Articles | Volume 16, issue 18
https://doi.org/10.5194/acp-16-12359-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-12359-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A numerical study of back-building process in a quasistationary rainband with extreme rainfall over northern Taiwan during 11–12 June 2012
Department of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan
Bing-Kui Chiou
Department of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan
George Tai-Jen Chen
Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
Hung-Chi Kuo
Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
Ching-Hwang Liu
Department of Atmospheric Sciences, Chinese Culture University, Taipei, Taiwan
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- Image of local energy anomaly during a heavy rainfall event S. Yang et al. 10.1088/1674-1056/26/11/119201
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- Impact of Assimilating Future Clear-Air Radial Velocity Observations from Phased-Array Radar on a Supercell Thunderstorm Forecast: An Observing System Simulation Experiment Study Y. Huang et al. 10.1175/MWR-D-19-0391.1
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- Ensemble-based sensitivity analysis and predictability of an extreme rainfall event over northern Taiwan in the Mei-yu season: The 2 June 2017 case C. Wang et al. 10.1016/j.atmosres.2021.105684
- Case Study of a Morning Convective Rainfall Event over Southwestern Taiwan in the Mei-Yu Season under Weak Synoptic Conditions C. WANG et al. 10.2151/jmsj.2018-051
- Diagnosis of the Dynamic Efficiency of Latent Heat Release and the Rapid Intensification of Supertyphoon Haiyan (2013) H. Kuo et al. 10.1175/MWR-D-18-0149.1
- Mechanisms for a Record‐Breaking Rainfall in the Coastal Metropolitan City of Guangzhou, China: Observation Analysis and Nested Very Large Eddy Simulation With the WRF Model Y. Huang et al. 10.1029/2018JD029668
- Kinetic mass-transfer calculation of water isotope fractionation due to cloud microphysics in a regional meteorological model I. Tsai et al. 10.5194/acp-19-1753-2019
- Impact of Assimilating Radar Data with 3D Thermodynamic Fields in an Ensemble Kalman Filter: Proof of Concept and Feasibility C. Ke et al. 10.1175/MWR-D-22-0128.1
- Analysis of heavy rainfall and barrier-jet evolution during Mei-Yu season using multiple Doppler radar retrievals: a case study on 11 June 2012 C. Ke et al. 10.1080/16000870.2019.1571369
- Evaluation of Mei-yu heavy-rainfall quantitative precipitation forecasts in Taiwan by a cloud-resolving model for three seasons of 2012–2014 C. Wang et al. 10.5194/nhess-22-23-2022
- Meteotsunamis in the Tamsui River estuary, Taiwan L. Lin et al. 10.1016/j.ecss.2024.108704
- Where and why do Mei-yu season Heavy-rainfall quantitative precipitation forecasts in Taiwan improve the most using a higher model resolution C. Wang et al. 10.1007/s11069-024-06825-5
- Numerical Study on the Impacts of Hydrometeor Processes on the “21·7” Extreme Rainfall in Zhengzhou Area of China W. Gao et al. 10.1007/s00376-024-3365-x
- An Evaluation of WRF Rainfall Forecasts in Taiwan during Three Mei-Yu Seasons from 2008 to 2010 C. Wang et al. 10.1175/WAF-D-16-0190.1
- Study of an Asymmetric and Anticyclonic Bow Echo Near Taiwan C. Wang et al. 10.3390/atmos13020331
1 citations as recorded by crossref.
Latest update: 21 Nov 2024
Short summary
In this study, the back-building process of a quasistationary convective line with extreme rainfall is investigated using a cloud model. At the initiation stage of new cells, thermodynamic processes of near-surface latent heating coupled with adiabatic cooling above along the convergence line, rather than dynamic pressure perturbations, are found to be important. The stronger uplift and cooling aloft provided by old cells made their upstream areas more favorable for new cell development.
In this study, the back-building process of a quasistationary convective line with extreme...
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