In July-August 2022, Yangtze River Valley (YRV) experienced unprecedented hot summer, with the number of heatwave days exceeding climatology by four standard deviations. The heatwaves and associated severe droughts affected about 38 million people and caused devastating economic losses of about five billion US dollars. Here we present convergent empirical and modelling evidence to show that the record-breaking Pakistan rainfall, along with the 2022 tripe-dip La Niña, produces anomalous high pressure over YRV, causing intense heatwaves. The La Niña-induced second-highest sea surface temperature gradient in the equatorial western Pacific suppresses western Pacific convection and extends the subtropical high westward. More importantly, the tremendous diabatic heating associated with the unprecedented Pakistan rainfall reinforces the downstream Rossby wave train, extending the upper-level South Asia High eastward and controlling the entire YRV. The overlay of the two high-pressure systems sustains sinking motion and increases solar radiation reaching the ground, causing recurrent heat waves.

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Abstract. The modern instrumental record (1979–2006) is analyzed in an attempt to reveal the dynamical structure and origins of the major modes of interannual variability of East Asian summer monsoon (EASM) and to elucidate their fundamental differences with the major modes of seasonal variability. These differences are instrumental in understanding of the forced (say orbital) and internal (say interannual) modes of variability in EASM. We show that the leading mode of interannual variation, which accounts for about 39% of the total variance, is primarily associated with decaying phases of major El Nino, whereas the second mode, which accounts for 11.3% of the total variance, is associated with the developing phase of El Nino/La Nina. The EASM responds to ENSO in a nonlinear fashion with regard to the developing and decay phases of El Nino. The two modes are determined by El Nino/La Nina forcing and monsoon-warm ocean interaction, or essentially driven by internal feedback processes within the coupled climate system. For this internal mode, the intertropical convergence zone (ITCZ) and subtropical EASM precipitations exhibit an out-of-phase variations; further, the Meiyu in Yangtze River Valley is also out-of-phase with the precipitation in the central North China. In contrast, the slow and fast annual cycles forced by the solar radiation show an in-phase correlation between the ITCZ and subtropical EASM precipitation. Further, the seasonal march of precipitation displays a continental-scale northward advance of a rain band (that tilts in a southwest-northeastward direction) over the entire Indian and East Asian summer monsoon from mid-May toward the end of July. This uniformity in seasonal advance suggests that the position of the northern edge of the summer monsoon or the precipitation over the central North China may be an adequate measure of the monsoon intensity for the forced mode, while the intensity of the internal mode of EASM variability should measured by the intensity of Meiyu. Given the fact that the annual modes share the similar external forcing with orbital variability, the results presented here may help to understand the differences in the EASM variability on the interannual and orbital time scales.

Northeast China (NEC) is located between the subtropical monsoon and temperate-frigid monsoon regions and exhibits two successive rainy seasons with different natures: the northeast cold vortex rainy season in early summer (May-June) and the monsoon rainy season in late summer (July-August).Summer rainfall over NEC (NECR) has a fundamental in uence on society, yet its successful seasonal prediction remains a long-term scienti c challenge to current dynamical models. The poor NECR prediction skill is partly attributed to the large NECR variability at both the interannual and interdecadal time scales. Here, we focus on the oceanic drivers of the late summer NECR variability and associated physical processes at interannual time scale. Then, we establish an empirical prediction model to predict the interannual variability of summer NECR at one-month lead time (in June). The analysis of observations spanning 40 years reveals three physically and synergistically in uencing predictors of the late summer NECR interannual variability. Above-normal NECR is preceded in the previous spring by (a) warm sea surface temperature (SST) anomalies in the tropical northern Indian Ocean, (b) a positive thermal contrast tendency in the tropical West-East Paci c SST, and (c) a positive tendency of the North Atlantic tripolar SST. These precursors enhance the anomalous low-level anticyclone over the Northwest Paci c and southerly anomalies over NEC in late summer, which are bene cial to enhancing NECR. An empirical prediction model built on these three predictors achieves a forecast temporal correlation coe cient (TCC) skill of 0.72 for 1961-2019, and a 17-year (2003-2019) independent forecast shows a signi cant TCC skill of 0.70. The skill is substantially higher than that of ve state-of-the-art dynamical models and their ensemble mean for 1979-2019 (TCC=0.24). These results suggest that the proposed empirical model is a very meaningful approach for the prediction of NECR, although the dynamical prediction of NECR has considerable room for improvement.