ARC-Based Absolute Calibration Method for Weather Radar Reflectivity
The detection accuracy of weather radar directly affects the precision of meteorological monitoring and early warning, so it is important to establish a mature calibration framework. Active Radar Calibrator (ARC) can generate simulated targets with predefined Doppler frequency and radar cross-section at designated distances, serve as a critical tool for end-to-end absolute calibration of weather radars. This study proposes an ARC-based absolute calibration method for weather radar reflectivity (Z) and develops a Weather radar active calibrator (WARC) tailored for meteorological applications. Firstly, a calibration model for Z was established based on electromagnetic scattering theory, considering factors such as WARC-radar distance, atmospheric attenuation path differences, and radome losses. Secondly, a traceable WARC-RCS calibration chain was constructed to align measurements with national metrological standards. Finally, cross-validation experiments on the accuracy ofWARC and passive suspended metal spheres were conducted at the Changsha Meteorological Radar Calibration Center, by using an S-band reference weather radar. Results demonstrate that the WARC system simultaneously generates four simulated targets with quantifiable parameters. The mean calibration error for Z was -0.325 dB, while velocity and spectral width mean errors were -0.041 m/s and 0.021 m/s, respectively. WARC performance align closely with that of traditional metal sphere calibration methods, confirming both the accuracy and practicality of the simulated targets it generates.
Authors
- Fei Ye (ORCID: https://orcid.org/0000-0002-3771-2576)
- Houjun Sun (ORCID: https://orcid.org/0000-0001-6933-5261)
- Jiaxuan Cao (ORCID: https://orcid.org/0000-0001-6705-8600)
- Jianjun Ma (ORCID: https://orcid.org/0000-0002-7799-0167)
- Nan Shao (ORCID: https://orcid.org/0000-0002-5911-7073)
- Ting Yang (ORCID: https://orcid.org/0009-0000-1302-013X)
- Jie Liu (ORCID: https://orcid.org/0000-0003-2305-4346)
- Xiaopeng Wang
Institutions
- Beijing Institute of Technology (CN)
- China Meteorological Administration (CN)
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3603593
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00