DOI QR코드

DOI QR Code

Comparison of Cloud Top Height Observed by a Ka-band Cloud Radar and COMS

Ka-band 구름레이더와 천리안위성으로 관측된 운정고도 비교

  • Oh, Su-Bin (Forecast Research Laboratory, National Institute of Meteorological Research, KMA) ;
  • Won, Hye Young (Forecast Research Laboratory, National Institute of Meteorological Research, KMA) ;
  • Ha, Jong-Chul (Forecast Research Laboratory, National Institute of Meteorological Research, KMA) ;
  • Chung, Kwan-Young (Forecast Research Laboratory, National Institute of Meteorological Research, KMA)
  • 오수빈 (기상청 국립기상연구소 예보연구과) ;
  • 원혜영 (기상청 국립기상연구소 예보연구과) ;
  • 하종철 (기상청 국립기상연구소 예보연구과) ;
  • 정관영 (기상청 국립기상연구소 예보연구과)
  • Received : 2013.11.09
  • Accepted : 2013.12.17
  • Published : 2014.03.31

Abstract

This study provides a comparative analysis of cloud top heights observed by a Ka-band cloud radar and the Communication, Ocean and Meteorological Satellite (COMS) at Boseong National Center for Intensive Observation of severe weather (NCIO) from May 25, 2013 (1600 UTC) to May 27. The rainfall duration is defined as the period of rainfall from start to finish, and the no rainfall duration is defined as the period other than the rainfall duration. As a result of the comparative analysis, the cloud top heights observed by the cloud radar have been estimated to be lower than that observed by the COMS for the rainfall duration due to the signal attenuation caused by raindrops. The stronger rainfall intensity gets, the more the difference grows. On the other hand, the cloud top heights observed by the cloud radar have been relatively similar to that observed by the COMS for the no rainfall duration. In this case, the cloud radar can effectively detect cloud top heights within the range of its observation. The COMS indicates the cloud top heights lower than the actual ones due to the upper thin clouds under the influence of ground surface temperature. As a result, the cloud radar can be useful in detecting cloud top heights when there are no precipitation events. The COMS data can be used to correct the cloud top heights when the radar gets beyond the valid range of observation or there are precipitation events.

Keywords

References

  1. Ahlgrimm, M., and R. Forbes, 2013: Improving the representation of low clouds and drizzle in the ECMWF model based on ARM observations from the Azores. Mon. Wea. Rev., doi: http://dx.doi.org/10.1175/MWRD-13-00153.1.
  2. Bodas-Salcedo, A., M. J. Webb, M. E. Brooks, M. A. Ringer, K. D. Williams, S. F. Milton, and D. R. Wilson, 2008: Evaluating cloud systems in the Met Office global forecast model using simulated CloudSat radar reflectivities. J. Geophys. Res., 113, D00A13.
  3. Bouniol, D., and Coauthors, 2010: Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models. J. Appl. Meteor. Climatol., 49, 1971-1991. https://doi.org/10.1175/2010JAMC2333.1
  4. Choi, Y.-S., C.-H. Ho, M.-H. Ahn, and Y.-M. Kim, 2007: An exploratory study of cloud remote sensing capabilities of the communication, ocean and meteorological satellite (COMS) imagery. Int. J. Remote Sens., 28, 4715-4732. https://doi.org/10.1080/01431160701264235
  5. Choi, Y.-S., and C.-H. Ho, 2009: Validation of the cloud property retrievals from the MTSAT-1R imagery using MODIS observations. Int. J. Remote Sens., 30, 5935-5958. https://doi.org/10.1080/01431160902791887
  6. Gerard, L., J.-M. Piriou, R. Brozkova, and J.-F. Geleyn, 2009: Cloud and precipitation parameterization in a meso-gamma-scale operational weather prediction model. Mon. Wea. Rev., 137, 3960-3977. https://doi.org/10.1175/2009MWR2750.1
  7. Hobbs, P. V., N. T. Funk, R. R. Weiss, J. D. Locatelli, and K. R. Biswas, 1985: Evaluation of a 35 GHz radar for cloud physics research. J. Atmos. Oceanic Technol., 2, 35-48. https://doi.org/10.1175/1520-0426(1985)002<0035:EOAGRF>2.0.CO;2
  8. Hollars, S., Q. Fu, J. Comstock, and T. Ackerman, 2004: Comparison of cloud-top height retrievals from groundbased 35 GHz MMCR and GMS-5 satellite observations at ARM TWP Manus site. Atmos. Res., 72, 169-186. https://doi.org/10.1016/j.atmosres.2004.03.015
  9. Jakob, C., R. Pincus, C. Hannay, and K.-M. Xu, 2004: Use of cloud radar observations for model evaluation: A probabilistic approach. J. Geophys. Res., 109, D03202.
  10. Kalesse, H., and P. Kollias, 2013: Climatology of high cloud dynamics using profiling ARM Doppler radar observations. J. Climate, 26, 6340-6359. https://doi.org/10.1175/JCLI-D-12-00695.1
  11. Kneifel, S., M. Maahn, G. Peters, and C. Simmer, 2011: Observation of snowfall with a low-power FM-CW K-band radar (Micro Rain Radar). Meteor. Atmos. Phys., 113, 75-87. https://doi.org/10.1007/s00703-011-0142-z
  12. Kobayashi, F., T. Takano, and T. Takemura, 2011: Isolated cumulonimbus initiation observed by 95-GHz FMCW radar, X-band radar, and photogrammetry in the Kanto region, Japan. SOLA, 7, 125-128. https://doi.org/10.2151/sola.2011-032
  13. Kollias, P., G. G. Tselioudis, and B. A. Albrecht, 2007: Cloud climatology at the Southern Great Plains and the layer structure, drizzle, and atmospheric modes of continental stratus. J. Geophys. Res., 112, D09116.
  14. Krofli, R. A., and R. D. Kelly, 1996: Meteorological research applications of MM-wave radar. Meteor. Atmos. Phys., 59, 105-121. https://doi.org/10.1007/BF01032003
  15. Lhermitte, R., 1990: Attenuation and scattering of millimeter wavelength radiation by clouds and precipitation. J. Atmos. Ocean. Technol., 7, 464-479. https://doi.org/10.1175/1520-0426(1990)007<0464:AASOMW>2.0.CO;2
  16. Lopez, P., 2002: Implementation and validation of a new prognostic large-scale cloud and precipitation scheme for climate and data-assimilation purposes. Quart. J. Roy. Meteor. Soc., 128, 229-258. https://doi.org/10.1256/00359000260498879
  17. Mace G. G., C. Jakob, and K. P. Moran, 1998: Validation of hydrometeor occurrence predicted by the ECMWF model using millimeter wave radar data. Geophys. Res. Lett., 25, 1645-1648. https://doi.org/10.1029/98GL00845
  18. METRI/KMA, 2009: Development of meteorological data processing system of communication, ocean and meteorological satellite. pp 846.
  19. O'Connor, E. J., R. J. Hogan, and A. J. Illingworth, 2005: Retrieving stratocumulus drizzle parameters using Doppler radar and lidar. J. Appl. Meteor., 44, 14-27. https://doi.org/10.1175/JAM-2181.1
  20. Polkinghorne, R., and T. Vukicevic, 2011: Data assimilation of cloud-affected radiances in a cloud-resolving Model. Mon. Wea. Rev., 139, 755-773. https://doi.org/10.1175/2010MWR3360.1
  21. Polkinghorne, R., and T. Vukicevic, and K. F. Evans, 2010: Validation of cloud-resolving model background data for cloud data assimilation. Mon. Wea. Rev., 138, 781-795. https://doi.org/10.1175/2009MWR3012.1
  22. Sakurai, N., K. Iwanami, T. Maesaka, S.-I. Suzuki, S. Shimizu, R. Misumi, D.-S. Kim, and M. Maki, 2012: Case study of misoscale convective echo behavior associated with cumulonimbus development observed by ka-band Doppler radar in the Kanto region, Japan. SOLA, 8, 107-110. https://doi.org/10.2151/sola.2012-027
  23. Stokes, G. M., and S. E. Schwartz, 1994: The Atmospheric Radiation Measurement (ARM) program: Programmatic background and design of the cloud and radiation test bed. Bull. Amer. Meteor. Soc., 75, 1201-1221. https://doi.org/10.1175/1520-0477(1994)075<1201:TARMPP>2.0.CO;2
  24. Syrett, W. J., B. A. Albrecht, and E. E. Clothiaux, 1996: Vertical cloud structure in a midlatitude cyclone from a 94-GHz radar. Mon. Wea. Rev., 123, 3393-3407.
  25. Weisz, E., J. Li, W. P. Menzel, A. K. Heidinger, B. H. Kahn, and C. Y. Liu, 2007: Comparison of AIRS, MODIS, CloudSat and CALIPSO cloud top height retrievals. Geophys. Res. Lett., 34, L17811. https://doi.org/10.1029/2007GL030676
  26. Yoshida, Y., S. Asano, and K. Iwanami, 2006: Retrieval of microphysical properties of water, ice, and mixedphase cloud using a triple-wavelength radar and microwave radiometer. J. Meteor. Soc. Japan., 84, 1005-1031. https://doi.org/10.2151/jmsj.84.1005
  27. Zhong, L., L. Liu, M. Deng, and X. Zhou, 2012: Retrieving microphysical properties and air motion of cirrus clouds based on the Doppler moments method using cloud radar. Adv. Atmos. Sci., 29, 611-622. https://doi.org/10.1007/s00376-011-0112-x
  28. Zhong, L., L. Liu, M. Deng, S. Feng, R. Ge, and Z. Zhang, 2011: A 35-GHz polarimetric Doppler radar and Its application for observing clouds associated with typhoon Nuri. Adv. Atmos. Sci., 28, 945-956. https://doi.org/10.1007/s00376-010-0073-5

Cited by

  1. -LWC relationship using Ka-band cloud radar and a microwave radiometer vol.25, pp.3, 2018, https://doi.org/10.1002/met.1710
  2. Verification and correction of cloud base and top height retrievals from Ka-band cloud radar in Boseong, Korea vol.33, pp.1, 2016, https://doi.org/10.1007/s00376-015-5058-y
  3. Rain‐rate estimation algorithm using signal attenuation of Ka‐band cloud radar pp.1469-8080, 2020, https://doi.org/10.1002/met.1825