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Ming Shaohui, Meng Yingjie, Tian Gang, et al. xxxx. Applicability study of national multi-source merged precipitation products in the Hanjiang waterway J. Torrential Rain and Disasters,45(x):xx-xx. DOI: 10.12406/byzh.2025-087
Citation: Ming Shaohui, Meng Yingjie, Tian Gang, et al. xxxx. Applicability study of national multi-source merged precipitation products in the Hanjiang waterway J. Torrential Rain and Disasters,45(x):xx-xx. DOI: 10.12406/byzh.2025-087

Applicability study of national multi-source merged precipitation products in the Hanjiang waterway

  • To evaluate the applicability of national multi-source merged precipitation products (ART_5 km and ART_1 km) over the Hanjiang waterway, this study employs dichotomous and continuous variable indices to systematically assess the performance of the two products during 2022-2023 from the perspectives of precipitation intensity, reach-specific spatial differences, and typical precipitation events. The results are as follows. (1) Both products exhibit limited capability in detecting precipitation occurrence, yet demonstrate favorable correlations with meteorological gauge observations for precipitating samples, with only slight systematic underestimation and good overall stability. (2) Marked precipitation intensity dependence is observed. Both products perform optimally for light precipitation, whereas significant systematic underestimation emerges for heavy precipitation and missed detections occur for extreme precipitation; at the daily scale, correlations remain favorable for moderate rain and above. (3) Notable spatial heterogeneity is evident. The middle reach shows the best dichotomous detection, the upper reach exhibits the largest quantitative estimation errors, and the lower reach suffers degraded detection and concentrated errors under heavy precipitation despite maintaining adequate capability in capturing temporal evolution. (4) Substantial temporal differences are found. Except during the dry season (December-February), both products maintain strong correlations with gauge observations. Light precipitation shows minimal and stable errors throughout the year; moderate precipitation achieves the highest detection accuracy during transitional periods (March-April and September-October) with small quantitative biases; heavy precipitation performs better in the rainy season (June-August) but features large spatial dispersion, pronounced afternoon errors, and occasional missed detections for extreme events. (5) Analysis of typical events reveals that both products effectively capture the spatiotemporal evolution of precipitation (including rainband movement and the position and structure of heavy precipitation centers). ART_5 km performs better for moderate and lighter precipitation, while ART_1 km shows greater advantage in detecting heavy precipitation. In summary, both products can provide data support for shipping warnings at different risk levels along the Hanjiang waterway, and heavy precipitation estimates remain valuable for high-risk warning decisions after threshold optimization.
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