Dominant Modes of China Summer Extreme Heat Waves Driven by Global Sea Surface Temperature and Atmospheric Internal Variability
This study applies the maximum temperatures at more than 2000 Chinese stations to investigate the dominant modes of China summer heat waves (HWs). The first empirical orthogonal function (EOF) mode of the HW days reflects an increased frequency of HWs in northern China (NC), while the second and thi...
| Main Authors: | , , , , |
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| Format: | Text |
| Language: | unknown |
| Published: |
Columbia University
2019
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.7916/d8-4hsd-mh96 https://academiccommons.columbia.edu/doi/10.7916/d8-4hsd-mh96 |
| Summary: | This study applies the maximum temperatures at more than 2000 Chinese stations to investigate the dominant modes of China summer heat waves (HWs). The first empirical orthogonal function (EOF) mode of the HW days reflects an increased frequency of HWs in northern China (NC), while the second and third modes represent two distinct interannual modes, with key regions over the Yangtze River valley (YRV) and southern China (SC), respectively. The NC HWs are possibly associated with the Atlantic–Eurasian teleconnection, showing zonally propagating wave trains over the North Atlantic and Eurasian continent. The YRV HWs are proposed to be linked to the North Atlantic Oscillation, which may trigger a southeastward-propagating wave train over northern Russia and East Asia that results in a high pressure anomaly over the YRV. The SC HWs are obviously dominated by the Indian Ocean and northwest Pacific warm SSTs owing to the transition from the preceding El Niño to La Niña, which excites above-normal highs over SC. The anomalously high pressures over NC, the YRV, and SC are usually accompanied by descending air motions, clear skies, decreased precipitation, and increased solar radiation, which jointly cause a drier and hotter soil condition that favors the emergence of HWs. The GFDL HiRAM experiments are able to reproduce the historical evolution of NC and SC HWs, but fail to capture the YRV HWs. The correlation coefficient between model PC1 (PC2) and observed PC1 (PC3) for the period of 1979–2008 is 0.65 (0.38), which significantly exceeds the 95% (90%) confidence level, indicating that this model has a more faithful representation for the SST-forced HWs. |
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