Numerical simulation of water vapor transport and cloud microphysical processes in a warm-sector heavy rainfall event over Fujian Province

doi:10.11755/j.issn.1006-7639-2026-04-0647

Abstract

Abstract:

To reveal the formation mechanisms of warm-sector heavy rainfall in Fujian and to improve the regional heavy rainfall forecasting capability, the Weather Research and Forecasting model version 4.0 (WRF V4.0) and the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) were used to simulate and analyze a warm-sector heavy rainfall event that occurred in Sanming City, Fujian Province, on 16 May 2019. The analysis focused on the circulation background, water vapor transport patterns, and cloud microphysical characteristics of the event. The results are as follows: (1) The warm-sector heavy rainfall event occurred under a favorable circulation configuration featuring upper-level divergence and low-level jet convergence. The “train effect” of mesoscale convective cells was the direct cause of the extreme precipitation, and the WRF model reproduced this heavy rainfall event reasonably well. (2) The southern boundary served as the primary water vapor inflow channel, and 850 hPa and 925 hPa were the key transport levels. The continuous water vapor supply provided favorable conditions for the maintenance of the “train effect”. (3) The in-cloud hydrometeors classified according to the Lin microphysics parameterization scheme exhibited a pronounced vertical stratification structure. The simulation showed that water vapor and graupel particles were crucial to precipitation development and that the precipitation was characterized by enhancement at night and a peak in the early morning. (4) Graupel grew rapidly by accreting supercooled water, and its melting served as an important initiation mechanism for precipitation, whereas the accretion of cloud water by rain dominated the sustained growth of rainwater. Ice-phase microphysical processes thus played a key role in this simulated warm-sector heavy rainfall event.

Key words: warm-sector heavy rainfall, numerical simulation, water vapor transport, cloud microphysics, graupel

摘要：

为揭示福建暖区暴雨的发生机理，提升区域暴雨预报能力，利用WRF V4.0模式与拉格朗日混合单粒子轨道模型（Hybrid Single-Particle Lagrangian Integrated Trajectory Model，HYSPLIT），对2019年5月16日福建三明市暖区暴雨过程开展模拟分析，研究其环流背景、水汽输送规律和云微物理特征。结果表明：（1）此次暖区暴雨发生在高层辐散、低层急流辐合的有利环流配置下，中尺度对流单体“列车效应”是造成极端降水的直接成因，WRF模式较好模拟了本次暴雨过程。（2）南边界为主要水汽输入通道，850 hPa与925 hPa为关键输送层，持续的水汽补给为“列车效应”的维持提供条件。（3）基于Lin参数化方案分类的云内水凝物呈现显著垂直分层结构，模拟显示水汽与霰粒子是降水发展的关键，降水呈夜间增强、清晨达峰值的变化特征。（4）霰碰并过冷水迅速增长，其融化是产生降水的重要启动机制，而云雨碰并过程则主导雨水的持续增长，冰相微物理过程在本次模拟的暖区暴雨中扮演了关键角色。

关键词: 暖区暴雨, 数值模拟, 水汽输送, 云微物理, 霰粒子

CLC Number:

P458

YIN Shucheng, LIU Jingru, PEI Changchun, LIN Zilun, CHENG Si, JIANG Yue. Numerical simulation of water vapor transport and cloud microphysical processes in a warm-sector heavy rainfall event over Fujian Province[J]. Journal of Arid Meteorology, 2026, 44(4): 647-658.

阴蜀城, 刘婧茹, 裴昌春, 林子伦, 程思, 蒋悦. 福建一次暖区暴雨水汽输送与云微物理过程数值模拟[J]. 干旱气象, 2026, 44(4): 647-658.

Figures/Tables 12

Fig.1 Triple-nested simulation domains of the WRF V4.0 model and terrain height （the color shaded， Unit： m）

Fig.2 Synoptic-scale background patterns at 20:00 on 15 May 2019: 200 hPa geopotential height (blue solid lines, Unit: dagpm), temperature (red dashed lines, Unit: ℃), wind field (wind vectors, Unit: m·s-1), and divergence (the color shaded, Unit: 10-4·s-1) (a); 500 hPa (b) and 700 hPa (c) geopotential height (blue solid lines, Unit: dagpm), temperature (red dashed lines, Unit: ℃), and wind field (wind vectors, the shading indicates jet stream regions, Unit: m·s-1); 850 hPa geopotential height (blue solid lines, Unit: dagpm), temperature (red dashed lines, Unit: ℃), wind field (wind vectors, Unit: m·s-1), and water vapor flux (the color shaded, Unit: g·cm-1·hPa-1·s-1) (d)

Fig.3 Hourly changes of TBB， radar reflectivity， and surface rainfall intensity at Sanming National Station from 00：00 to 12：00 on 16 May 2019

Fig. 4 Spatial distributions of 24 h accumulated precipitation observations (a) and WRF D03 simulation (b) from 20:00 on 15 to 20:00 on 16 May 2019 (Unit: mm) (The black rectangle indicates the heavy rainfall area)

Fig.5 Time series variations of observed and simulated area-averaged hourly precipitation over the heavy rainfall region from 20：00 on 15 to 20：00 on 16 May 2019

Tab.1 Water vapor budget at the boundaries of the D03 region

时间	东边界	南边界	西边界	北边界	经向输送	纬向输送
5月15日14：00	-9.88	12.72	18.08	-11.57	1.15	8.20
5月15日20：00	-3.38	10.47	15.01	-6.18	4.29	11.63
5月16日02：00	-5.84	16.14	14.80	-2.67	13.47	8.96
5月16日08：00	-7.96	15.25	16.66	-2.47	12.78	8.70

Fig. 6 Backward trajectories of water vapor (a) and time series of specific humidity (b) at Sanming National Station at 00:00 on 16 May 2019

Fig. 7 Time-height cross sections of area-averaged mixing ratios of six types of hydrometeors over the heavy rainfall region from 20:00 on 15 to 20:00 on 16 May 2019 (blue dashed line denotes area-averaged precipitation over the heavy rainfall region)

Fig. 8 Vertical profiles of mixing ratios for five hydrometeor species over the heavy rainfall region at 00:00 (a), 02:00 (b), 03:30 (c), 06:30 (d), and 08:00 (e) on 16 May 2019

Fig. 9 Vertical profiles of the conversion rates of main source and sink terms for rainwater in the heavy precipitation region at 00:00 (a), 02:00 (b), 03:30 (c), 06:30 (d), and 08:00 (e) on 16 May 2019 (colored solid lines: source terms, included accretion of cloud water by rain (PRACW) and melting of graupel to form rain (PGMLT); colored dashed lines: sink terms, included accretion of rain by cloud ice (PIACR), accretion of rain by snow (PSACR), and rain evaporation (PREVP); the black dashed line indicates the 0 ℃ level height)

Fig. 10 Vertical profiles of the conversion rates of major source and sink terms for snow in the heavy precipitation region at 00:00 (a), 02:00 (b), 03:30 (c), 06:30 (d), and 08:00 (e) on 16 May 2019 (colored solid lines: source terms, included accretion of cloud water by snow (PSACW), transfer rate of cloud ice to snow through the Bergeron process (PSFI), accretion of rain by cloud ice (PIACR), and accretion of rain by snow (PSACR); colored dashed lines: sink terms, included accretion of snow by graupel (PGACS) and accretion of snow by rain (PRACS); the black dashed line indicates the 0 ℃ level height)

Fig. 11 Vertical profiles of the conversion rates of major source and sink terms for graupel in the heavy precipitation region at 00:00 (a), 02:00 (b), 03:30 (c), 06:30 (d), and 08:00 (e) on 16 May 2019 (colored solid lines: source terms, included accretion of cloud water by graupel (PGACW), accretion of rain by graupel (PGACR), accretion of rain by snow (PSACR), and accretion of rain by cloud ice (PIACR); orange dashed lines: sink terms, graupel melting to form rain (PGMLT); the black dashed line indicates the 0 ℃ level height)

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