Extreme cold wave in early November 2021 in China and the influences from the meridional pressure gradient over East Asia  被引量:1

在线阅读下载全文

作  者:Xiang LI Ying-Juan ZHANG Hui GAO Ting DING 

机构地区:[1]National Climate Center,China Meteorological Administration,Beijing 100081,China [2]Beijing Meteorological Service,Beijing 100089,China

出  处:《Advances in Climate Change Research》2022年第6期797-802,共6页气候变化研究进展(英文版)

基  金:National Key R&D Programme of China(2018YFC1505600);National Natural Science Foundation(NSFC42175048).

摘  要:In early November 2021,China experienced its second strongest cold wave event during 1981-2021.Although the Siberian high is considered the main factor influencing cold wave events in East Asia,it was not extremely strong from 4 to November 9,2021.The spatial distribution of the correlation coefficients between the sea level pressure and the daily temperature anomalies shows a monopole pattern,with a notable negative centre in the southern part of the Siberian high monitoring domain.However,the correlation between the sea level pressure and temperature drop presents a typical dipole pattern,with a distinct negative centre in the northern monitoring domain and a positive centre in southern East Asia.During the November 2021 super cold wave process,the sea level pressure anomalies display a dipole pattern with a higher centre in the north and a lower centre in the south owing to the northward shift of the Intertropical Convergence Zone.The meridional pressure gradient index clearly reveals the non-negligible effect of subtropical low-pressure on this super cold wave process,indicating its possibly essential supplementary role in enhancing this process.The above findings provide a new understanding of its mechanism and long-range forecasts.

关 键 词:Cold wave Siberian high Meridional pressure gradient Dipole pattern 

分 类 号:P73[天文地球—海洋科学]

 

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