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Ensemble mean forecast errors during a tropical cyclone event are probed with a spherical wavelet transform constructed by the lifting scheme. Coefficient spectra and associated filtered error components are examined during the forecast, with an emphasis on feature detection, for mean sea level pressure and wind components. Leading wavelet coefficients within a reference circle centered on the estimated cyclone track demonstrate a clear affinity for local error extrema, reflecting the transform’s feature detection capacity. Compression performance of the transform is also demonstrated by truncated wavelet expansions, which exhibit contrasting behavior reflecting fundamental structural differences between the wind and pressure error fields.

An optimum design approach to reverse-flow cyclones based on the concept of optimizing cyclone dimensions is introduced in this paper. This approach involves optimizing cyclone dimensions by categories, calculating cyclone performance by correlating similitude numbers and optimizing the combination of four cyclone parameters, D, K_A, and v_i, which has been proven to be applicable not only for single-stage cyclone, but also for multistage cyclone separators. Applications of the designed cyclones in FCC units and acrylonitrile reactors are also presented.

Disasters, predicted to increase in intensity and frequency in the near future as a result of climate change, are cross-scale in their impact, disrupting functioning across multiple levels of socio-cultural systems in which individuals’ lives are embedded. Governments all over the world need policies to plan support for community preparedness and recovery from disasters and to this end they need to understand and model disaster resilience as accurately as possible. Disasters can be either rapid or slow onset events, requiring differing responses to facilitate resilience. These might be at community and/or individual scales. The interconnectedness of resilience at individual and community scales requires multilevel preparedness, responses and mitigation strategies. A useful lens with which to investigate these interconnections for policy creation is Bronfenbrenner’s bioecological theory. This chapter describes research conducted in four disaster impacted regional Australian towns using Bronfenbrenner’s bioecological theory to assess and model disaster resilience. The four sites experienced flood, cyclone, bushfire and drought respectively, resulting in damage running into many millions of dollars. The research validated the use of Bronfenbrenner’s theory for modeling disaster resilience. Results highlighted several important areas for targeted government policy to promote disaster resilience, manage risk and reduce individuals’ vulnerability in diverse settings.

The present study carries out the comparison of the water level associated with the numerical methods: Finite Difference Method (FDM) and Finite Volume Method (FVM) and the simulation considered on the present climate condition along the coast of Bangladesh. The governing equations of the first model are discretized through FDM and solved by a conditionally stable semi implicit manner on an Arakawa C-grid system. For the second model, α-coordinate is used for the irrational bottom slope representation and the mesh grid of the study domain is generated by the unstructured triangular cells. The feasible study domain with coast and island boundaries are approximated through proper stair steps for the FDM and the unstructured mesh representation for FVM. A one-way nested scheme technique is applied to the first model to include coastal intricacies as well as to preserve computational cost. Both the models are applied to extrapolate sea-surface elevation associated with the catastrophic cyclone 1991(BOB 01) along the seashore of Bangladesh. The simulation results from both the models are statistically copacetic and make a good acquiescent with some observed and reported data. In the statistical viewpoint, both the method has a good acceptance in storm surge simulation, but this study ensures the strong positive reconciliation with observed data and FVM simulation data. In Bangladesh region, it will be wise decision to use Finite Volume Methods for simulating the storm surge.