Aspects of Observed Gust Factors in Landfalling Tropical Cyclones: Gust Components, Terrain, and Upstream Fetch Effects

2014 ◽  
Vol 155 (1) ◽  
pp. 129-155 ◽  
Author(s):  
Craig Miller ◽  
Juan-Antonio Balderrama ◽  
Forrest Masters
2005 ◽  
Vol 44 (2) ◽  
pp. 270-280 ◽  
Author(s):  
B. M. Paulsen ◽  
J. L. Schroeder

Abstract A gust factor, defined as the ratio between a peak wind gust and mean wind speed over a period of time, can be used along with other statistics to examine the structure of the wind. Gust factors are heavily dependent on upstream terrain conditions (roughness), but are also affected by transitional flow regimes (specifically, changes in terrain and the distance from the upstream terrain change to the measuring device), anemometer height, stability of the boundary layer, and, potentially, the presence of deep convection. Previous studies have yielded conflicting results regarding differences in gust factors that might exist between winds generated by tropical cyclones and those generated by extratropical systems. Using high-resolution wind speed data collected from both landfalling tropical cyclones and extratropical systems, two databases of wind characteristics were developed. Gust factors from tropical cyclone and extratropical winds were examined, summarized, and compared. Further analysis was conducted to examine and compare the characteristics of the associated tropical and extratropical wind speed histograms. As expected, the mean gust factor was found to increase with increasing upstream surface roughness. Some differences were observed between data from the tropical environment and the extratropical environment. Mean gust factors from the tropical regime were found to be higher than mean gust factors from the extratropical environment within each roughness regime and the wind speed histograms generated from data from the two environments indicated some differences.


2021 ◽  
Vol 38 (10) ◽  
pp. 1791-1802
Author(s):  
Peiyan Chen ◽  
Hui Yu ◽  
Kevin K. W. Cheung ◽  
Jiajie Xin ◽  
Yi Lu

AbstractA dataset entitled “A potential risk index dataset for landfalling tropical cyclones over the Chinese mainland” (PRITC dataset V1.0) is described in this paper, as are some basic statistical analyses. Estimating the severity of the impacts of tropical cyclones (TCs) that make landfall on the Chinese mainland based on observations from 1401 meteorological stations was proposed in a previous study, including an index combining TC-induced precipitation and wind (IPWT) and further information, such as the corresponding category level (CAT_IPWT), an index of TC-induced wind (IWT), and an index of TC-induced precipitation (IPT). The current version of the dataset includes TCs that made landfall from 1949–2018; the dataset will be extended each year. Long-term trend analyses demonstrate that the severity of the TC impacts on the Chinese mainland have increased, as embodied by the annual mean IPWT values, and increases in TCinduced precipitation are the main contributor to this increase. TC Winnie (1997) and TC Bilis (2006) were the two TCs with the highest IPWT and IPT values, respectively. The PRITC V1.0 dataset was developed based on the China Meteorological Administration’s tropical cyclone database and can serve as a bridge between TC hazards and their social and economic impacts.


2021 ◽  
Author(s):  
Pang‐Chi Hsu ◽  
Kuan‐Chieh Chen ◽  
Chih‐Hua Tsou ◽  
Huang‐Hsiung Hsu ◽  
Chi‐Cherng Hong ◽  
...  

2020 ◽  
Vol 8 (3) ◽  
Author(s):  
Long Yang ◽  
Gabriele Villarini ◽  
Zhenzhong Zeng ◽  
James Smith ◽  
Maofeng Liu ◽  
...  

2019 ◽  
Vol 63 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Zuo Jia ◽  
Fumin Ren ◽  
Dalin Zhang ◽  
Chenchen Ding ◽  
Mingjen Yang ◽  
...  

2014 ◽  
Vol 27 (12) ◽  
pp. 4642-4654 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Gabriele Villarini ◽  
Gabriel A. Vecchi ◽  
Ming Zhao ◽  
...  

Abstract In this work the authors investigate possible changes in the intensity of rainfall events associated with tropical cyclones (TCs) under idealized forcing scenarios, including a uniformly warmer climate, with a special focus on landfalling storms. A new set of experiments designed within the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group allows disentangling the relative role of changes in atmospheric carbon dioxide from that played by sea surface temperature (SST) in changing the amount of precipitation associated with TCs in a warmer world. Compared to the present-day simulation, an increase in TC precipitation was found under the scenarios involving SST increases. On the other hand, in a CO2-doubling-only scenario, the changes in TC rainfall are small and it was found that, on average, TC rainfall tends to decrease compared to the present-day climate. The results of this study highlight the contribution of landfalling TCs to the projected increase in the precipitation changes affecting the tropical coastal regions.


2017 ◽  
Vol 18 (4) ◽  
pp. 957-976 ◽  
Author(s):  
Ping Lu ◽  
James A. Smith ◽  
Ning Lin

Abstract A framework to characterize the distribution of flood magnitudes over large river networks is developed using the Delaware River basin in the northeastern United States as a principal study region. Flood magnitudes are characterized by the flood index, which is defined as the ratio of the flood peak for a flood event to the historical 10-yr flood magnitude. Event flood peaks are computed continuously over the drainage network using a distributed hydrologic model, CUENCAS, with high-resolution radar rainfall fields as the principal forcing. The historical 10-yr flood is calculated based on scaling relationships between the 10-yr flood and drainage area. Summary statistics for characterizing the probability distribution and spatial correlation of flood magnitudes over the drainage network are developed based on the flood index. This framework is applied to four flood events in the Delaware River basin that reflect the principal flood-generating mechanisms in the eastern United States: landfalling tropical cyclones (Hurricane Ivan in September 2004 and Hurricane Irene in August 2011), late winter/early spring extratropical systems (April 2005), and warm season convective systems (June 2006). The framework can be utilized to characterize the spatial distribution of floods, most notably for floods caused by landfalling tropical cyclones, which play an important role in controlling the upper tail of flood peak magnitudes over much of the eastern United States.


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