气候变化领域集成服务门户(CCPortal): An Improved ENSO Ensemble Forecasting Strategy Based on Multiple Coupled Model Initialization Parameters

CCPortal

DOI	10.1029/2019MS001620
	An Improved ENSO Ensemble Forecasting Strategy Based on Multiple Coupled Model Initialization Parameters
	Wang Y.; Huang P.; Wang L.; Wang P.; Wei K.; Zhang Z.; Yan B.
发表日期	2019
ISSN	19422466
起始页码	2868
结束页码	2878
卷号	11 期号:9
英文摘要	Accurate prediction of El Niño–Southern Oscillation (ENSO) at relatively long timescales is propitious to forecasting other climate variables and meteorological disasters. Here, we use a coupled general circulation model, ICMv2, to investigate the influence of an initialization parameter, sea surface temperature (SST)-nudging strength, on ENSO prediction skill in the model's 1981–2010 hindcast experiments and suggest a multiple initialization parameter ensemble (MIPE) forecast as a new ensemble forecasting strategy to improve ENSO prediction skill. Different SST-nudging strengths produce different ENSO prediction skill via the generated various initial values. Selecting initial values closest to the observed SST (represented by reanalysis data) and increasing the ensemble size is inefficient in improving the skill of single initialization parameter ensemble (SIPE) forecasts. With ensemble members from different SST-nudging strength groups, the MIPE forecasts are significantly more skillful than the SIPE forecasts at 1- to 10-month lead time. More than 96% of 20,000 MIPE experiments generated by a Monte Carlo approach have larger anomaly correlation coefficient than SIPE at 1- to 9-month lead time. Our findings suggest that MIPE forecasting is another efficient strategy that can improve ENSO prediction skill besides multimodel and multimember ensembles using different initial values with random disturbances. © 2019. The Authors.
英文关键词	ENSO prediction skill; ICMv2; multiple initialization parameters; SST-nudging strength
语种	英语
scopus关键词	Atmospheric pressure; Climatology; Oceanography; Surface waters; Coupled general circulation models; ENSO prediction skill; ICMv2; Meteorological disasters; multiple initialization parameters; Sea surface temperature (SST); Southern oscillation; SST-nudging strength; Forecasting; El Nino-Southern Oscillation; ensemble forecasting; general circulation model; meteorology; parameter estimation; sea surface temperature
来源期刊	Journal of Advances in Modeling Earth Systems
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156867
作者单位	Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; College of Earth Sciences, University of Chinese Academy of Sciences, Beijing, China; State key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Joint Center for Global Change Studies (JCGCS), Beijing, China; National Marine Environmental Forecasting Center, Beijing, China
推荐引用方式 GB/T 7714	Wang Y.,Huang P.,Wang L.,et al. An Improved ENSO Ensemble Forecasting Strategy Based on Multiple Coupled Model Initialization Parameters[J],2019,11(9).
APA	Wang Y..,Huang P..,Wang L..,Wang P..,Wei K..,...&Yan B..(2019).An Improved ENSO Ensemble Forecasting Strategy Based on Multiple Coupled Model Initialization Parameters.Journal of Advances in Modeling Earth Systems,11(9).
MLA	Wang Y.,et al."An Improved ENSO Ensemble Forecasting Strategy Based on Multiple Coupled Model Initialization Parameters".Journal of Advances in Modeling Earth Systems 11.9(2019).