对冬季云贵—华南准静止锋上一次多相态降水过程的模拟研究

doi:10.11755/j.issn.1006-7639(2024)-01-0075

摘要/Abstract

摘要：

云贵—华南准静止锋使其以北地区成为研究冬季雨雪过渡区内不同降水相态的理想平台。通过对2018年1月25—27日南方凝冻天气过程中天气学和云微物理参数的分析，定性探讨了次冻结层的温度与冰核活化温度对不同降水相态形成的影响，进而利用耦合BTC降水相态诊断方案（简称“BTC方案”）的WRF（Weather Research and Forecasting）模式，对本次凝冻天气的降水相态、冻雨发生区域与冻雨量进行数值模拟。结果表明：横贯云贵高原和南岭地区的准静止锋导致的锋前“冷—暖—冷”的温度垂直结构有利于多相态降水的形成。耦合BTC方案的WRF模式可模拟出不同降水相态落区的空间分布，其模拟冻雨落区时空分布与观测基本一致，但冰粒的空报率非常高。分析WRF模式模拟的多相态降水时温度、相对湿度和水成物的垂直分布特征，云内水成物初始相态为液态，在高空逆温层存在的前提下，次冻结层中冰核活化温度是区分冻雨和冰粒的临界指标且具有明确的物理机制。利用次冻结层中的冰核活化温度来代替BTC方案中有关冻雨和冰粒的判据后，冻雨落区预报准确率较BTC方案提高了13%，表明直接利用次冻结层的冰核活化温度判断冻雨可行。

关键词: 凝冻天气, 准静止锋, 冰核活化温度, 冻雨参数化方案, 降水相态

Abstract:

The presence of the Yungui-Huanan quasi-stationary front make its north region an ideal platform for studying different precipitation phase across the rain-snow transition zone. The impact of the temperature the subfreezing layer and the activation temperature of the ice core on the formation of different precipitation phases were qualitatively explored based on the analyses of the meteorological and cloud microphysical parameters over a southern freezing weather event from January 25 to 27, 2018. The precipitation phase, the freezing-rain zone, and the total amount of freezing rain in this case were simulated as well by the use of the WRF model coupling the BTC precipitation phase diagnosis parameterization scheme. The results show that a “cold-warm-cold” vertical temperature structure formed by the quasi-stationary fronts across the Yunnan-Guizhou Plateau and the Southern Ridge region is favorable for the occurrence of multi-phase precipitation. The spatial distribution of different precipitation phase drop zones can be well simulated by the WRF model coupled with the BTC parameterization scheme, showing good agreement with observations, but the false rate for ice particles is relatively high. The vertical distribution characteristics of temperature, relative humidity and hydrometeors during the multi-phase precipitation simulated by WRF model are analyzed. The initial phase of hydrometeors in the cloud is liquid. Under the premise of the existence of high-altitude inversion layer, the ice core activation temperature in the subfreezing layer is the critical index to distinguish freezing rain and ice particles and has a clear physical mechanism. The accuracy of freezing rain prediction is improved by 13% after by substituting the ice core activation temperature of the subfreezing layer for the discrimination of freezing rain and ice particles in the BTC scheme, which indicates the feasibility of the use of the ice core activation temperature in the subfreezing layer to determine freezing rain.

Key words: freezing weather, quasi-stationary front, ice core activation temperature, freezing rain parameterization scheme, precipitation phase

中图分类号:

杨旗, 张海鹏, 吴建蓉, 李昊, 曾华荣, 陆正奇. 对冬季云贵—华南准静止锋上一次多相态降水过程的模拟研究[J]. 干旱气象, 2024, 42(1): 75-83.

YANG Qi, ZHANG Haipeng, WU Jianrong, LI Hao, ZENG Huarong, LU Zhengqi. Simulation of a multi-phase precipitation process over Yungui-Huanan quasi-stationary front in winter[J]. Journal of Arid Meteorology, 2024, 42(1): 75-83.

图/表 6

图1 WRF模式嵌套区域设置

Fig.1 The setting of WRF model domain

图2 2018年1月24—27日逆温层（灰色填色区）和观测冻雨发生站点（黑色圆点）的空间分布（绿色、红色、蓝色实线分别为地面、850 hPa和700 hPa的0 ℃等温线）

Fig.2 Spatial distribution of the inverse layer（gray color filling area） and the observation freezing rain stations（black dots） from 24 to 27 January 2018 （The green，red，and blue solid lines are the 0°C isotherms at ground level，850 hPa，and 700 hPa，respectively.）

图3 2018年1月25日08：00（a）、20：00（b），26日08：00（c）、20：00（d），27日08：00（e）、20：00（f）WRF模式模拟（彩色填色区）及观测（散点）的各相态降水空间分布

Fig.3 Spatial distribution of different precipitation phase for WRF model simulations（color filled areas） and observations（scattered points） at 08：00（a） and 20：00（b） on 25，08：00（c） and 20：00（d） on 26，08：00（e） and 20：00（f） on 27 January 2018

图4 2018年1月25日20：00（a、b）、27日20：00（c、d）贵阳（a、c）和长沙（b、d）站的温度（T）、相对湿度（RH）廓线观测值与模拟值

Fig.4 The observation and simulation of temperature（T） and relative humidity（RH） profiles at Guiyang（a，c） and Changsha（b，d） station at 20： 00 on 25（a，b） and 20： 00 on 27（c，d） January 2018

图5 2018年1月25日和27日20：00温度（红色等值线）、冰晶（蓝色等值线）、雪（绿色等值线）及云水含量（彩色填色区）沿贵阳（a、b）和长沙（c、d）站的经度-高度剖面（黑色填色区域为地形）

Fig.5 The longitude-height sections of temperature（red contours），ice crystals（blue contours），snow（green contours），and cloud-water content（color filled areas） along the Guiyang（a，b） and Changsha（c，d） stations at 20：00 on 25 and 27 January 2018 （Black filled areas are terrain）

图6 2018年1月25日20：00（a）、26日20：00（b）、27日20：00（c）BTC改进方案模拟12 h累积冻雨量（彩色填色区）与观测冻雨发生站点（黑色圆点）空间分布

Fig.6 Spatial distribution of 12-hour accumulated freezing rainfall simulated by the improved BTC scheme（color filled areas） and the observation freezing rain stations（black dots） at 20：00 on 25（a），20：00 on 26（b），20：00 on 27（c） January 2018

参考文献 39

[1]	陈荣, 王建英, 杨文军, 等, 2023. 银川市大气边界层逆温影响因素及其与冬季PM_2.5的关系[J]. 干旱气象, 41(1): 123-131. DOI
[2]	褚颖佳, 郭飞燕, 高帆, 等, 2023. 冷涡影响下两次不同类型强对流过程对比分析[J]. 干旱气象, 41(2): 279-289. DOI
[3]	杜小玲, 彭芳, 武文辉, 2010. 贵州冻雨频发地带分布特征及成因分析[J]. 气象, 36(5): 92-97.
[4]	杜骦, 周宁, 韩永翔, 等, 2019. 河南省一次冻雨过程中电线积冰厚度模拟[J]. 气象, 45(5): 641-650.
[5]	李清华, 孟洁, 李劲松, 等, 2022. 山西省不同重现期下电线覆冰厚度空间分布及区划[J]. 干旱气象, 40(1): 156-165. DOI
[6]	欧建军, 周毓荃, 杨棋, 等, 2011. 我国冻雨时空分布及温湿结构特征分析[J]. 高原气象, 30(3): 692-699.
[7]	秦沛, 韩永翔, 陆正奇, 等, 2021. 南岭地形对湖南省冻雨形成与分布的敏感性研究[J]. 灾害学, 36(4): 188-193.
[8]	陆正奇, 2022. 冬季降水相态的理论模型构建及地形的影响研究[D]. 南京: 南京信息工程大学.
[9]	任曼琳, 李忠燕, 王博卿, 等, 2023. 2021/2022年冬季贵州凝冻天气阶段性特征及成因[J]. 干旱气象, 41(5): 744-752. DOI
[10]	索渺清, 丁一汇, 鲁亚斌, 等, 2018. 中国南方准静止锋对冬季大范围冻雨的影响[J]. 气象学报, 76(4): 525-538.
[11]	陶玥, 李宏宇, 刘卫国, 2013. 南方不同类型冰冻天气的大气层结和云物理特征研究[J]. 高原气象, 32(2): 501-518. DOI
[12]	佟华, 张玉涛, 2019. GRAPES_MESO模式预报降水相态诊断及应用研究[J]. 大气科学学报, 42(4): 502-512.
[13]	王馨, 卢毅, 张旭, 等, 2020. 冀北地区输电线路覆冰风险预报研究[J]. 干旱气象, 38(1): 164-168.
[14]	武辉芹, 张金满, 赵增保, 2017. 河北省输电线路冰害的气象要素时空分布特征[J]. 干旱气象, 35(6): 991-997. DOI
[15]	赵琳娜, 马清云, 杨贵名, 等, 2008. 2008年初我国低温雨雪冰冻对重点行业的影响及致灾成因分析[J]. 气候与环境研究, 13(4): 556-566.
[16]	赵琳娜, 慕秀香, 马翠平, 等, 2021. 冬季稳定性降水相态预报研究进展[J]. 应用气象学报, 32(1): 12-24.
[17]	赵思雄, 孙建华, 2008. 2008年初南方雨雪冰冻天气的环流场与多尺度特征[J]. 气候与环境研究, 13(4): 351-367.
[18]	周悦, 2012. 电线积冰形成机理研究:观测和模拟[D]. 南京: 南京信息工程大学.
[19]	宗志平, 马杰, 张恒德, 等, 2013. 近几十年来冻雨时空分布特征分析[J]. 气象, 39(7): 813-820.
[20]	ALMONTE J D, STEWART R E, 2019. Precipitation transition regions over the southern Canadian Cordillera during January-April 2010 and under a pseudo-global-warming assumption[J]. Hydrology and Earth System Sciences, 23(9): 3 665-3 682.
[21]	BOCCHIERI J R, 1980. The objective use of upper air soundings to specify precipitation type[J]. Monthly Weather Review, 108(5): 596-603.
[22]	CORTINAS J V, BRILL K F, BALDWIN M E, 2002. Probabilistic forecasts of precipitation type[C]// Preprints, 16th Conf. on Probability and Statistics in the Atmospheric Sciences, Orlando, FL, American Meteorological Society.
[23]	CREIGHTON G, KUCHERA E, ADAMS-SELIN R, et al, 2014. AFWA diagnostics in WRF[M]. Nebraska: Air Force Weather Agency.
[24]	DUDHIA J, 1989. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model[J]. Journal of the Atmospheric Sciences, 46(20): 3 077-3 107.
[25]	FARZANEH M A, VOLAT C, LEBLOND A, 2008. Atmospheric icing of power networks[M]. Berlin: Springer Science & Business Media.
[26]	GLAHN H R, BOCCHIERI J R, 1975. Objective estimation of the cond1-tional probability of frozen precipitation[J]. Monthly Weather Review, 103(1): 3-15.
[27]	HONG S Y, NOH Y, DUDHIA J, 2006. A new vertical diffusion package with an explicit treatment of entrainment processes[J]. Monthly weather review, 134(9): 2 318-2 341.
[28]	HOUSTON T G, CHANGNON S A, 2007. Freezing rain events: A major weather hazard in the conterminous US[J]. Natural Hazards, 40(2): 485-494.
[29]	HUFFMAN G J, NORMAN G A, 1988. The supercooled warm rain process and specification of freezing precipitation[J]. Monthly Weather Review, 116(11): 2 172-2 182.
[30]	IKEDA K, STEINER M, PINTO J, et al, 2013. Evaluation of cold-season precipitation forecasts generated by the hourly updating high-resolution rapid refresh model[J]. Weather and Forecasting, 28(4): 921-939.
[31]	MCQUEEN H R, KEITH H C, 1956. The ice storm of January 7-10, 1956 over the northeastern United States[J]. Monthly Weather Review, 84(1): 35-45.
[32]	MLAWER E J, TAUBMAN S J, BROWM P D, et al, 1997. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave[J]. Journal of Geophysical Research Atmospheres, 102(D14): 16 663-16 682.
[33]	NIU G Y, YANG Z L, MITCHELL K E, et al, 2011. The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements[J]. Journal of Geophysical Research, 116(D12), D12109. DOI: 10.1029/2010JD015139.
[34]	RAUBER R M, OLTHOFF L S, RAMAMURTHY M K, et al, 2000. The relative importance of warm rain and melting processes in freezing precipitation events[J]. Journal of Applied Meteorology, 39(7): 1 185-1 195.
[35]	REEVES H D, ELMORE K L, RYZHKOV A, et al, 2014. Sources of uncertainty in precipitation-type forecasting[J]. Weather and Forecasting, 29(4): 936-953.
[36]	STEWART R E, KING P, 1987. Freezing precipitation in winter storms[J]. Monthly Weather Review, 115(7): 1 270-1 280.
[37]	THOMPSON G, RASMUUSSEN R M, MANNING K, 2004. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis[J]. Monthly Weather Review, 132(2): 519-542.
[38]	WAGNER J A, 1957. Mean temperature from 1000 MB to 500 MB as a predictor of precipitation type[J]. Bulletin of the American Meteorological Society, 38(10): 584-590.
[39]	YOUNG W R, 1978. Freezing precipitation in the Southeastern United States[D]. Texas: Texas A & M University.