Liu Xiaolu, Zhang Yuan, Liu Dongsheng. Calibration for data observed by airborne hot-wire liquid water content sensor. J Appl Meteor Sci, 2021, 32(6): 748-758. DOI:  10.11898/1001-7313.20210609.
Citation: Liu Xiaolu, Zhang Yuan, Liu Dongsheng. Calibration for data observed by airborne hot-wire liquid water content sensor. J Appl Meteor Sci, 2021, 32(6): 748-758. DOI:  10.11898/1001-7313.20210609.

Calibration for Data Observed by Airborne Hot-wire Liquid Water Content Sensor

DOI: 10.11898/1001-7313.20210609
  • Received Date: 2021-09-07
  • Rev Recd Date: 2021-10-27
  • Publish Date: 2021-11-23
  • 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.
  • Fig. 1  Negative value proportion(a), minimum(b) and maximum(c) values of liquid water content determined by Solution 1 in positive temperature levels

    Fig. 2  Flight track and position projection of ground- based microwave radiometer on 1 Dec 2015 aircraft and ground-based microwave radiometer

    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

    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

    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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    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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    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
    NCIP>0
    NPIP>0
    NCIP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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    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
    DownLoad: Download CSV
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    • Received : 2021-09-07
    • Accepted : 2021-10-27
    • Published : 2021-11-23

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