Print Email Facebook Twitter Error Features in Predicting Typhoon Winds Title Error Features in Predicting Typhoon Winds: A Case Study Comparing Simulated and Measured Data Author Peng, Shaoyuan (China Construction Science and Industry Co., Shenzhen) Liu, Y. (TU Delft Team Riccardo Ferrari) Li, Renge (China Construction Science and Industry Co., Shenzhen) Wei, Ying (China Construction Science and Industry Co., Shenzhen) Chan, Pak Wai (Hong Kong Observatory) Li, Sunwei (Tsinghua University) Date 2022 Abstract Simulating a typhoon’s wind field via mesoscale models is important in terms of providing not only the guidelines for urban planning and onshore/offshore constructions, but also the provision of insight into the dynamics and thermodynamics of tropical cyclone systems. Therefore, the errors that are contained in simulation results were investigated in the present study, in association with large-scale meteorological patterns and localized wind conditions in the typhoon boundary layer. In detail, the full-set three-dimensional simulations of three typhoon cases were carried out in order to provide the typhoon wind fields that were required to compare with the observations that were obtained through land weather stations and offshore buoys. Although the reliability of typhoon simulations has been thoroughly investigated, the previous works mostly concentrated on the configurations and dynamic core of the model. The present study reveals, however, the influences of the characteristics of the specific weather system on the simulation’s results, which provides the foundation for the proposition of empirical corrections to improve the mesoscale simulation results of typhoon wind fields without updating the model’s algorithm. Subject Error featuresLarge-scale meteorological patternLocalized wind conditionsNumerical simulationTyphoon wind fields To reference this document use: http://resolver.tudelft.nl/uuid:f4a6dac7-65f5-43ba-b31f-6fd7794ff94c DOI https://doi.org/10.3390/atmos13020158 ISSN 2073-4433 Source Atmosphere, 13 (2) Part of collection Institutional Repository Document type journal article Rights © 2022 Shaoyuan Peng, Y. Liu, Renge Li, Ying Wei, Pak Wai Chan, Sunwei Li Files PDF atmosphere_13_00158_v3_1.pdf 28.35 MB Close viewer /islandora/object/uuid:f4a6dac7-65f5-43ba-b31f-6fd7794ff94c/datastream/OBJ/view