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

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 Ku-band 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.

Graphical abstract

Keywords

calibration error / ground-based radar / reflectivity / correction / precipitation estimates

References

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

[2] 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

[3] 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 doi:10.1029/2020JD032482

[4] 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

[5] 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,

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

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

[8] 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)

[9] 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

[10] 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)

[11] 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

[12] 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

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

[14] 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

[15] 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

[16] 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

[17] 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

[18] 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

[19] 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

[20] 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

[21] 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

[22] 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

[23] 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

[24] 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

[25] 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

[26] 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

[27] 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

[28] 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

[29] 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

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

[31] 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

[32] Tao S Y (1980). Rainstorm in China. Beijing: Science Press (in Chinese)

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

[34] 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

[35] 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)

[36] 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)

[37] 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

[38] 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

[39] 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)

[40] 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)

[41] 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)

[42] 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

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

[44] 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

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

[46] 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)

[47] 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)

[48] 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)

Acknowledgments

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).

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