Hurricane Scenario Generation for Uncertainty Modeling of Coastal and Inland Flooding

Deep uncertainty in long-term hurricane risk: Scenario generation and implications for future climate experiments

Current projections of long-term trends in Atlantic hurricane activity due to climate change are deeply uncertain, both in magnitude and sign. This creates challenges for adaptation planning in exposed coastal communities. We present a framework to support the interpretation of current long-term tropical cyclone projections, which accommodates the nature of the uncertainty and aims to facilitat...

Modeling of storm-induced coastal flooding for emergency management

This paper describes a model package that simulates coastal flooding resulting from storm surge and waves generated by tropical cyclones. The package consists of four component models implemented at three levels of nested geographic regions, namely, ocean, coastal, and nearshore. The operation is automated through a preprocessor that prepares the computational grids and input atmospheric condit...

Future studies and scenario planning for health services development in Makran coastal Region

Optimizing irradiance estimates for coastal and inland water imaging spectroscopy

Next generation orbital imaging spectrometers, with advanced global remote sensing capabilities, propose to address outstanding ocean science questions related to coastal and inland water environments. These missions require highly accurate characterization of solar irradiance in the critical 380–600 nm spectral range. However, the irradiance in this spectral region is temporally variable and d...

Integrated Inspection Planning and Preventive Maintenance for a Markov Deteriorating System Under Scenario-based Demand Uncertainty

In this paper, a single-product, single-machine system under Markovian deterioration of machine condition and demand uncertainty is studied.  The objective is to find the optimal intervals for inspection and preventive maintenance activities in a condition-based maintenance planning with discrete monitoring framework. At first, a stochastic dynamic programming model whose state variable is the ...