins, extremely severe cyclones form in the Bay of Bengal that cause extensive casualties in the Bay of Bengal rim countries including India, Bangladesh and Myanmar (Chittibabu et al., 2004;Madsen and Jakobsen, 2004;Kikuchi et al., 2009;Lin et al., 2009;Yanase et al., 2010). Not only the fatalities but also the economic loss due to these cyclones is huge. ...
The cyclones during November in the Bay of Bengal follow two distinct tracks. Analysis for the period 1982-2019 shows that some cyclones move west-northwestward and make landfall at Odisha, Andhra Pradesh, Tamil Nadu coasts of India or Sri Lanka coast while others move north-northeastwards and make landfall at West Bengal, Bangladesh or Myanmar coast. Our analysis shows there is a significant difference in the steering winds governing these two different cyclone tracks. The north-northeastward moving cyclones are associated with an anomalous upper-level cyclonic circulation over India which is part of a subtropical Rossby wave train triggered by an anomalous upper-level convergence over the Mediterranean region. This wave train propagates along the subtropical westerly jet from the East Atlantic/Mediterranean region and reaches the Indian subcontinent in four days. It induces an anomalous cyclonic circulation over the Indian landmass and provides south-to-north and west-to-east steering over the Bay of Bengal, causing the cyclones to move in a north-northeastward direction. On the other hand, for west-northward moving cyclones, there is no Rossby wave intrusion over the Indian subcontinent, hence the cyclones move in west-northwestward direction assisted by the beta effect and climatological winds which are from east to west over the south and central Bay of Bengal. This shows that the track of cyclones in the north Indian Ocean can be modulated by atmospheric changes in the extratropics and can act as a precursor for the prediction of the track of cyclones in this region.
... A storm surge is defined as an abnormal rise of ocean water level over the predicted astronomical tide caused by natural forcings such as low atmospheric pressure and wind stress. The increase in surge level can be even up to 10 m (Madsen and Jakobsen, 2004), resulting in significant casualties and loss of properties. In the past two decades, 2.6 million people have died worldwide due to storm surges (Small and Nicholls, 2003). ...
The estimation of maximum storm surges along a coast is indispensable for emergency action planning, design, and adaptation of coastal infrastructure. The existing studies on the Bay of Bengal coast have used synthetic tracks with constant track parameters such as the maximum wind speed, radius of maximum wind, and central pressure to estimate the probable maximum storm surges. However, the analysis of the best tracks from the Joint Typhoon Warning Center during 1978–2019 shows that the track parameters vary from origin to landfall locations. The reported studies along the Bay of Bengal have failed to capture such variations and overestimated probable maximum storm surges due to constant track parameters. Therefore, this study proposes a methodology for estimating wind speed of various return periods and associated track parameters that vary along a synthetic track. The wind speed of different return periods is computed at each eye location using the probabilistic approach. Thus, the calculated wind speeds vary from origin to landfall locations, and such a pattern of wind speed variation is observed to be similar to the historical cyclones. The radius of maximum wind and central pressure is calculated using the regression equations derived from historical tracks. The accuracy of the proposed methodology is investigated by simulating the cyclones Thane and Vardah that occurred along the Tamil Nadu coast. The results suggest that the varying track parameters using the proposed methodology produce realistic surge values similar to parameters from best track data, and it overcomes the overestimation of surge heights. The proposed methodology is further utilized to analyze the maximum surge scenarios along the Tamil Nadu coast resulting from various track shifts and angles of attack. The proposed methodology is expected to improve the estimation of storm surges in other basins. This article is protected by copyright. All rights reserved.
... Despite the relatively smaller number of cyclones, more than 80% of global fatalities occur due to tropical cyclones in this region, mostly due to coastal flooding (Beal et al., 2020). Several of the most devastating cyclones that formed in the Bay of Bengal caused extensive casualties in the Bay of Bengal rim countries, particularly in India, Bangladesh, and Myanmar (Madsen and Jakobsen, 2004;Kikuchi et al., 2009;McPhaden et al., 2009). Basin-wise, the Bay of Bengal cyclone contribution is 4%, and the Arabian Sea cyclone contribution is 2% to the annual global frequency of the cyclones (Fig. 2). ...
The north Indian Ocean accounts for 6% of the global tropical cyclones annually. Despite the small fraction of cyclones, some of the most devastating cyclones have formed in this basin, causing extensive damage to the life and property in the north Indian Ocean rim countries. In this review article, we highlight the advancement in research in terms of ocean-atmosphere interaction during cyclones in the north Indian Ocean and identify the gap areas where our understanding is still lacking.
There is a two-way ocean-atmosphere interaction during cyclones in the north Indian Ocean. High sea surface temperatures (SSTs) of magnitude 28–29 °C and above provide favorable conditions for the genesis and evolution of cyclones in the Arabian Sea and the Bay of Bengal. On the other hand, cyclones induce cold and salty wakes. Cyclone induced cooling depends on the translation speed of the cyclone, wind power input, ocean stratification, and the subsurface conditions dictated by the ocean eddies, mixed layer and the barrier layer in the north Indian Ocean. The average cyclone-induced SST cooling is 2–3 °C during the pre-monsoon season and 0.5–1 °C during the post-monsoon season. This varying ocean response to cyclones in the two seasons in the Bay of Bengal is due to the difference in the ocean haline stratification, whereas, in the Arabian Sea it is due to the difference in cyclone wind power input and ocean thermal stratification. The oceanic response to cyclone is asymmetric due to the asymmetry in the cyclone wind stress, cyclone induced rainfall and the dynamics of the ocean inertial currents. The cyclone induced wake is salty and is the saltiest in the Bay of Bengal among all the ocean basins. The physical response of the ocean to the cyclone is accompanied by a biological response also, as cyclones induce large chlorophyll blooms in the north Indian Ocean that last from several days to weeks.
SSTs leading to cyclogenesis in the Arabian Sea are 1.2–1.4 °C higher in the recent decades, compared to SSTs four decades ago. Rapid warming in the north Indian Ocean, associated with global warming, tends to enhance the heat flux from the ocean to the atmosphere and favor rapid intensification of cyclones. Monitoring and forecasting rapid intensification is a challenge, particularly due to gaps in in-situ ocean observations. Changes in ocean-cyclone interactions are emerging in recent decades in response to Indian Ocean warming, and are to be closely monitored with improved observations since future climate projections demonstrate continued warming of the Indian Ocean at a rapid pace along with an increase in the intensity of cyclones in this basin.
... Regarding the hazard component, research has mainly focused on forecasting the incidence and magnitude of disasters. For example, Madsen and Jakobsen (2004 ) Quantitative methods, among them Multi-Criteria Analysis (MCA), have also been applied to assess vulnerability (Ball et al. 2012 ). Li et al. (2013 ) estimated the flood relative vulnerability at the county (city) level in Dongting Lake, China, using disaster system science as theoretical background and the technical support of GIS and Remote Sensing (RS). ...
Humanitarian logistics activities have mainly focused on the response stage of the disaster management cycle. The concept of risk vulnerability enhances the scope of disaster management by highlighting the importance of improving the activities of the preparation stage. This work proposes a vulnerability index that comprises the dimensions of hazard, social and economic exposure, and preparedness. Three quantitative techniques are combined to identify key indicators comprising the index, determine the relative importance of the vulnerability dimensions, and categorize the states of Mexico according to their level of vulnerability toward hydrological disasters. The addition of both economic and social exposure in a vulnerability index acknowledges that the characteristics of the population influence their capacity to cope with disasters and uncovers the importance of adjusting strategies to local drawbacks and needs.KeywordsVulnerability assessmentSocial exposureHydrological events
... Storm surge, the abnormal rise in sea level by intense cyclonic storm is a natural calamity that has the potentiality to cause death and also destruction by coastal f looding [5,9,14,15,18,25,31]. Indian National Centre for Ocean Information Services (INCOIS) has categorized the entire Indian coast into four based on surge height from the viewpoint of storm potential viz., very high-risk zones (> 5 m), high-risk zones (3-5 m), moderate-risk zones (1.5-3 m), and low-risk zones (< 1.5 m). ...
Amphan (16–21 May 2020) is the most intense tropical storm in the history of West Bengal during recent decades (2011–2020). After the 1999 Odisha Super Cyclone (OSuC), it is also the most intense super cyclonic storm (SuCS) that has originated over the Bay of Bengal (BoB) and caused irreparable damages during the storm event. The intensification time of Amphan was slow initially, but it grew from category 1 to 5 in record time, just within 18 h. This paper highlights mainly the pre-disaster state-level preparedness and also the severity of cyclonic storm Amphan on West Bengal. To map the flooded areas of southern West Bengal, the Sentinel-1 SAR dataset have been analyzed in the Google Earth Engine (GEE) environment. The results derived from the pixel-based analysis show that nearly 1075 km² of land has been inundated due to intense rainfall and storm surges during Amphan. The powerful high storm surge is also responsible for the embankment breaching, which is 160 km long along the coastal belt of West Bengal.
... In current state-of-art of storm surge forecast, both simulated wind fields and parametric wind fields are used to drive the storm surge models. In some cases the simulated wind fields by numerical models are used (Bilskie et al., 2020;Valchev et al., 2018), while in other cases the wind fields are calculated with parametric wind models according to the forecasted tracks (Cyriac et al., 2018;Madsen and Jakobsen, 2004;Murty et al., 2017;Pan et al., 2016;Paul et al., 2018;Rajasekaran et al., 2008). The parametric wind model is preferred in many cases because it allows a forecast simulation to be launched as soon as a forecasted track is issued, instead of waiting for mesoscale model data to be transferred and pre-processed. ...
This paper proposed a probability forecast methodology for the storm surges induced by tropical cyclones, including a probability forecast method of tropical cyclone tracks and a probability forecast scheme of storm surge levels. The probability forecast method of tropical cyclone tracks is developed based on the Error-Estimation Ensemble (EEE) method. Empirical distributions of the positions of the tropical cyclone centers around the EEE-forecasted ones are gained and used to make probability forecast of tropical cyclone tracks. It performs well in hindcasting the tropical cyclones that moved in the 24-h warning line of China in 2018. The probability forecast of storm surge levels is based on the probability forecast of tropical cyclone tracks. Under a given target fall-in probability, five possible tracks are used to drive the storm surge model and yields five forecasts of storm surge levels, the envelope of which is taken as the possible variation range of water level under the target fall-in probability. Using the probability forecast method, six launches of the probability forecast of three typical storm surges that affects the Changjiang Estuary are conduced, and the performance of the probability forecast method is assessed via a comparison between the target and realistic fall-in probabilities.
... Cyclones also cause floods of higher magnitude (Bern et al. 1993;Kostaschuk et al. 2001;Pradhan et al. 2007), based on factors such as cyclone velocity and the duration of persistence in an area (Madsen and Jakobsen 2004;Terry 2009). A cyclone consequently causes storm surges that could be heightened during high tides and extended hours of precipitation, affecting the intensity of flooding events. ...
Compared with larger nations, small island developing states (SIDS) are disproportionately
affected by natural disasters relative to size and frequency. Social, environmental and
economic complexities are integral in making SIDS more vulnerable to such catastrophes.
Floods and droughts have drastic impacts on societies; however, few studies have been
performed in the Pacific region to reduce risks. Drought indices are useful to understand
vulnerabilities and can be used to improve knowledge of spatial and temporal distribution of
drought and floods, thereby improving preparedness. For this research, the following drought
indices were tested for the Fiji region: Standardised Precipitation Index (SPI), Standardised
Precipitation Evapotranspiration Index (SPEI), Effective Drought Index (EDI) and self�calibrated Palmer Drought Severity Index (PDSI). Because of the importance of agriculture
in Fiji, the performance of each index was verified using two plant productivity indices:
Enhanced Vegetation Index (EVI) and Normalised Difference Vegetation Index (NDVI). It
was concluded that the EDI is the best-performing index and precipitation is a suitable
parameter which can be used in monitoring hydrological extremes in island states such as
Fiji. Further, a meta-analysis was carried out, and it was concluded that wavelet-transformed
artificial neural networks (WANNs) have the best performance to forecast drought indices.
Therefore, we employed an artificial neural network (ANN) as well as a WANN model to
forecast the EDI using climate indices. The models showed promising results in predicting
EDI; however, both the models showed average performance in predicting extreme events.
Instances of over-prediction and under-prediction were noted for both the models from the
categorical verification. We also used multivariate statistical techniques to carry out spatial
drought modelling. The results were not better than those of the neural networks; however,
multivariate techniques have added advantages such as identifying relationships between
response and explanatory variables, which can be used with other modelling techniques. In
conclusion, neural networks can be used to implement an operational hydrological extreme
monitoring system in Fiji. Further testing and optimisation to better predict extreme events
will be useful for informing the public; this area warrants future investigation.
... Storm surge flooding sends a massive wave of water crashing against the coast. Realtime assimilation of precipitation data and forecasts is critical for flash flood forecasting [17]. Kenitra city part of the Sebou watershed, is potentially facing the risk of flooding which is increasingly recurrent and which is exacerbated by climate change and rapid urbanization. ...
The Kenitra city located in western of Morocco. It is a port on the Sbu river, has a population in 2014 of 431,282. This city has known a rapid growth in the number of inhabitants due to the migration of the surrounding villages, as well as the growth of a group of industrial activities, as this city is the third economic city in Morocco, as it contains the third industrial zone in Morocco, this region follows the activity of car factories. Given its social and economic importance, protecting it from flood risks is a priority for decision-makers. In this paper, we developed a hydrological model using HEC-HMS tools for the purpose of protecting human life and economic activities from the risk of floods. The forecast model has been used in order to identify and regions at risk from flooding and to take other precautions to protect life. Additionally, a forecast can provide the basis for preparing critical infrastructure for floods in order to minimize damage.
... The model used a dynamic storm model (Jelesnianski and Taylor 1973), the same as Flather (1994). Madsen and Jakobsen (2004) developed a modeling system to predict both surge heights and flooding. For operational purposes, the Bangladesh Meteorological Department (BMD) developed a regression and steeringcum-persistence model (STP and STEEPER Model) for tracking cyclones and initially used an empirical formula for storm surge prediction (Khan 1995;Debsarma 2009). ...
Tropical cyclone (TC) is considered as the most dangerous and devastating hydrometeorological natural hazards in the coastal regions. On average, one severe cyclone strikes Bangladesh coast every three years. On the other hand, under significant sediment discharge from the Ganges-Brahmaputra-Meghna (GBM) River system (1.0 ~ 2.4 billion tons/year), Bengal delta dramatically changes its shorelines and bathymetry and has been gaining about 400 km² land at the eastern part of the Meghna Estuary for the last twenty-seven (1991–2018) years. This study aims to investigate the impact of morphological changes on storm surge induced inundation characteristics on the newly reclaimed coastal lands along with different hypothetical land elevations and Sea level Rise (SLR) scenarios. Five different cyclone tracks are used to generate different cyclonic scenarios with the same strength as TC-1991. This study involves the application of the Delft-3D numerical model and ArcGIS to simulate, calculate, and visualize inundation. The results show that inundation heights strongly depend on the cyclone tracks even if the strength (wind speed and pressure drop) remains the same for all tracks. Also, with the accretion of lands, the inundation depth and extent will decrease at the mainland but increase at the accreted lands and the offshore islands, while with higher land elevation of the accreted lands, it will decrease. With SLRs, the offshore islands and accreted lands are more susceptible than the mainland. The impact of the all over land along with a 1.0 m Sea Level Rise (SLR) on the inundation depth and extent pattern will strongly depend on the elevation of the accreted lands.
... The north Indian Ocean accounts for only 6% of the global annual cyclone frequency (Singh and Roxy, 2022). Despite the fewer number of cyclones as compared to other basins, extremely severe cyclones form in the Bay of Bengal that cause extensive casualties in the Bay of Bengal rim countries including India, Bangladesh and Myanmar (Chittibabu et al., 2004;Madsen and Jakobsen, 2004;Kikuchi et al., 2009;Lin et al., 2009;Yanase et al., 2010). Not only the fatalities but also the economic loss due to these cyclones is huge. ...
The cyclones during November in the Bay of Bengal follow two distinct tracks. Analysis for the period 1982–2019 shows that some cyclones move west-northwestward and make landfall at Odisha, Andhra Pradesh, Tamil Nadu coasts of India or Sri Lanka coast while others move north-northeastwards and make landfall at West Bengal, Bangladesh or Myanmar coast. Our analysis shows there is a significant difference in the steering winds governing these two different cyclone tracks. The north-northeastward moving cyclones are associated with an anomalous upper-level cyclonic circulation over India which is part of a sub-tropical Rossby wave train triggered by an anomalous upper-level convergence over the Mediterranean region. This wave train propagates along the subtropical westerly jet from the East Atlantic/Mediterranean region and reaches the Indian subcontinent in four days. It induces an anomalous cyclonic circulation over the Indian landmass and provides south-to-north and west-to-east steering over the Bay of Bengal, causing the cyclones to move in a north-northeastward direction. On the other hand, for west-northward moving cyclones, there is no Rossby wave intrusion over the Indian subcontinent, hence the cyclones move in west-northwestward direction assisted by the beta effect and climatological winds which are from east to west over the south and central Bay of Bengal. This shows that the track of cyclones in the north Indian Ocean can be modulated by atmospheric changes in the extratropics and can act as a precursor for the prediction of the track of cyclones in this region.
... Furthermore, an online coupling of the hydrodynamics and the short waves is also necessary to account for the wave set-up (Deb and Ferreira, 2016;Krien et al., 2017). The capability of the model to simulate the wetting and drying is also necessary to model the inundation (Madsen and Jakobsen, 2004). ...
The Bay of Bengal is a well-known breeding ground to some of the deadliest cyclones in history. Despite recent advancements, the complex morphology and hydrodynamics of this large delta and the associated modelling complexity impede accurate storm surge forecasting in this highly vulnerable region. Here we present a proof of concept of a physically consistent and computationally efficient storm surge forecasting system tractable in real time with limited resources. With a state-of-the-art wave-coupled hydrodynamic numerical modelling system, we forecast the recent Supercyclone Amphan in real time. From the available observations, we assessed the quality of our modelling framework. We affirmed the evidence of the key ingredients needed for an efficient, real-time surge and inundation forecast along this active and complex coastal region. This article shows the proof of the maturity of our framework for operational implementation, which can particularly improve the quality of localized forecast for effective decision-making over the Bengal delta shorelines as well as over other similar cyclone-prone regions.
... One can find numerous studies in the literature that discuss the impact of tropical cyclone-induced disastrous storm surges in the Bay of Bengal. Some of the pioneering and notable studies include Murty and Flather (1994), Das (1994), Dube et al. (1997), Madsen and Jakobsen (2004), Rao et al. (2007), and many others. Several factors that directly contribute to disastrous storm surge in the Bay of Bengal region are discussed in these studies. ...
The Bay of Bengal and the Gulf of Mexico are the two water bodies on the globe that are most prone to storm surges generated by tropical cyclones. In this chapter, a review has been made of the storm surge problem in the Bay of Bengal region located in the North Indian Ocean. Using the contemporary numerical models, not only storm surge elevations but also coastal inundations were computed for some recent cyclones in the Bay of Bengal. These models included the interactions between storm surges, tides, and wind waves. However, it should be noted that one of the challenging issues, which still remains unsolved to a large extent, is computing the interaction between storm surges and river flooding, and the contribution of this interaction to coastal flooding and inundation. A dramatic example of such an interaction was during the 29 October 1999 cyclone on the Odisha coast.
... The impact of storm surge and associated inundation from tropical cyclones is one among the natural hazards faced by the coastal community worldwide. One can find discussions on the disastrous effect of storm surge and inundation reported in numerous published works (Ali 1979;Flather 1994;Dube et al. 1997;Madsen and Jakobsen 2004;Center 2007;Ray et al. 2011, and so on). In general, there are three major factors: hydrodynamic, meteorological, and hydrologic, that can affect the storm surge characteristics. ...
The head Bay of Bengal region that borders the North Indian Ocean is crisscrossed with numerous tidal creeks, riverine systems and channels that play an important role in storm surge studies. In particular, the storm surge resulting from the landfall of tropical cyclone over this region can interact with the river systems and thereby modify the characteristics of storm surge. Several studies were attempted to understand the behaviour of storm surges and associated inundation for the Indian coast; however, the role of hydrologic component in modifying storm surge received less attention. The present study considers a stretch of Hooghly River channel in West Bengal that provides the navigable route to two important national ports, and important in context to socioeconomic implications. The state-of-art advanced circulation model (ADCIRC) hydrodynamic model used in this study incorporates the riverine stretch and investigates the effect of river discharge on storm surge propagation along the upstream reaches of the Hooghly River. In addition, the river-tide interaction was studied with differential river discharge volumes of 1000 and 3000 m 3 s −1 that corresponds to the respective minimum and maximum discharges. Model simulations well represented the upstream tidal propagation as well the reversal of tidal currents in the river. Also the effect of variable river discharge volumes in modifying the limit of flood flow was clear from simulation. The results signify that limit of flood flow was seen nearly 70 km in the river upstream for discharge volume corresponding to 1000 m 3 s −1 and reduced to 62 km on increasing the discharge to 3000 m 3 s −1. The effect of wind stress on storm surge penetration into river was also investigated using the hypothetical Aila cyclone wind field. Moreover, the combined effect due to varying river discharge volumes and wind stress on storm surge characteristics was also studied. The study is an effort to understand the role of river-tide-storm surge interaction very useful in a real-time storm surge forecasting system. ARTICLE HISTORY
... The country's physical vulnerability is exacerbated by factors like high population density, poverty, and limited access to water supply, sanitation, energy, and health services (Huq and Rabbani 2015). Besides, certain factors, such as the geographical location in the tropical monsoon climate and the strange natural setting, make Bangladesh frequently prone to cyclones and storms (Madsen and Jakobsen 2004;Paul and Rahman 2006;Paul 2009;Malak et al. 2020). Bangladesh has been observing many cyclones in the past decades, and coastal regions are the most vulnerable to those cyclones where climate change impacts make the situation worse (Malak et al. 2020). ...
Climate change is a big challenge now. Currently, researchers, academics, and policymakers focus on coping with and dealing with the adverse effects of climate change. However, due to climate change impacts, it is impossible to determine the number of coping strategies, primarily when the appropriate coping and adaptation strategies depend on the socioeconomic and cultural context of vulnerable communities facing climate change-related extreme events. Therefore, we cannot deny the current debate between coping strategies and climate change adaptation. In this case, the chapter addresses existing definitions, discussions, and pieces of evidence on coping strategies and adaptations for dealing with the adverse impacts of climate change. It also discusses with examples how the various relationships between climate change-related events and coping strategies or adaptations are different. Researchers present theoretical backgrounds in understanding the nexus between climate change and coping strategies and adaptation contextually. The chapter also includes some discussions of the above linkage in Bangladesh’s context. Finally, various empirical studies provide thoughts that the connection between climate change, tackling strategies, and adaptation varies in terms of the severity and types of climate change-related events in which socioeconomic, sociodemographic, and cultural aspects mediate the relationship.
... This study found a reasonable agreement between model simulated inland flooding and what was observed. An integrated forecast system has been developed by Madsen and Jakobsen (2004) for Bangladeshi coast by using the MIKE 21 together with other models' components. This model served to analyse the storm surge height and inland flooding caused by Super Cyclone in April 1991. ...
Tropical cyclone (TC) is a well-known natural disaster that can devastate much of a society, environment, economy and result in people’s deaths. The North Indian Ocean (NIO) is one ocean basin that is very prone to TC. TCs often cause huge human casualties in densely populated communities like Bangladesh, India and Myanmar around the Bay of Bengal (BoB) region of the NIO. Therefore, it is urgent to analyse the impacts of TC-induced storm surge activity over NIO under different climatic scenarios for better preparation. This study has been conducted aiming to analyse potential impacts of TCs from storm surges both for the past (1990–2010) and future (2075–2099). To fulfil research objective, future TCs scenarios were obtained from the U.S. Geophysical Fluid Dynamics Laboratory climate model under the IPCC RCP warming scenarios. Then, JMA-MRI storm surge model for NIO were used for estimating TCs induced surge heights. While almost all intense TCs had historically made landfall around the BoB region, climate model projection simulated more intense TCs over the AS, which indicates larger and more destructive TCs especially around the coastal areas of the AS. It is also found the probability of TC track shift from the eastern part to the western part of both basins at the end of this century. The storm surge model estimates twice the size of the surge in the future and especially over the AS. Furthermore, spatial variation of TCs activities and their associated surge heights are found which largely depends on TC intensity and topography. In conclusion, it is expected that higher maximum surge level over the NIO especially over the AS basin will occur if the projected TC activity is robust. This study provides crucial information that can be used for short- and long-term disaster preparation.
... Despite the relatively smaller number of cyclones, more than 80% of global fatalities occur due to tropical cyclones in this region, mostly due to coastal flooding (Beal et al. 2020). Several of the most devastating cyclones that formed in the Bay of Bengal caused extensive casualties in the Bay of Bengal rim countries, particularly in India, Bangladesh, and Myanmar (Madsen and Jakobsen 2004;Kikuchi et al. 2009;McPhaden et al. 2009). Basin-wise, the Bay of Bengal cyclone contribution is 4%, and the Arabian Sea cyclone contribution is 2% to the annual global frequency of the cyclones ( Figure 2). ...
The north Indian Ocean accounts for 6% of the global tropical cyclones annually. Despite the small fraction of cyclones, some of the most devastating cyclones have formed in this basin, causing extensive damage to the life and property in the north Indian Ocean rim countries. In this review article, we highlight the advancement in research in terms of ocean-atmosphere interaction during cyclones in the north Indian Ocean and identify the gap areas where our understanding is still lacking.
Preprint of the article submitted to Earth Science Reviews.
... However, considering that it is impossible to avoid such events, prevention and preparation are always needed. In literature, extreme event predictions (Ferreira and Guedes Soares, 1998;Izaguirre et al., 2013;Lowe and Gregory, 2005;McInnes et al., 2007), the storm forecasting (Madsen and Jakobsen, 2004;Mattocks and Forbes, 2008;Rego and Li, 2009;Verlaan et al., 2005), the early warning techniques (Ciavola et al., 2011a(Ciavola et al., , 2011bGall et al., 2013;Jones et al., 2017) and in general the storm management are vital for everyone who lives, works and is generally active along the coasts (Hissel et al., 2014;Spencer et al., 2015). A close-up coastal zone management (Chadenas et al., 2014;Curtis, 2013;De la Torre et al., 2013;Hallegatte et al., 2013;Jaranovic et al., 2017;Musereau and Regnauld, 2014), the optimal design of port and coastal structures (Altomare et al., 2015;Basco, 2016;Burmeister et al., 2015;Do et al., 2016;Hatzikyriakou and Lin, 2017;McCullough et al., 2013;Mohd Anuar et al., 2018;Mooyaart and Jonkman, 2017;Phan and Simiu, 2011;Rao and Mandal, 2005;Takahashi et al., 2014;Van Doorslaer et al., 2017) and the public awareness (Lane et al., 2015;National Research Council, 2014;Paton et al., 2017) received considerable attention in recent years. ...
Taking into consideration the changing climate, researchers are mainly interested in measuring this change in many different sectors. Regarding the coastal areas, the effects are related inter alias to the sea level rise, but also the increase and the severity of storms incidence. In conjunction with the astronomical tide, coastal storms can cause extreme wave runup and overtopping phenomena in ports, and coastal structures, the consequences of which may be disastrous, mainly affecting the operation and the reliability of infrastructure. Consequently, the analysis of coastal storms is necessary for any future technical study in coastal engineering, for the design of port and coastal structures and the coastal management also. Coastal storms as multivariate and extreme events necessitate a detailed and multivariate analysis of many parameters. This work aims to review and highlight the most significant issues in coastal storm analysis, to summarise the knowledge and the current trends of coastal storms research, by exploring the scientific background through a literature overview. A guiding framework of storm analysis should include the most important aspects of this work which are: the coastal storm definition, the description of their severity, the understanding of the synoptic systems formation, the storm surges and the time-series analysis, the thresholds for their identification, the impacts, their classification, and finally the impacts of coastal storms on coastal human population.
... There may have been uncertainty in our simulated water level magnitude, which may come from the cyclone track, maximum sustained wind speed and radius (Madsen and Jakobsen, 2004). Uncertainties in each of the parameters mentioned have been estimated with freely available data sources keeping the other parameters at a fixed value. ...
The ultimate goal and highlight of this paper are to explore water levels along the coast of Bangladesh efficiently due to the nonlinear interaction of tide and surge by employing the method of lines (MOLs) with the aid of newly proposed RKAHeM(4, 4) technique. In this regard, the spatial derivatives of shallow water equations (SWEs) were discretized by means of a finite difference method to obtain a system of ordinary differential equations (ODEs) of initial valued with time as an independent variable. The obtained system of ODEs was solved by the RKAHeM(4, 4) technique. One-way nested grid technique was exercised to incorporate coastal complexities closely with minimum computational cost. A stable tidal oscillation was produced over the region of interest by applying the most influential tidal constituent M2 along the southern open boundary of the outer scheme. The newly developed model was applied to estimate water levels due to the non-linear interaction of tide and surge associated with the catastrophic cyclone April 1991 along the coast of Bangladesh. The approach employed in the study was found to perform well and ensure conformity with real-time observations.
... One can find numerous studies in the literature that discuss the impact of tropical cyclone-induced disastrous storm surges in the Bay of Bengal. Some of the pioneering and notable studies include Murty and Flather (1994), Das (1994), Dube et al. (1997), Madsen and Jakobsen (2004), Rao et al. (2007), and many others. Several factors that directly contribute to disastrous storm surge in the Bay of Bengal region are discussed in these studies. ...
The Bay of Bengal and the Gulf of Mexico are the two water bodies on the globe that are most prone to storm surges generated by tropical cyclones. In this chapter, a review has been made of the storm surge problem in the Bay of Bengal region located in the North Indian Ocean. Using the contemporary numerical models, not only storm surge elevations but also coastal inundations were computed for some recent cyclones in the Bay of Bengal. These models included the interactions between storm surges, tides, and wind waves. However, it should be noted that one of the challenging issues, which still remains unsolved to a large extent, is computing the interaction between storm surges and river flooding, and the contribution of this interaction to coastal flooding and inundation. A dramatic example of such an interaction was during the 29 October 1999 cyclone on the Odisha coast.
... There may have been uncertainty in our simulated water level magnitude, which may come from the cyclone track, maximum sustained wind speed and radius (Madsen and Jakobsen, 2004). Uncertainties in each of the parameters mentioned have been estimated with freely available data sources keeping the other parameters at a fixed value. ...
The numerical method of lines (MOLs) in coordination with the classical fourth-order Runge‒Kutta (RK(4, 4)) method is used to solve shallow water equations (SWEs) for foreseeing water levels owing to the nonlinear interaction of tide and surge accompanying with a storm along the coast of Bangladesh. The SWEs are developed by extending the body forces with tide generating forces (TGFs). Spatial variables of the SWEs along with the boundary conditions are approximated by means of finite difference technique on an Arakawa C-grid to attain a system of ordinary differential equations (ODEs) of initial valued in time, which are being solved with the aid of the RK(4, 4) method. Nested grid technique is adopted to solve coastal complexities closely with least computational cost. A stable tidal solution in the region of our choice is produced by applying the tidal forcing with the major tidal constituent M2 (lunar semi-diurnal) along the southern open-sea boundary of the outer scheme. Numerical experimentations are carried out to simulate water levels generated by the cyclonic storm AILA along the coast of Bangladesh. The model simulated results are found to be in a reasonable agreement with the limited available reported data and observations.
... Despite the fact that only seven percent of the global cyclones occur in the NIO, they are considered to be relatively fatal. Studies reporting the magnitude of damages caused by Cyclone Bhola (1970) [1] and Odisha Super Cyclone (1999) [2] eventuated from the BoB, exemplify the evident cataclysmic consequences of such extreme storm surge events. Hence, precise quantification (prediction) of such enormous surges through numerical modeling would greatly facilitate in extenuating the disaster management aspects during such calamities. ...
Tropical cyclones have always proved the extent of its catastrophe on several occurrences over the years. In particular, the Bay of Bengal (BoB) basin in the Northern Indian Ocean has produced such historic devastating events, thereby mandating accurate real-time predictions. Numerical modeling of storm surge has always been an arduous task, as it is integrated with various uncertain factors. Among those, the major governing component being the wind forcing or the wind stress — that signifies, the computational accuracy of simulated surge and wave parameters. The present study is aimed at analysing the most suited wind drag evaluation method for real-time predictions of storm surge along the BoB. Cyclone Phailin (2013) was considered for the numerical simulations. To evaluate the wind drag coefficient, three most extensively used linear empirical relations along with the enhanced Wave Boundary Layer Model (e_WBLM) were used. The surge was subsequently simulated (using the coupled hydrodynamic circulation and wave model: ADCIRC and SWAN, respectively), individually for each of the above wind stress methods to obtain the corresponding storm surge (residual) and the storm wave features. The modeled values were further validated with the in-situ data obtained from tide gauge station and buoys respectively. It was quite intuitively observed that, e_WBLM based results correlated well with the in-situ values than its linear counterparts since, the former pragmatically includes the effects of air-sea interaction at high wind speeds in the model. The e_WBLM-based computation of significant wave heights (Hs) in deep as well as shallow water, nevertheless enabled efficient and reasonably-reliable estimations of the peak incidents.
... This study considers a coupled hydrodynamic (HD) module and spectral wave (SW) module implemented in the commercial program Mike 21. The HD module solves the depth-integrated incompressible Reynolds-averaged Navier-Stokes equations and has been used by other researchers to study storm surge [13]. The SW module simulates the growth, propagation, and decay of wind-waves and swell using the third-generation spectral wind-wave model and has been shown to have reasonable results for hurricane conditions [3,14]. ...
Assessment of multiple hazards in the hurricane-induced offshore environment is a complex problem, involving the correlation in space and in time of many variables, such as wind speed, significant wave height, surge height and others. There is a scarcity of measurements of these conditions during hurricanes and, as a result, numerical models are usually adopted to estimate these variables in space and in time. Such models are highly complex and computationally demanding and metamodels have the potential to simplify and expedite their use in design and risk assessment of the extreme offshore environment. Kriging, a popular metamodeling method, is adopted in this study to predict time-dependent seastate during hurricane conditions. A subset of a synthetic hurricane catalog is selected and the corresponding seastate conditions are estimated using the commercial numerical model Mike 21 HD/SW. The Kriging model is then adopted to emulate the results of the numerical model and the performance of the Kriging model is evaluated using cross-validation. The impact of several features of the Kriging model on the model’s performance is discussed, including, in particular, the time instances in the input vector, the size of the dataset, and the type of regression and correlation models.
... Almost 14% of the population of India have their habitats along the coastal stretches and are highly vulnerable to such extreme sea-level events. In the recorded history of such events, the surge (~10 m) caused by Cyclone Bhola in the year 1970 on the coasts of Bangladesh (Madsen and Jakobsen, 2004) is considered the most intensive one. A Super Cyclonic Storm (SCS) that made its landfall in the Odisha coast in 1999 is observed to be the highest (of about 7.5 m) surge causing event in context of Indian scenario (Dube et al., 2000). ...
Modelling of storm surge numerically has always been strenuous as it is associated with various influencing factors. The major governing component being the wind forcing or the wind stress - that signifies the compu-tational accuracy of simulated surge and wave parameters. The present study is aimed at analysing the most reliable wind drag evaluation method for real-time predictions of storm surge. In an attempt to examine the same, two tropical cyclones (Thane and Vardah) eventuated in the Northern Indian Ocean were modelled. Four most widely used linear empirical and quadratic relations along with the enhanced Wave Boundary Layer Model (WBLM) were executed for the estimations of wind drag coefficient. The surge was subsequently simulated (using the coupled hydrodynamic circulation and wave model: ADCIRC and SWAN, respectively), individually for each of the above wind stress methods to obtain the corresponding water levels and wave features. The modelled values were further validated with the observed water level and wave data. It was quite intuitively observed that, WBLM outperformed (i.e. significantly correlated with the observed values) its linear counterparts since, the former pragmatically includes the effects of air-sea interface at high wind speeds in the model. However, due to insufficiency of the observed parameters, water levels obtained at locations of maximum wind speeds could not be satisfactorily validated. The WBLM-based computation of significant wave heights in deep as well as shallow water nevertheless enabled efficient and reasonably-reliable estimations of the peak incidents (along with relative wave directions and energy densities). Although this study essentially includes cyclonic wind velocities, it was identified that - with given wind field that includes the ‘pre-existing’ wind-wave climate in the relevant domain (i.e. before the cyclone genesis) the modelled estimates could be more precise.
... These events seriously affect the livelihoods of vulnerable populations (Ayeb-Karlsson et al. 2016;Garai 2014;Parvin et al. 2016). Particular factors, including geographical position, a tropical monsoon climate and a peculiar natural setting make Bangladesh vulnerable to frequent cyclones and storm surges (As-Salek 1998; Madsen and Jakobsen 2004;Paul and Rahman 2006;Paul 2009). Such events are quite common in Bangladesh (Ali 1999;Paul 2009;Paul and Routray 2013). ...
This study addresses how perception of risk of child mortality, land ownership and household type influence fertility preferences. The study focuses on four distinct villages: two vulnerable to cyclones and floods and two not usually subject to the impacts of extreme weather events (EWEs). The study uses a mixed-methods approach in collecting relevant information from 759 randomly selected ever- married women at reproductive age who had at least one child and were living with their husband during the field survey. The descriptive findings demonstrate that fertility preferences vary regarding perceived risk of child death, land ownership and household type, and that the influences of these factors vary for areas vulnerable to EWEs and not vulnerable to EWEs. Binary logistic regression analysis reveals that perceived risk of child death from EWEs and land ownership are the significant covariates in areas vulnerable to EWEs. In contrast, experience with child death, land ownership and household type are the most influential covariates explaining variation in fertility preferences in the areas not vulnerable to EWEs. The findings of the study can inform policy recommendations in terms of effective disaster management programs and family planning initiatives during climate-related events.
... In addition, the shape parameter B and the maximum wind speed radius R max are two essential parameters in the model, which control the eye diameter of the typhoon and affect the accuracy of the reconstructed wind field. Studies have applied different formulas to solve parameters B( Madsen and Jakobsen, 2004;Rego and Li, 2010). Mattocks and Forbes (2008) proposed a more detailed equation to calculate the parameter B: ...
Taking severe typhoon Kalmaegi (2014) as an example, which is chosen due to its good availability of observations from mulitplatforms, the application ability of different wind field models and wave boundary layer model (WBLM) are investigated simultaneously in WAVEWATCH III model (WW3). First, based on the comparisons between measurements of two in situ buoys and model results, a better-quality wind forcing from WRF’s output stands out slightly compared with other two constructed wind fields during the time segment of “During-TY”. Second, the comparisons of simulated results by using different drag coefficient schemes between WBLM and the original parameterisation formula in ST2 package are further implemented. The good performance of drag coefficient Cd from WBLM under high-wind conditions, which is embedded into ST2 wind-input source function, is also verified by several data set of field observations. As a result, on the basis of the observations from buoy-based and radar altimeter measurements (RAs), the values of significant wave height ( Hs) from simulation with WBLM are weaker at high sea state areas ( Hs>6 m) compared with that from the ST2 scheme, which coincide with the general knowledge that the amount of momentum exchange at the air-sea interface plays a vital role in the development of typhoon waves. Limited by less frequently sampled collocated measurements under high-wind conditions, the effectiveness of improvement for typhoon waves simulation using WBLM in WW3 requires more validation cases in future work.
... While all previous studies advanced the state-of-the-art in simulating hydrodynamic and atmospheric physical processes due to TCs in the Bay of Bengal, none aimed to forecast both storm surge and storm surge induced inundation in the coast of Bangladesh on a real-time basis. Madsen and Jakobsen (2004) developed a modeling system to predict both surge heights and flooding, which consists of three modules: (1) a statistical model for forecasting cyclone track and wind speed; (2) an analytical model for generating wind and pressure fields; and (3) a data assimilation system for incorporating observed wind and pressure intensities in computing cyclonic parameters. While the combined modeling framework was able to track TC to respective inundation in coastal areas, the cumulative uncertainties in the forecast in the three modules were found to be too high for operational purposes. ...
Storm surge induced by tropical cyclones (TCs) has become a global concern
due to its catastrophic and expensive impacts on many coastal and
tropical areas. It is also evident that global sea level rise (SLR) is expected
to amplify coastal flood risk in the future. The exposure and vulnerability
to flooding due to storm surge and SLR are particularly higher in the
developing countries with densely populated low-lying coastal areas.
Bangladesh is known for being one of the most natural disaster prone
countries in the world, where storm surge and coastal flooding have lifethreatening
impacts to millions of people living in its coastal region. The
country lies within an active delta with hydromorphologically dynamic
coastal lands and its livelihood is highly dependent on its natural resources.
High subsidence rates, increase in upstream river flows, and human interventions
are also exacerbating the existing inundation regimes and drainage
situations in the coastal areas of Bangladesh. Finally, an ecosystembased
approach has the potential to mitigate the twin threats of SLR and
TC in a difficult biophysical and socioeconomic setting like that of coastal
areas of Bangladesh.
Tropical cyclones strike massive devastation of agricultural crops in South Asian countries practically every year. For assessing impacts on primary land use and land cover (LULC) classes of Patuakhali district in Bangladesh, this study utilized the Landsat-8 image dataset to compute change detection indices of a consistent cyclone landfall period in the late rainy season (October and November). Different stage of cyclones based on their wind speed (km/h) were also analyzed to explore agricultural crop change detection due to the tropical cyclone (TC) Bulbul (made landfall on November 9th, 2019). Three years later, cyclone Sitrang made landfall on October 24th, 2022, and was employed for the test results that the Bulbul’s rice growth vegetation index (RGVI)-CD trained in the study’s machine learning (ML) system. Therefore, the objective of this study was to determine rice crop changes from RGVI due to a cyclone (Bulbul) to evaluate growth change status by another cyclone (Sitrang) using machine learning system. In Patuakhali district, the rice crops were damaged mainly and affected in classification as moderately changed detected (MCD) 26.07%, very changed detected (VCD) 48.83%, and extremely changed detected (ECD) 17.73% in total agricultural lands area (1548.93 km2). It was also significantly monitored for the rice crops to change as rice growth vegetation index (RGVI)-CD related to cyclone wind speed (km/h), DEM, distance from the rivers, and shorelines. From the result, the symmetric regression of coefficient (R2) of (i) linear regression, (ii) fine tree, (iii) support vector machine, (iv) ensemble boosted trees, and (v) trilayered neural network were obtained 0.735, 0.734, 0.737, 0.756 and 0.736 as good-fitted test outcomes respectively. Applying the five machine learning models that were created from cyclone Sitrang, it was discovered that the test set in this system was accurate to the observed forecast with acceptable RMSE and MAE values. Therefore, study can be helpful for researchers creating new damaged and yield loss area assessment policies to help TC-affected farming communities, especially rice growers, prepare an effective emergency response plan for their socioeconomic needs fulfillment in the changing climate perspectives for attaining sustainable development.
Floods are ranked among the largest and costliest natural disasters globally having major impact on various economic sectors. In India, flooding is one of the three prominent climate extremes, other two being droughts and cyclones. Flood forecasting and warning system is an important tool for effective management of water resources and for emergency response services. Across the globe, several flood forecasting tools have been developed to address specific or local challenges, but no single tool provides a complete operational solution that is applicable universally. In India, flood forecasts for major interstate rivers and projects are currently prepared and disseminated by Central Water Commission (CWC). However, the desirable lead-time and reliability for flood forecasting requires considerable improvements. The recent research and developments in flood forecasting attempt to consider rainfall forecasts, to significantly improve upon the lead-time to forecast flood. At present, India
Meteorological Department (IMD) generates precipitation forecasts for short-range (up to 72 hours), medium range (4 to 10 days) and long range (30 days and up to one season), which may
be used to generate short-range and medium range streamflow forecasts in a basin. The reliability of the streamflow forecast is based on the accuracy of the rainfall forecast, hydrological model and its parameters, and initial conditions. This paper has reviewed the ensemble framework adopted in streamflow forecasting across the globe and their applicability in Indian context with a focus to address the present gaps and challenges in flood forecasting. The review will provide an overview of this methodology and its relevance in operational flood forecasting. The paper also briefly describes the recent initiatives in India in this field.
The concept of resilience is a well-recognized field of study that is increasingly advanced among scholars, professionals, and practitioners. Resilience thinking helps to understand how a particular system works that incorporates both natural phenomena and social perspectives involving with disturbances, surprises, and uncertainty that affect socio-ecological systems. We argue resilience as the capacity of a system to evolve and function in a dynamic way through adaptive cycle where households and communities are linked to the problem of riverbank erosion in Bangladesh. Few studies have been conducted to understand how communities that face enormous threats and challenges related to chronic and acute riverbank erosions in the Bangladesh coastal delta. In this study, we explore and theorize how riverbank erosion impacts Lower-Meghna River basin community and their coping strategies through resilience thinking and adaptive capacities. Information used in this study are collected from questionnaire surveys, Focus Group Meetings (FGMs), and key personnel interviews from Ramgati Upazilla of Lakshmipur District, Bangladesh, which indicate that respondents experience significant household displacement due to riverbank erosion. Respondents were asked about what coping mechanisms they adopted in response to recent riverbank erosions. Results indicate that relatives, neighbors, and local community members primarily provide shelters and support for those families that were affected by the riverbank erosions.
Considering Bangladesh as one of the most prone to cyclones, the government of Bangladesh and international cooperation agencies are trying to mitigate the damages and losses of cyclones through the construction of cyclone shelters in the coastal belt of the country. This research aims to find out the influence of the socio-spatial distribution of refuge shelters on evacuation decisions. An empirical study was conducted in Charmadras Union of the Charfasson Upazila of Bhola district in Bangladesh. Employed a structured survey questionnaire, a total of 115 individual households were interviewed along with some key informants interviews. The spatial distribution of the cyclone shelters is analyzed using the satellite image. Results show that the spatial distribution of cyclone shelter doesn’t affect the evacuation decisions, rather than a set of social factors influence on the people’s evacuation decisions. Among them, the decision making process of cyclone shelter and it’s location selection, better facilities in the shelter, in particular, the facilities for women, children and elderly people. Besides, access to information and individual household level risk perception and refugee preferences influence the evacuation decisions. Since cyclone shelter is one of the major programs of disaster risk reduction measures in Bangladesh, the study finding is helpful for future policy planning in the face of climate change.
Coastal inundation is the flooding of coastal zone resulting from increased river discharge, spring tides, severe storms, or generation of powerful waves from tectonic activity (tsunami). This article discusses the critical factors that contribute to coastal inundation. Among the probable factors that cause coastal flooding and destruction, storm surge is the most frequent, and hence this article provides a detailed evaluation of the progress made in storm inundation research. Recent advances in coastal inundation modelling include efforts to understand the nonlinear dynamic interaction of near-shore waves, wind and atmospheric pressure with still water sea level and coastal currents, and their combined effects on storm surge along the coast and interaction with coastal morphology. An advanced storm-surge model comprises different modules, viz. an atmospheric component, and two ocean components for surge and wave simulations; these modules are coupled with each other. The nesting of regional coastal model with an ocean-wide model captures the far-field boundary forcing of extreme events that usually originate from the warm open ocean. Even though significant advancements reported on the efficiency and accuracy of storm surge and inundation prediction, further studies are required to understand the nonlinear interaction of storm surge with coastal landforms and their vegetation (land cover). In the context of rising sea level, increased tropical cyclone activity and rapid shoreline change, it is pertinent to evaluate the future flooding risk associated with landfall of tropical cyclones in densely populated coastal cities.
Data assimilation (DA) is an essential element for the next generation of operational forecast systems for estuaries, to improve estuarine management. With limited resources and prohibitive cost to collect observations for such system, sensor choice and location is of prime importance in improving hydrodynamic model performance. In this study, we examine an optimal ensemble-based DA platform for improving the hydrodynamic modelling of a shallow estuary. Using an ensemble Kalman filter (EnKF), a set of synthetic (twin) experiments was conducted to test different DA scenarios covering observation types (i.e. water level and velocity) and noise modelling. We also evaluated the impact of the observation location on the DA performance by performing an observing system simulation experiment (OSSE). Results revealed that the assimilation of a single variable can significantly enhance the accuracy of the variable being assimilated, while the level of improvement for another variable is smaller. However, the best model estimates were obtained via a multivariate EnKF (i.e. both observations are assimilated). EnKF was robust to under and overestimation of the model errors, although overestimation led to slightly greater improvements. Our analysis showed that model performance is more sensitive to velocity observation location, rather than water level. These findings suggest that locations with strong velocity gradients are the locations where the hydrodynamic model needs to be enhanced, and accordingly, they are the preferable locations to deploy a velocity sensor.
The Bay of Bengal is a well-known breeding ground to some of the deadliest cyclones in history. Despite recent advancements, the complex morphology and hydrodynamics of this large delta and the associated modelling computational costs impede the storm surge forecasting in this highly vulnerable region. Here we present a proof of concept of a physically consistent and computationally efficient storm surge forecasting system tractable in real-time with limited resources. With a state-of-the-art wave-coupled hydrodynamic numerical modelling system, we forecast the recent super cyclone Amphan in real-time. From the available observations, we assessed the quality of our modelling framework. We affirmed the evidence of the key ingredients needed for an efficient, real-time surge and inundation forecast along this active and complex coastal region. This article shows the proof of the maturity of our framework for operational implementation, which can particularly improve the quality of localized forecast for effective decision-making.
Each year, about 10,000 people die due to the destruction caused by tropical cyclones. A fully developed tropical cyclone has the ability to release heat of the order of 1016 Joules per second. They are responsible for the generation of heavy winds and rainfall, and inundation in the coastal regions, affecting the lives of millions of people. Over the last 15 years, there has been scientific breakthroughs in estimating the track of a cy- clone, but more often that not, its intensity is not prognosticated correctly. Forecasting a cyclone precisely is very challenging because of a variety of factors, and is, therefore, an interesting field of research. The thesis focuses on developing a novel cyclone pre- diction approach, its evolution as it reaches the shoreline, and the subsequent coastal inundation.
As storm surge models are becoming more and more complex, the amount of com- putation required has seen an exponential increase. At the same time, the clock speed of the CPUs hasn’t seen a significant increase in the last 10 years. The second aim of this thesis is to present the necessity of HPC in weather forecasting and climate models, wherein investigators and scientists are required to deal with large datasets and perform multiple simulations with slightly perturbed initial and boundary conditions on higher order governing equations to obtain an ensemble forecast. For this research, analysis and fine-tuning of several parameters for simulations is achieved using a fast numeri- cal solver that implements High Performance Computing (HPC) using general purpose GPUs.
An altered version of finite element method is used. The CPU code, accelerated using OpenMP has been developed by Shagun Agarwal, PhD Student, IIT Madras as part of his doctoral research and we aim to increase its computational efficiency using GPUs. Test cases are run in the East Coast of Tamil Nadu.
From dynamical considerations, the maximum wind speed in a tropical cyclone depends upon the pressure gradient, the range with respect to the storm centre, and the air density at the spot at which the maximum wind occurs inside the storm. It is nearly impossible to obtain direct measurements of these parameters in the cyclones because of their violent nature. A more practical approach is provided by the relation between the maximum winds and the central pressures in the storms. In the present paper the relationship between maximum wind speed and the minimum sea level pressure in cyclonic storms occurring in the Bay of Bengal and Arabian Sea has been studied with the help of the available observations from ships, recoanaissance aircraft and the coastal stations. On the basis of these data, best fit equation for the maximum wind speeds applicable for the Indian Seas has been expirically derived.
Statistical analog models for the prediction of tropical cyclone motion have been developed for all of the world's tropical cyclone basins. The popularity and success of these models is related to their ability to optimize the variance reducing potential of climatology and persistence, At the same time, they effectively recognize certain repetitious synoptic patterns without having to use fields of sometimes unavailable and often unreliable synoptic data over the tropics. The analog method can be simulated by the use of continuous function derived through the use of multivariate regression analysis. This method simulates all aspects of the analog process including the derivation of probability ellipses while avoiding certain operational problems inherent to the purely analog approach. This paper describes the derivation of such a model for the north Indian Ocean tropical cyclone basin. It is patterned after an earlier paper (Neumann and Randrianarison 1976) which describes the development of a similar model for the southwest Indian Ocean tropical cyclone basin.
An analytic model of the radial profiles of sea level pressure and winds in a hurricane is presented. The equations contain two parameters which may be empirically estimated from observations in a hurricane or determined climatologically to define a standard hurricane; example are given. The model is shown to be generally superior to two other widely used models and is considered to be a valuable aid in operational forecasting, case studies and engineering work.
The depth-averaged, numerical storm-surge model developed by Hubbert et al. (1990) has been configured to provide a stand-alone system to forecast tropical cyclone storm surges. The atmospheric surface pressure and surface winds are derived from the analytical-empirical model of Holland (1980) and require only cyclone positions, central pressures, and radii of maximum winds. The model has been adapted to run on personal computers in a few minutes so that multiple forecast scenarios can be tested in a forecast office in real time. The storm surge model was tested in hindcast mode on four Australian tropical cyclones. For these case studies the model predicted the sea surface elevations and arrival times of surge peaks accurately, with typical elevation errors of 0.1 to 0.2 m and arrival time errors of no more than 1 h. Second order effects, such as coastally-trapped waves, were also well simulated. The model is now being used by the Australian Tropical Cyclone Warning Centres (TCWC's) for operatio...
The successful application of a conceptual rainfall-runoff (CRR) model depends on how well it is calibrated. Despite the popularity of CRR models, reports in the literature indicate that it is typically difficult, if not impossible, to obtain unique optimal values for their parameters using automatic calibration methods. Unless the best set of parameters associated with a given calibration data set can be found, it is difficult to determine how sensitive the parameter estimates (and hence the model forecasts) are to factors such as input and output data error, model error, quantity and quality of data, objective function used, and so on. Results are presented that establish clearly the nature of the multiple optima problem for the research CRR model SIXPAR. These results suggest that the CRR model optimization problem is more difficult than had been previously thought and that currently used local search procedures have a very low probability of successfully finding the optimal parameter sets. Next, the performance of three existing global search procedures are evaluated on the model SIXPAR. Finally, a powerful new global optimization procedure is presented, entitled the shuffled complex evolution (SCE-UA) method, which was able to consistently locate the global optimum of the SIXPAR model, and appears to be capable of efficiently and effectively solving the CRR model optimization problem.
The field of storm surge modeling has developed and matured considerably over the past 30 years. Several operational surge models have been implemented in Europe over the past decade. These operational advances have been accompanied by research into new areas, chiefly coupled surge-wave models and data assimilation, both of which are covered in this review. Surge-wave models attempt to provide more realistic model physics for the crucial area of air-sea interaction. Assimilation techniques use available data to generate improved numerical solutions, despite model inadequacies. The current activity in surge modeling and related areas is highlighted by the large proportion of recent papers cited in this work. Despite this activity, there is a general recognition that inadequate meteorological inputs remain the weak link in surge modeling. In addition, the advances in midlatitude modeling are not mirrored in the tropics. This is largely due to difficulties in predicting the paths and properties of tropical storms, but it also serves to emphasize the importance that has been attached to storm surge modeling in Europe.
Present day instrumentation networks already provide immense quantities of data, very little of which provides any insights into the basic physical processes that are occurring in the measured medium. This is to say that the data by itself contributes little to the knowledge of such processes. Data mining and knowledge discovery aim to change this situation by providing technologies that will greatly facilitate the mining of data for knowledge. In this new setting the role of a human expert is to provide domain knowledge, interpret models suggested by the computer and devise further experiments that will provide even better data coverage. Clearly, there is an enormous amount of knowledge and understanding of physical processes that should not be just thrown away. Consequently, we strongly believe that the most appropriate way forward is to combine the best of the two approaches: theory-driven, understanding-rich with data-driven discovery process. This paper describes a particular knowledge discovery algorithm—Genetic Programming (GP). Additionally, an augmented version of GP—dimensionally aware GP—which is arguably more useful in the process of scientific discovery is described in great detail. Finally, the paper concludes with an application of dimensionally aware GP to a problem of induction of an empirical relationship
A data set consisting of observations of significant wave height and wind speed within mature hurricanes has been obtained from the GEOSAT satellite mission. Due to the global coverage of the satellite, this data set is extensive, consisting of 100 hurricanes. In addition, as the satellite rapidly propagates across the region influenced by the hurricane wind field, an almost instantaneous cross-section through the hurricane is observed. These features mean that the data set is significantly more comprehensive than those previously presented. The observations confirm the importance of both the maximum wind speed within the hurricane and the velocity of forward movement in determining the magnitude and distribution of the significant wave height field. The data are presented in terms of a relatively simple parametric hurricane wave model. This model represents both a compact description of the data and a tool for engineering design.
The four primary predictors are 1) the difference between the current storm intensity and an estimate of the maximum possible intensity determined from the sea surface temperature, 2) the vertical shear of the horizontal wind, 3) persistence, and 4) the flux convergence of eddy angular momentum evaluated at 200 mb. The sea surface temperature and vertical shear variables are averaged along the track of the storm during the forecast period. The sea surface temperatures along the storm track are determined from monthly climatological analyses linearly interpolated to the position and date of the storm. The vertical shear values along the track of the storm are estimated using the synoptic analysis at the beginning of the forecast period. All other predictors are evaluated at the beginning of the forecast period. -from Authors
The topic of the paper is quantitative skill assessment in numerical flow modelling. Conceptual model definition, discretization aspects, quality assessment of the var- ious types of model input data and model validation data, quantitative and ob- jective norms and criteria for validation and assessment of results are discussed. Introductory sections discuss the definition of the concepts and terminology, and the characterization of the types of geophysical data that are used. This is followed by addressing the need for explicit model definition. In a further section we discuss the well-known method of the not formally structured process of calibration and validation by hand through visual inspection of the results, based on knowledge of the processes and insight. The strong potential of the newly available automatic parameter identification techniques to support insight and knowledge is discussed as well. The various aspects are illustrated on the step by step set up and validation of the Dutch Continental Shelf Model. This model is extensively used for simulation of tide and surge on the Northwest European Continental Shelf. The integration of a dedicated version as a module for six-hourly surge forecasting in the automatic production line of the Royal Netherlands Meteorological Institute (KNMI) is dis- cussed next. It serves as a vehicle to illustrate the crucial aspects of elicitation, quantification and actual guaranteeing of skill and quality that is required when one applies a model as an fully operational decision support tool. In the success of such applications the model's extension with data-assimilation schemes and its interfacing with other models which provide input data play a key role. To preserve model integrity and model skill, the automatic input of time varying field data re- quires a rigorous automatic data-quality screening, however. The paper shows that the concepts and tools for quantitative skill assessment of coastal ocean models- particularly for water levels- exist; conscientious application will lead to a model whose skill can be assessed quite clearly in an explicit, objective and quantified manner.
Negative surges destroy coastal aquaculture installations and hinder rescue-evacuation operations during cyclones and storm surges in the Meghna estuary in Bangladesh. The influence of the characteristics of the cyclones striking the Noakhali-Chittagong-Cox's Bazar coast on the negative surges in the Meghna estuary is examined. This study uses a (1/120)° resolution numerical model, which includes the offshore islands and bathymetric details of the worst-affected northernmost pan of the Meghna estuary. The model was verified by the observed data of official agencies like the Bangladesh Department of Hydrography. The negative surges in the Meghna estuary are found to have a duration of 4-6 h, occurring before the main surge. The negative surges in the region show remarkable sensitivity to the astronomical tides and to the propagation path of a cyclone. The mechanism of negative surges in the Meghna estuary is also discussed.
A numerical model for simulating and predicting tides and storm surges in regions that include areas of open sea combined with estuarine channels and intertidal banks is described. The model makes use of modified depth-averaged equations with a numerical scheme in which the solution of 1D equations for narrow channels, 2D equations for the open sea. The model is applied to the northern shelf of the Bay of Bengal and the Ganges Delta devastated by a cyclone surge in April 1991. Hindcast and "forecast' simulations of this event, using forcing derived from a semianalytical cyclone model with data supplied by the Joint Typhoon Warning Center (JTWC), are described. The timing of cyclone landfall and its coincidence with high tide determine the area worst affected by flooding. The "forecast' was based on a standard JTWC warning issued 12-18 hours ahead of the event. The predicted landfall was located accurately but its timing was about 5 hours late. As a result, the area of highest water levels shifted north. Finally, results for the April 1991 storm are compared with those from a simulation of the great cyclone in November 1970. -from Author
Observational information from 533 radial flight legs executed by the
National Hurricane Research Laboratory over a 13-year period (1957-69)
is used to present the structural characteristics and the variability of
the hurricane's inner core region. Tangential and radial winds,
D-values, and adjusted temperatures are composited with respect to the
Radius of Maximum Wind (RMW) in order to construct a five-level mean
symmetric storm and a five-level mean asymmetric storm. The slope of the
RMW with height and the position of the RMW relative to the inner cloud
wall are presented. Utilizing these results, an idealized, steady-state
schematic model of the flow conditions in the inner hurricane core is
presented. Storms are stratified by deepening and filling tendency,
intensity and storm speed. Finally, the variations of the RMW with
latitude, maximum wind, inner radar radius, central pressure, and other
features are discussed.Many significant features are noted: 1) storm
inflow is confined almost exclusively to the lowest layer and occurs at
radii larger than the RMW; 2) inside the RMW (i.e., in the eye) outflow
is present; 3) the warmest cyclone temperatures result from subsidence
and occur just inside the eye-wall cloud edge where the sinking is
strongest; 4) the largest D-value and adjusted temperature gradients
occur at and just outside the RMW; 5) the largest convergence occurs in
the lowest layer at the RMW; 6) the slope of the RMW with height is
small and appears to be a function of intensity; 7) the maximum winds
occur within the eye wall cloud area; 8) inner core winds are shown to
have a natural asymmetry beyond that induced by storm motion; 9)
vertical wind shears in deepening storms are much smaller than in
filling storms; 10) in intense storms the maximum winds occur closer to
the center than in weaker storms; 11) faster moving storms were more
intense than slower moving storms; and 12) at high latitudes the maximum
winds occur further away from the storm center than at low latitudes.
Other features are shown and discussed.
The empirical formula proposed recently relating wind-stress coefficient to wind velocity, C10=(0.8+0.065 U10)×10-3, appears to be applicable even in hurricanes. This formula also agrees with the correlation curve proposed earlier, C10=[kappa/ln(1/aC10F2)]2, F=U10/(gZ)1/2, where a=0.0185 is the Charnock constant and Z=10 m in the anemometer height.
The Meghna Estuary is a coastal plain estuary on the coast of Bangladesh. The important driving forces for the flow in the Estuary are the bathymetry, tides and the outflow from the Meghna River. A numerical model covering the northern half of the Bay of Bengal including the Meghna Estuary was set up with the objective to increase our understanding of the hydrographic features and morphological dynamics in the Estuary, especially in the case where man-made physical interventions are constructed. The simulations revealed a counter-clockwise residual circulation with a northward net flow in the Sandwip Channel of 10000m3s−1 during the dry season and 15000m3s−1 during the wet season. The residual flow is forced by tides together with the bathymetry. During the dry season the flow is approximately equal to the river discharge and during the wet season it is approximately one-third to one-sixth of the river discharge. The residual circulation to some extent traps the river water inside the Meghna Estuary and is one of the reasons for the relatively low salinity in the estuary even during the dry season. It is also believed to be important for the morphological development. Finally, a suggested intervention north of Sandwip shows to stop the residual circulation in the Estuary, for which reason it was advised not to construct such an intervention without further detailed investigations.
To establish useful warning systems for hurricanes, it is necessary to
accurately predict both hurricane intensity and track. But although the
forecasting of hurricane tracks has improved over the past 30 years, the
factors that control the intensity of hurricanes are still poorly
understood, leading to almost no reliability in forecasts of hurricane
intensity evolution. Efforts to improve intensity forecasts have focused
almost exclusively on characterizing the dynamical interactions between
hurricanes and their atmospheric environment. Here I use a simple
numerical model to demonstrate that, in most cases, the evolution of
hurricane intensity depends mainly on three factors: the storm's initial
intensity, the thermodynamic state of the atmosphere through which it
moves, and the heat exchange with the upper layer of the ocean under the
core of the hurricane. Such a limited number of controlling factors
offers hope that, given an accurate forecast of a hurricane's track, its
intensity can be reliably forecast using very simple models.
A numerical hydrodynamic model of the North Sea and the Baltic Sea receiving meteorological forcing from a high resolution limited area model has been running operationally since 1990. The experience with this model is described from a quantitative skill assessment point of view. This includes the setting up of the model, the verification of the model in hindcast, the operational forecast experience and procedures to improve the forecasts by initialization of the model prior to the forecast.
A technique for using satellite pictures to analyse and forecast tropical cyclone intensifies is described. The cloud features used to estimate the cyclone's intensity and its future change of intensity are described. Procedures for interpreting cloud characteristics and their day-by-day changes within the guidance and constraints of an empirical model of tropical cyclone changes are outlined.
Studies are described that use a fine-resolution numerical model and incorporate the islands and detailed bottom topography of the Meghna estuary. They show that depending on the characteristics of the atmospheric cyclone and the astronomical tide, storm surges can be coastal trapped in the Meghna estuary and propagate like edge waves along the coastline causing widespread devastation and enormous loss of life and property. The funneling effect of the narrowing estuary acts strongly on the pressure response and predominantly in the region north of Sandwip Island. The combination of coastal trapping and the funneling effect results in the widespread nature of the surges in the Meghna estuary. The widespread nature of the surges is directly proportional to the wind inflow angle and to the radius of maximum cyclonic wind, but inversely proportional to the angle of crossing of the cyclone as made with the coastline. The cyclone striking the Noakhali-Chittagong coast produces more widespread surges than does a cyclone striking the Chittagong-Cox's Bazar coast. A rapidly moving cyclone drives the surges toward the northern coast. If a cyclone strikes during the ebb tide phase, then nonlinear tide-surge interaction also generates separate surges far to the west in the Khepupara region.
The paper presents the wind shear stress on the sea surface as well as the velocity profile in stably stratified atmospheric boundary layer flow over wind waves by using similarity theory. For a given geostrophic velocity, Coriolis parameter, spectral peak period and stratification parameter, the sea surface shear stress is determined. Further, the direction of the sea surface shear stress and the velocity profile are given. Parameterizations of the results are also presented. Finally, the engineering relevance of the results is discussed, and, if the wind velocity at the 10 m elevation is available, a simplified method of calculating the sea surface shear stress is given.
The ways in which engineering systems fail (i.e., their occurence and frequency) demonstrate considerable differences between hypothetical models assumed for design and actual performance. All materials contain imperfections. All systems are subject to complex interrelationships, material defects, structural deficiencies, human errors, ambient fluctuations, and, hence, to varying degrees of randomness (uncertainties). Various methods have been offered to accomodate uncertainty. The most common, by far, is to assign single-valued point estimates that reflect central tendencies or implied levels of conservatism. Analyses are then reduced to deterministic treatments. More direct probabilistic methods employ Monte Carlo simulations or truncated Taylor series. However, analyses rapidly become exceedingly difficult, if not impossible, for these methods for all but a very few uncorrelated random variables. These matters and others have been ameliorated by Rosenblueth's point estimate method.1 Many problems are encountered that require numerous correlated random variables. For such systems all of the above methods become untractable. This paper presents a simple procedure that accomodates the analyses of such systems.
For the prediction of the storm surges of Bangladesh, a model has been developed by incorporating the islands and the bathymetrical details. The effects of the Swatch of No Ground, the sea level rises and the bottom level changes have been found to be active in the water regime of the Bay of Bengal. The model further indicates that the sea-level rise will result in proportional increase in surge-height and the bathymetrical rise will prolong the peak of the storm surges. Storm-surge models so far proposed for Bangladesh are discussed emphasizing the new ideas developed and the deficiencies remaining. The areas of research-needs in the storm-surge modeling activities for Bangladesh are pointed out and a set of recommendations is made.
Cyclone forced storm surges cause severe damage to coastal structures and loss of human lives and properties. In cyclone protection and warning it is important to be able to calculate the cyclone air pressure and wind field on the basis of rather limited information, such as cyclone position, pressure drop, maximum wind speed and radius to maximum wind speed. In the present work, parametric cyclone models based on such limited information are investigated and compared. Analytical expressions of the tangential and radial velocity distributions are derived from the governing momentum equations. It is found that the analytical models provide very similar air pressure and tangential wind speed distributions. Instead of using a simple formulation of the deflection angle, the derived analytical expression of the radial velocity distribution is used and compared to earlier numerical solutions. A procedure is formulated for estimation of the shape of the cyclone on the basis of maximum wind speed versus pressure drop relations. Finally, examples of comparisons of measured and calculated air pressures and wind speeds and directions are presented.
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