气候变化领域集成服务门户(CCPortal): Deep learning for bias correction of MJO prediction

CCPortal

DOI	10.1038/s41467-021-23406-3
	Deep learning for bias correction of MJO prediction
	Kim H.; Ham Y.G.; Joo Y.S.; Son S.W.
发表日期	2021
ISSN	2041-1723
卷号	12 期号:1
英文摘要	Producing accurate weather prediction beyond two weeks is an urgent challenge due to its ever-increasing socioeconomic value. The Madden-Julian Oscillation (MJO), a planetary-scale tropical convective system, serves as a primary source of global subseasonal (i.e., targeting three to four weeks) predictability. During the past decades, operational forecasting systems have improved substantially, while the MJO prediction skill has not yet reached its potential predictability, partly due to the systematic errors caused by imperfect numerical models. Here, to improve the MJO prediction skill, we blend the state-of-the-art dynamical forecasts and observations with a Deep Learning bias correction method. With Deep Learning bias correction, multi-model forecast errors in MJO amplitude and phase averaged over four weeks are significantly reduced by about 90% and 77%, respectively. Most models show the greatest improvement for MJO events starting from the Indian Ocean and crossing the Maritime Continent. © 2021, The Author(s).
语种	英语
scopus关键词	air-ice interaction; atmospheric convection; correction; error analysis; machine learning; Madden-Julian oscillation; prediction; sampling bias; socioeconomic conditions; weather forecasting; article; deep learning; Indian Ocean; oscillation; prediction; skill; Indian Ocean
来源期刊	Nature Communications
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/251434
作者单位	School of Marine and Atmospheric Sciences, Stony Brook University, New York, NY, United States; Department of Oceanography, Chonnam National University, Gwangju, South Korea; School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
推荐引用方式 GB/T 7714	Kim H.,Ham Y.G.,Joo Y.S.,et al. Deep learning for bias correction of MJO prediction[J],2021,12(1).
APA	Kim H.,Ham Y.G.,Joo Y.S.,&Son S.W..(2021).Deep learning for bias correction of MJO prediction.Nature Communications,12(1).
MLA	Kim H.,et al."Deep learning for bias correction of MJO prediction".Nature Communications 12.1(2021).