Characteristics of tropical cyclones in high-resolution models in the present climate

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models. Key Points: Multimodel comparison of tropical cyclone activity in global climate models Geographic distribution of the TC activity is similar to observed Most models produce tropical cyclones weaker than observe

Cluster analysis of downscaled and explicitly simulated North Atlantic tropical cyclone tracks

A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in U.S. landfalling systems. Here, the authors present a tentative study that examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models withmoderate to high horizontal resolution (1°-0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and subtropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks' seasonality, intensity, and power dissipation index in each cluster are documented for both configurations. The authors' results show that, except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. The authors also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, the authors examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others

Rainfall prediction for landfalling tropical cyclones : perspectives of mitigation

The torrential rainfall associated with landfalling tropical cyclones (TCs) often represents the major impact to coastal regions, but at the same time an enormous challenge to meteorologists and forecasts. This chapter first discusses the complex dynamical processes involved in TC landfalls, which are related to the increased surface roughness and reduced surface moisture fluxes of land. The result is often certain patterns of convection and rainfall asymmetry in the landfalling TCs, but these patterns are not well explained by current theories or conceptual models. With emphasis of development of rainfall prediction techniques according to the needs of mitigation, the requirements on the skill of rainfall forecasts from the perspectives of mitigation are reviewed. Then, the operation and performance of several statistical TC rainfall models are discussed including the rainfall climatology-persistence model (R-CLIPER) for the Taiwan area. A topographic component is developed for R-CLIPER through multiple regression analyses, which improves the model's performance in reproducing the local extreme rain that is lacking in the original model. Finally, the importance of utilizing remote-sensing data in TC rainfall prediction is discussed, and how TC rainfall statistical models can be applied to risk analyses under the consideration of global changes.27 page(s