Liu Jian, Zhang Wenjian, Zhu Yuanjing, et al. Case study on cloud properties of heavy rainfall based upon satellite data. J Appl Meteor Sci, 2007, 18(2): 158-164.
Citation: Liu Jian, Zhang Wenjian, Zhu Yuanjing, et al. Case study on cloud properties of heavy rainfall based upon satellite data. J Appl Meteor Sci, 2007, 18(2): 158-164.

Case Study on Cloud Properties of Heavy Rainfall Based upon Satellite Data

  • Received Date: 2006-04-20
  • Rev Recd Date: 2006-11-01
  • Publish Date: 2007-04-30
  • Heavy rainfall is one of meteorological disasters in China. Precipitation has complex spatial and temporal distribution. It is difficult to get 3 dimension information by regular observation method. Remote sensing is a kind of useful ways to monitor precipitation. Weather satellites have high space and time resolution which are becoming a kind of important measurements. Cloud is one of key factors to produce precipitation. To do research on heavy rainfall, it is needed to understand cloud properties well.It is important to investigate the relationship between clouds and strong precipitations and try to reveal kinds of cloud properties which can produce heavy rainfall by satellite data. Visible, infrared and microwave data of FY-1D, EOS and NOAA satellites are used to analyze cloud properties of the heavy rainfall case. Visible and infrared radiance data have high spatial resolution, and can be used to show the detailed property information of small convective cloud. But properties of cloud on visible and infrared channel don't have clear relationship with precipitation. In the atmosphere, rain particles have strongereffect than clouds on microwave. Rain particles also absorb and re-emit more radiance than cloud particles. Compared with visible and infrared data, microwave data can show the structure properties of strong precipitation cloud, although its spatial resolution is low. So it is very helpful to monitor 3 dimension properties of convective cloud if these different kinds of data can be combined together. Cloud phase, cloud optical thickness and cloud vertical structure are selected as analysis physical parameters. Using visible and infrared data, cloud phase and optical thickness can be retrieved. Microwave data can be directly obtained from NOAA/AMSU data. Precipitation data are also used to validate the analysis results.A heavy rainfall happens in Huaihe River drainage area from June 23 to 27, 2002. This precipitation process is selected to study the relationship between cloud properties and heavy precipitation. Combined data(cloud phase, cloud optical thickness, microwave data and surface precipitation data)are used. Case study shows that clouds are mainly made up of ice clouds or large water cloud particles with thick cloud optical thickness when heavy rain happens. When cloud optical thickness increases or cloud optical thickness maintains large value during 6 hours, strong precipitation occurs on the surface. There exists a good positive relationship between precipitation and cloud optical thickness. The stronger the precipitation, the thicker the cloud optical thickness, or the more precipitation, the larger optical thickness difference during 6 hours. Clouds with stable large optical thickness or with great optical thickness increase will produce strong precipitation on the surface during a period of time. Different microwave channel data show different information coming from different atmosphere layer. When heavy rain appears, different microwave channel data could show strong convective structure from low layer to high layer of atmosphere. Analysis results show that cloud properties of heavy rain are shown better when different kinds of satellite remote sensing data are combined together.
  • Fig. 1  Cloud phase images of FY-1D, EOS and NOAA on June 25, 2002

    (hourly precitiation r in situ is overlapped)

    Fig. 2  Retrieved cloud optical thickness images of FY-1D(a)and NOAA(b)

    (hourly precipitation r in stiu is overlapped)

    Fig. 3  The statistical relationship between precipitation and cloud optical thickness

    Fig. 4  Composed image of 6-hour cloud optical thickness change

    (red:retrieved NOAA cloud optical thickness; green:the difference between retrieved FY-1D and NOAA cloud optical thickness; blue:retrieved FY-1D cloud optical thickness; 6 h precipitation is overlapped)

    Fig. 5  Four microwave channel images of NOAA/AMSU-B on June 25, 2002

    Fig. 6  Brightness temperature distribution of pix els at 183. 3±1 GHz, 183.3±3 GHz, 183. 3±7 GHz和89 GHz along 116°E

    Fig. 7  Composed image containing NOAA16/AMSU 89 GHz and cloud optical thickness

    (hourly precipitation r in situ is overlapped)

    Table  1  Spectral properties and main purposes of AMSU-B

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    • Received : 2006-04-20
    • Accepted : 2006-11-01
    • Published : 2007-04-30

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