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Calibration for Data Observed by Airborne Hot-wire Liquid Water Content Sensor
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摘要: 机载含水量仪是目前云中液态水含量唯一的探测仪器,其准确性直接影响人工增雨作业条件判别。基于2015年和2017年四川盆地南部开展的10架次飞机云物理探测试验,考察机载热线含水量仪LWC-100探测数据发现存在异常极大值、负值数量多等问题。通过分析DMT（Droplet Measurement Technologies）公司云粒子探头（cloud droplet probe,CDP）、云粒子图像探头（cloud imaging probe,CIP）、降水粒子图像探头（precipitation imaging probe,PIP）数据,提出对入云前的干功率进行重新计算的3种方法:方法1以CDP探头的不同粒子尺度分档为标准,不低于某一档尺度的粒子数浓度大于0记为入云；方法2以CDP的数浓度大于10 cm-3为入云判定条件；方法3以CDP,CIP,PIP 3种探头探测的粒子数浓度同时大于0记为入云。结果显示:3种方法均有效纠正液态水含量不为0的情况,负值数量也较探测数据明显减少。方法1以不小于5 μm的粒子数浓度大于0记为入云,校验计算得到的液态水含量以负值数量和大小作为评价依据较方法2和方法3更优。Abstract: Based on the cloud microphysical detection data of 10-sortie aircraft over southern Sichuan Basin in 2015 and 2017, the liquid water content measured by DMT (Droplet Measurement Technologies) hot-wire liquid water content sensor is examined, and abnormal values in maximum, minimum and negative values are found.There are 4 possible causes for the abnormal maximum, minimum and negative values of liquid water content. First, the errors are caused by multiple parameters such as temperature, air pressure and vacuum velocity, which may lead to the error superposition of calculated values. Second, the on-board operators didn't calibrate the zero before entering the cloud. Third, the on-board operators only calibrate the zero once before entering the cloud during the whole flight. Fourth, the interval between cloud entry and exit is too short, so that the manual zero calibration is inaccurate.Using cloud particle spectrum data from cloud droplet probe (CDP), cloud imaging probe (CIP) and precipitation imaging probe (PIP), three solutions are proposed for calibrating hot-wire liquid water content sensor. Solution 1 is to set the criteria for entering cloud as the concentration of particle above a certain size from CDP probe greater than 0. Solution 2 is to set the criteria for entering cloud as the number concentration of cloud particles greater than 10 cm-3 from CDP probe. Solution 3 is to set the criteria for entering cloud as the number concentration from CDP, CIP and PIP probe greater than 0. The results show that when the number concentration is 0 from CDP, CIP and PIP probe, the original non-zero liquid water content problems are corrected by these solutions.To avoid the influence of ice phase particles on CDP number concentration, the verification is carried out in the positive temperature zone. All the test results show that the negative proportion of liquid water content is also significantly reduced compared with the original data. Solution 1 reduces the negative proportion of liquid water content, and make the minimum and maximum more reasonable than other scales. The liquid water content measured by Solution 1 are more reasonable than Solution 2 and 3.
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图 1 方法1确定的10个架次正温区的液态水含量负值占比(a)、最小值(b)和最大值(c)
Fig. 1 Negative value proportion(a), minimum(b) and maximum(c) values of liquid water content determined by Solution 1 in positive temperature levels
图 2 2015年12月1日飞机探测的飞行轨迹和地基微波辐射计位置投影
Fig. 2 Flight track and position projection of ground- based microwave radiometer on 1 Dec 2015 aircraft and ground-based microwave radiometer
图 3 2015年12月1日飞机探测要素随时间变化(a)飞行高度和温度,(b)粒子数浓度,(c)液态水含量,(d)飞机与微波辐射计水平距离
Fig. 3 Factors of time series from flight detection on 1 Dec 2015 (a)flight altitude and temperature, (b)particles number concentration, (c)liquid water content, (d)horizontal distance between aircraft and groud-based microwave radiometer
图 4 2015年12月1日飞机与地基微波辐射计水平距离20 km范围内的液态水含量随时间变化
Fig. 4 Time series of liquid water content within 20 km of horizontal distance between aircraft and ground-based microwave radiometer from flight on 1 Dec 2015
表 1 机载云物理探测系统
Table 1 Airborne cloud microphysical detection system
设备类型 测量范围 探测要素 热线含水量仪 0~3 g·m-3 液态水含量 云粒子探头 2~50 μm 小云粒子谱 云粒子图像探头 25~1550 μm 大云粒子谱、二维图像 降水粒子图像探头 100~6200 μm 降水粒子谱、二维图像 飞机综合气象要素测量系统 温、压、湿、风、GPS轨迹 
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表 2 液态水含量数据概况
Table 2 Overview of liquid water content data
架次 日期 整段飞行 NCDP=NCIP=NPIP=0 L1/(g·m-3) L2/(g·m-3) L1/(g·m-3) L1方差 L2/(g·m-3) L2方差 1 2015-11-28 -1.70~1.15 0~2.68 -1.67~0.31 0.050 0~1.65 1.600 2 2015-12-01(白天) -0.30~0.60 -0.28~1.26 -0.29~0.27 0.009 -0.28~1.25 0.040 3 2015-12-01(夜间) -1.86~0.88 0~2.21 -1.86~0.23 0.065 0~1.47 1.380 4 2015-12-10 -2.12~2.99 0~5.31 -0.48~0.16 0.038 0~1.54 1.000 5 2015-12-12 -1.57~31.52 -0.90~2.64 -1.57~31.52 1.150 -0.90~1.33 0.090 6 2015-12-13 -3.78~40.74 -11.54~9.11 -1.41~40.74 2.940 -0.004~6.78 0.150 7 2015-12-18 -1.64~44.19 0~49.61 -0.52~1.40 0.060 0.66~3.27 1.000 8 2017-10-31 -2.26~0.04 -1.54~1.25 -1.42~-0.22 0.080 -0.64~0.15 0.003 9 2017-11-27 -0.81~69.13 -3.78~1.12 -0.81~69.13 159.580 -3.78~1.11 0.180 10 2017-12-01 -1.15~-0.42 -0.67~0.85 -0.99~-0.61 0.410 -0.42~0.85 0.010
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表 3 入云判别方法与指标阈值
Table 3 Solutions and thresholds for in-cloud determination
方法 参考因素 入云的判别指标阈值 备注 1 尺度、数浓度 Ni>0 Ni为不低于第i档尺度粒子数浓度 2 数浓度 NCDP>10 cm-3 NCDP为CDP探头测得粒子总数浓度 3 数浓度 NCDP>0
或NCIP>0
或NPIP>0NCIP为CIP探头测得粒子总数浓度,
NPIP为PIP探头测得粒子总数浓度
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表 4 正温区的液态水含量的探测数据及3种方法校验值对比
Table 4 Comparisons between probe data and those determined by three solutions for liquid water content in the positive temperature levels
架次 探测数据 方法1 方法2 方法3 L2/(g·m-3) 负值占比/% 液态水含量/ (g·m-3) 负值占比/% 液态水含量/ (g·m-3) 负值占比/% 液态水含量/ (g·m-3) 负值占比/% 1 0~2.68 0 -0.18~0.51 2.48 -0.22~0.49 3.64 -0.13~0.53 8.45 2 -0.11~1.26 5.58 -0.23~0.95 1.43 -0.93~0.94 1.50 -0.66~0.95 13.83 3 0~2.21 0 -0.12~0.36 0.50 -0.25~0.33 1.03 -0.29~3.14 19.57 4 0~1.91 0 -0.14~0.29 1.09 -0.16~0.29 0.94 -0.83~5.39 15.32 5 -0.02~2.64 1.91 -0.28~1.33 4.08 -0.28~1.33 4.34 -2.06~1.53 8.27 6 -11.54~2.86 4.93 -0.02~0.10 0.10 0 0 -0.40~0.39 14.48 7 0~1.42 0 -0.18~0.07 1.97 0 0 -0.37~5.21 15.27 8 -1.78~1.25 81.95 -0.03~1.27 0.59 -0.007~1.27 0.32 -0.03~1.27 0.45 9 -0.128~1.12 10.98 -0.003~0.17 0.36 0~0.17 0 -1.15~1.10 2.73 10 -0.67~0.05 37.36 -0.005~0.01 1.35 0~0.003 0 -0.21~0.02 21.90
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