A study on the subseasonal forecast of low frequency rainfall over the lower reaches of Yangtze River Valley based on the 50-80 d oscillation
Low-frequency component of daily rainfall in the lower reaches of the Yangtze River Valley (LYRV) and the principal components of the global 850 hPa low-frequency zonal wind for the period of 1979-2000 were used to develop the extended complex autoregressive model (ECAR) for subseasonal forecast of the 50-80 d low-frequency rainfall component in the LYRV.This type of climate forecast method,which is based on a data-driven model,can not only reflect the lagged variation information between the principal low-frequency component of global circulation and the low-frequency component of rainfall over the LYRV in a complex space,but also can well describe the variation of the principal component of the climate system in a low dimensional space.A 14 a hindcast was conducted in the recent study for subseasonal forecast of the low-frequency component of rainfall in the LYRV during the period from 2001 to 2014.These experimental results show that this ECAR model has a good skill for the forecast of the 50-80 d low-frequency component of the rainfall in the LYRV at a lead time of approximately 52 d.The ECAR model performs much better than the traditional autoregressive (AR) model,and it performs best in June -August.Hence,the development and variation of the major 50-80 d oscillation of global circulation and the temporal evolution of the relationship between the oscillation and the low-frequency component of rainfall in the LYRV are very helpful for intraseasonal forecast of variations in rainfall in the LYRV at a lead time of 50-60 d,particularly in the summer.The 50-80 d oscillation of circulation associated with the East Asian meridional tripole pattern (EAT) is considered to be the main factor that affects the subseasonal variation of rainfall in the LYRV.
50-80 d oscillationEast Asian meridional tripole patternLow frequency rainfall in the lower reaches of the Yangtze River ValleyForecasting model of ECARSubseasonal forecast
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