Skip to main content
SpringerLink
Log in

Consistency correction of echo intensity data for multiple radar systems and its application in quantitative estimation of typhoon precipitation

  • Research Article
  • Published:
Frontiers of Earth Science Aims and scope Submit manuscript

Abstract

Calibration error is one of the primary sources of bias in echo intensity measurements by ground-based radar systems. Calibration errors cause data discontinuity between adjacent radars and reduce the effectiveness of the radar system. The Global Precipitation Measurement Kuband Precipitation Radar (GPM KuPR) has been shown to provide stable long-term observations. In this study, GPM KuPR observations were converted to S-band approximations, which were then matched spatially and temporally with ground-based radar observations. The measurements of stratiform precipitation below the melting layer collected by the KuPR during Typhoon Ampil were compared with those of multiple radar systems in the Yangtze River Delta to determine the deviations in the echo intensity between the KuPR and the ground-based radar systems. The echo intensity data collected by the ground-based radar systems was corrected using the KuPR observations as reference, and the correction results were verified by comparing them with rain gauge observations. It was found that after the correction, the consistency of the echo intensity measurements of the multiple radar systems improved significantly, and the precipitation estimates based on the revised ground-based radar observations were closer to the rain gauge measurements.

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

  • Atlas D (2002). Radar calibration: some simple approaches. Bull Am Meteorol Soc, 83(9): 1313–1316

    Article  Google Scholar 

  • Awaka J, Le M, Chandrasekar V, Yoshida N, Higashiuwatoko T, Kubota T, Iguchi T (2016). Rain type classification algorithm module for GPM dual-frequency precipitation radar. J Atmos Ocean Technol, 33 (9): 1887–1898

    Article  Google Scholar 

  • Bao X W, Wu L G, Zhang S, Li L M, Zhao B K (2020). Distinct raindrop size distributions of convective inner-and outer-rainband rain in Typhoon Maria (2018). J Geophys Res Atmos, 125e2020JD032482

  • Biswas S, Chandrasekar C V (2018). Cross-validation of observations between the GPM dual-frequency precipitation radar and ground based dual-polarization radars. Remote Sens, 10(11): 1773

    Article  Google Scholar 

  • Chandrasekar V, Hou A, Smith E, Bringi V N, Rutledge S A, Gorgucci E, Petersen W A, Jackson G S (2008). Potential role of dual-polarization radar in the validation of satellite precipitation measurements: rationale and opportunities. Bull Am Meteorol Soc, 89(8): 1127–1146

    Article  Google Scholar 

  • Chen L S, Luo Z X, Li Y (2004). Research advances on tropical cyclone landfall progress. Acta Meteorol Sin, 62: 541–549

    Google Scholar 

  • Chen L, Ding Y (1979). An Introduction to the Western Pacific Typhoon. Beijing: Science Press, 1–491 (in Chinese)

    Google Scholar 

  • Cheng Z Q, Chen L S, Xu X D (2005). Research progress on typhoon heavy rainfall in China for last ten years. Meteorol Mon, 31(12): 3–9 (in Chinese)

    Google Scholar 

  • Chu Z, Ma Y, Zhang G, Wang Z, Han J, Kou L, Li N (2018). Mitigating spatial discontinuity of multi-radar QPE based on GPM/KuPR. Hydrology, 5(3): 48

    Article  Google Scholar 

  • Dong M Y, Chen L S, Zheng P Q (2009). Research progress on abrupt intensification of heavy rainfall and super heavy rainfall associated with landfalling tropical cyclones. J Trop Meteorol, 25: 495–502 (in Chinese)

    Google Scholar 

  • Duan W L, He B, Nover D, Fan J, Yang G, Chen W, Meng H, Liu C (2016). Floods and associated socioeconomic damages in China over the last century. Nat Hazards, 82(1): 401–413

    Article  Google Scholar 

  • Francisco J T, Turk F J, Petersenc W, Hou A Y, García-Ortegae E, Machado L A T, Angelis C F, Salio P, Kidd C, Huffman G J, de Castroa M (2012). Global precipitation measurement: methods, datasets and applications. Atmos Res, 104–105(1): 70–97

    Google Scholar 

  • Goddard Space Flight Center (2014). Validation Network Data Product User’s Guide Volume 1-TRMM Data Products. Available online at NASA website

  • Han J, Chu Z G, Wang Z H, Xu D, Li N, Kou L, Xu F, Zhu Y Q (2018). The establishment of optimal ground-basedradar datasets by comparison and correlation analyses with space-borne radar data. Meteorol Appl, 25(1): 161–170

    Article  Google Scholar 

  • Hou A Y, Kakar R K, Neeck S, Azarbarzin A A, Kummerow C D, Kojima M, Oki R, Nakamura K, Iguchi T (2014). The global precipitation measurement mission. Bull Am Meteorol Soc, 95(5): 701–722

    Article  Google Scholar 

  • Iguchi T, Kozu T, Meneghini R, Awaka J, Okamoto K (2000). Rain-profiling algorithm for the TRMM precipitation radar. J Appl Meteorol, 39(12): 2038–2052

    Article  Google Scholar 

  • Iguchi T, Seto S, Awaka J, Meneghini R, Kubota T, Oki R, Chandra V, Kawamoto N (2016). Performance of the dual-frequency precipitation radar on the GPM core satellite. Geophys Res Abstr, 18: EGU2016–EGU11581

    Google Scholar 

  • Kim J H, Ou M L, Park J D, Morris K R, Schwaller M R, Wolff D B (2014). Global precipitation measurement (GPM) ground validation (GV) prototype in the Korean Peninsula. J Atmos Ocean Technol, 31 (9): 1902–1921

    Article  Google Scholar 

  • Kozu T, Kawanishi T, Kuroiwa H, Kojima M, Oikawa K, Kumagai H, Okamoto K, Okumura M, Nakatsuka H, Nishikawa K (2001). Development of precipitation radar onboard the Tropical Rainfall Measuring Mission (TRMM) satellite. IEEE Trans Geosci Remote Sens, 39(1): 102–116

    Article  Google Scholar 

  • Li Y, Chen L S, Xu X D (2005). Numerical experiments of the impact of moisture transportation on sustaining of the landfalling tropical cyclone and precipitation. Chin J Atmos Sci, 29: 91–98

    Google Scholar 

  • Liao L, Meneghini R (2009). Changes in the TRMM Version-5 and Version-6 precipitation radar products due to orbit boost. J Meteorol Soc Jpn, 87A: 93–107

    Article  Google Scholar 

  • Liao L, Meneghini R, Iguchi T (2001). Comparisons of rain rate and reflectivity factor derived from the TRMM precipitation radar and the WSR-88D over the Melbourne, Florida. J Atmos Ocean Technol, 18 (12): 1959–1974

    Article  Google Scholar 

  • Liu Z C, Li B, Zhai W Q (2002). The New Generation of Weather Radar System Environment and Operation Management. Beijing: China Meteorological Press: 102–104

    Google Scholar 

  • Ma Y, Chandrasekar V, Biswas S K (2020). A Bayesian correction approach for improving dual-frequency precipitation radar rainfall rate estimates. J Meteorol Soc Japan, 98(3): 511–525

    Article  Google Scholar 

  • Ma Y, Zhang Y, Yang D, Farhan S B (2015). Precipitation bias variability versus various gauges under different climatic conditions over the Third Pole Environment (TPE) region. Int J Climatol, 35(7): 1201–1211

    Article  Google Scholar 

  • Meneghini R, Kim H, Liao L, Jones J A, Kwiatkowski J M (2015). An initial assessment of the surface reference technique applied to data from the dual-frequency precipitation radar (DPR) on the GPM Satellite. J Atmos Ocean Technol, 32: 2281–2296

    Article  Google Scholar 

  • Morris K R, Schwaller M R (2011). Sensitivity of space-borne and ground radar comparison results to data analysis methods and constraints. In: 35th Conf on Radar Meteorology, Pittsburgh, PA, American Meteorological Society

    Google Scholar 

  • Nasrollahi N, Agha K A, Li J L, Gao X, Hsu K, Sorooshian S (2012). Assessing the impacts of different WRF precipitation physics in hurricane simulations. Weather Forecast, 27(4): 1003–1016

    Article  Google Scholar 

  • Seto S, Iguchi T (2015). Inter-comparison of attenuation correction methods for the GPM dual-frequency precipitation radar. J Atmos Ocean Technol, 32(5): 915–926

    Article  Google Scholar 

  • Shi P J (2016). Natural Disasters in China. Beijing: Springy and Beijing Normal University Press, 1–103

    Google Scholar 

  • Smith J A, Seo D J, Baeck M L, Hudlow M D (1996). An inter-comparison Study of NEXRAD Precipitation Estimates. Water Resour Res, 32(7): 2035–2045

    Article  Google Scholar 

  • Tao S Y (1980). Rainstorm in China. Beijing: Science Press (in Chinese)

    Google Scholar 

  • Tokay A, Bashor P G, Habib E, Kasparis T (2008). Raindrop size distribution measurements in tropical cyclones. Mon Weather Rev, 136(5): 1669–1685

    Article  Google Scholar 

  • Vaccarono M, Bechini R, Chandrasekar C V, Cremonini R, Cassardo C (2016). An integrated approach to monitoring the calibration stability of operational dual-polarization radars. Atmos Meas Tech, 9(11): 5367–5383

    Article  Google Scholar 

  • Wang Y P, Cui X P, Ran L K (2015a). Diagnosis of dynamical parameters in torrential rain associated with typhoon “Bilis” in 2006. Chin J Atmos Sci, 39: 747–756 (in Chinese)

    Google Scholar 

  • Wang Z H, Li S Y, Dai J H (2015b). Comparative case study on the observations between the space-borne radar and ground-based radar. Plateau Meteorol, 34(3): 804–814 (in Chinese)

    Google Scholar 

  • Warren R A, Protat A, Siems S T, Ramsay H A, Louf V, Manton M J, Kane T A (2018). Calibrating ground-basedradars against TRMM and GPM. J Atmos Ocean Technol, 35(2): 323–346

    Article  Google Scholar 

  • Wen L, Zhao K, Chen G, Wang M, Zhou B, Huang H, Hu D, Lee W C, Hu H (2018). Drop size distribution characteristics of seven typhoons in China. J Geophys Res D Atmospheres, 123(12): 6529–6548

    Article  Google Scholar 

  • Wu T, Wan Y F, Wo W F, Leng L (2013). Design and application of radar reflectivity quality control algorithm in SWAN. Meteorol Sci Tech, 41(5): 809–817 (in Chinese)

    Google Scholar 

  • Xiao Y J, Liu L P (2007). Study of method for interpolating data from weather radar network to 3D grid and mosaics. Acta Meteorol Sin, 64 (5): 647–657 (in Chinese)

    Google Scholar 

  • Xiao Y J, Liu L P, Yang H P (2006). A contrast analysis of synchronous observations from regional radar network. Acta Meteorol Sin, 65(6): 919–927 (in Chinese)

    Google Scholar 

  • Xu W, Zhuo L, Zheng J, Ge Y, Gu Z, Tian Y (2016). Assessment of the casualty risk of multiple meteorological hazards in China. Int J Environ Res Public Health, 13(2): 222

    Article  Google Scholar 

  • Yu H, Chen L (2019). Impact assessment of landfalling tropical cyclones: introduction to the special issue. Front Earth Sci, 13(4): 669–671

    Article  Google Scholar 

  • Zhang J, Howard K, Langston C, Vasiloff S, Kaney B, Arthur A, Van Cooten S, Kelleher K, Kitzmiller D, Ding F, Seo D J, Wells E, Dempsey C (2011). National mosaic and multi-sensor QPE (NMQ) system: description, results, and future plans. Bull Am Meteorol Soc, 92(10): 1321–1338

    Article  Google Scholar 

  • Zhang P C, Du B Y, Dai T P (2000). Radar Meteorology. Beijing: China Meteorological Press, 165–169

    Google Scholar 

  • Zhang Q H, Wei Q, Chen L S (2010). Impact of landfalling tropical cyclones in mainland China. Sci Sinica Terrae, 40(7): 941–946 (in Chinese)

    Google Scholar 

  • Zhang S, Wang Z H, Zhao B K, Chen Y C (2019). Using space-borne radar data to correcting calibration errors in ground-based radar. Clim Env Res, 24(5): 576–584 (in Chinese)

    Google Scholar 

  • Zhu Y Q, Wang Z H, Li N (2016). Consistency analysis and correction for observations from the radar at Nanjing. Acta Meteorol Sin, 74(2): 298–308 (in Chinese)

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Key Projects of the National Key R&D Program (No. 2018YFC1506303), the Key Program for International S&T Cooperation Projects of China (No. 2017YFE0107700), the National Natural Science Foundation of China (Grant Nos. 41775064 and 41806046), Shanghai Natural Science Foundation (No. 21ZR1477300), and Fujian Key Laboratory of Severe Weather Open Foundation (No. 2020TFS02).

Author information

Authors and Affiliations

  1. Shanghai Typhoon Institute, China Meteorological Administration, Shanghai, 200030, China

    Shuai Zhang, Bingke Zhao, Jie Tang, Limin Lin, Xiaoqin Lu & Jiaming Yan

  2. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation (China Meteorological Administration), Nanjing University of Information Science & Technology, Nanjing, 210044, China

    Shuai Zhang & Zhigang Chu

  3. Hainan Institute of Meteorological Sciences, Haikou, 570203, China

    Jing Han

  4. Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province, Haikou, 570203, China

    Jing Han

  5. Fujian Key Laboratory of Severe Weather, Fuzhou, 350001, China

    Shuai Zhang

  6. Fujian Key Laboratory of Granular Computing and Application, Minnan Normal University, Zhangzhou, 363000, China

    Shuai Zhang

Authors
  1. Shuai Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jing Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bingke Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhigang Chu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jie Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Limin Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xiaoqin Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jiaming Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shuai Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, S., Han, J., Zhao, B. et al. Consistency correction of echo intensity data for multiple radar systems and its application in quantitative estimation of typhoon precipitation. Front. Earth Sci. 16, 99–108 (2022). https://doi.org/10.1007/s11707-021-0902-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11707-021-0902-0

Keywords

Search

Navigation