Detecting the melting layer with a micro rain radar using a neural network approach

被引:5
|
作者
Brast, Maren [1 ]
Markmann, Piet [1 ]
机构
[1] METEK Meteorol Messtech GmbH, Fritz Str Mann Str 4, D-25337 Elmshorn, Germany
关键词
DOPPLER RADAR; BRIGHT BAND;
D O I
10.5194/amt-13-6645-2020
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A new method to determine the melting layer height using a micro rain radar (MRR) is presented. The MRR is a small vertically pointing frequency-modulated continuous-wave radar that measures Doppler spectra of precipitation. From these Doppler spectra, various variables such as Doppler velocity or spectral width can be derived. The melting layer is visible due to higher reflectivity and an acceleration of the falling particles, among others. These characteristics are fed to a neural network to determine the melting layer height. To train the neural network, the melting layer height is determined manually. The neural network is trained and tested using data from two sites that cover all seasons. For most cases, the neural network is able to detect the correct melting layer height well. Sensitivity studies show that the neural network is able to handle different MRR settings. Comparisons to radiosonde data and cloud radar data show a good agreement with respect to the melting layer heights.
引用
收藏
页码:6645 / 6656
页数:12
相关论文
共 50 条
  • [31] A Recurrent Neural Network Approach to Pulse Radar Detection
    Sailaja, Anangi
    Sahoo, Ajit Kumar
    Panda, Ganapati
    Baghel, Vikas
    [J]. 2009 ANNUAL IEEE INDIA CONFERENCE (INDICON 2009), 2009, : 57 - +
  • [32] RADAR SIGNAL CATEGORIZATION USING A NEURAL NETWORK
    ANDERSON, JA
    GATELY, MT
    PENZ, PA
    COLLINS, DR
    [J]. PROCEEDINGS OF THE IEEE, 1990, 78 (10) : 1646 - 1657
  • [33] Radar precipitation estimation using neural network
    Liu, HP
    Chandrasekar, V
    [J]. 28TH CONFERENCE ON RADAR METEOROLOGY, 1997, : 202 - 203
  • [34] Using artificial neural network approach to predict rain attenuation on earth-space path
    Yang, HW
    He, C
    Song, WT
    Zhu, HW
    [J]. IEEE ANTENNAS AND PROPAGATION SOCIETY INTERNATIONAL SYMPOSIUM, VOLS 1-4: TRANSMITTING WAVES OF PROGRESS TO THE NEXT MILLENNIUM, 2000, : 1058 - 1061
  • [35] Examination of a Winter Storm Using a Micro Rain Radar and AMDAR Aircraft Soundings
    Smith, Barrett L.
    Blaes, Jonathan L.
    [J]. JOURNAL OF OPERATIONAL METEOROLOGY, 2015, 3 (14) : 156 - 171
  • [36] Integrated Neural Network Approach for Enhanced Vital Signal Analysis Using CW Radar
    Yoon, Won Yeol
    Kwon, Nam Kyu
    [J]. ELECTRONICS, 2024, 13 (13)
  • [37] A neural network approach to target classification for active safety system using microwave radar
    Park, Seongkeun
    Hwang, Jae Pil
    Kim, Euntai
    Lee, Heejin
    Jung, Ho Gi
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (03) : 2340 - 2346
  • [38] Effective approach for detecting the single trial ERP using rational Gaussian neural network
    Shen, Minfen
    Zhang, Yuzheng
    Zhu, Yisheng
    Beadle, Patch
    [J]. 2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 33 - 36
  • [39] Radar Vertical Profile of Reflectivity Correction with TRMM Observations Using a Neural Network Approach
    Wang, Yadong
    Zhang, Jian
    Chang, Pao-Liang
    Cao, Qing
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2015, 16 (05) : 2230 - 2247
  • [40] AQI prediction using layer recurrent neural network model: a new approach
    Ahmad, Shadab
    Ahmad, Tarique
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2023, 195 (10)