• Brandes, E. A., Zhang G. , and Vivekanandan J. , 2002: Experiments in rainfall estimation with a polarimetric radar in a subtropical environment. J. Appl. Meteor., 41 , 674685.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bringi, V. N., and Chandrasekar V. , 2001: Polarimetric Doppler Weather Radar: Principles and Applications. Cambridge University Press, 648 pp.

    • Search Google Scholar
    • Export Citation
  • Bringi, V. N., Chandrasekar V. , and Xiao R. , 1998: Raindrop axis ratios and size distributions in Florida rainshafts: An assessment of multiparameter radar algorithms. IEEE Trans. Geosci. Remote Sens., 36 , 703715.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bringi, V. N., Wang Y. , and Hubbert J. , 2002: Polarimetric data evaluation in severe storms using two research dual-polarized radars. Proc. Second European Conf. on Radar Meteorology, Delft, Netherlands, ERAD, 73–77.

    • Search Google Scholar
    • Export Citation
  • Brotzge, J., Westbrook D. , Brewster K. , Hondl K. , and Zink M. , 2005: The meteorological command and control structure of a dynamic, collaborative, automated radar network. Preprints, 21st Int. Conf. on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, San Diego, CA, Amer. Meteor. Soc., 19.15. [Available online at http://ams.confex.com/ams/pdfpapers/85177.pdf].

    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., Cooper W. A. , and Bringi V. , 1988: Axis ratios and oscillations of raindrops. J. Atmos. Sci., 45 , 13231333.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., Meneghini R. , and Zawadzki I. , 2003: Global and local measurement of precipitation by radars. Radar and Atmospheric Science: A Collection of Essays in Honor of David Atlas, Meteor. Monogr., No. 30, Amer. Meteor. Soc., 215–236.

    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., Lim S. , Bharadwaj N. , Li W. , McLaughlin D. , Bringi V. N. , and Gorgucci E. , 2004: Principles of networked weather radar operation at attenuating frequencies. Proc. Third European Conf. on Radar Meteorology, Visby, Sweden, ERAD, 109–114.

    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., McLaughlin D. , Brotzge J. , Zink M. , Philips B. , and Wang Y. , 2008: Distributed collaborative adaptive radar network: Preliminary results from the CASA IP1 testbed. 2008 IEEE Radar Conf., Rome, Italy, IEEE, doi:10.1109/RADAR.2008.4721125.

    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., Willie D. , Wang Y. , Lim S. , and McLaughlin D. , 2009: Attenuation margin requirements in a networked radar system for observation of precipitation. IEEE Int. Geoscience and Remote Sensing Symp., IGARSS 2009, Vol. 2, Cape Town, South Africa, IEEE, 957–959.

    • Search Google Scholar
    • Export Citation
  • Chandrasekar, V., and Coauthors, 2010: The CASA IP1 test-bed after 5 years operation: Accomplishments, breakthroughs, challenges and lessons learned. Sixth European Conf. on Radar Meteorology, Sibiu, Romania, in press.

    • Search Google Scholar
    • Export Citation
  • Cifelli, R., Kennedy P. , Chandrasekar V. , Nesbitt S. W. , Rutledge S. A. , and Carey L. D. , 2005: Polarimetric rainfall retrievals using blended algorithms. Preprints, 32nd Conf. on Radar Meteorology, Albuquerque, NM, Amer. Meteor. Soc., 9R.1.

    • Search Google Scholar
    • Export Citation
  • Giangrande, S. E., and Ryzhkov A. V. , 2008: Estimation of rainfall based on the results of polarimetric echo classification. J. Appl. Meteor. Climatol., 47 , 24452462.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gorgucci, E., Scarchilli G. , and Chandrasekar V. , 1999: Specific differential phase estimation in the presence of nonuniform rainfall medium along the path. J. Atmos. Oceanic Technol., 16 , 16901697.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gorgucci, E., Scarchilli G. , Chandrasekar V. , and Bringi V. N. , 2001: Rainfall estimation from polarimetric radar measurements: Composite algorithms immune to variability in raindrop shape–size relation. J. Atmos. Oceanic Technol., 18 , 17731786.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gorgucci, E., Chandrasekar V. , Bringi V. N. , and Scarchilli G. , 2002: Estimation of raindrop size distribution parameters from polarimetric radar measurements. J. Atmos. Sci., 59 , 23732384.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Junyent, F., and Chandrasekar V. , 2009: Theory and characterization of weather radar networks. J. Atmos. Oceanic Technol., 26 , 474491.

  • Maki, M., and Coauthors, 2008: X-band polarimetric radar network in the Tokyo Metropolitan area—X-NET. Proc. Fifth European Conf. on Radar Meteorology, Helsinki, Finland, ERAD, 3.7. [Available online at http://erad2008.fmi.fi/proceedings/extended/erad2008-0020-extended.pdf].

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 2010: Evaluating polarimetric X-band radar rainfall estimators during HMT. J. Atmos. Oceanic Technol., 27 , 122134.

  • Matrosov, S. Y., Clark K. A. , Martner B. E. , and Tokay A. , 2002: X-band polarimetric radar measurements of rainfall. J. Appl. Meteor., 41 , 941952.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., Cifelli R. , Kennedy P. C. , Nesbitt S. W. , Rutledge S. A. , Bringi V. N. , and Martner B. E. , 2006: A comparative study of rainfall retrievals based on specific differential phase shifts at X- and S-band radar frequencies. J. Atmos. Oceanic Technol., 23 , 952963.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McLaughlin, D., and Coauthors, 2009: Short-wavelength technology and the potential for distributed networks of small radar systems. Bull. Amer. Meteor. Soc., 90 , 17971817.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • National Research Council, 2005: Flash Flood Forecasting over Complex Terrain: With an Assessment of the Sulphur Mountain NEXRAD in Southern California. National Academy Press, 206 pp.

    • Search Google Scholar
    • Export Citation
  • National Research Council, 2008: Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. National Academy Press, 250 pp.

    • Search Google Scholar
    • Export Citation
  • Ogden, F., Sharif H. , Senarath S. , Smith J. , Baeck M. , and Richardson J. , 2000: Hydrologic analysis of the Fort Collins, Colorado, flash flood of 1997. J. Hydrol., 228 , 82100.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Park, S-G., Maki M. , Iwanami K. , Bringi V. N. , and Chandrasekar V. , 2005: Correction of radar reflectivity and differential reflectivity for rain attenuation at X band. Part II: Evaluation and application. J. Atmos. Oceanic Technol., 22 , 16331655.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Philips, B., and Coauthors, 2007: Integrating end user needs into system design and operation: The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). Preprints, 16th Conf. on Applied Climatology, San Antonio, TX, Amer. Meteor. Soc., 3.14. [Available online at http://ams.confex.com/ams/pdfpapers/119996.pdf].

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., and Zrnic D. , 1998: Beamwidth effects on the differential phase measurements of rain. J. Atmos. Oceanic Technol., 15 , 624634.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., Giangrande S. E. , and Schuur T. J. , 2005: Rainfall estimation with a polarimetric prototype of WSR-88D. J. Appl. Meteor., 44 , 502515.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sachidananda, M., and Zrnic D. S. , 1986: Differential propagation phase shift and rainfall rate estimation. Radio Sci., 21 , 235247.

  • Thurai, M., and Bringi V. N. , 2005: Drop axis ratios from a 2D video disdrometer. J. Atmos. Oceanic Technol., 22 , 966978.

  • Vieux, B. E., and Bedient P. B. , 2004: Assessing urban hydrologic prediction accuracy through event reconstruction. J. Hydrol., 299 , 217236.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Y., and Chandrasekar V. , 2009: Algorithm for estimation of the specific differential phase. J. Atmos. Oceanic Technol., 26 , 25692582.

    • Search Google Scholar
    • Export Citation
  • Willie, D., Li W. , Wang Y. , and Chandrasekar V. , 2006: Attenuation statistics for X-band radar design. Proc. IEEE Int. Geoscience and Remote Sensing Symp., IGARSS 2006, Denver, CO, IEEE, 2647–2650.

    • Search Google Scholar
    • Export Citation
  • Zink, M., Lyons E. , Westbrook D. , Pepyne D. , Pilips B. , Kurose J. , and Chandrasekar V. , 2008: Meteorological command & control: Architecture and performance evaluation. Proc. IEEE Int. Geoscience and Remote Sensing Symp., IGARSS 2008, Vol. 5, Boston, MA, IEEE, 152–155.

    • Search Google Scholar
    • Export Citation
  • Zrnić, D., and Ryzhkov A. , 1996: Advantages of rain measurements using specific differential phase. J. Atmos. Oceanic Technol., 13 , 454464.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 474 308 12
PDF Downloads 459 305 14

Quantitative Precipitation Estimation in the CASA X-band Dual-Polarization Radar Network

View More View Less
  • 1 Colorado State University, Fort Collins, Colorado
Restricted access

Abstract

This paper presents the sensing aspects and performance evaluation of the quantitative precipitation estimation (QPE) system in an X-band dual-polarization radar network developed by the Collaborative Adaptive Sensing of the Atmosphere (CASA) Engineering Research Center. CASA’s technology enables precipitation observation close to the ground and QPE is one of the important applications. With expanding urbanization all over the world, vulnerability to floods has increased from intense rainfall such as urban flash floods. The QPE products that are derived at high spatiotemporal resolution, which is enabled by the deployment of a dense radar network, have the potential to improve the prediction of flash-flooding threats when coupled with hydrological models. Derivation of QPE from radar observations is a challenging process, in which the use of dual-polarization radar variables is advantageous. At X band, the specific differential propagation phase (Kdp) between the orthogonal linear polarization states is particularly appealing. The Kdp field is robustly acquired using an adaptive estimation method, and a simple R(Kdp) relation is used to perform precipitation estimation in this X-band radar network. Radar observations and QPE from multiyear field experiments are used to demonstrate the performance of rainfall estimation from the single-parameter Kdp-based rainfall product. The operational feasibility of radar QPE using an X-band radar network is critically assessed.

Corresponding author address: Yanting Wang, Campus Delivery 1373, Colorado State University, Fort Collins, CO 80523. Email: ytwang@engr.colostate.edu

Abstract

This paper presents the sensing aspects and performance evaluation of the quantitative precipitation estimation (QPE) system in an X-band dual-polarization radar network developed by the Collaborative Adaptive Sensing of the Atmosphere (CASA) Engineering Research Center. CASA’s technology enables precipitation observation close to the ground and QPE is one of the important applications. With expanding urbanization all over the world, vulnerability to floods has increased from intense rainfall such as urban flash floods. The QPE products that are derived at high spatiotemporal resolution, which is enabled by the deployment of a dense radar network, have the potential to improve the prediction of flash-flooding threats when coupled with hydrological models. Derivation of QPE from radar observations is a challenging process, in which the use of dual-polarization radar variables is advantageous. At X band, the specific differential propagation phase (Kdp) between the orthogonal linear polarization states is particularly appealing. The Kdp field is robustly acquired using an adaptive estimation method, and a simple R(Kdp) relation is used to perform precipitation estimation in this X-band radar network. Radar observations and QPE from multiyear field experiments are used to demonstrate the performance of rainfall estimation from the single-parameter Kdp-based rainfall product. The operational feasibility of radar QPE using an X-band radar network is critically assessed.

Corresponding author address: Yanting Wang, Campus Delivery 1373, Colorado State University, Fort Collins, CO 80523. Email: ytwang@engr.colostate.edu

Save