摘要
本文利用毫米波云雷达联合称重式雨量计、气球探空和S波段天气雷达在北京对2015年11月三次降雪进行了观测,以2015年11月22~23日降雪过程为例,主要从降雪系统的宏观结构特征、微物理变化以及毫米波雷达在降雪探测中电磁波衰减情况、雪粒子含水量和地面降雪量估测几方面进行初步分析。结果表明:(1)毫米波云雷达具有高时空分辨率,能对降雪系统进行精细化探测,在降雪系统发展最旺盛的阶段能够通过反射率(Z)、退极化比(LDR)和径向速度(V)初步判断出云中是否含有过冷液滴;(2)降雪回波强度最大值能反映整层云系中含水量最大的区域,当最大值Z大于20 d BZ时,最大值的大小、最大值持续时间、最大值出现的高度与地面降水量成正相关,速度最大值表示云中粒子上升最大速度(速度为正时)或者粒子下落的最小速度(速度为负时),主要分布在-0.5~2 m s^(-1),速度最小值表示粒子下落的最大速度,主要在-3^-1 m s^(-1);(3)随着高度增加反射率的垂直廓线会出现多个峰值,这是由于不同高度层风速分布不均造成的,降雪回波这种特点比降雨回波更明显;(4)对比Ka与S波段雷达反射率可知,两雷达反射率平均差值小于2.5 d BZ,Ka波段反射率略大S波段雷达反射率;(5)降雪量反演与地面降雪量仪数据对比,逐小时降雪量反演精度为20.38%,累计降雪量反演误差为6.58%,24小时累计降雪量绝对误差为1.9 mm,说明云雷达估算累计降雪量具有较高的可行性,能够很准确的反映地面实际降雪情况,当降雪系统发展旺盛时,雪粒子含水量分布在0.05~0.15 g m^(-3),在降雪初期或者降雪系统消散期,雪粒子含水量一般小于0.04 g m^(-3),能够很好地反映出整层降雪回波的雪粒子含水量。这些云雷达在降雪观测中的应用和初步分析结果可以更好的地了解降雪系统宏微观结构,为云模式的发展和人工影响天气中增雪潜力评估提供一些参考。
Three snow cases were observed using millimeter wave cloud radar, weighing rain gauge, balloon sounding and S band radar in Beijing area in December 2015. A preliminary analysis on the macro and micro structure characteristics of snow clouds, the electromagnetic wave attenuation of millimeter wave cloud radar, the snow water content, and estimation of total snow amount for the Dec 22-Dec 23 snow case was conducted. The results show that： （1） With high spatial-temporal resolution, the millimeter wave cloud radar is good at observing details of snow cloud system. The supercooled liquid particles could be detected by reflectivity Z, linear depolarization ratio （LDR） and radial velocity （l/）. （2） The maximum radar reflectivity could represent the max water content area in the snow cloud. The maximum value of Z and its duration and occurrence height were proportional to surface snowfall amount when the value of Z was greater than 20 dBZ. The maximum terminal velocity means the maxium ascending V （when V〉0） or the minimum descending v （when V〈0）, which was within the range of --0.5-2 m s-l. The minimum value of terminal velocity represents the maximum falling velocity of the particles, which is within the range of --3---1 m s-1. （3） There could have several peaks in the reflectivity profile with increasing height due to different wind speeds at different heights. This characteristic of radar reflectivity is much more obvious in snow case than in rain case. （4） The difference in reflectivity between Ka and S band radars was less than 2.5 dBZ. The reflectivity of Ka band radar was slightly larger than that of S band radar. （5） Comparing the snowfall retrieved from radar data with surface gauge measurements, it was found that the accuracy of hourly snow retrievals was 20.38% and the error in the retrievals of snowfall amount was 6.58%. The absolute value of error in 24-h snowfall was 1.9 mm. The above result suggests that the radar snowfall retrieval has high practicability in reflecting the surface snowfall. The snow water content was between 0.05 g m-3 and 0.15 g m-3 in thriving snow clouds. At the early stage of snowfall or when the snow clouds started to dissipate, the snow water content was less than 0.04 g m-3 Radar observations could well reflect the snow water content in the entire layer with a decent quality. Results of the present study indicate that with the application of cloud radar and preliminary analysis on radar observations of snow clouds, we can get a better understanding of the macro and micro structures of snow clouds and provide information for the development of cloud model and snow seeding potential evaluation.
出处
《大气科学》
CSCD
北大核心
2018年第1期134-149,共16页
Chinese Journal of Atmospheric Sciences
基金
北京市科技计划项目D171100000717001
北京市自然科学基金资助项目8174068
8172023
北京市气象局科技项目BMBKJ201506001~~
关键词
毫米波
云雷达
降雪量
含水量
Millimeter wave, Cloud radar, Snowfall, Water content
