Tropical cyclones (TCs) in their most intense expression (hurricanes or typhoons) are the main natural hazards known to humankind. The impressive socioeconomic consequences for countries dealing with TCs make our ability to model these organized convective structures a key issue to better understanding their nature and their interaction with the climate system. The destructive effects of TCs are mainly caused by three factors: strong wind, storm surge, and extreme precipitation. These TC-induced effects contribute to the annual worldwide damage of the order of billions of dollars and a death toll of thousands of people. Together with the development of tools able to simulate TCs, an accurate estimate of the impact of global warming on TC activity is thus not only of academic interest but also has important implications from a societal and economic point of view. The aim of this article is to provide a description of the TC modeling implementations available to investigate present and future climate scenarios.
The two main approaches to dynamically model TCs under a climate perspective are through hurricane models and climate models. Both classes of models evaluate the numerical equations governing the climate system. A hurricane model is an objective tool, designed to simulate the behavior of a tropical cyclone representing the detailed time evolution of the vortex. Considering the global scale, a climate model can be an atmosphere (or ocean)-only general circulation model (GCM) or a fully coupled general circulation model (CGCM). To improve the ability of a climate model in representing small-scale features, instead of a general circulation model, a regional model (RM) can be used: this approach makes it possible to increase the spatial resolution, reducing the extension of the domain considered. In order to be able to represent the tropical cyclone structure, a climate model needs a sufficiently high horizontal resolution (of the order of tens of kilometers) leading to the usage of a great deal of computational power.
Both tools can be used to evaluate TC behavior under different climate conditions. The added value of a climate model is its ability to represent the interplay of TCs with the climate system, namely two-way relationships with both atmosphere and ocean dynamics and thermodynamics. In particular, CGCMs are able to take into account the well-known feedback between atmosphere and ocean components induced by TC activity and also the TC–related remote impacts on large-scale atmospheric circulation.
The science surrounding TCs has developed in parallel with the increasing complexity of the mentioned tools, both in terms of progress in explaining the physical processes involved and the increased availability of computational power. Many climate research groups around the world, dealing with such numerical models, continuously provide data sets to the scientific community, feeding this branch of climate change science.
Scott C. Hagen, Davina L. Passeri, Matthew V. Bilskie, Denise E. DeLorme, and David Yoskowitz
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Natural Hazard Science. Please check back later for the full article.
Worldwide, low-lying coastal land margins are becoming increasingly vulnerable to natural and manmade disasters due to the effects of climate change, population dynamics, saltwater intrusion, loss of coastal ecosystems, and erosion of coastlines. In 2003, it was estimated that 1.2 billion people (23% of the world’s population) lived within 100 km of a shoreline and 100 m in elevation of mean sea level. As populations increase, coastal areas are also susceptible to additional stresses due to land-use and hydrological changes. In addition to human communities, the coastal land margin includes ecologically and economically significant estuaries and wetlands. Coastal wetlands and marshes provide food, shelter, and nursery areas for commercially harvested fish and shellfish. Wetlands also help protect coastal communities by mitigating impacts of storm surge and erosion.
A System of Systems (SoS) approach is best for assessing potential future coastal hazards and their impacts. Employing an SoS framework permits new patterns and properties to emerge (i.e., nonlinear and dynamic effects of climate change) that would otherwise be unobserved using simplified models. The SoS framework also allows the sea level rise (SLR) projections, and other subsystems, to be linked to carbon emission scenarios so the full climate change impact is considered for all subsystems. Furthermore, this approach to studying coastal hazards supports the translation of science to application as coastal managers require scientific data regarding the potential impacts of SLR to make informed decisions to manage human and natural communities. Synergetic studies that integrate the dynamic interaction among physical, ecological, and anthropogenic environments are required to better predict the impacts to the coastal system in a more holistic fashion. Individually, observations and modeling are insufficient for making scientifically defensible, detailed, and credible assessments of the dynamic response of the coastal region under future SLR conditions. The capability exists to model the bio-geo-physical system, link that modeling to the historic record, and produce a dynamic coastal response to SLR using a SoS framework. Further, incorporating economic and ecosystem services valuations into the SoS enables stakeholders to better understand and assess future coastal hazards and enhance coastal resiliency.