Editorial Type:
Article
Article Type:
Research Article

Understanding Radar Refractivity: Sources of Uncertainty

David Bodine * School of Meteorology, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Dan Michaud * School of Meteorology, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Robert D. Palmer * School of Meteorology, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Pamela L. Heinselman NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma

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Jerry Brotzge Center for Analysis and Prediction of Storms, Norman, Oklahoma

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Nick Gasperoni * School of Meteorology, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Boon Leng Cheong Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Ming Xue Center for Analysis and Prediction of Storms, Norman, Oklahoma

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Jidong Gao Center for Analysis and Prediction of Storms, Norman, Oklahoma

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Print Publication:
01 Dec 2011
DOI:
https://doi.org/10.1175/2011JAMC2648.1
Page(s):
2543–2560
Restricted access

Abstract

This study presents a 2-yr-long comparison of Weather Surveillance Radar-1988 Doppler (WSR-88D) refractivity retrievals with Oklahoma Mesonetwork (“Mesonet”) and sounding measurements and discusses some challenges to implementing radar refractivity operationally. Temporal and spatial analyses of radar refractivity exhibit high correlation with Mesonet data; however, periods of large refractivity differences between the radar and Mesonet are observed. Several sources of refractivity differences are examined to determine the cause of large refractivity differences. One source for nonklystron radars includes magnetron frequency drift, which can introduce errors up to 10 N-units if the frequency drift is not corrected. Different reference maps made at different times can “shift” refractivity values. A semiautomated method for producing reference maps is presented, including trade-offs for making reference maps under different conditions. Refractivity from six Mesonet stations within the clutter domain of the Oklahoma City, Oklahoma, WSR-88D (KTLX) is compared with radar refractivity retrievals. The analysis revealed that the six Mesonet stations exhibited a prominent diurnal trend in differences between radar and Mesonet refractivity measurements. The diurnal range of the refractivity differences sometimes exceeded 20 or 30 N-units in the warm season, which translated to a potential dewpoint temperature difference of several degrees Celsius. A seasonal analysis revealed that large refractivity differences primarily occurred during the warm season when refractivity is most sensitive to moisture. Ultimately, the main factor in determining the magnitude of the differences between the two refractivity platforms is the vertical gradient of refractivity because of the difference in observation height between the radar and a surface station.

Corresponding author address: Dr. Robert Palmer, School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd., Suite 5900, Norman, OK 73072. E-mail: rpalmer@ou.edu

Abstract

This study presents a 2-yr-long comparison of Weather Surveillance Radar-1988 Doppler (WSR-88D) refractivity retrievals with Oklahoma Mesonetwork (“Mesonet”) and sounding measurements and discusses some challenges to implementing radar refractivity operationally. Temporal and spatial analyses of radar refractivity exhibit high correlation with Mesonet data; however, periods of large refractivity differences between the radar and Mesonet are observed. Several sources of refractivity differences are examined to determine the cause of large refractivity differences. One source for nonklystron radars includes magnetron frequency drift, which can introduce errors up to 10 N-units if the frequency drift is not corrected. Different reference maps made at different times can “shift” refractivity values. A semiautomated method for producing reference maps is presented, including trade-offs for making reference maps under different conditions. Refractivity from six Mesonet stations within the clutter domain of the Oklahoma City, Oklahoma, WSR-88D (KTLX) is compared with radar refractivity retrievals. The analysis revealed that the six Mesonet stations exhibited a prominent diurnal trend in differences between radar and Mesonet refractivity measurements. The diurnal range of the refractivity differences sometimes exceeded 20 or 30 N-units in the warm season, which translated to a potential dewpoint temperature difference of several degrees Celsius. A seasonal analysis revealed that large refractivity differences primarily occurred during the warm season when refractivity is most sensitive to moisture. Ultimately, the main factor in determining the magnitude of the differences between the two refractivity platforms is the vertical gradient of refractivity because of the difference in observation height between the radar and a surface station.

Corresponding author address: Dr. Robert Palmer, School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd., Suite 5900, Norman, OK 73072. E-mail: rpalmer@ou.edu
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Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Acevedo, O. C., and D. R. Fitzjarrald, 2001: The early evening surface-layer transition: Temporal and spatial variability. J. Atmos. Sci., 58, 2650–2667.

    • Search Google Scholar
    • Export Citation

  • Barrios, A. E., 1994: A terrain parabolic equation model for propagation in the troposphere. IEEE Trans. Antennas Propag., 42, 90–98.

  • Bean, B. R., and E. J. Dutton, 1968: Radio Meteorology. Dover Publications, 435 pp.

  • Bodine, D., R. D. Palmer, B. L. Cheong, P. L. Heinselman, D. S. Michaud, and G. Zhang, 2009: Can high-resolution surface moisture fields be retrieved in supercells? Preprints, 34th Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., P6.3. [Available online at http://ams.confex.com/ams/34Radar/techprogram/paper_155541.htm.]

    • Search Google Scholar
    • Export Citation

  • Bodine, D., P. L. Heinselman, B. L. Cheong, R. D. Palmer, and D. Michaud, 2010: A case study on the impact of moisture variability on convection initiation using radar refractivity retrievals. J. Appl. Meteor. Climatol., 49, 1766–1778.

    • Search Google Scholar
    • Export Citation

  • Boudjabi, C., and J. Parent du Châtelet, 2008: Validation of refractivity measurements with magnetron transmitter radar. Proc. Fifth European Conf. on Radar Meteorology and Hydrology, Helsinki, Finland, IEEE, P3.8.

    • Search Google Scholar
    • Export Citation

  • Brock, F. V., K. C. Crawford, R. L. Elliott, G. W. Cuperus, S. J. Stadler, H. L. Johnson, and M. D. Eilts, 1995: The Oklahoma Mesonet: A technical overview. J. Atmos. Oceanic Technol., 12, 5–19.

    • Search Google Scholar
    • Export Citation

  • Cheong, B. L., and R. D. Palmer, 2009: Single-scan radar refractivity retrieval (SR3): Theory and simulations. Preprints, 34th Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., 8A.6. [Available online at http://ams.confex.com/ams/34Radar/techprogram/paper_155648.htm.]

    • Search Google Scholar
    • Export Citation

  • Cheong, B. L., R. D. Palmer, C. D. Curtis, T.-Y. Yu, D. S. Zrnić, and D. Forsyth, 2008: Refractivity retrieval using the phased-array radar: First results and potential for multimission operation. IEEE Trans. Geosci. Remote Sens., 46, 2527–2537.

    • Search Google Scholar
    • Export Citation

  • Crook, N. A., 1996: Sensitivity of moist convection forced by boundary layer processes to low-level thermodynamic fields. Mon. Wea. Rev., 124, 1767–1785.

    • Search Google Scholar
    • Export Citation

  • Dabberdt, W. F., and T. W. Schlatter, 1996: Research opportunities from emerging atmospheric observing and modeling capabilities. Bull. Amer. Meteor. Soc., 77, 305–323.

    • Search Google Scholar
    • Export Citation

  • Emanuel, K., and Coauthors, 1995: Report of the first prospectus development team of the U.S. Weather Research Program to NOAA and the NSF. Bull. Amer. Meteor. Soc., 76, 1194–1208.

    • Search Google Scholar
    • Export Citation

  • Fabry, F., 2004: Meteorological value of ground target measurements by radar. J. Atmos. Oceanic Technol., 21, 560–573.

  • Fabry, F., 2006: The spatial variability of moisture in the boundary layer and its effect on convective initiation: Project-long characterization. Mon. Wea. Rev., 134, 79–91.

    • Search Google Scholar
    • Export Citation

  • Fabry, F., C. Frush, I. Zawadzki, and A. Kilambi, 1997: On the extraction of near-surface index of refraction using radar phase measurements from ground targets. J. Atmos. Oceanic Technol., 14, 978–987.

    • Search Google Scholar
    • Export Citation

  • Fitzjarrald, D. R., and G. G. Lala, 1989: Hudson Valley fog environments. J. Appl. Meteor., 28, 1303–1328.

  • Gasperoni, N. A., M. Xue, R. D. Palmer, J. Gao, B. L. Cheong, and D. S. Michaud, 2009: Low-level moisture analysis from refractivity data derived from a network of S-band and X-band radars using ARPS 3DVAR. Preprints, 34th Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., 10B.1. [Available online at http://ams.confex.com/ams/34Radar/techprogram/paper_155971.htm.]

    • Search Google Scholar
    • Export Citation

  • Heinselman, P. L., B. L. Cheong, R. D. Palmer, D. Bodine, and K. Hondl, 2009: Radar refractivity retrievals in Oklahoma: Insights into operational benefits and limitations. Wea. Forecasting, 24, 1345–1361.

    • 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, 1797–1817.

    • Search Google Scholar
    • Export Citation

  • McPherson, R. A., and Coauthors, 2007: Statewide monitoring of the mesoscale environment: A technical update on the Oklahoma Mesonet. J. Atmos. Oceanic Technol., 24, 301–321.

    • Search Google Scholar
    • Export Citation

  • Michaud, D. S., 2010: Validation of radar estimation of low-level moisture fields using refractivity retrieval statistical analysis. M.S. thesis, School of Meteorology, University of Oklahoma, 127 pp.

    • Search Google Scholar
    • Export Citation

  • Montmerle, T., A. Caya, and I. Zawadzki, 2002: Short-term numerical forecasting of a shallow storms complex using bistatic and single-Doppler radar data. Wea. Forecasting, 17, 1211–1225.

    • Search Google Scholar
    • Export Citation

  • National Research Council, 1998: The Atmospheric Sciences: Entering the Twenty-First Century. National Academy Press, 373 pp.

  • Nicol, J., T. Darlington, A. Illingworth, K. Bartholemew, M. Kitchen, and E. Delaygue, 2008: Operational testing of radar refractivity retrieval for the UK radar network. Proc. Fifth European Conf. on Radar Meteorology and Hydrology, Helsinki, Finland, IEEE, 2.6.

    • Search Google Scholar
    • Export Citation

  • Park, S., and F. Fabry, 2010: Simulation and interpretation of the phase data used by the radar refractivity retrieval algorithm. J. Atmos. Oceanic Technol., 27, 1286–1301.

    • Search Google Scholar
    • Export Citation

  • Roberts, R. D., and Coauthors, 2008: REFRACTT 2006: Real-time retrieval of high-resolution, low-level moisture fields from operational NEXRAD and research radars. Bull. Amer. Meteor. Soc., 89, 1535–1548.

    • Search Google Scholar
    • Export Citation

  • Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic, 666 pp.

  • Sun, J., 2005: Convective-scale assimilation of radar data: Progress and challenges. Quart. J. Roy. Meteor. Soc., 131, 3439–3463.

  • Wakimoto, R. M., and H. V. Murphey, 2009: Analysis of a dryline during IHOP: Implications for convection initiation. Mon. Wea. Rev., 137, 912–936.

    • Search Google Scholar
    • Export Citation

  • Weckwerth, T. M., C. R. Pettet, F. Fabry, S. Park, M. A. LeMone, and J. W. Wilson, 2005: Radar refractivity retrieval: Validation and application to short-term forecasting. J. Appl. Meteor., 44, 285–300.

    • Search Google Scholar
    • Export Citation
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