Skip to main content
SpringerLink
Log in

Evaluating the Algorithm for Correction of the Bright Band Effects in QPEs with S-, C- and X-Band Dual-Polarized Radars

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

Abstract

The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant overestimation in quantitative precipitation estimation (QPE) based on the Z–R (reflectivity factor–rain rate) relationship. The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity (VPR) correction. In this study, we applied bright-band correction algorithms to evaluate three different bands (S-, C- and X-band) of dual-polarized radars and to reduce overestimation errors in Z–R relationship–based QPEs. After the reflectivity was corrected by the algorithms using average VPR (AVPR) alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient (AVPR+CC), the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gauge observations, separately. The overestimation of Z–R relationship–based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE (root-mean-square error), RMAE (relative mean absolute error) and RMB (relative mean bias) of QPEs, averaged over all eight cases, the AVPR method improved from 2.28, 0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR+CC method improved to 1.44, 0.55 and 0.30, respectively. The QPEs after AVPR+CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.

摘要

零度层亮带是指融化的冰晶粒子造成反射率因子增大的带区, 其存在会引起基于Z-R关系的定量估测降水(QPE)明显高估. 采用反射率因子垂直廓线(VPR)进行零度层亮带订正可以减弱QPE高估. 本文将此订正方法应用于三个不同波段(S, C, X)的双线偏振雷达上, 以减小QPE高估误差. 采用平均反射率因子垂直廓线法(AVPR)和平均反射率因子垂直廓线与平均相关系数垂直廓线相结合的方法(AVPR+CC)分别对反射率因子进行订正, 采用8次降水过程比较订正前后反射率因子反演的降水, 并与地面雨量站实测降水比较. 结果表明, 当小时降雨量小于5mm时, 两种订正方法均能有效减弱零度层亮带存在引起的QPE高估. 采用均方根误差, 相对平均绝对误差和相对平均偏差三个参数进行误差分析, 平均来看, AVPR法分别从2.28, 0.94和0.78提高到1.55, 0.60和0.40, AVPR+CC法分别提高到1.44, 0.55和0.30. AVPR+CC法订正后的反射率因子反演的QPE误差小于AVPR法, 三个波段雷达具有相似的结果.

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

  • Boodoo, S., D. Hudak, N. Donaldson, and M. Leduc, 2010: Application of dual-polarization radar melting-layer detection algorithm. Journal of Applied Meteorology and Climatology, 49, 1779–1793, https://doi.org/10.1175/2010JAMC2421.1.

    Article  Google Scholar 

  • Bringi, V. N., T. D. Keenan, and V. Chandrasekar, 2001: Correcting c-band radar reflectivity and differential reflectivity data for rain attenuation: A self-consistent method with constraints. IEEE Trans. Geosci. Remote Sens., 39, 1906–1915, https://doi.org/10.1109/36.951081.

    Article  Google Scholar 

  • Bringi, V. N., V. Chandrasekar, N. Balakrishnan, and D. S. Zrnic, 1990: An examination of propagation effects in rainfall on radar measurements at microwave frequencies. J. Atmos. Oceanic Technol., 7, 829–840, https://doi.org/10.1175/1520-0426(1990)007<0829:AEOPEI>2.0.CO;2.

    Article  Google Scholar 

  • Cifelli, R., V. Chandrasekar, S. Lim, P. C. Kennedy, Y. Wang, and S. A. Rutledge, 2011: A new dual-polarization radar rainfall algorithm: Application in Colorado precipitation events. J. Atmos. Oceanic Technol., 28, 352–364, https://doi.org/10.1175/2010JTECHA1488.1.

    Article  Google Scholar 

  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828.

    Article  Google Scholar 

  • Fabry, F., and I. Zawadzki, 1995: Long-term radar observations of the melting layer of precipitation and their interpretation. J. Atmos. Sci., 52, 838–851, https://doi.org/10.1175/1520-0469(1995)052<0838:LTROOT>2.0.CO;2.

    Article  Google Scholar 

  • Giangrande, S. E., and A. V. Ryzhkov, 2005: Calibration of dualpolarization radar in the presence of partial beam blockage. J. Atmos. Oceanic Technol., 22, 1156–1166, https://doi.org/10.1175/JTECH1766.1.

    Article  Google Scholar 

  • Giangrande, S. E., J. M. Krause, and A. V. Ryzhkov, 2008: Automatic designation of the melting layer with a polarimetric prototype of the WSR-88D radar. Journal of Applied Meteorology and Climatology, 47, 1354–1364, https://doi.org/10.1175/2007JAMC1634.1.

    Article  Google Scholar 

  • Haimberger, L., C. Tavolato, and S. Sperka, 2012: Homogenization of the global radiosonde temperature dataset through combined comparison with reanalysis background series and neighboring stations. J. Climate, 25, 8108–8131, https://doi.org/10.1175/JCLI-D-11-00668.1.

    Article  Google Scholar 

  • Hall, W., M. A. Rico-Ramirez, and S. Krämer, 2015: Classification and correction of the bright band using an operational C-band polarimetric radar. J. Hydrol., 531, 248–258, https://doi.org/10.1016/j.jhydrol.2015.06.011.

    Article  Google Scholar 

  • Hubbert, J. C., S. M. Ellis, M. Dixon, and G. Meymaris, 2010: Modeling, error analysis, and evaluation of dual-polarization variables obtained from simultaneous horizontal and vertical polarization transmit radar. Part I: Modeling and antenna errors. J. Atmos. Oceanic Technol., 27, 1583–1598, https://doi.org/10.1175/2010JTECHA1336.1.

    Google Scholar 

  • Jameson, A. R., 1992: The effect of temperature on attenuationcorrection schemes in rain using polarization propagation differential phase shift. J. Appl. Meteor., 31, 1106–1118, https://doi.org/10.1175/1520-0450(1992)031<1106:TEOTOA>2.0.CO;2.

    Article  Google Scholar 

  • Kalogiros, J., M. N. Anagnostou, E. N. Anagnostou, M. Montopoli, E. Picciotti, and F. S. Marzano, 2013: Correction of polarimetric radar reflectivity measurements and rainfall estimates for apparent vertical profile in stratiform rain. Journal of Applied Meteorology and Climatology, 52, 1170–1186, https://doi.org/10.1175/JAMC-D-12-0140.1.

    Article  Google Scholar 

  • Kumar, V. S., and T. M. Naseef, 2015: Performance of ERAInterim wave data in the nearshore waters around India. J. Atmos. Oceanic Technol., 32, 1257–1269, https://doi.org/10.1175/JTECH-D-14-00153.1.

    Article  Google Scholar 

  • Liu, X. Y., H. P. Yang, J. T. Li, B. Li, K. Zhao, and Y. Y. Zheng, 2010: CINRAD radar quantitative precipitation estimation group system. Meteorological Monthly, 36, 90–95. (in Chinese with English abstract).

    Google Scholar 

  • Mooney, P. A., F. J. Mulligan, and R. Fealy, 2011: Comparison of ERA-40, ERA-Interim and NCEP/NCAR reanalysis data with observed surface air temperatures over Ireland. International Journal of Climatology, 31, 545–557, https://doi.org/10.1002/joc.2098.

    Article  Google Scholar 

  • Park, S. G., V. N. Bringi, V. Chandrasekar, M. Maki, and K. Iwanami, 2005a: Correction of radar reflectivity and differential reflectivity for rain attenuation at X band. Part I: Theoretical and empirical basis. J. Atmos. Oceanic Technol., 22, 1621–1632, https://doi.org/10.1175/JTECH1803.1.

    Article  Google Scholar 

  • Park, S. G., M. Maki, K. Iwanami, V. N. Bringi, and V. Chandrasekar, 2005b: Correction of radar reflectivity and differential reflectivity for rain attenuation at X band. Part II: Evaluation and application. J. Atmos. Oceanic Technol., 22, 1633–1655, https://doi.org/10.1175/JTECH1804.1.

    Article  Google Scholar 

  • Park, H. S., A. V. Ryzhkov, D. S. Zrnic, and K. E. Kim, 2009: The hydrometeor classification algorithm for the polarimetric WSR-88D: Description and application to an MCS. Wea. Forecasting, 24, 730–748, https://doi.org/10.1175/2008WAF2222205.1.

    Article  Google Scholar 

  • Qi, Y. C., and J. Zhang, 2013: Correction of radar QPE errors associated with low and partially observed brightband layers. Journal of Hydrometeorology, 14, 1933–1943, https://doi.org/10.1175/JHM-D-13-040.1.

    Article  Google Scholar 

  • Qi, Y. C., J. Zhang, and P. F. Zhang, 2013a: A real-time automated convective and stratiform precipitation segregation algorithm in native radar coordinates. Quart. J. Roy. Meteor. Soc., 139, 2233–2240, https://doi.org/10.1002/qj.2095.

    Article  Google Scholar 

  • Qi, Y. C., J. Zhang, P. F. Zhang, and Q. Cao, 2013b: VPR correction of bright band effects in radar QPEs using polarimetric radar observations. J. Geophys. Res., 118, 3627–3633, https://doi.org/10.1002/jgrd.50364.

    Google Scholar 

  • Qi, Y. C., J. Zhang, Q. Cao, Y. Hong, and X. M. Hu, 2013c: Correction of radar QPE errors for nonuniform VPRs in mesoscale convective systems using TRMM observations. Journal of Hydrometeorology, 14, 1672–1682, https://doi.org/10.1175/JHM-D-12-0165.1.

    Article  Google Scholar 

  • Smith, C. J., 1986: The reduction of errors caused by bright bands in quantitative rainfall measurements made using radar. J. Atmos. Oceanic Technol., 3, 129–141, https://doi.org/10.1175/1520-0426(1986)003<0129:TROECB>2.0.CO;2.

    Article  Google Scholar 

  • Sánchez-Diezma, R., I. Zawadzki, and D. Sempere-Torres, 2000: Identification of the Bright Band through the Analysis of Volumetric Radar Data. J. Geophys. Res., 105, 2225–2236, https://doi.org/10.1029/1999JD900310.

    Article  Google Scholar 

  • Shusse, Y., N. Takahashi, K. Nakagawa, S. Satoh, and T. Iguchi, 2011: Polarimetric radar observation of the melting layer in a convective rainfall system during the rainy season over the East China Sea. Journal of Applied Meteorology and Climatology, 50, 354–367, https://doi.org/10.1175/2010JAMC2469.1.

    Article  Google Scholar 

  • Sun, H. M., P. Y. Zhang, Z. Jiang, and H. Y. Li, 2015: Automated correction of the bright band of weather radar reflectivity data in radar quantitative precipitation estimation. Transactions of Atmospheric Sciences, 38, 492–501, https://doi.org/10.13878/j.cnki.dqkxxb.20121207001 (in Chinese with English abstract)

    Google Scholar 

  • Wang, H., H. C. Lei, and J. F. Yang, 2017: Microphysical processes of a stratiform precipitation event over Eastern China: Analysis using micro rain radar data. Adv. Atmos. Sci., 34(12), 1472–1482, https://doi.org/10.1007/s00376-017-7005-6.

    Article  Google Scholar 

  • Wang, Y. T., and V. Chandrasekar, 2009: Algorithm for estimation of the specific differential phase. J. Atmos. Oceanic Technol., 26, 2565–2578, https://doi.org/10.1175/2009JTECHA1358.1.

    Article  Google Scholar 

  • White, A. B., P. J. Neiman, F. M. Ralph, D. E. Kingsmill, and P. O. G. Persson, 2003: Coastal orographic rainfall processes observed by radar during the California Land-Falling Jets Experiment. Journal of Hydrometeorology, 4, 264–282, https://doi.org/10.1175/1525-7541(2003)4<264:CORPOB>2.0.CO;2.

    Article  Google Scholar 

  • Wu, C., L. P. Liu, M. Wei, B. Z. Xi, and M. H. Yu, 2018: Statistics-based optimization of the polarimetric radar Hydrometeor Classification Algorithm and its application for a squall line in South China. Adv. Atmos. Sci., 35(3), 296–316, https://doi.org/10.1007/s00376-017-6241-0.

    Article  Google Scholar 

  • Xiao, Y. J., L. P. Liu, Z. H. Li, and H. Y. Wang, 2010: Automatic recognition and removal of the bright band using radar reflectivity data. Plateau Meteorology, 29, 197–205. (in Chinese with English abstract).

    Google Scholar 

  • Yang, Y., X. Chen, and Y. C. Qi, 2013: Classification of convective/ stratiform echoes in radar reflectivity observations using a fuzzy logic algorithm. J. Geophys. Res., 118, 1896–1905, https://doi.org/10.1002/jgrd.50214.

    Google Scholar 

  • Zhang, J., and Y. C. Qi, 2010: A real-time algorithm for the correction of brightband effects in radar-derived QPE. Journal of Hydrometeorology, 11, 1157–1171, https://doi.org/10.1175/2010JHM1201.1.

    Article  Google Scholar 

  • Zhang, J., C. Langston, and K. Howard, 2008: Brightband identification based on vertical profiles of reflectivity from the WSR-88D. J. Atmos. Oceanic Technol., 25, 1859–1872, https://doi.org/10.1175/2008JTECHA1039.1.

    Article  Google Scholar 

  • Zhang, J., Y. C. Qi, D. Kingsmill, and K. Howard, 2012: Radarbased quantitative precipitation estimation for the cool season in complex terrain: Case studies from the NOAA hydrometeorology testbed. Journal of Hydrometeorology, 13, 1836–1854, https://doi.org/10.1175/JHM-D-11-0145.1.

    Article  Google Scholar 

  • Zhuang, W., L. P. Liu, and Z. Q. Hu, 2013: Application of bright band identification and correction in radar-based QPE over Tibetan Plateau. Meteorological Monthly, 39, 1004–1013, https://doi.org/10.7519/j.issn.1000-0526.2013.08.007. (in Chinese with English abstract)

    Google Scholar 

Download references

Acknowledgements

This research was funded by a China National 973 Program on Key Basic Research project (Grant No. 2014CB441401), the Beijing Municipal Natural Science Foundation (Grant No. 8141002), and the Public Welfare Industry (Meteorology) of China (Grant No. GYHY201106046). The authors greatly appreciate the immense assistance provided by the other participants at the Institute of Atmospheric Physics and the Meteorological Bureau of Beijing and Xiamen, China.

Author information

Authors and Affiliations

  1. Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    Yang Cao & Hongbin Chen

  2. College of Electronic Engineering, Chengdu University of Information Technology, Chengdu, 610225, China

    Yang Cao, Debin Su & Xingang Fan

  3. Sichuan Meteorological Disasters Prevention Technology Center, Chengdu, 610072, China

    Yang Cao

  4. Department of Geography and Geology, Western Kentucky University, Bowling Green, KY, 42101, USA

    Xingang Fan

  5. China Meteorological Administration Key Laboratory of Atmospheric Sounding, Chengdu, 610225, China

    Debin Su

Authors
  1. Yang Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Debin Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xingang Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hongbin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hongbin Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cao, Y., Su, D., Fan, X. et al. Evaluating the Algorithm for Correction of the Bright Band Effects in QPEs with S-, C- and X-Band Dual-Polarized Radars. Adv. Atmos. Sci. 36, 41–54 (2019). https://doi.org/10.1007/s00376-018-8032-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00376-018-8032-7

Key words

关键词

Search

Navigation