Skip to main content
SpringerLink
Log in

A model for retrieval of dual linear polarization radar fields from model simulation outputs

  • Published:
Advances in Atmospheric Sciences Aims and scope Submit manuscript

Abstract

An algorithm for retrieving polarimetric variables from numerical model fields is developed. By using this technique, radar reflectivity at horizontal polarization, differential reflectivity, specific differential phase shift and correlation coefficients between the horizontal and vertical polarization signals at zero lag can be derived from rain, snow and hail contents of numerical model outputs. Effects of environmental temperature and the melting process on polarimetric variables are considered in the algorithm. The algorithm is applied to the Advanced Regional Prediction System (ARPS) model simulation results for a hail storm. The spatial distributions of the derived parameters are reasonable when compared with observational knowledge. This work provides a forward model for assimilation of dual linear polarization radar data into a mesoscale model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Balakrishnan, N., and D. S. Zrnic, 1990: Use of polarization to characterize precipitation and discriminate large hail.J. Atmos. Sci.,47, 1525–1540.

    Article  Google Scholar 

  • Brandes, E. A., A. V. Ryzhkov, and D. S. Zrnic, 2001: An evaluation of radar rainfall estimates from specific differential phase.J. Atmos. Oceanic Technol.,18, 363–375.

    Article  Google Scholar 

  • Brunkow, D., V. N. Bringi, P. Kennedy, and S. Rutledge, 2000: A description of the CSU-CHILL national radar facility.J. Atmos. Oceanic Technol.,17, 1596–1608.

    Article  Google Scholar 

  • Dixon, M., and G. Wiener, 1993: TITAN: Thunderstorm Identification, Tracking, Analysis, and Nowcasting-A radar-based methodology.J. Atmos. Oceanic Technol.,10, 785–797.

    Article  Google Scholar 

  • Doviak, R., and D. S. Zrnic, 1993:Doppler Radar and Weather Observation. Academic Press, 209–279.

  • Doviak, R., V. N. Bringi, A. Ryzhkov, A. Zahrai, and D. Zrnic, 2000: Consideration for polarimetric upgrades to WSR-88D radar.J. Atmos. Oceanic Technol.,17, 257–278.

    Article  Google Scholar 

  • Gorgucci, E., V. Chandrasekar, V. N. Bringi, and G. Scarchilli, 2002: Estimation of raindrop size distribution parameters from polarimetric radar measurements.J. Atmos. Sci.,59, 2373–2384.

    Article  Google Scholar 

  • Hodur, R. M., 1997: The Naval Research Laboratory’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS).Mon. Wea. Rev.,125, 1414–1430.

    Article  Google Scholar 

  • Hubbert, J. V., V. N. Bringi, and L. D. Carey, 1998: CSUCHILL polarimetric radar measurements from a severe hail storm in Eastern Colorado.J. Appl. Meteor.,37, 749–775.

    Article  Google Scholar 

  • Jameson, A. R., 1989: The interpretation and meteorological application of radar backscatter amplitude ratios at linear polarizations.J. Atmos. Oceanic Technol.,6, 908–919.

    Article  Google Scholar 

  • Klemp, J. B., and D. R. Durran, 1983: An upper boundary condition permitting internal gravity wave radiation in numerical mesoscale models.Mon. Wea. Rev.,111, 430–444.

    Article  Google Scholar 

  • Lin, Y. L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model.J. Appl. Meteor.,22, 1065–1092.

    Article  Google Scholar 

  • Liu, H. P., and V. Chandrasekar, 2000: Classification of hydrometeors based on polarimetric radar measurements: Development of fuzzy logic and neuro-fuzzy systems andin situ verification.J. Atmos. Oceanic Technol.,17, 140–164.

    Article  Google Scholar 

  • Marshall, J. S., and W. Palmer, 1948: The distribution of raindrops with size.J. Meteor.,5, 165–166.

    Google Scholar 

  • Nascimento, E. L., 2002: Dynamic Adjustment in an Idealized Numerically-Simulated Bow Echo. Ph. D dissertation, University of Oklahoma, 301pp.

  • Pierce, C. E., and P. J. Hardaker. 2000: GANDOLF: A system for generating automated nowcasts of convective precipitation.Meteor. Appl.,7, 341–360.

    Article  Google Scholar 

  • Qiu, C. J., and Q. Xu, 1992: A simple adjoint method of wind analysis for single-Doppler data.J. Atmos. Oceanic Technol.,9, 588–598.

    Article  Google Scholar 

  • Ryzhkov, A. V., and D. S. Zrnic, 1996: Assessment of rainfall measurement that uses specific differential phase.J. Appl. Meteor.,35, 2080–2090.

    Article  Google Scholar 

  • Ryzhkov, A. V., and D. S. Zrnic, 1998: Discrimination between Rain and Snow with a Polarimetric Radar.J. Appl. Meteoro.,37, 1228–1240.

    Article  Google Scholar 

  • Ryzhkov, A., and D. S. Zrnic, 2003: Discrimination between rain and snow with polarimetric NEXRAD radar. Preprints,31st Conference on Radar Meteorology, Seattle, WA, Amer. Meteor. Soc., 635–638.

  • Ryzhkov, A. V., D. S. Zrnic, and B. A. Grdon, 1998: Polarimetric method for ice water content determination.J. Appl. Meteor.,37, 125–134.

    Article  Google Scholar 

  • Sachidananda, M., and D. S. Zrnic, 1987: Rain rate estimates from differential polarization measurements.J. Atmos. Oceanic Technol.,4, 588–598.

    Article  Google Scholar 

  • Schuur, T., A. Ryzhkov, P. Heinselman, D. S. Zrnic, D. Burgess, and K. Scharfenberg, 2003: Observations and classification of echoes with polarimetric WSR88D radar. Report of National Severe Storm Laboratory, Norman, OK, 46pp.

  • Seliga, T. A., V. N. Bringi, and H. H. Al-Khatib, 1981: A preliminary study of comparative measurements of rainfall rate using the differential reflectivity radar technique and a raingauge network.J. Appl. Meteor.,20, 1362–1368.

    Article  Google Scholar 

  • Smith, P. L. Jr., C. G. Myers, and H. D. Orville, 1975: Radar reflectivity factor calculations in numerical cloud models using bulk parameterization of precipitation.J. Appl. Meteor.,14, 1156–1165.

    Article  Google Scholar 

  • Straka, J. M., D. S. Zrnic, and A. V. Ryzhkov, 2000: Bulk hydrometeor classification and quantification using polarimetric radar data: Synthesis of relations.J. Appl Meteor.,39, 1341–1372.

    Article  Google Scholar 

  • Sun, J., and N. A. Crook, 1997: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part I: Model development and simulated data experiments.J. Atmos. Sci.,54, 1642–1661.

    Article  Google Scholar 

  • Vivekanandan, J., V. N. Bringi, M. Hagen, and P. Meischner, 1994: Polarimetric radar studies of atmospheric ice particles.IEEE Trans. Geosci. Remote Sens.,32, 1–10

    Article  Google Scholar 

  • Vivekanandan, J., S. M. Ellis, R. Oye, D. S. Zrnic, A. V. Ryzhkov, and J. Straka, 1999: Cloud microphysics retrieval using S-band dual-polarization radar measurements.Bull. Amer. Meteor. Soc.,80, 381–388.

    Article  Google Scholar 

  • Vivekanandan, J., R. Raghavan, and V. N. Bringi, 1993: Polarimetric radar modeling of mixtures of precipitation particles.IEEE Trans. Geosci. Remote Sens.,31, 1017–1030.

    Article  Google Scholar 

  • Wilson, J. W., and C. K. Mueller, 1993: Nowcasts of thunderstorm initiation and evolution.Wea. Forecasting,8, 113–131

    Article  Google Scholar 

  • Xue, M., K. K. Droegemeier, and V. Wong, 1995: The Advanced Regional Prediction System and real-time storm weather prediction. Preprints,International Workshop on Limited-Area and Variable Resolution Models, Beijing, China, WMO, 7pp.

    Google Scholar 

  • Xu, Q., H. D. Gu, and C. J. Qiu, 2001: Simple adjoint retrievals of wet-microburst winds and gust-front winds from single-Doppler radar data.J. Appl. Meteor.,40, 1485–1499.

    Article  Google Scholar 

  • Zrnic, D. S., and A. V. Ryzhkov, 1998: Observations of insects and birds with a polarimetric radar.IEEE Trans. Geosci. Remote Sens.,36, 661–668.

    Article  Google Scholar 

  • Zrnic, D. S., N. Balakrishnan, C. L. Ziegler, V. N. Bringi, K. Aydin, and T. Matejka, 1993: Polarimetric signatures in the stratiform region of a mesoscale convective system.J. Appl. Meteor.,32, 678–693.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, 100081, Beijing

    Liu Liping

  2. National Severe Storm Laboratory, National Oceanic and Atmospheric Administration, Norman, Oklahoma, USA

    Qin Xu

  3. The Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma, USA

    Liu Liping, Zhang Pengfei & Liu Shun

  4. The Center for Analysis Prediction of Storms, University of Oklahoma, Norman, USA

    Kong Fanyou

Authors
  1. Liu Liping
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhang Pengfei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qin Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kong Fanyou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Liu Shun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Liu Liping.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liping, L., Pengfei, Z., Xu, Q. et al. A model for retrieval of dual linear polarization radar fields from model simulation outputs. Adv. Atmos. Sci. 22, 711–719 (2005). https://doi.org/10.1007/BF02918714

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02918714

Key words

Search

Navigation