高原气象

高原气象 >

2018 , Vol. 37 >Issue 1: 223 - 233

DOI: https://doi.org/10.7522/j.issn.1000-0534.2016.00127

论文

毫米波雷达反演层状云液态水路径研究

  • 姚志刚 ,
  • 杨超 ,
  • 赵增亮 ,
  • 王磊
展开
  • 北京应用气象研究所, 北京 100029

收稿日期: 2016-07-15

  网络出版日期: 2018-02-28

基金资助

国家自然科学基金项目(41575031, 41375024);中国博士后基金项目(2015M580124);部级重点课题(QX2015040311A12005);国家重大专项课题(GFZX04021201)

收起

Study of the Stratiform Cloud Liquid Water Path Retrieval from the Millimeter Wave Radar Data

  • YAO Zhigang ,
  • YANG Chao ,
  • ZHAO Zengliang ,
  • WANG Lei
Expand
  • Beijing Institute of Applied Meteorology, Beijing 100029, China

Received date: 2016-07-15

  Online published: 2018-02-28

Fold

摘要

为了从毫米波雷达观测数据准确反演云中液态水路径，利用中国区域飞机探测资料得到的云粒子谱参数，基于2008年寿县ARM-AMF地基毫米波云雷达观测，针对层状云采用不同的云粒子谱参数假定，由物理迭代法和经验关系法反演云中液态水路径，并与地基微波辐射计的云水产品进行对比，开展了基于地基毫米波雷达的层状云液态水路径反演算法的对比分析。结果表明，反演结果与谱参数的选取以及云的特征密切相关，但物理迭代法总体上优于传统的经验关系法且前者对谱参数假定的依赖性相对较弱；基于中国区域的飞机探测资料得到的谱参数能够得到更优的反演结果；云中可能存在的大粒子是云雷达液态水路径反演高估的可能原因之一。最后，提出了基于云特征的谱参数选择方案，显著改进了云中液态水路径的反演结果。

关键词： 毫米波雷达; 液态水路径; 反演; 微波辐射计

本文引用格式

姚志刚 , 杨超 , 赵增亮 , 王磊 . 毫米波雷达反演层状云液态水路径研究[J]. 高原气象, 2018 , 37(1) : 223 -233 . DOI: 10.7522/j.issn.1000-0534.2016.00127

Abstract

Clouds play an important role in the weather prediction and global climate changes. Cloud liquid water path (LWP) is one of the important cloud microphysical parameters. LWP can be extracted from the millimeter wave radar. To investigate the dependence of the LWP retrieval on retrieval methods and cloud particle spectrum assumptions and improve the LWP retrieval, based on the cloud particle spectrum parameters from the aircraft detection data over China, the retrieval experiments are carried out by using the ground-based millimeter wave radar data in Shouxian from AMF-ARM Mobile Facility in 2008. Based on different cloud particle spectrum parameter assumptions, a physical iteration method and a statistical regression method are respectively used to retrieve the stratiform cloud LWP. And the results are evaluated with the products from the collocated microwave radiometer products. It is shown that although the results are strongly dependent on the spectrum assumption of the cloud particles, the physical iteration method less depends on the cloud spectrum assumption than the statistical regression method. Overall, the retrieval results from the physical iteration method agree better with the radiometer based LWP than those from the statistical regression method. Particularly, the spectrum of the clouds from the aircraft based measurements over China favor the LWP retrievals. The further analysis indicates that the ignorance of the large size particles could lead to the overestimation of the LWP retrievals, which increases with the increase of the radar reflectivity. Finally, a spectrum parameter selection scheme based on different cloud characteristics is proposed. The results show that the new scheme can significantly improve the agreement of the LWP retrievals with the microwave radiometer results.

Key words： Millimeter wave rada; liquid water path; retrieval; microwave radiometer

参考文献

[1]Atlas D, 1954. The estimation of cloud parameters by radar[J]. J Meteor, 11(4):309-317.
[2]Austin R T, Stephens G L, 2001. Retrieval of stratus cloud microphysical parameters using millimeter-wave radar and visible optical depth in preparation for CloudSat. Ⅰ-Algorithm formulation[J]. J Geophys Res, 106(D22):28233-28242.
[3]Austin R T, 2007. Level 2B radar-only cloud water content (2B-CWC-RO) process description document[J/OL]. CloudSat Data Processing Cent., Coop. Inst. for Res. in the Atmos., Colo. State Univ., Fort Collins. <a href="http://cloudsat.cira.colostate.edu/dataICDlist.php" target="_blank">http://cloudsat.cira.colostate.edu/dataICDlist.php</a>. [2016-07-14]
[4]Cadeddu M P, Liljegren J C, Turner D D, 2013. The Atmospheric Radiation Measurements (ARM) program network of microwave radiometers:instrumentation, data, and retrievals[J]. Atmospheric Measurement Techniques, 6(9):2359-2372. DOI:10. 5194/amt-6-2359-2013.
[5]Ware R, Cimini D, Herzegh P, et al, 2004. Ground-based microwave radiometer measurements during precipitation[C]//Rome, Italy: 8th Specialist Meeting on Microwave Radiometry, 24-27.
[6]Cornell D, Donahue C A, Keith C, 1995. A comparison of aircraft icing forecast models[R]. Air Force Combat Climatology Center Scott AFB IL.
[7]Crewell S, L?hnert U, 2003. Accuracy of cloud liquid water path from ground-based microwave radiometry 2. Sensor accuracy and synergy[J]. Radio Science, 38(3):8042. DOI:10. 1029/2002RS002634.
[8]Fox N I, Illingworth A J, 1997. The retrieval of stratocumulus cloud properties by ground-based cloud radar[J]. J Appl Meteor, 36(5):485-492.
[9]Han Q, Welch R, Chou J, et al, 1995. Validation of satellite retrievals of cloud microphysics and liquid water path using observations from FIRE[J]. J Atmos Sci, 52(23):4183-4195.
[10]Jolivet D, 2005. Quantification of the accuracy of liquid water path fields derived from NOAA 16 advanced very high resolution radiometer over three ground stations using microwave radiometers[J]. J Geophys Res, 110(D11):D11204. DOI:10. 1029/2004JD005205.
[11]Li J, Menzel W P, Zhang W, et al, 2004. Synergistic use of MODIS and AIRS in a variational retrieval of cloud parameters[J]. J Appl Meteor, 43(11):1619-1634.
[12]Li J, Wolf W W, Menzel W P, et al, 2000. Global soundings of the atmosphere from ATOVS measurements:The algorithm and validation[J]. J Appl Meteor, 39(8):1248-1268.
[13]Li L, Heymsfield G M, Tian L, et al, 2005. Measurements of ocean surface backscattering using an airborne 94-GHz cloud radar-Implication for calibration of airborne and spaceborne W-band radars[J]. J Atmos Ocean Technol, 22(7):1033-1045.
[14]Liljegren J C, 2002. Microwave radiometer profiler handbook[M]. Washington D C:Manual, Argonne National Laboratory.
[15]Matrosov S Y, Uttal T, Hazen D A, 2004. Evaluation of radar reflectivity-based estimates of water content in stratiform marine clouds[J]. J Appl Meteor, 2004, 43(3):405-419.
[16]Mattioli V, Westwater E R, Cimini D, et al, 2007. Analysis of radiosonde and ground-based remotely sensed PWV data from the 2004 North Slope of Alaska Arctic Winter Radiometric Experiment[J]. J Atmos Ocean Technol, 24(3):415-431.
[17]Miles N L, Verlinde J, Clothiaux E E, 2000. Cloud droplet size distributions in low-level stratiform clouds[J]. J Atmos Sci, 57(2):295-311.
[18]Pazmany A L, Sekelsky J B M S M, McLaughlin D J, et al, 2001. 2B. 1 multi-frequency radar estimation of cloud and precipitation properties using an artificial neural network[C]//Conference on Radar Meteorology of the American Meteorological Society. American Meteorological Society, 30: 154-156.
[19]Rodgers C D, 2000. Inverse methods for atmospheric sounding:Theory and practice[M]. Singapore:World scientific.
[20]Sauvageot H, Omar J, 1987. Radar reflectivity of cumulus clouds[J]. J Atmos Ocean Technol, 4(2):264-272.
[21]Somerville R C J, Remer L A, 1984. Cloud optical thickness feedbacks in the C<i>O</i><sub>2</sub> climate problem[J]. J Geophys Res, 89(D6):9668-9672.
[22]Stokes G M, Schwartz S E, 1994. The Atmospheric Radiation Measurement (ARM) program:Programmatic background and design of the cloud and radiation test bed[J]. Bull Amer Meteor Soc, 75(7):1201-1221.
[23]Greenwald T J, Christopher S A, Chou J, et al, 1999. Intercomparison of cloud liquid water path derived from the GOES 9 imager and ground based microwave radiometers for continental stratocumulus[J]. J Geophys Res, 104(D8):9251-9260.
[24]Turner D D, Clough S A, Liljegren J C, et al, 2007. Retrieving liquid water path and precipitable water vapor from the Atmospheric Radiation Measurement (ARM) Microwave Radiometers[J]. IEEE Trans Geosci Remote Sens, 45(11):3680-3690.
[25]Wang L, Li C, Yao Z, et al, 2014. Application of aircraft observations over Beijing in cloud microphysical property retrievals from CloudSat[J]. Adv Atmos Sci, 31(4):926-937.
[26]Westwater E R, 1978. The accuracy of water vapor and cloud liquid determination by dual-frequency ground-based microwave radiometry[J]. Radio Science, 13(4):677-685.
[27]Yao Z, Li J, Han H J, et al, 2012. Asian dust height and infrared optical depth retrievals over land from hyperspectral longwave infrared radiances[J]. J Geophys Res, 117(D19):D19202. DOI:10. 1029/2012JD017799.
[28]Feng W W, Yao Z G, Han Z G, et al, 2009. Analysis of the cloud liquid water path from satellite-borne millimeter wave cloud Radar[J]. Journal of PLA University of Science and Technology (Natural Science Edition), 10(Suppl1):95-102.<br/>冯伟伟, 姚志刚, 韩志刚, 等, 2009.星载毫米波云雷达反演液态水云含水量的算法性能分析[J].解放军理工大学学报(自然科学版), 10(增刊1):95-102.
[29]Jiang F, Wei C, Lei H C, et al, 2004. Measurement of column cloud liquid water content by airborne upward-looking microwave radiometer (Ⅱ):Retrieval method[J]. Plateau Meteor, 23(1):33-39.<br/>江芳, 魏重, 雷恒池, 等, 2004.机载微波辐射计测云中液态水含量(Ⅱ):反演方法[J].高原气象, 23(1):33-39.
[30]Liu L P, Zhou M, 2016. Characteristics of bright band and automatic detection algorithm with vertical pointed Ka band cloud Radar[J]. Plateau Meteor, 35 (3):734-744. DOI:10. 7522/j. issn. 1000-0534. 2014. 00160.<br/>刘黎平, 周淼, 2016.垂直指向的Ka波段云雷达观测的0℃层亮带自动识别及亮带的特征分析[J].高原气象, 35 (3):734-744.
[31]Peng L, Chen H B, Li B, 2011. An application of Fuzzy Logic Method to cloud hydrometeor classifications using the ARM WACR data[J]. Remote Sensing Technology and Application, 36(1):1-10.<br/>彭亮, 陈洪滨, 李柏, 2011.模糊逻辑法在3mm云雷达反演云中水凝物粒子相态中的应用[J].遥感技术与应用, 36(1):1-10.
[32]Peng L, Chen H B, Li B, 2012. A case study of deriving vertical airs velocity from 3-mm cloud radar[J]. Chinese J Atmos Sci, 36(1):1-10.<br/>彭亮, 陈洪滨, 李柏, 2012. 3 mm多普勒云雷达反演云内空气垂直速度的研究[J].大气科学, 36(1):1-10.
[33]Qiu Y J, Yang H W, Ni T, et al, 2012. Cloud property analysis by using DOE AMF measurements in Shouxian of China[J]. Trans Atmos Sci, 35(1):80-86.<br/>邱玉珺, 杨会文, 倪婷, 等, 2012.基于美国AMF寿县观测的云特性研究[J].大气科学学报, 35(1):80-86.
[34]Wang L, Li C C, Zhao Z L, et al, 2014. Application of 2D habit classification in cloud microphysics analysis[J]. Chinese J Atmos Sci, 38 (2):201-212.<br/>王磊, 李成才, 赵增亮, 等, 2014.二维粒子形状分类技术在云微物理特征分析中的应用[J].大气科学, 38 (2):201-212.
[35]Wang S H, Han Z G, Yao Z G, et al, 2011. Analysis on cloud vertical structure over China and its neighborhood based on CloudSat Data[J]. Plateau Meteor, 30 (1):38-52.<br/>王帅辉, 韩志刚, 姚志刚, 等, 2011.基于CloudSat资料的中国及周边地区云垂直结构统计分析[J].高原气象, 30 (1):38-52.
[36]Wu J X, Wei M, Zhou J, 2014. Simulated calculation of backscattering characteristics of hexagonal ice crystals with 94 GHz Radar[J]. Plateau Meteor, 33(1):252-260. DOI:10. 7522/j. issn. 1000-0534. 2013. 00003.<br/>吴举秀, 魏鸣, 周杰, 2014.六角形冰晶的94 GHz毫米波后向散射特性的模拟计算分析[J].高原气象, 33(1):252-260.
[37]Yao Z Y, Wang G H, You L G, et al, 2001. Microwave remote sensing of cloud liquid water path over Shouxiang[J]. J Appl Meteor Sci, 12(Suppl1):88-95.<br/>姚展予, 王广河, 游来光, 等, 2001.寿县地区云中液态水含量的微波遥感[J].应用气象学报, 12(增刊1):88-95.
[38]Ye P L, Wang T H, Shang K Z, et al, 2014. Analysis of cloud vertical structure over western China based on active satellite data[J]. Plateau Meteor, 33(4):977-987. DOI:10. 7522/j. issn. 1000-0534. 2013. 00158.<br/>叶培龙, 王天河, 尚可政, 等, 2014.基于卫星资料的中国西部地区云垂直结构分析[J].高原气象, 33(4):977-987.
[39]Zhang Y P, Zhang W X, Lü D R, et al, 2014. Cloud top heights measured by METOP-A IASI Instrument compared with ground-based cloud radar[J]. Chinese J Atmos Sci, 38 (5):874-884.<br/>张艳品, 章文星, 吕达仁, 等, 2014.卫星(IASI探测仪)观测云顶高与地基云雷达观测的对比验证[J].大气科学, 38 (5):874-884.
[40]Zhang W X, Lü D R, 2012. Cloud base heights by ground based sky IR brightness temperature measurements compared with Cloud radar and Ceilometer in Shouxian[J]. Chinese J Atmos Sci, 36(4):657-672.<br/>章文星, 吕达仁, 2012.地基热红外云高观测与云雷达及激光云高仪的相互对比[J].大气科学, 36(4):657-672.
Options
文章导航

/

〈 〉

本系统由北京玛格泰克科技发展有限公司设计开发 技术支持：support@magtech.com.cn