Numerical simulation and generation mechanism of a near-cloud turbulence encounter in southeast coast of China

doi:10.11755/j.issn.1006-7639-2024-06-0922

Abstract

Abstract:

It is of great significance to study the near-cloud turbulence for improving the prediction ability of aircraft turbulence and ensuring the safety of air transportation. The WRF (Weather Research and Forecasting) model v4.3.1 is used to conduct a high-resolution numerical simulation of a moderate intensity near-cloud turbulence event over Fujian Province, China. The synoptic-scale background and turbulence indices are examined, and the causes of the turbulence event are analyzed. A sensitivity experiment excluding the moist process is conducted to investigate the impact of cloud system evolution on the turbulence generation. The results indicate that the turbulence event was mainly influenced by the low-level clouds area on the periphery of the cold high-pressure system over the southeast coastal region of China. The upper level southern jet stream gradually moved eastward above the turbulence region, and vertical wind shear enhanced and tropopause folding phenomenon was observed. The high-resolution simulation reasonably reproduced the large-scale circulation during the turbulence event. The turbulence indices, including Ri (Richardson number) and NCSU1 index (Version 1 of North Carolina State University Index), effectively indicated the intensity and location of this turbulence event. Inertial instability and high turbulence kinetic energy (TKE) values were distributed around the cloud region near the turbulence area. Specifically, influenced by stratiform clouds, the increment of zonal wind in the turbulence area gradually increased from south to north and the increment of the meridional wind gradually decreased from west to east, both contributing to negative absolute vorticity. Updrafts near the cloud top affected the local wind field in the turbulence region. Downdrafts mixed with saturated moist air through the cloud top, leading to inertial instability and ultimately causing the turbulence event. In contrast, the TKE in the turbulence region disappeared in the absence of clouds, and the vertical wind shear weakened, both two turbulence indices failed to diagnose the turbulence event.

Key words: near-cloud turbulence, inertial instability, WRF model, vertical wind shear

摘要：

研究近云区湍流对于提高飞机颠簸预报能力，保障航空运输安全具有重要意义。利用WRF（Weather Research and Forecasting）V4.3.1模式对我国福建省上空一次中等强度近云区湍流事件开展高分辨率数值模拟，对天气尺度背景和颠簸指数进行检验，分析此次湍流事件的形成原因；借助不考虑湿过程的敏感试验，研究云系演变对湍流产生的影响机制。结果表明：此次湍流事件主要受东南沿海地区冷高压外围低层云区影响，高层南支急流逐渐向东移至湍流区上方，垂直风切变较强，伴有对流层顶折叠现象。高分辨率模拟能够合理再现湍流期间环流背景。颠簸指数（Ri数和NCSU1）对本次湍流事件的强度和位置有较好的指示作用。湍流区附近的惯性不稳定与湍流耗散动能（Turbulent Kinetic Energy，TKE）大值区均分布在云区周围，受云区影响，湍流区内纬向风增量自南向北逐渐增强，经向风增量自西向东减弱，贡献了负绝对涡度，云顶高度附近的上升气流影响了上方湍流区局地风场；下沉气流经云顶与饱和湿空气混合稀释，引起惯性不稳定，最终导致湍流事件发生。而无云时湍流区TKE消失，垂直风切变减弱，两种颠簸指数也未能诊断出湍流事件。

关键词: 近云区湍流, 惯性不稳定, WRF模式, 垂直风切变

CLC Number:

HE Peilin, WU Di, WANG Kehua, LI Kenan. Numerical simulation and generation mechanism of a near-cloud turbulence encounter in southeast coast of China[J]. Journal of Arid Meteorology, 2024, 42(6): 922-933.

何沛霖, 吴迪, 王柯化, 李克南. 东南沿海一次近云区湍流事件的数值模拟与产生机制研究[J]. 干旱气象, 2024, 42(6): 922-933.

Figures/Tables 13

Fig.1 The distribution of topography （Unit： m） of the WRF model simulation area （a） and D04 nested area （b）（The black circle in the fig. a and the black dotted line in the fig. b indicate the route of the aircraft）

Tab.1 Configuration and parameterizations conducted in the simulation

模式方案	具体参数
云微物理方案	Thompson （Thompson et al.， 2008）
积云对流方案	KF （Kain， 2004）
行星边界层方案	Mellor-Yamada-Janjic （Janjic， 1944）
地表表层方案	Monin-Obukhov （Janjic， 1944）
陆面过程方案	Unified Noah （Tewari et al.， 2004）
长波辐射方案	RRTMG （Iacono et al.， 2008）
短波辐射方案	RRTMG （Iacono et al.， 2008）

Fig.2 The geopotential height field （black solid lines， Unit： gpm） and horizontal wind field （wind vectors， Unit： m·s-1） at 500 hPa （a）， temperature of black body （TBB） from the Japanese Himawari 8 satellite （the gray shaded， Unit： °C） and mean sea level pressure （black solid lines， Unit： hPa）（b） at 06：00 on 24 February 2017 （The black circle in fig. a and the mark “△” in fig. b represent the location of the turbulence and the waypoints on the flight route， respectively， and the letter “H” in fig. b denotes the center of closed high-pressure）

Fig.3 The horizontal wind speed （the color shaded， Unit： m·s-1）， geopotential height field （blue solid lines， Unit： gpm） and temperature field （red dashed lines， Unit： °C） at 400 hPa （a， c）， and the corresponding distribution of potential vorticity field （the color shaded， Unit： PVU， 1 PVU=10-6 K·kg-1·m2·s-1）， geopotential height field （blue solid lines， Unit： gpm） and horizontal wind field （wind vectors， Unit： m·s-1）（b， d） at 00：00 （a， b）， 06：00 （c， d） on 24 February 2017 （The black circles indicate the location where aircraft turbulence occurred， the same as below）

Fig.4 The horizontal wind speed （the color shaded， Unit： m·s-1）， geopotential height field （blue solid lines， Unit： gpm） and temperature field （red dashed lines， Unit： °C） at 400 hPa （a）， and the corresponding potential vorticity field （the color shaded， Unit： PVU， 1 PVU=10-6 K·kg-1·m2·s-1）， geopotential height field （blue solid lines， Unit： gpm） and horizontal wind field （wind vectors， Unit： m·s-1）（b） at 06：00 simulated by WRF model on 24 February 2017

Fig.5 The spatial distribution of the Richardson number （Ri）（a， d）， vertical wind shear （b， e， Unit： 10-2 s-1）， and atmospheric stability N2 （c， f， Unit： 10-4 s-2） at 7.2 km height at 01：00 （a， b， c） and 07：00 （d， e， f） on 24 February 2017 simulated by the control experiment （the black solid line is the longitude （119.45°E） of the turbulence center）

Fig.6 The latitude-height sections of the Richardson number （Ri）（a） and NCSU1 index （Unit： 10-12 s-3）（b） along 119.45°E at 07：00 on 24 February 2017 simulated by the control experiment （The black solid lines are the equipotential temperature lines， Unit： K； the black spots area at the bottom represent the terrain， and the black rectangles indicate the location where aircraft turbulence occurred）

Fig.7 The horizontal wind speed （the color shaded， Unit： m·s-1）， pressure field （blue solid lines， Unit： hPa）， temperature field （red dashed lines， Unit： °C）（a， c） at 7.2 km height， the latitude-height sections of horizontal wind speed （the color shaded， Unit： m·s-1）， equipotential temperature lines （black solid lines， Unit： K） and 1.5 PVU equipotential vorticity lines （blue solid lines）（b， d） along 119.45°E at 01：00 （a， b） and 07：00 （c， d） on 24 February 2017 simulated by the control experiment （The black circles indicate the location where aircraft turbulence occurred， the gray shaded area represents the terrain， the same as below）

Fig.8 The absolute vorticity （the color shaded， Unit： 10-5 s-1）， pressure field （blue solid lines， Unit： hPa） and horizontal wind field （wind vectors， Unit： m·s-1）（a）， the TBB （the color shaded， Unit： °C） and turbulence kinetic energy （red solid lines， only showing the values greater than 0.1 m2·s-2）（b） at 7.2 km height at 07：00 on 24 February 2017 in D04 region simulated by the control experiment

Fig.9 The latitude-height sections of the Richardson number （Ri）（a）， NCSU1 index （b， Unit： 10-12 s-3）， vertical wind shear （c， Unit： 10-2 s-1）， atmospheric stability N2 （d， Unit： 10-4 s-2） along 119.45°E at 07：00 on 24 February 2017 simulated by the sensitivity experiment （The black solid lines are the equipotential temperature lines， Unit： K； the blue solid lines are 1.5 PVU equipotential vorticity lines）

Fig.10 The difference field of the horizontal wind speed （the color shaded， Unit： m·s-1）， wind vector （vectors， Unit： m·s-1） between control and sensitivity experiments （a）， the latitude-height sections of horizontal wind speed difference between control and sensitivity experiments （the color shaded， Unit： m·s-1）， equipotential temperature lines （black solid lines， Unit： K） and 1.5 PVU equipotential vorticity lines （blue solid lines） along 119.45°E simulated by sensitivity experiment （b） at 7.2 km height at 07：00 on 24 February 2017

Fig.11 The difference field of meridional wind （a） and zonal wind （b） between the control experiment and the sensitivity experiment at 07： 00 on February 24， 2017 （The green solid line represents the absolute vorticity zero line simulated by the control experiment， Unit： 10-5 s-1）

Fig.12 The vertical sections of the total hydrometeor mixing ratio content （the color shaded， Unit： g·kg-1）， instantaneous wind field （arrow vectors， Unit： m·s-1） and temperature field （black dashed line， Unit： °C） at 07：00 on 24 February 2017 simulated by control experiment along 26.25°N （a） and 119.45°E （b）

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