Multi-week prediction of South-East Asia rainfall variability during boreal summer in CFSv2

Ren-feng, Liu; Wang, Wanqiu

doi:10.1007/s00382-014-2401-4

Cited by 5 publications

(1 citation statement)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another goal of this study is to evaluate CFSv2's capability of reproducing the BSISO's influences on extreme rainfall probability. Liu and Wang () have shown that the intraseasonal forecast skill of rainfall in CFSv2 tends to be higher when the amplitudes of the MJO and BSISO are lager, especially for the BSISO. Figure shows the bivariate ACC of the CFSv2 BSISO1 (Figure a) and BSISO2 (Figure b) with the observationally based counterpart.…”

Section: Predictability Of Extreme Rainfall In Cfsv2mentioning

confidence: 99%

Impact of Boreal Summer Intraseasonal Oscillation on Rainfall Extremes in Southeastern China and its Predictability in CFSv2

Ren

et al. 2018

JGR Atmospheres

View full text Add to dashboard Cite

The boreal summer intraseasonal oscillation (BSISO) is one of the dominant modes of intraseasonal variability of the tropical climate system, which has prominent northward propagation extending much further from the equator. The impacts of BSISO on extreme rainfall in eastern China were studied using the BSISO indices and daily rainfall data in China. We revealed that the responses of extreme rainfall to BSISO activity in eastern China are not spatially uniform. Under the influences of BSISO1, the probability‐distribution functions of rainfall in two southeastern China subregions: South China and Yangtze River Valley significantly skew toward larger values, respectively, in phases 4 and 8, and phases 3 and 4 with the probability of 90th extremes increased by 35–45% relative to May–August rainfall probability‐distribution function, showing southward propagation with the speed of 1.96°/phase. Under the BSISO2, the probability of the 90th extremes increased more than 40% in South China and Yangtze River Valley, respectively, during phases 4–5 and phases 6–7, showing northward propagation with a speed of 2.75°/phase. Physical analysis showed that the increased probability of extreme rainfall is associated with intensifying moisture convergence and upward moisture transport during BSISO active phases. The hindcasts from the Climate Forecast System version 2 have been used to evaluate the modulations of BSISO on extreme rainfall and associated predictability. It was shown that the Climate Forecast System version well reproduces the modulations of BSISO on extreme rainfall within 2 weeks. These results demonstrate the feasibility to develop medium‐to‐extended‐range probabilistic forecasts of extreme rainfall for southeastern China.

show abstract

Section: Predictability Of Extreme Rainfall In Cfsv2mentioning

confidence: 99%