高原气象

高原气象 >

2019 , Vol. 38 >Issue 5: 1017 - 1026

DOI: https://doi.org/10.7522/j.issn.1000-0534.2018.00140

论文

一次罕见的山东半岛西部海效应暴雪过程的特征及机理研究

  • 郑怡 ,
  • 杨成芳 ,
  • 郭俊建 ,
  • 张磊 ,
  • 焦艳
展开
  • 山东省气象台, 山东 济南 250031;国家海洋局北海预报中心, 山东 青岛 266061

收稿日期: 2018-03-22

  网络出版日期: 2019-10-28

基金资助

国家自然科学基金项目（41475038）；环渤海区域科技协同创新基金项目（QYXM201708）

收起

Analysis on the Characteristics and Mechanism of a Rare Ocean-effect Snowstorm in the Western Shandong Peninsula

  • ZHENG Yi ,
  • YANG Chengfang ,
  • GUO Junjian ,
  • ZHANG Lei ,
  • JIAO Yan
Expand
  • Shandong Meteorological Observatory, Ji'nan 250031, Shandong, China;North China Sea Marine Forecast Center of State Oceanic Administration, Qingdao 266061, Shandong, China

Received date: 2018-03-22

  Online published: 2019-10-28

Fold

摘要

利用高时空分辨率MODIS和HIMAWARI-8卫星云图，多普勒天气雷达，风廓线雷达，加密自动站、浮标站及常规观测等多种观测资料，结合NCEP/NCAR逐日6 h再分析资料和ERA_Interim再分析资料，对2015年11月2526日山东半岛西部和北部海效应暴雪过程的降雪特征和形成机理进行了分析。结果表明：（1）此次过程中高空冷涡位置异常偏西偏南，对应地面等压线气旋式弯曲异常偏西，冷空气强盛，为半岛西部产生暴雪提供了有利的大尺度背景条件。（2）此次海效应暴雪过程存在多条降雪云带并有云带合并发展现象，每条云带内部可能存在多个云团（线），云带的位置和发展强度对降雪落区和降雪量具有良好的指示性。（3）对应强降雪时段，渤海海面海气温差为14℃左右，半岛西部存在不稳定层结，地面辐合线提供动力触发机制，前期水汽积累和后期强水汽辐合提供了充分的水汽条件，低层辐合区长期维持使降雪云带强烈发展并产生"列车效应"，是导致此次半岛西部产生暴雪的主要原因。（4）此次暴雪过程中，山东半岛西部在能量和水汽方面优于半岛北部，且动力维持机制与半岛北部不同，其低层900 hPa以下存在西北风和偏北风的辐合。

关键词： 山东半岛西部; 海效应暴雪; 云带特征; 动力机制

本文引用格式

郑怡 , 杨成芳 , 郭俊建 , 张磊 , 焦艳 . 一次罕见的山东半岛西部海效应暴雪过程的特征及机理研究[J]. 高原气象, 2019 , 38(5) : 1017 -1026 . DOI: 10.7522/j.issn.1000-0534.2018.00140

Abstract

In this study, amount of available observational data were used, including satellites (MODIS and HIMAWARI-8), Doppler radar, profile radar, automatic stations, buoy stations, routine observation data, FNL atmospheric reanalysis data and ERA_Interim reanalysis data. The ocean-effect snowstorm occurring in the western and northern Shandong Peninsula during 25-26, November 2015 was diagnostically analyzed. The results are as follows:(1)In this case, the cold air was strong, the cold vortex was located westward and southward, corresponding to the surface isobaric cyclone bending anomaly, which provided a favorable large-scale background condition for the snowstorm in the western peninsula. (2) There were many snow cloud bands in the snow process, and there may be multiple cloud clusters in each cloud band. The location and development intensity of the cloud belt had a good indication for the snowfall area and amount. (3) Corresponding to the strong snowfall period, the Sea-air temperature difference was around 14℃, there were unstable stratification in the western Shandong Peninsula, the ground convergence line provided the dynamic trigger mechanism, the water vapor accumulated in the early stage and the strong water vapor convergence in the later stage provided sufficient water vapor conditions. The low level convergence area maintaining long time made the snowstorm cloud belts develop strongly and produced "train effect", which was the main cause of the blizzard in the western part of the peninsula. (4) In the course of the blizzard, the western part of the peninsula was superior to the northern part in terms of energy and water vapor, and the dynamic maintenance mechanism was different from the northern part. The convergence of the northwest wind and the northerly wind existed below 900 hPa, which can be used as a reference in the future weather forecast.

Key words： The western Shandong; ocean-effect snowsto; cloud characteristic; dynamical mechanism

参考文献

[1]David A R K, Ronald A S, 1995. A satellite study of cloud-band frequencies over the Great Lakes[J]. Journal of Applied Meteorology, 34(9):2083-2090.
[2]David M S, Derek S A, David J S, et al, 2004. Snowbands during the Cold-Air Outbreak of 23 January 2003[J]. Monthly Weather Review, 132:827-842.
[3]Heather D R, Daniel T D, 2013. The Dependence of QPF on the Choice of Microphysical Parameterization for Lake-Effect Snowstorms[J]. Journal of Applied Meleorology and Chimate, 52:363-377.
[4]Heather D R, Shiyuan Z, 2015. The Dependence of QPF on the Choice of Boundary-and Surface-Layer Parameterization for a Lake-Effect Snowstorm[J]. Monthly Weather Review, 54:1177-1190.
[5]Higuehi K, 1963. The Band Structure of Snowfalls[J]. Journal of the Meteorological Society of Japan, 41(1):53-70.
[6]James W S, Leah S C, 2017. The OWLeS IOP2b Lake-effect snowstorm:shoreline geometry and the mesoscale forcing of precipitation[J]. Monthly Weather Review, 145:2421-2436.
[7]Joshua J S, Kristovich A R, Hjelmfelt M R, 2006. Boundary Layer and Microphysical Influences of Natural Cloud Seeding on a Lake-effect Snow Storm[J]. Monthly Weather Review, 134(7):1842-1858.
[8]McVehill G E, Peace R L, 1965. Some studies of lake effect snowfall from Lake Erie[C]. Proceedings of 8th Conference on Great Lakes Research, 262-272.
[9]Petterssen, Calabrese P A, 1959. On some weather influences due to warming of the air by the Great Lakes in Winter[J]. Journal of Meteorology, 16(6):646-652.
[10]Philip T B, Bart G, Leah S C, et al, 2017. The OWLeS IOP2b Lake-Effect Snowstorm:Dynamics of the Secondary Circulation[J]. Monthly Weather Review, 145:2437-2459.
[11]Steenburgh W J, Daryl J O, 2001. Multiscale analysis of the 7 December 1998 Great Salt Lake-Effect Snowstorm[J]. Monthly Weather Review, 129:1296-1317.
[12]Steenburgh W J, Scott F H, Daryl J O, 2000. Climatology of Lake-Effect Snowstorms of the Great Salt Lake[J]. Monthly Weather Review, 128:709-727.
[13]曹钢锋, 张善君, 朱官忠, 等, 1988.山东天气分析与预报[M].北京:气象出版社, 292-298.
[14]褚昭利, 李建华, 崔宜少, 2012.山东半岛一次冷涡强冷流降雪过程分析[J].山东气象, 32(129):13-16.
[15]崔宜少, 张丰启, 李建华, 等, 2008.2005年山东半岛连续三次冷流暴雪过程的分析[J].气象科学, 28(4):395-401.
[16]付亮, 赵宇, 杨成芳, 等, 2018.影响东北的北上温带气旋暴雪的统计特征[J].高原气象, 37(6):1705-1715. DOI:10.7522/j.issn.1000-0534.2018.00099.
[17]高晓梅, 杨成芳, 王世杰, 等, 2017.莱州湾冷流降雪的气候特征及其成因分析[J].气象科技, 45(1):130-138.
[18]胡列群, 黄镇, 黄慰军, 等, 2012. MODIS数据云相态反演在一次暴雪过程中的应用[J].应用气象学报, 23(5):609-613.
[19]胡顺起, 曹张弛, 陈滔, 2017.山东省南部一次极端特大暴雪过程诊断分析[J].高原气象, 36(4):984-992. DOI:10.7522/j.issn.1000-0534.2016.00134.
[20]李刚, 党英娜, 袁海豹, 2007.烟台冷流强降雪天气预报指标统计分析[J].山东气象, 136-140.
[21]李建华, 崔宜少, 单宝臣, 2007.山东半岛低空冷流降雪分析研究[J].气象, 33(5):49-55.
[22]李建华, 崔宜少, 杨成芳, 2015.不同中心位置的山东半岛冷流暴雪天气分析[J].中国海洋大学学报, 45(8):10-18.
[23]梁军, 张胜军, 黄艇, 等, 2015.辽东半岛2次高影响冷流降雪的对比分析[J].干旱气象, 33(3):444-451.
[24]林曲凤, 吴增茂, 梁玉海, 等, 2006.山东半岛一次强降雪过程中的中尺度特征分析[J].中国海洋大学学报, 36(6):908-914.
[25]刘晶, 李娜, 陈春艳, 2018.新疆北部一次暖区暴雪过程锋面结构及中尺度云团分析[J].高原气象, 37(1):158-166. DOI:10.7522/j.issn.1000-0534.2017.00008.
[26]孙殿光, 黄本峰, 薛波, 等, 2016.山东半岛三次冷流暴雪气流结构差异性分析[J].高原气象, 35(3):800-808. DOI:10.7522/j.issn.1000-0534.2015.00017.
[27]孙兴池, 王文毅, 阎立凤, 等, 2007, 2005年山东半岛特大暴风雪分析[J].中国海洋大学学报, 37(6):879-884.
[28]孙艳辉, 李泽椿, 寿绍文, 2017.东北地区两次历史罕见暴风雪天气过程的分析[J].高原气象, 36(2):549-561. DOI:10.7522/j.issn.1000-0534.2017.00012.
[29]杨成芳, 2010.渤海海效应暴雪的三维热力结构特征[J].中国海洋大学学报, 40(2):17-27.
[30]杨成芳, 高留喜, 王方, 2011.一次异常强渤海海效应暴雪的三维运动研究[J].高原气象, 30(5):1213-1223.
[31]杨成芳, 李泽椿, 李静, 等, 2008.山东半岛一次持续性强冷流降雪过程的成因分析[J].高原气象, 27(2):442-450.
[32]杨成芳, 王俊, 2009.利用单多普勒雷达资料做冷流暴雪的中尺度分析[J].高原气象, 28(5):1034-1043.
[33]杨成芳, 周雪松, 2012.渤海海效应暴雪微物理过程的数值模拟[J].中国海洋大学学报, 42(增刊):10-17.
[34]杨成芳, 周雪松, 王业宏, 2007.山东半岛冷流降雪的气候特征及其前兆信号[J].气象, 33(8):76-82.
[35]于群, 周发琇, 汤子东, 等, 2011.冬季山东半岛局地性降水气候的形成[J].高原气象, 30(3):719-726.
[36]于晓晶, 辜旭赞, 李红莉, 2013.山东半岛一次冷流暴雪过程的中尺度模拟与云微物理特征分析[J].气象, 39(8):955-964.
[37]张剑英, 1983.冬季半岛地区"冷流低云"的云图特征[J].山东气象, 4:21-29.
[38]张黎红, 2004.大连地方性冷流降雪成因分析[J].辽宁气象, 4:12-13.
[39]赵宇, 蓝欣, 杨成芳, 2018.一次江淮气旋极端雨雪过程的云系特征和成因分析[J].高原气象, 37(5):1325-1340. DOI:10.7522/j.issn.1000-0534.2018.00024.
[40]郑丽娜, 王坚红, 杨成芳, 等, 2014.莱州湾西北与山东半岛北部强海效应降雪个例分析[J].气象, 40(5):605-611.
[41]郑怡, 高山红, 吴增茂, 2014.渤海海效应暴雪云特征的观测分析[J].应用气象学报, 25(1):71-82.
[42]周淑玲, 丛美环, 吴增茂, 等, 2008.2005年12月321日山东半岛持续性暴雪特征及维持机制[J].应用气象学报, 19(4):444-453.
[43]周淑玲, 李宏江, 吴增茂, 等, 2011.山东半岛冬季冷流暴雪的气候特征及其成因征兆[J].自然灾害学报, 20(3):91-98.
[44]周淑玲, 王科, 杨成芳, 等, 2016.一次基于综合探测资料的山东半岛冷流暴雪特征分析[J].气象, 42(10):1213-1222.
[45]周淑玲, 朱先德, 符长静, 等, 2009.山东半岛典型冷涡暴雪个例对流云及风场特征的观测与模拟[J].高原气象, 28(4):935-944.
[46]周雪松, 杨成芳, 王辉, 2013.山东半岛海效应降雪中逆风区的形成机制研究[J].海洋湖沼通报, 4:25-33.
[47]朱乾根, 林锦瑞, 寿绍文, 等, 2007.天气学原理和方法[M].北京:气象出版社, 276-294.
[48]朱营礼, 吴增茂, 林曲凤, 等, 2010.山东半岛冷流暴雪过程的个例分析[J].中国海洋大学学报, 40(增刊):1-7.
Options
文章导航

/

〈 〉

本系统由北京玛格泰克科技发展有限公司设计开发 技术支持：support@magtech.com.cn