1-3 of 3 Results  for:

  • Tropical Storms x
Clear all

Article

A Relational Approach to Risk Communication  

Jing Zhu and Raul P. Lejano

It is instructive to juxtapose two contrasting models of risk communication. The first views risk communication as a product that is packaged and transmitted, unmodified and intact, to a passive public. The second, a relational approach, views it as a process in which experts, the public, and agencies engage in open communication, regarding the public as an equal partner in risk communication. The second model has the benefit of taking advantage of the public’s local knowledge and ability to engage in risk communication themselves. Risk communication should be understood as more of a dynamic process, and less of a packaged object. An example of the relational model is found in Bangladesh’s Cyclone Preparedness Programme, which has incorporated the relational model in its disaster risk reduction training for community volunteers. Nevertheless, the two contrasting models, in practice, are never mutually exclusive, and both are needed for effective disaster risk prevention.

Article

The Global Climatology of Tropical Cyclones  

Hamish Ramsay

Tropical cyclones, also known as hurricanes or typhoons, are one of the most violent weather phenomena on the planet, posing significant threats to those living near or along coastlines where tropical cyclone–related impacts are most pronounced. About 80 tropical cyclones form annually, a rate that has been remarkably steady over the period of reliable historical record. Roughly two thirds of these storms form in the Northern Hemisphere from about June to November, while the remaining third form in the Southern Hemisphere typically during the months of November to May. Our understanding of the global and regional spatial patterns, the year-to-year variability, and temporal trends of these storms has improved considerably since the advent of meteorological satellites in the 1960s because of advances in both remote-sensing technology and operational analysis procedures. The well-recognized spatial patterns of tropical cyclone formation and tracks were laid out in a series of seminal papers in the late 1960s and 1970s and remain an accurate sketch even to this day. Concerning the year-to-year variability of tropical cyclone frequency, the El Niño Southern Oscillation (ENSO) has by far the most dominant influence across multiple ocean basins, so much so that it is typically used as the main predictor for statistical forecasts of seasonal tropical cyclone activity. ENSO has a modulating influence on atmospheric circulation patterns, even in regions remote to the tropical Pacific, which, in turn, can act to enhance or inhibit tropical cyclone formation. While the meteorological and climate community has come a long way in our understanding of the global and regional climatological features of tropical cyclones, as well as some aspects of the broader relationship between tropical cyclones and climate, we are still hindered by temporal inconsistencies within the historical record of storm data, particularly pertaining to tropical cyclone intensity. Despite recent efforts to homogenize the historical record using satellite-derived intensity data back to the early 1980s, the relatively short period makes it difficult to discern secular trends due to anthropogenic climate change from natural trends occurring on decadal to multidecadal time scales.

Article

Modeling Tropical Cyclones in a Changing Climate  

Enrico Scoccimarro

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.