Application of the Doppler weather radar in real-time quality control of hourly gauge precipitation in eastern China
Open accessAbstract
The current real-time operational quality control method for hourly rain gauge records at meteorological stations of China is primarily based on a comparison with historical extreme records, and the spatial and temporal consistencies of rain records. However, this method might make erroneous judgments for heavy precipitation because of its remarkable inhomogeneous features. In this study, we develop a Radar Supported Operational Real-time Quality Control (RS_ORQC) method to improve hourly gauge precipitation records in eastern China by using Doppler weather radar data and national automatic rain-gauge network in JJA (i.e., June, July and August) between 2010 and 2011. According to the probability density function (PDF) and cumulative probability density function (CDF), we establish the statistic relationships between NSN precipitation records under 7 radar coverage and radar quantitative precipitation estimation (QPE). The other NSN records under 5 radar coverage are used for the verification. The results show that the correct rate of this radar-supported new method in judging gauge precipitation is close to 99.95% when the hourly rainfall rate is below 10 mm h − 1 and is 96.21% when the rainfall intensity is above 10 mm h − 1 . Moreover, the improved quality control method is also applied to evaluate the quality of provincial station network (PSN) precipitation records over eastern China. The correct rate of PSN precipitation records is 99.92% when the hourly rainfall rate is below 10 mm h − 1 , and it is 93.33% when the hourly rainfall rate is above 10 mm h − 1 . Case studies also exhibit that the radar-supported method can make correct judgments for extreme heavy rainfall.
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Compared with traditional approaches, multi-source collaborative QC methods integrate various observational data and effectively reduce the false alarm rate in anomaly detection.
“Compared with traditional approaches, these methods integrate various observational data, including Doppler weather radar, geostationary meteorological satellite, and weather detector, effectively reducing the false alarm rate in anomaly detection [27][28][29].”
From A Machine Learning-Based Quality Control Algorithm for Heavy Rainfall Using Multi-Source Data (2025) · cites this paper as [27]
Multi-source data collaborative QC for precipitation has demonstrated significant advantages.
“With the advancement of ground-and satellite-based observation technologies and the explosive growth of meteorological data, multi-source data collaborative QC for precipitation has demonstrated significant advantages [27][28][29][30][31].”
From A Machine Learning-Based Quality Control Algorithm for Heavy Rainfall Using Multi-Source Data (2025) · cites this paper as [27]
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A Machine Learning-Based Quality Control Algorithm for Heavy Rainfall Using Multi-Source Data
Sun, H., Zhou, Q., Shi, L., Li, C., Qin, S., Yao, D., Xu, M., Huang, Y., Hu, Q., & Guan, Y. (2025) · Remote Sensing · doi:10.3390/rs17243976 · Cited by 4 · see citing works
- Authors
- Zhong, L., Zhang, Z., Chen, L., Yang, J., & Zou, F.
- Affiliations
- Chinese Academy of Meteorological Sciences (CN)
- China Meteorological Administration (CN)
- Corresponding author
- Zhong, Lingzhi
- Venue
- Atmospheric Research
- Publisher
- Elsevier BV
- Published
- 2016-05
- Volume
- 172-173
- Pages
- 109-118
- ISSN
- 0169-8095 (ISSN-L)
- OpenAlex
- W2222638777
- Cited by
- 21
- References
- 0
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2023: 1 · 2022: 2 · 2021: 1 · 2020: 4 · 2019: 2 · 2018: 2 · 2017: 2 · 2016: 1
- FWCI
- 1.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Atmospheric Research (publishedVersion, cc-by-nc-nd)
- Funders
- National Natural Science Fund of China (91437214)
- National Key Basic Research Project of China (2012BAC22B04)
- Topics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Precipitation Measurement and Analysis
- Physical Sciences › Environmental Science › Water Science and Technology › Hydrology and Watershed Management Studies
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Keywords
- Doppler weather radar, radar quantitative precipitation estimation, heavy rainfall, extreme rainfall, eastern China
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