Affiliation:
1. Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan University Shanghai China
2. Chinese Academy of Meteorological Sciences Beijing China
3. College of Physics and Technology Suzhou University of Science and Technology Suzhou China
4. Laboratory for Climate Studies National Climate Research Center, China Meteorological Administration (CMA) Beijing China
5. College of Physical Science and Technology Yangzhou University Yangzhou China
Abstract
AbstractThis study investigates the connection between significant sea surface temperature (SST) anomalies in the North Pacific during boreal spring (February–April, FMA) and the subsequent South China Sea (SCS) summer monsoon (SCSSM) onset. The SST anomalies, similar to the Pacific meridional mode (PMM), referred to as the PMM+ mode, are defined to examine the new influencing factor on the SCSSM onset. Our findings reveal that the (February–March–April, FMA) PMM+ has a noteworthy positive correlation with the subsequent May SCSSM onset date, with this correlation being minimally affected by the El Niño–Southern Oscillation (ENSO) during preceding winter. A robust positive PMM+ in boreal spring can be persist until May via atmosphere–ocean interaction. The cooling area over Western North Pacific would reduce precipitation heating, thereby generating Rossby waves that reinforce the formation of the anomalous anticyclone over the SCS. As a result, easterly winds and suppressed convection prevail over the SCS, making the SCSSM break out later than normal. Furthermore, the amplification of anticyclonic vorticity anomalies also strengthens the western North Pacific subtropical high (WNPSH) stronger and shifts its position further westward compared to normal years, thereby blocking active convection to the west of the SCS. Given the weakened relationship between El Niño–Southern Oscillation (ENSO) and the SCSSM onset in recent years, the PMM+ could be considered as a promising preceding signal for the SCSSM onset, thus holding significant implications for the SCSSM prediction efforts.
Funder
National Natural Science Foundation of China
National Key Research and Development Program of China