access icon openaccess Variation of multimodality in rainfall drop size distribution with wind speeds and rain rates

In the coming years, there will be more usage of the millimetre/sub-millimetre frequencies due to congestion of the lower frequencies. At these frequencies, precipitation greatly affects the quality of service, by attenuating signals, hence the need for a thorough study and understanding in order to design mitigation techniques for improved signal quality. Previous studies modelled rainfall data using mostly unimodal statistical distributions, which may not fit multimodality encountered in the data. This paper looks at the prediction of the number of modes, given rain rates and wind speeds by looking at the occurrence of multimodality in rainfall data captured at Chilbolton Observatory, southern England from 2003 to 2009. From the drop size distributions, it develops a novel model based on the Gaussian mixture model. This enables the multimodal distributions observed by various researchers to be modelled. It provides expressions for calculating model parameters as a function of rain rate, R (mm/h) and wind speed, W (m/s). The model parameters include number of modes N m , standard deviation σ 1 σ m of each mode along with corresponding means, μ 1μ m . The study concludes that multimodality exists, and the average number of modes tends to increase with increasing wind speeds and rain rates.

Inspec keywords: rain; Gaussian processes; wind

Other keywords: AD 2003 to 2009; signal quality; Gaussian mixture model; mitigation techniques; unimodal statistical distribution; millimetre-submillimetre frequencies; rainfall drop size distribution; Chilbolton Observatory; rain rates; southern England; multimodal distribution; wind speeds

Subjects: Winds and their effects in the lower atmosphere; Water in the atmosphere (humidity, clouds, evaporation, precipitation); Europe

References

    1. 1)
      • 28. Thurai, M., Bringi, V.N., Kennedy, P.C., et al: ‘Towards completing the rain drop size distribution spectrum: a case study involving 2D video disdrometer, droplet spectrometer, and polarimetric radar measurements in Greeley, Colorado’. AMS Conf. on Radar Meteorology, Norman, OK, USA, September 2015.
    2. 2)
    3. 3)
    4. 4)
      • 1. Weiwen, L., Diallo, B., Michelson, D.G.: ‘Fade slope analysis of Ka-band LEO satellite links’. IEEE 66th Vehicular Technology Conf. VTC-2007 Fall, 2007.
    5. 5)
      • 5. Levine, L.M.: ‘The distribution function of cloud and rain drops by sizes’, Dokl. Akad. Nauk., SSSR, 1954, 94, (6), pp. 10451048. (Translated by Assoc. Tech. Services Inc., East Orange, NJ) cited in Mueller, Eugene Albert: ‘Radar Cross Sections from Drop Size Spectra’, PhD thesis in Electrical Engineering, Graduate College of the University of Illinois, Urbana, IL, US, 1966.
    6. 6)
    7. 7)
      • 16. Ekerete, K.E., Hunt, F.H., Agnew, J.L., et al: ‘Multimodality in the rainfall drop size distribution in southern England’. Seventh EAI Int. Conf. on Wireless and Satellite Systems, (WiSATS 2015), Norcroft Centre, University of Bradford, Bradford, England, 6th–7th July 2015.
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
      • 8. Owolawi, P.: ‘Raindrop size distribution model for the prediction of rain attenuation in Durban’, Prog. Electromagn. Res., 2011, 7, (6), pp. 516523.
    13. 13)
    14. 14)
      • 13. McFarquhar, G.M.: ‘Raindrop size distribution and evolution’, in Testik, F.Y., Gebremichael, M. (eds.): ‘Rainfall: state of the science, (American Geophysical Union, Washington, DC, USA, Geophysical Monograph Series 191, 2010), pp. 4960, doi: 10.1029/2010GM000971.
    15. 15)
      • 17. Distromet Ltd.: ‘Disdrometer RD-80 instruction manual’ (Distromet Ltd, Basel, Switzerland, 2002).
    16. 16)
    17. 17)
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