Interdecadal Changes in the Relationship between Wintertime Surface Air Temperature over the Indo-China Peninsula and ENSO

气候学 异常(物理) 反气旋 海面温度 平流 厄尔尼诺南方涛动 半岛 大气环流 地质学 环境科学 大气科学
作者
Juncong Li,Zhiping Wen,Xiuzhen Li,Yuanyuan Guo
出处
期刊:Journal of Climate [American Meteorological Society]
卷期号:35 (3): 975-995 被引量:3
标识
DOI:10.1175/jcli-d-21-0477.1
摘要

Abstract Interdecadal variations of the relationship between El Niño–Southern Oscillation (ENSO) and the Indo-China Peninsula (ICP) surface air temperature (SAT) in winter are investigated in the study. Generally, there exists a positive correlation between them during 1958–2015 because the ENSO-induced anomalous western North Pacific anticyclone (WNPAC) is conducive to pronounced temperature advection anomalies over the ICP. However, such correlation is unstable in time, having experienced a high-to-low transition around the mid-1970s and a recovery since the early 1990s. This oscillating relationship is owing to the anomalous WNPAC intensity in different decades. During the epoch of high correlation, the anomalous WNPAC and associated southwesterly winds over the ICP are stronger, which brings amounts of warm temperature advection and markedly heats the ICP. In contrast, a weaker WNPAC anomaly and insignificant ICP SAT anomalies are the circumstances for the epoch of low correlation. It is also found that substantial southwesterly wind anomalies over the ICP related to the anomalous WNPAC occur only when large sea surface temperature (SST) anomalies over the northwest Indian Ocean (NWIO) coincide with ENSO (viz., when the ENSO–NWIO SST connection is strong). The NWIO SST anomalies are capable of driving favorable atmospheric circulation that effectively alters ICP SAT and efficiently modulates the ENSO–ICP SAT correlation, which is further supported by numerical simulations utilizing the Community Atmospheric Model, version 4 (CAM4). This paper emphasizes the non-stationarity of the ENSO–ICP SAT relationship and also uncovers the underlying modulation factors, which has important implications for the seasonal prediction of the ICP temperature.
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