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

doi:10.1007/s11707-021-0902-0

Front. Earth Sci.

2022, Vol. 16

Issue (1) : 99-108 https://doi.org/10.1007/s11707-021-0902-0

RESEARCH ARTICLE

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

Shuai ZHANG^1,^2,^5,⁶(

), Jing HAN^3,⁴, Bingke ZHAO¹, Zhigang CHU², Jie TANG¹, Limin LIN¹, Xiaoqin LU¹, Jiaming YAN¹

¹. Shanghai Typhoon Institute, China Meteorological Administration, Shanghai 200030, Chin
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
³. Hainan Institute of Meteorological Sciences, Haikou 570203, China
⁴. Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province, Haikou 570203, China
⁵. Fujian Key Laboratory of Severe Weather, Fuzhou 350001, China
⁶. Fujian Key Laboratory of Granular Computing and Application, Minnan Normal University, Zhangzhou 363000, China

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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.

Keywords calibration error ground-based radar reflectivity correction precipitation estimates

Corresponding Author(s): Shuai ZHANG

Online First Date: 23 September 2021 Issue Date: 04 March 2022

Cite this article:

Shuai ZHANG,Jing HAN,Bingke ZHAO, et al. Consistency correction of echo intensity data for multiple radar systems and its application in quantitative estimation of typhoon precipitation[J]. Front. Earth Sci., 2022, 16(1): 99-108.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-021-0902-0
https://academic.hep.com.cn/fesci/EN/Y2022/V16/I1/99

Fig.1 Schematic illustration of the geometry-matching method (Solid lines represent the KuPR scanning beam; dashed lines represent the GR sweeps; shading represents the overlap area) (Goddard Space Flight Center, 2014).

Fig.2 The best track of typhoon Ampil (from 23:00, July 21 to 05:00, July 23, 2018 (UTC+ 8)), effective precipitation observation range (150 km) of the three radars and rain gauge stations.

Fig.3 The three-radar mosaic of the echo intensity at 1-km height before correction (NT, QP, and ZS radar) at 02:30, July 22, 2018 (UTC), the black triangles represent the locations of the radars, and the black ellipse highlights the discontinuity area.

Fig.4 Sketch of the “floating cylinder” for data comparison between two adjacent ground-based radars.

Fig.5 Time series of the reflectivity factors of the three radars and deviations between QP, ZS, and NT radar. (a) Nantong radar vs. QP radar; (b) NT radar vs. ZS radar. The black lines represent the deviations.

Tab.1 Statistics of the deviations of echo intensity between NT and QP radar, NT and ZS radar

Tab.2 Statistics of the reflectivity factor deviations between the three GRs and the KuPR on July 22, 2018, during typhoon Ampil

Fig.6 The three-radar mosaic of the echo intensity at 1-km height after the correction (NT, QP, and ZS radar) at 02:30, July 22, 2018 (UTC), the black triangles represent the locations of the radars.

Fig.7 The three-radar mosaic of the echo intensity at 1-km height before correction (NT, QP, and ZS radar) at 19:30, August 02, 2018 (UTC), the black triangles represent the locations of the radars, and the black ellipse highlights the discontinuity area.

Fig.8 Time series of the reflectivity factors of QP, ZS, and NT radars and time series of reflectivity factor differences between the radars. Left: NT radar vs. QP radar; Right: QP radar vs. ZS radar. The black lines represent the deviations.

Fig.9 The three-radar mosaic of the echo intensity at 1-km height after correction (NT, QP, and ZS radar) at 19:30, August 02, 2018 (UTC), the black triangles represent the locations of the radars.

Fig.10 The Z (reflectivity factor)-R (rain rate) relationship Z = 112.29R^1.64 derived from disdrometers deployed in Nanhui and Expo stations during typhoon Ampil, and two commonly used relations.

Tab.3 Statistics of the deviations between rain gauge data and QPEs derived from the GRs’ observation (NT, QP, and ZS) during typhoon Ampil

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