Hsieh, Y.-H.Y.-H.HsiehLee, C.-S.C.-S.LeeCHUNG-HSIUNG SUI2018-09-102018-09-102017http://www.scopus.com/inward/record.url?eid=2-s2.0-85032200514&partnerID=MN8TOARShttp://scholars.lib.ntu.edu.tw/handle/123456789/402011The WRF Model is used to simulate 52 tropical cyclones (TCs) that formed in the western North Pacific during 2008-09 to study the influence of the low-frequency mode of environmental vorticity on TC formation [Vmax ~ 25 kt (~13ms-1)]. All simulations, using the same model setting, are repeated at four distinct initial times and with two different initial datasets. These TCs are classified into two groups based on the environmental 850-hPa low-frequency vorticity (using a 10-day low-pass filter) during the period 24-48 h prior to TC formation. Results show that theWRFModel is more capable of simulating the TC formation process, but with larger track errors for TCs formed in an environment with higher low-frequency vorticity (HTC). In contrast, the model is less capable of simulating the TC formation process for TCs formed in an environment with lower low-frequency vorticity (LTC), but with smaller track errors. Fourteen selected TCs are further simulated to examine the sensitivity of previous results to different cumulus parameterization schemes. Results show that the capability of theWRFModel to simulateHTCformation is not sensitive to the choice of cumulus scheme. However, for an LTC, the simulated convection pattern is very sensitive to the cumulus scheme used; therefore, model simulation capability for LTC depends on the cumulus scheme used. Results of this study reveal that the convection process is not a dominant factor in HTC formation, but is very important for LTC formation. © 2017 American Meteorological Society.Numerical analysis/modeling; Tropical cyclones[SDGs]SDG13Clouds; Low pass filters; Tropics; Vorticity; Convection patterns; Convection process; Cumulus parameterization schemes; Formation process; Low-frequency modes; Numerical analysis/modeling; Tropical cyclone; Western North Pacific; Hurricanes; atmospheric dynamics; climate modeling; cloud cover; computer simulation; cumulus; cyclogenesis; error analysis; numerical model; tropical cyclone; vorticity; weather forecasting; Pacific Ocean; Pacific Ocean (North)journal article10.1175/MWR-D-17-0085.12-s2.0-85032200514WOS:000412896100013