A tripole pattern of summer surface air temperature anomalies over northern Eurasia and its precursory signals in the tropical Atlantic and northern Asian land

This study investigates the variability of summer surface air temperature (SAT) over northern Eurasia and its precursory signals in the tropical Atlantic and northern Asian land. The leading mode of summer SAT variations features a northern Eurasian SAT tripole (NEST) pattern, with two same‐sign SAT...

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Veröffentlicht in:International journal of climatology 2021-05, Vol.41 (6), p.3688-3704
Hauptverfasser: He, Kejun, Liu, Ge, Wu, Renguang, Li, Jingxin, Wang, Huimei, Yue, Xiaoyuan
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Sprache:eng
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Zusammenfassung:This study investigates the variability of summer surface air temperature (SAT) over northern Eurasia and its precursory signals in the tropical Atlantic and northern Asian land. The leading mode of summer SAT variations features a northern Eurasian SAT tripole (NEST) pattern, with two same‐sign SAT anomaly regions over eastern Europe–western Siberia and the Far East region and an opposite‐sign SAT anomaly region around the Baikal Lake. It is found that sea surface temperature (SST) or SAT anomalies in the tropical Atlantic and rainfall‐soil moisture anomalies around the Baikal Lake during May can modulate the NEST pattern. The SST anomalies in the tropical Atlantic persist from May to summer and induce a downstream zonal wave train across northern Eurasia, consequently causing the variation in the summer NEST pattern. May rainfall anomalies around the Baikal Lake affect the overlying atmospheric circulation during summer through the ‘memory’ effect of soil moisture and the soil moisture‐rainfall interaction, correspondingly modulating the downstream wave train and the associated NEST pattern. Based on the above results, a statistical prediction model is established using the two precursory signals, that is, SAT in the tropical Atlantic and rainfall around the Baikal Lake during May. The leave‐three‐out cross‐validation shows that the model has a high skill in predicting the summer NEST pattern, with a correlation coefficient of 0.51 (significant at the 99.8% confidence level) between observation and prediction during the period 1980–2016. Schematic diagram explaining the NEST pattern.
ISSN:0899-8418
1097-0088
DOI:10.1002/joc.7043