Preprints
https://doi.org/10.5194/egusphere-2026-2230
https://doi.org/10.5194/egusphere-2026-2230
27 Jul 2026
 | 27 Jul 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Development of a dual-polarization Zdr radar operator with ice-phase hydrometeor classification for variational assimilation systems (RadDualIceVar v1.0)

Liu Yi, Feifei Shen, Zhixin He, and Dongmei Xu

Abstract. A differential reflectivity (Zdr) observation operator incorporating ice-phase hydrometeor classification was developed to explicitly account for ice-phase hydrometeor contributions in the data assimilation. This proposed observation operator is then implemented within a three-dimensional variational (3DVAR) data assimilation framework for direct assimilating radar Zdr observations. Its performance was evaluated using both single-observation and cycling assimilation experiments for a typhoon case. Results from the single-observation test indicate that assimilating Zdr introduces additional microphysical constraints, leading to more effective adjustments of hydrometeor compared with reflectivity-only assimilation. In the cycling assimilation experiments, the combined reflectivity and Zdr (RFZDR) configuration produces a more physically consistent representation of reflectivity and Zdr, along with a more realistic vertical and horizontal distribution of hydrometeors. These improvements propagate into short-term precipitation forecasts, with RFZDR exhibiting lower root-mean-square errors, enhanced spatial consistency, and gains in heavy precipitation metrics.

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Liu Yi, Feifei Shen, Zhixin He, and Dongmei Xu

Status: open (until 21 Sep 2026)

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Liu Yi, Feifei Shen, Zhixin He, and Dongmei Xu
Liu Yi, Feifei Shen, Zhixin He, and Dongmei Xu
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Latest update: 28 Jul 2026
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Short summary
This study presents a new approach for using dual-polarization radar data to improve rainfall forecasts, particularly during severe storms. The method establishes a more advanced framework that better connects radar observations with the physical processes governing rain and ice particles, while ensuring consistent and reliable updates within the forecasting system. Tests using real cases demonstrate more realistic storm structures and improved short-term rainfall predictions.
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