Liang et al. (2025) Optimized classification reveals typical summer precipitation anomaly patterns and associated circulation features over the Yangtze-Huai river Valley

Identification

• Journal: Theoretical and Applied Climatology
• Year: 2025
• Date: 2025-12-11
• Authors: Liaofeng Liang, Jun Xia, Juying Chen, Zehai Wang
• DOI: 10.1007/s00704-025-05948-4

Research Groups

• National Institute of Natural Hazards, Ministry of Emergency Management of China
• Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
• State Key Laboratory of Water Resources Engineering and Management, Wuhan University
• State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences

Short Summary

This study developed an optimized classification scheme to identify and characterize nine distinct summer precipitation anomaly patterns (PAPs) over the Yangtze-Huai River Valley (YHRV) from 1951 to 2020. The research reveals their associated large-scale atmospheric circulation features and a significant temporal shift towards fewer drought patterns, providing a refined basis for improved seasonal forecasting and disaster prevention.

Objective

• To develop and apply an optimized classification methodology that overcomes the limitations of traditional approaches, providing a more robust and physically meaningful representation of precipitation anomaly patterns (PAPs) over the YHRV.
• To leverage this improved classification to investigate the distinct large-scale atmospheric circulation features associated with each identified PAP, thereby providing insight into the physical processes governing their formation.

Study Configuration

• Spatial Scale: Yangtze-Huai River Valley (YHRV), China, using data from 50 meteorological stations and ERA5 reanalysis data at 0.25° × 0.25° horizontal resolution.
• Temporal Scale: Summer (June, July, August) precipitation and atmospheric data from 1951 to 2020 (70 years). Anomalies are defined relative to the 1991–2020 climatological reference period.

Methodology and Data

• Models used:
  • Non-parametric Mann-Kendall (MK) test and Theil-Sen slope estimator for trend analysis.
  • Empirical Orthogonal Function (EOF) analysis for preliminary classification of precipitation variability.
  • Iterative optimization scheme using Pearson correlation coefficient (R > 0.4) and sign probability (SP > 0.6) for robust classification of PAPs.
  • Composite analysis to identify large-scale atmospheric circulation patterns.
  • Two-tailed Student’s t-test (p < 0.05) for statistical significance assessment.
• Data sources:
  • Monthly precipitation observation data from 50 meteorological stations in the YHRV, obtained from the China Meteorological Administration’s National Climate Center.
  • ERA5 global reanalysis product from the European Centre for Medium-Range Weather Forecasts (ECMWF), providing monthly averaged data for geopotential (z), specific humidity (q), and zonal (u) and meridional (v) wind components at standard pressure levels (specifically 500 hPa geopotential height and 850 hPa water vapor flux).
  • Shuttle Radar Topography Mission (SRTM) data for Digital Elevation Model (DEM).

Main Results

• Summer precipitation across the YHRV shows a statistically significant increasing trend of 1.027 mm/year (p < 0.05) from 1951 to 2020, with 78% of stations exhibiting positive trends (mean: 1.49 mm/year).
• The optimized classification scheme identified nine distinct PAP types with high statistical reliability, achieving maximum average pattern correlations (R) of 0.85 and average sign probabilities (SP) of 0.9. This approach significantly improved composite correlation for 78.7% of the years analyzed compared to preliminary classifications.
• The nine PAP types are grouped into three families: Uniform Patterns (Region-wide Positive/Negative - RWP/RWD), Regional Patterns (e.g., Middle and Lower reaches Positive/Negative - MLP/MLD), and Dipole Patterns (North-South/South-North dipole - NSP/SNP).
• A distinct temporal shift was observed: the frequency of major drought patterns (RWD and MLD) declined markedly from 15 cases during 1951–1985 to only 5 cases during 1986–2020, contributing to the overall increasing precipitation trend.
• Composite analysis revealed distinct atmospheric mechanisms:
  • Extreme wet patterns (RWP) are characterized by a strong North Asian blocking high at upper levels, facilitating a low-level cyclonic circulation that funnels moisture into the YHRV.
  • Extreme dry patterns (RWD) are associated with a deep continental trough and a low-level anticyclone that effectively blocks moisture influx.
  • Regional patterns are driven by more localized circulation anomalies.
  • Dipole patterns are caused by a latitudinal shift in the main moisture transport axis, rather than a net change in moisture.

Contributions

• Developed and validated an optimized classification methodology for precipitation anomaly patterns (PAPs) that significantly improves upon traditional EOF-based methods by enhancing statistical reliability and physical interpretability.
• Identified nine statistically robust and physically distinct summer PAPs over the YHRV, providing a comprehensive framework for understanding regional precipitation variability.
• Established a physically coherent link between these specific PAPs and their associated large-scale atmospheric circulation features (500 hPa geopotential height) and low-level moisture transport mechanisms (850 hPa water vapor flux).
• Revealed a significant temporal shift in PAP frequency, particularly a marked decline in major drought patterns, offering a spatial pattern-based explanation for the observed increasing trend in regional summer precipitation.
• Provides a refined basis for improving seasonal forecasting capabilities and developing more targeted strategies for disaster prevention and water resource management in the YHRV.

Funding

• The National Key Research and Development Project (No. 2024YFC3013304)
• The National Natural Science Foundation of China (No. 42307124)
• The Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (No. 2019QZKK0903)
• The Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDA23040104)

Citation

@article{Liang2025Optimized,
  author = {Liang, Liaofeng and Xia, Jun and Chen, Juying and Wang, Zehai},
  title = {Optimized classification reveals typical summer precipitation anomaly patterns and associated circulation features over the Yangtze-Huai river Valley},
  journal = {Theoretical and Applied Climatology},
  year = {2025},
  doi = {10.1007/s00704-025-05948-4},
  url = {https://doi.org/10.1007/s00704-025-05948-4}
}