Skilful Forecasts of Summer Rainfall in the Yangtze River Basin from November  被引量:2

在线阅读下载全文

作  者:Philip E.BETT Nick DUNSTONE Nicola GOLDING Doug SMITH Chaofan LI 

机构地区:[1]Met Office Hadley Centre,FitzRoy Road,Exeter EX13PB,UK [2]Center for Monsoon System Research,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China [3]College of Earth and Planetary Sciences,University of the Chinese Academy of Sciences,Beijing 100049,China

出  处:《Advances in Atmospheric Sciences》2023年第11期2082-2091,共10页大气科学进展(英文版)

基  金:supported by the UK–China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund

摘  要:Variability in the East Asian summer monsoon(EASM)brings the risk of heavy flooding or drought to the Yangtze River basin,with potentially devastating impacts.Early forecasts of the likelihood of enhanced or reduced monsoon rainfall can enable better management of water and hydropower resources by decision-makers,supporting livelihoods and major economic and population centres across eastern China.This paper demonstrates that the EASM is predictable in a dynamical forecast model from the preceding November,and that this allows skilful forecasts of summer mean rainfall in the Yangtze River basin at a lead time of six months.The skill for May–June–July rainfall is of a similar magnitude to seasonal forecasts initialised in spring,although the skill in June–July–August is much weaker and not consistently significant.However,there is some evidence for enhanced skill following El Niño events.The potential for decadal-scale variability in forecast skill is also examined,although we find no evidence for significant variation.

关 键 词:seasonal forecasting interannual forecasting flood forecasting Yangtze basin rainfall East Asian summer monsoon 

分 类 号:P457.6[天文地球—大气科学及气象学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象