融化层附近降水粒子微物理特征的个例分析

本文给出了融化层中雪花融化过程特征和融化层附近降水粒子尺度谱分布函数；雪花、融雪、雨滴尺度谱分布均可用指数函数N=N0exp(-λD)来拟合。在融化层附近，谱参数N0、λ随温度升高而增大有正相关关系。谱参数N0、λ之间有幂指数关系N0=σλβ，降水水粒子相态不同，σ值差异明显。     

基于S波段双偏振雷达融化层识别算法的研究

基于融化层识别算法(melting layer detection algorithm,MLDA)原理,利用2020年7—8月济南、青岛两部S波段双偏振多普勒雷达体扫数据,进行融化层高度信息识别试验,根据试验结果在MLDA算法中引入径向连续性检验、增加扫描仰角范围与调整判别融化层出现的距离库总数阈值的改进措施,与改进前的MLDA算法进行了对比分析,得到以下结论:MLDA对融化层顶高度有一定识别效果,识别的融化层顶高度的平均绝对误差较大,融化层底高度过低;加入径向连续性检验(简称MLDA-R1)后,识别的融化层顶高度的平均绝对误差明显减小,融化层底对应温度与融化层厚度分布在合理区间,但是遗漏识别的试验数明显增加;在MLDA-R1基础上,扫描区域增加了3.3°仰角(简称MLDA-R2)并调整了判别融化层出现的距离库总数阈值(简称MLDA-R3),融化层遗漏识别的试验数明显减少,同时提高了对融化层高度信息的识别效果;一些降水回波与非降水回波混合的区域会被错误识别为融化层区域,影响MLDA算法对融化层的识别效果,仍需进一步改进。总体来看,改进后的MLDA更适用于我国S波段双偏多普勒振雷达,对雷...     

毫米波雷达资料融化层亮带特征的分析及识别

云的融化层亮带位置、厚度及其回波强度的垂直结构变化信息对于云和降水物理研究、人工影响天气指挥和效果评估,数值模拟云参数化均有非常重要的意义。为了了解云层融化层高度的精确位置,根据云雷达在广东、河北、吉林等不同云过程总计456个例分析(其中确认融化层明显个例34次),系统分析云雷达探测到融化层亮带宏观参量的统计情况,包括融化层厚度、反射率因子在融化层强度变化、退偏振因子在融化层的强度变化,并提出了一种结合垂直探测的云雷达探测到的雷达反射率因子(R)和退偏振因子(Ldr)垂直廓线数据,根据参量在融化层附近显著变化特性,识别零度层亮带高度和厚度的算法。同时选取个例对应观测时刻探空资料观测的0°层高度进行对比,反演的融化层高度等参数同实际情况比较接近,位于探空资料观测的0°层下方,而且退偏振因子对融化层的敏感程度大于反射率因子。     

关于冰雹的融化层高度

冰雹尤其是强冰雹预报的重要参数之一是冰雹融化层到地面的高度。长期以来国外英文文献上一直都将湿球温度0℃层(Wet Blub Zero,WBZ)作为冰雹融化层的近似高度,但这一事实一直没有引起国内预报人员和部分研究人员(包括作者在内)的足够注意。以至于一直到现在,国内绝大多数预报人员仍然将干球温度0℃层(Dry Blub Zero,DBZ)作为冰雹融化层的近似高度,这是一个错误。在WBZ和DBZ之间和上下一定范围内存在明显干空气(即温度露点差较大)时,二者高度会有明显的差距。本文主要阐明冰雹融化层的高度应该采用湿球温度0℃层(WBZ)高度而不是干球温度0℃层(DBZ)高度,说明了当对流层尤其对流层中层存在明显干层时,由于蒸发冷却引起的水膜再冻结会有利于大冰雹落地,而此时的冰雹融化层也就是湿球温度0℃层(WBZ)的高度明显低于干球温度0℃层(DBZ)的高度。文中给出了如何根据探空资料的T-logp图确定湿球温度垂直廓线进而确定湿球温度0℃层(WBZ)高度的方法。最后给出两个对比鲜明的例子,进一步说明对流层中层明显干层存在与否对冰雹融化层高度的影响,以及冰雹融化层高度的高低是决定冰雹大小甚至降雹与否的主要因子之一。     

毫米波测云雷达融化层自动识别技术

为了充分利用雷达数据中的融化层信息,通过分析融化层在反射率因子和线性退极化比(LDR)参量中的特性,结合国内某型毫米波测云雷达的特点,提出了一种融化层边界自动识别的技术。利用2010年5-10月国内某型毫米波测云雷达在杭州的探测资料及相应的探空资料,对识别结果以及算法中参数的敏感性进行了对比和分析。对比结果表明,该方法能有效识别亮带的存在,得到的融化层上边界平均高度与实测零度层高度的误差小于100 m。参数的敏感性分析表明,融化层在反射率和LDR中的特性存在差异,其厚度在600～1500 m。毫米波测云雷达距离分辨率高、LDR对融化层敏感以及使用反射率和LDR双重约束是识别出的融化层边界误差较小的原因。     

粒子边缘粘连对0℃层亮带雷达反射率因子的影响分析

针对云中粒子在融化、并合过程中的粘连现象对0℃层亮带的影响分析,利用离散偶极子近似算法(DDA)计算融化过程中两个大小相同的球形粒子在雷达发射波偏振方向上发生粘连后的散射特性,以两个等体积融化球为例,它们在雷达发射波偏振方向上发生粘连时的总后向散射截面σDDA,并与同体积融合球的后向散射截面σmieequal比较。结果表明:(1)在等体积直径较小时,σDDA/σmieequal≥1.5,随着等体积直径的变大,σDDA/σmieequal会减小趋向于1,甚至会1;(2)在同样的等体积直径处,σDDA/σmieequal随着融化程度的加深而增大,在谐振区可出现减小。引入"粘连概率p"参数刻画粘连影响,并应用于含有0℃层亮带的层状云的雷达反射率因子的定量模拟试验。结果表明,在粒子融化、并合过程中,在雷达发射波偏振方向上的粘连,可以有效地增大雷达反射率因子、使亮带现象更加突出。     

新型液氮载体外场催化试验

液氮冷冻成冰效率高，催化阉温高，经济实用，是前景很好的冷云(雾)催化剂，但由于蒸发太快，实际对云雾催化作业时，在播撒层很快蒸发殆尽，对比较深厚的云(雾)层不能充分有效地催化。为了增加液氮的沉降距离，提高其催化效率,我们在进行了大量室内外试验研究后，将最后筛选出的最佳液氮载体带到飞机上，进行了实际催化试验，其成冰效果比较明显，与室内试验结果一致。     

江苏省冰粒过程的天气特征和预报着眼点探讨

利用常规气象观测资料、微波辐射计资料和FNL再分析资料对2016年3月8日和2015年2月27日江苏省两次冰粒过程进行了对比分析,研究结果表明:(1)两次过程均是在后倾槽系统和东路冷空气的影响下产生的,环流形势为冰粒的产生提供了有利的大尺度条件;(2)在临近冰粒形成前,融化层和冻结层形成,而干层的形成时间要明显早于融化层和冻结层;(3)偏北的冷气流与偏南的暖气流随时间和空间分布不同导致温度平流分布不同,进而导致融化层和冻结层产生;(4)干层的形成主要是由于湿度平流随高度的分布差异造成的,水滴在干层中的蒸发吸热作用促进冻结层产生和维持。     

1960—2013年北京地区冻雨天气过程特征分析

利用地面气象站的观测资料、观象台的探空资料和NCEP/NCAR再分析资料对1960—2013年北京地区20个地面气象观测站冻雨天气过程的特征及其发生条件进行了分析。结果表明:1960—2013年北京地区11月至翌年4月均可能出现冻雨天气,北京东南部的大兴区和通州区、西北部的昌平区为冻雨发生相对较频繁的地区。低层丰富的水汽和抬升条件有利于冻雨天气的出现,大气层结的垂直结构可分为无融化层(整层<0℃)和有融化层(冷—暖—冷)两类,两种类型冻雨出现的概率相当(各占50%)。通过对北京地区冻雨天气过程典型个例的对比研究发现:850—700hPa暖平流对逆温强度的变化有重要影响;无融化层时,云顶高度较高,700hPa以下气层温度为-10~0℃,降水以过冷却水的形式降落至地面发生冻结形成冻雨;有融化层时,湿层较浅薄(位于850hPa以下),暖湿空气在近地层的"冷垫"上滑行,是此类冻雨发生的有利因素之一。     

人工增雨降温机理的数值模拟研究: 对流云个例试验

为减轻夏季用电负荷,2004年我国许多省市实施了碘化银催化增雨降温作业。本文利用数值模拟方法讨论了强对流云(冰雹云)催化降温的机理。模拟结果表明,实施碘化银催化后,地面降雨量增加、降雹量减少、地面温度降低。催化使得云中冰晶、霰和雨水的含量增加,造成云雨蒸发、霰的融化(蒸发)及冰晶升华量增加,从而使空气温度降低。     

两次华北冷涡过程雹云结构特征及AgI催化效果数值研究

用三维完全弹性非静力平衡雹云模式模拟了不同低涡雹云演变特征和人工引晶催化效果,结果表明:冷涡雹云中不存在大量的过冷雨滴,过冷水几乎是由云滴组成的,雹胚形成以云霰转化为主,由冰相过程形成降水粒子。近地面有薄逆温层云体,云底温度高,云中垂直运动强,云中过冷云水含量增长迅速且丰富。在雹云主要上升气流到达的过冷水含量大值区下方和过冷水大值区中心部位分别一次引进×107/kg碘化银粒子进行大剂量催化试验,碘化银主要以凝结-冻结方式核化成冰,雹胚浓度增加,雹胚过多争食抑制冰雹增长,使得冰雹直径明显减小。     

火箭增雨作业部位和催化剂量的确定

讨论了采用新一代多普勒雷达指挥火箭增雨作业时。对大连地区不同类型云催化时目标云选择、催化潜力判断、催化时机把握、催化部位确定的技术思路和方法。     

利用数字化雷达回波参数分析人工增雨播云条件

利用数字化测雨雷达观测的层状云雷达立体扫描资料和探空资料，分析得出层状云降水部分特征，并利用多元逐步回归获得催化作业效果指标y=2.0mm.h^-1，在使用雷达立体扫描资料进行人工增雨作业时指导方面做了探讨。     

Radar attenuation due to melting: a comparison of physical models proposed for the melting morphology

The radio wave attenuation through the melting layer at various frequencies is investigated. The effect of the melting morphology on the attenuation computed by the Mie theory is discussed. To obtain the rate of melting of snowflakes, a melting model is given. In this model, the six different patterns proposed by Fabry and Szyrmer [J. Atmos. Sci., 56 (1999) 3593] to calculate the permittivity of the melting particles are used and the specific attenuation for each morphology is obtained. A comparison between the computed specific attenuation computed for the frequencies 2.8, 9.4 and 22.2 GHz is made. This analysis suggests that the large variability in the specific attenuation given by these models is due to the melting morphology in which the melting snow is modeled as a snow sphere surrounded by a water shell.     

合肥地区一次小雨过程的W波段云雷达 的云物理特征分析

利用我国自己研制的W波段云雷达地基探测资料,分析了合肥一次小雨云系的微物理过程,然后利用两个不同地区的地基及机载探测资料,初步反演了水云及卷云的微物理参数。结果表明:(1)回波强度增大,多普勒速度、线性退极化比(LDR)、谱宽激增的地方为融化层顶,根据LDR亮带可初步判定融化层的厚度;(2)利用经验关系法,对卷云冰水含量和水云的液态水含量进行了反演,利用推导的公式反演得到冰晶云云粒子的有效半径;(3)利用逐库订正法对水云的回波强度进行订正,得到了衰减订正后的液态水含量,减小了反演误差。     

Supercooled drizzle formed by condensation–coalescence in the mid-winter season of the Canadian Arctic

Supercooled drizzle (freezing drizzle) was observed at Inuvik, N.W.T., Canada (68°22′N, 133°42′W) on December 20, 21 and 27, 1995. Meteorological conditions in which the supercooled drizzle could form under low temperatures (colder than −20°C) in the mid-winter season of the Canadian Arctic were examined from the sounding data and data measured by a passive microwave radiometer at ground level. The following results were obtained. (1) Supercooled drizzle fell to the ground with ice pellets and frozen drops on snow crystals. (2) The maximum size of supercooled drizzle particles increased as the depth of cloud layer saturated with respect to water increased. (3) Because a layer of air temperature higher than 0°C was not detected from the sounding data at Inuvik, melting of snow particles was impossible. It was concluded, therefore, that supercooled drizzle was formed by the condensation–coalescence process below freezing temperature.     

Impact of cloud microphysical processes on hurricane intensity, part 2: Sensitivity experiments

Summary Seven different microphysical sensitivity experiments were designed with an objective to evaluate their respective impacts in modulating hurricane intensity forecasts using mesoscale model MM5. Microphysical processes such as melting of graupel, snow and cloud ice hydrometeors, suppression of evaporation of falling rain, the intercept parameter and fall speed of snow and graupel hydrometeors are modified in the existing NASA Goddard Space Flight Center (GSFC) microphysical parameterization scheme. We studied the impacts of cloud microphysical processes by means of track, intensity, precipitation, propagation speed, kinematic and thermodynamic vertical structural characteristics of hurricane inner core. These results suggest that the set of experiments where (a) melting of snow, graupel and cloud ice were suppressed (b) melting of snow and graupel were suppressed and (c) where the evaporation of rain water was suppressed all produced most intense storms. The major findings of this study are the interconversion processes such as melting and evaporation among hydrometeors and associated feedback mechanism are significantly modulate the intensity of the hurricane. In particular an experiment where the melting of graupel, snow and cloud ice hydrometeors was eliminated from the model parameterization scheme produced the most explosively intensified storm. In the experiment where rain water evaporation was eliminated from the model, it produced a stronger storm as compared to the control run but it was not as strong as the storms produced from absence of melting processes. The impact on intensity due to variations made in intercept parameters of the hydrometeors (i.e., snow and graupel) were not that evident compared to other experiments. The weakest storm was noted in the experiment where the fall speeds of the snow hydrometeors were increased two fold. This study has isolated some of the factors that contributed to a stronger hurricane and concludes with a motivation that the findings from this study will help in further improvement in the design of sophisticated explicit microphysical parameterization for the mesoscale non-hydrostatic model for realistic hurricane intensity forecasts.     

Simulation of snow processes beneath a boreal scots pine canopy

A physically-based multi-layer snow model Snow-Atmosphere-Soil-Transfer scheme(SAST)and a land surface model Biosphere-Atmosphere Transfer Scheme(BATS)were employed to investigate how boreal forests influence snow accumulation and ablation under the canopy.Mass balance and energetics of snow beneath a Scots pine canopy in Finland at different stages of the 2003-2004 and 2004 2005 snow seasons are analyzed.For the fairly dense Scots pine forest,drop-off of the canopy-intercepted snow contributes,in some cases,twice as much to the underlying snowpack as the direct throughfall of snow.During early winter snow melting,downward turbulent sensible and condensation heat fluxes play a dominant role together with downward net longwave radiation.In the final stage of snow ablation in middle spring,downward net all- wave radiation dominates the snow melting.Although the downward sensible heat flux is comparable to the net solar radiation during this period,evaporative cooling of the melting snow surface makes the turbulent heat flux weaker than net radiation.Sensitivities of snow processes to leaf area index(LAI)indicate that a denser canopy speeds up early winter snowmelt,but also suppresses melting later in the snow season. Higher LAI increases the interception of snowfall,therefore reduces snow accumulation under the canopy during the snow season;this effect and the enhancement of downward longwave radiation by denser foliage outweighs the increased attenuation of solar radiation,resulting in earlier snow ablation under a denser canopy.The difference in sensitivities to LAI in two snow seasons implies that the impact of canopy density on the underlying snowpack is modulated by interannual variations of climate regimes.