An Objective Method for Defining Meiyu Onset in Lower Reaches of the Yangtze River Basin

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  • Corresponding author: Tim LI
  • doi: 10.1007/s13351-022-2069-3
  • Note: This paper has been peer-reviewed and is just accepted by J. Meteor. Res. Professional editing and proof reading are underway. Please use with caution.

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  • Meiyu is an important climate phenomenon in East Asia, and predicting its onset is critical for local community. Traditionally, the onset of Meiyu is determined by regional operational meteorological centers with some arbitrary criteria. In this study, an objective Meiyu onset index (MOI) is constructed based on large-scale atmospheric conditions such as temperature and relative humidity over the Lower Reach of Yangtze River Basin (LYRB). This objectively determined MOI is in good agreement with an integrated area-weighted onset index provided by regional climate centers. A composite analysis is further carried out to reveal large-scale circulation characteristics associated with an early and a late onset group. A La Nina like SST condition in the Pacific and enhance convection in Philippines are favorable precursory conditions for the early onset. Accompanied with the tropical signals are a Pacific-Japan (PJ) pattern in June and an anomalous anticyclone near Taiwan. Southerly anomalies to the west of the anticyclone transports high mean moisture northward, favoring the onset of Meiyu in LYRB. A linear regression model is constructed for the MOI forecast with three independent predictors. With 1981-2010 as a training period, the reconstructed MOI time series is able to capture the early and late onset years quite well. An independent forecast for the period of 2011-2020 shows a reliable skill. The correlation between the objectively determined MOI and the forecasted date is 0.6, exceeding a 95% confidence level. The newly developed MOI and the regression model can be easily implemented to operational centers for real-time application.

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An Objective Method for Defining Meiyu Onset in Lower Reaches of the Yangtze River Basin

    Corresponding author: Tim LI; 
  • 1. Minhang District Meteorological Observatory, Shanghai 201199, China
  • 2. Department of Atmospheric Sciences, School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, Hawaii, HI96822, USA
  • 3.  Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environmental Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China
  • 4. Shanghai Climate Center, Shanghai 200030, China

Abstract: 

Meiyu is an important climate phenomenon in East Asia, and predicting its onset is critical for local community. Traditionally, the onset of Meiyu is determined by regional operational meteorological centers with some arbitrary criteria. In this study, an objective Meiyu onset index (MOI) is constructed based on large-scale atmospheric conditions such as temperature and relative humidity over the Lower Reach of Yangtze River Basin (LYRB). This objectively determined MOI is in good agreement with an integrated area-weighted onset index provided by regional climate centers. A composite analysis is further carried out to reveal large-scale circulation characteristics associated with an early and a late onset group. A La Nina like SST condition in the Pacific and enhance convection in Philippines are favorable precursory conditions for the early onset. Accompanied with the tropical signals are a Pacific-Japan (PJ) pattern in June and an anomalous anticyclone near Taiwan. Southerly anomalies to the west of the anticyclone transports high mean moisture northward, favoring the onset of Meiyu in LYRB. A linear regression model is constructed for the MOI forecast with three independent predictors. With 1981-2010 as a training period, the reconstructed MOI time series is able to capture the early and late onset years quite well. An independent forecast for the period of 2011-2020 shows a reliable skill. The correlation between the objectively determined MOI and the forecasted date is 0.6, exceeding a 95% confidence level. The newly developed MOI and the regression model can be easily implemented to operational centers for real-time application.

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