Near-surface wind variability in Prydz Bay and Amery Ice Shelf region, East Antarctica: A four-decade SOM analysis

被引:0
|
作者
Yu, Lejiang [1 ]
Zhong, Shiyuan [2 ]
Xiao, Enzhao [1 ]
Zhang, Tijun [1 ]
Sun, Bo [1 ]
机构
[1] Polar Res Inst China, MNR Key Lab Polar Sci, Shanghai, Peoples R China
[2] Michigan State Univ, Dept Geog Environm & Spatial Sci, E Lansing, MI USA
关键词
Amery Ice Shelf; Antarctic climate; climate variability; near-surface wind fields; Prydz Bay; self-organizing map (SOM); KATABATIC WIND; SEA-ICE; COATS LAND; DRIVERS; SUMMER; REANALYSES; EVENTS; FLOW;
D O I
10.1002/joc.8624
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Near-surface wind fields in the Prydz Bay and Amery Ice Shelf region of East Antarctica play a crucial role in the formation and variability of Antarctic Bottom Water, a cold, dense water mass that sinks and spreads across the deep ocean basins influencing ocean circulation and modulating earth's climate system. This study investigates the primary modes of variability of these wind fields using the self-organizing map (SOM) method and data from the latest version of the European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalyses (ERA5), spanning four decades from 1979 to 2020. While the wind field climatology, characterized by small seasonal variation, is dominated by katabatic and large-scale forcing, the spatial patterns of the primary variability modes are mainly influenced by synoptic system activities. The overall trend in annual wind speed anomalies is positive across the study region, with the exception of the southwestern part and central Prydz Bay. However, significant trends are observed in only two out of nine SOM nodes (nodes 4 and 9), which collectively explain less than 30% of the averaged trends over the region. The interannual variability in the seasonal occurrences of certain nodes is linked to several well-known climate modes, including the El Ni & ntilde;o-Southern Oscillation, the Southern Annular Mode and Zonal Wavenumber 3. Our results provide a reference for forecasting the occurrence frequency of specific patterns, which could help mitigate the impact of extreme wind events through improved forecasting.
引用
收藏
页码:5075 / 5089
页数:15
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