Editorial Type:
Article
Article Type:
Research Article

Monitoring the Absolute Calibration of a Polarimetric Weather Radar

Michael Frech Meteorologisches Observatorium Hohenpeissenberg, Deutscher Wetterdienst, Hohenpeissenberg, Germany

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Martin Hagen Institut für Physik der Atmosphäre, DLR, Oberpfaffenhofen, Germany

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Theo Mammen Deutscher Wetterdienst, Hamburg, Germany

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Print Publication:
01 Mar 2017
DOI:
https://doi.org/10.1175/JTECH-D-16-0076.1
Page(s):
599–615
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Abstract

The absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant Z better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in smaller than 1 dB. The bias in is not captured with the classic one-point calibration, which is performed twice a day using a built-in test signal generator. This is attributed to the fact that the characterization of the transmit and receive path is not accurate enough. Solar interferences during the operational scanning are used to characterize the receiver. There, the bias found is small, about 0.2 dB, so that bias based on the comparison of the radar with external sensors is attributed to the transmit path. The representativeness of the disdrometer measurements are assessed using two additional disdrometers located within 200-m distance.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Michael Frech, michael.frech@dwd.de

Abstract

The absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant Z better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in smaller than 1 dB. The bias in is not captured with the classic one-point calibration, which is performed twice a day using a built-in test signal generator. This is attributed to the fact that the characterization of the transmit and receive path is not accurate enough. Solar interferences during the operational scanning are used to characterize the receiver. There, the bias found is small, about 0.2 dB, so that bias based on the comparison of the radar with external sensors is attributed to the transmit path. The representativeness of the disdrometer measurements are assessed using two additional disdrometers located within 200-m distance.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Michael Frech, michael.frech@dwd.de
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  • Adirosi, E., L. Baldini, N. Roberto, P. Gatlin, and A. Tokay, 2016: Improvement of vertical profiles of raindrop size distribution from micro rain radar using 2D video disdrometer measurements. Atmos. Res., 169, 404–415, doi:10.1016/j.atmosres.2015.07.002.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Atlas, D., 2002: Radar calibration: Some simple approaches. Bull. Amer. Meteor. Soc., 83, 1313–1316, doi:10.1175/1520-0477(2002)083<1313:RCSSA>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bringi, V. N., M. A. Rico-Ramirez, and M. Thurai, 2011: Rainfall estimation with an operational polarimetric C-band radar in the United Kingdom: Comparison with a gauge network and error analysis. J. Hydrometeor., 12, 935–954, doi:10.1175/JHM-D-10-05013.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bringi, V. N., M. Thurai, W. A. Petersen, and P. N. Gatlin, 2013: Using a network of 2D video disdrometers for external radar calibration of NASA’s S-band polarimetric radar. 36th Conf. on Radar Meteorology, Breckenridge, CO, Amer. Meteor. Soc., 10.3. [Available online at https://ams.confex.com/ams/36Radar/webprogram/Paper228161.html.]

  • Chandrasekar, V., L. Baldini, N. Bharadwaj, and P. Smith, 2015: Calibration procedures for global precipitation-measurements ground-validation radars. Radio Sci. Bull., 355, 45–73.

    • Search Google Scholar
    • Export Citation

  • Chen, Y., H. Liu, J. An, U. Görsdorf, and F. H. Berger, 2015: A field experiment on the small-scale variability of rainfall based on a network of Micro Rain Radars and rain gauges. J. Appl. Meteor. Climatol., 54, 243–255, doi:10.1175/JAMC-D-13-0210.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • de Moraes Frasson, R. P., L. Kindl da Cunha, and W. F. Krajewski, 2011: Assessment of the Thies optical disdrometer performance. Atmos. Res., 101, 237–255, doi:10.1016/j.atmosres.2011.02.014.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Diederich, M., A. Ryzhkov, C. Simmer, P. Zhang, and S. Trömel, 2015: Use of specific attenuation for rainfall measurement at X-band radar wavelengths. Part I: Radar calibration and partial beam blockage estimation. J. Hydrometeor., 16, 487–502, doi:10.1175/JHM-D-14-0066.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Doviak, R. J., and D. S. Zrnić, 2006: Doppler Radar and Weather Observations. Dover Publications Inc., 592 pp.

  • Frech, M., 2013: Monitoring the data quality of the new polarimetric weather radar network of the German Meteorological Service. 36th Conf. on Radar Meteorology, Breckenridge, CO, Amer. Meteor. Soc., 9B.3. [Available online at https://ams.confex.com/ams/36Radar/webprogram/Paper228472.html.]

  • Frech, M., and J. Steinert, 2015: Polarimetric radar observations during an orographic rain event. Hydrol. Earth Syst. Sci., 19, 1141–1152, doi:10.5194/hess-19-1141-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Frech, M., B. Lange, T. Mammen, J. Seltmann, C. Morehead, and J. Rowan, 2013: Influence of a radome on antenna performance. J. Atmos. Oceanic Technol., 30, 313–324, doi:10.1175/JTECH-D-12-00033.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Friedrich, K., S. Higgins, F. J. Masters, and C. R. Lopez, 2013: Articulating and stationary PARSIVEL disdrometer measurements in conditions with strong winds and heavy rainfall. J. Atmos. Oceanic Technol., 30, 2063–2080, doi:10.1175/JTECH-D-12-00254.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gage, K. S., C. R. Williams, P. E. Johnston, W. L. Ecklund, R. Cifelli, A. Tokay, and D. A. Carter, 2000: Doppler radar profilers as calibration tools for scanning radars. J. Appl. Meteor., 39, 2209–2222, doi:10.1175/1520-0450(2001)040<2209:DRPACT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gebremichael, M., and W. F. Krajewski, 2004: Assessment of the statistical characterization of small-scale rainfall variability from radar: Analysis of TRMM ground validation datasets. J. Appl. Meteor., 43, 1180–1199, doi:10.1175/1520-0450(2004)043<1180:AOTSCO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gorgucci, E., G. Scarchilli, and V. Chandrasekar, 1992: Calibration of radars using polarimetric techniques. IEEE Trans. Geosci. Remote Sens., 30, 853–858, doi:10.1109/36.175319.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gourley, J. J., A. J. Illingworth, and P. Tabary, 2009: Absolute calibration of radar reflectivity using redundancy of the polarization observations and implied constraints on drop shapes. J. Atmos. Oceanic Technol., 26, 689–703, doi:10.1175/2008JTECHA1152.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hauser, D., and P. Amayenc, 1981: A new method for deducing hydrometeor-size distributions and vertical air motions from Doppler radar measurements at vertical incidence. J. Appl. Meteor., 20, 547–555, doi:10.1175/1520-0450(1981)020<0547:ANMFDH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Holleman, I., A. Huuskonen, M. Kurri, and H. Beekhuis, 2010: Operational monitoring of weather radar receiving chain using the sun. J. Atmos. Oceanic Technol., 27, 159–166, doi:10.1175/2009JTECHA1213.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Joss, J., J. Thams, and A. Waldvogel, 1968: The accuracy of daily rainfall measurements by radar. 13th Radar Meteorology Conf., Montreal, QC, Canada, Amer. Meteor. Soc., 448–451.

  • Kumjian, M. R., and A. V. Ryzhkov, 2010: The impact of evaporation on polarimetric characteristics of rain: Theoretical model and practical implications. J. Appl. Meteor. Climatol., 49, 1247–1267, doi:10.1175/2010JAMC2243.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lee, C. K., G. Lee, I. Zawadzki, and K.-E. Kim, 2009: A preliminary analysis of spatial variability of raindrop size distributions during stratiform rain events. J. Appl. Meteor. Climatol., 48, 270–283, doi:10.1175/2008JAMC1877.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Peters, G., B. Fischer, H. Münster, M. Clemens, and A. Wagner, 2005: Profiles of raindrop size distributions as retrieved by microrain radars. J. Appl. Meteor., 44, 1930–1949, doi:10.1175/JAM2316.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Peters, G., B. Fischer, and M. Clemens, 2010: Rain attenuation of radar echoes considering finite-range resolution and using drop size distributions. J. Atmos. Oceanic Technol., 27, 829–842, doi:10.1175/2009JTECHA1342.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., S. E. Giangrande, V. M. Melnikov, and T. J. Schuur, 2005: Calibration issues of dual-polarization radar measurements. J. Atmos. Oceanic Technol., 22, 1138–1155, doi:10.1175/JTECH1772.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Skolnik, M., 2001: Introduction to Radar Systems. McGraw-Hill, 772 pp.

  • Thurai, M., V. N. Bringi, L. D. Carey, P. Gatlin, E. Schultz, and W. A. Petersen, 2012: Estimating the accuracy of polarimetric radar–based retrievals of drop-size distribution parameters and rain rate: An application of error variance separation using radar-derived spatial correlations. J. Hydrometeor., 13, 1066–1079, doi:10.1175/JHM-D-11-070.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tokay, A., P. Hartmann, A. Battaglia, K. S. Gage, W. L. Clark, and C. R. Williams, 2009: A field study of reflectivity and Z–R relations using vertically pointing radars and disdrometers. J. Atmos. Oceanic Technol., 26, 1120–1134, doi:10.1175/2008JTECHA1163.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tokay, A., D. B. Wolf, and W. A. Peterson, 2014: Evaluation of the new version of the laser-optical disdrometer, OTT Parsivel2. J. Atmos. Oceanic Technol., 31, 1276–1288, doi:10.1175/JTECH-D-13-00174.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tracksdorf, P., N. Rathmann, M. Werner, J. Steinert, and M. Frech, 2013: Operational utilisation of polarimetric C-band weather radar measurements at Deutscher Wetterdienst: The project “Radarmassnahmen.” 36th Conf. on Radar Meteorology, Breckenridge, CO, Amer. Meteor. Soc., 365. [Available online at https://ams.confex.com/ams/36Radar/webprogram/Paper228851.html.]

  • Wilks, D. S., 2011: Statistical Methods in the Atmospheric Sciences. International Geophysics Series, Vol. 100, Academic Press, 676 pp.

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