Linkages of unprecedented 2022 Yangtze River Valley heatwaves to Pakistan flood and triple-dip La Niña

Heatwaves over East Asia have become more frequent and intense, with notable events over the Yangtze River Valley (YRV) in 2013, North China in 2018, and South China in 2020. Heatwaves are typically associated with high-pressure systems that induce subsidence, reduce cloud cover, and increase surface solar radiation. Over the YRV, the western Pacific subtropical High (WPSH) often dominates midsummer circulation and is critical to heatwave formation, while the upper-tropospheric South Asia High (SAH) can also strengthen and maintain heatwaves via promoting descent. The westward expansion of the WPSH frequently coincides with the eastward extension of the SAH, likely through SAH-enhanced divergence and zonal temperature gradients over subtropical East Asia. Tropical sea surface temperature (SST) forcing modulates the WPSH through several pathways: tropical North Atlantic warming can enhance WPSH via a zonal overturning circulation and a Rossby wave response; Indian Ocean warming can suppress western North Pacific convection through the Indo–western Pacific capacitor effect; and ENSO exerts a crucial influence on interannual WPSH variability via air–sea interactions. Two leading WPSH modes have been emphasized: an atmosphere–ocean interaction mode (linked to lingering El Niño effects with Indian Ocean warming and WNP cooling) and a La Niña–forced mode (enhanced WPSH during summertime La Niña). Extratropical teleconnections (e.g., Scandinavian pattern, Silk Road pattern, and the circumglobal teleconnection, CGT) also impact East Asian summer climate by modulating the westerly jet and promoting SAH/WPSH expansions. The CGT, often excited by Indian summer monsoon (ISM) rainfall via diabatic heating, propagates along the westerly jet waveguide. In 2022, the YRV experienced exceptionally intense and prolonged heatwaves in July–August, with regionally averaged SAT and heatwave days anomalies of 2.42 K and 23.12 days, respectively, and HWDs exceeding climatology by four standard deviations. The resulting drought affected about 38 million people and caused large economic losses. Even after removing long-term trends, 2022 remained the hottest midsummer on record (1979–2022). This study aims to understand the causes of the record-breaking heatwave days over the YRV in midsummer 2022. We find that traditional thinking emphasizing La Niña alone cannot explain the extremity; instead, unprecedented Pakistan floods played a leading role. These findings aid understanding and prediction of extreme East Asian heatwaves.

Prior work has established that: (1) High-pressure systems (WPSH at low levels and SAH aloft) are central to East Asian heatwaves via subsidence, reduced cloud cover, and enhanced solar radiation. (2) Tropical SST forcings modulate WPSH: tropical North Atlantic warming induces a zonal overturning circulation leading to enhanced WPSH; Indian Ocean warming triggers Kelvin waves suppressing WNP convection via the Indo–western Pacific capacitor; ENSO strongly influences WPSH interannual variability through coupled air–sea processes. Wang et al. identified two leading WPSH modes: an atmosphere–ocean interaction mode (post–El Niño, Indian Ocean warming and WNP cooling) and a La Niña–forced mode (summer La Niña enhancing WPSH). (3) Extratropical teleconnections, including the Scandinavian pattern, Silk Road pattern, and the CGT, can propagate from the North Atlantic/Eurasia to East Asia, shifting the westerly jet, promoting SAH northeastward and WPSH westward extensions, and fostering heatwaves. ISM rainfall and associated diabatic heating are key in exciting and maintaining the CGT. These frameworks underpin the investigation into why 2022 YRV heatwaves were unprecedented.

Observations and reanalyses: Daily 2-m air temperature from 2,479 CMA stations (1951–2022) were used. Atmospheric circulation (geopotential height, wind) came from ERA5 reanalysis (0.25°×0.25°, 1979–2022). Monthly diabatic heating (JRA-55 diagnostics, 1.25°×1.25°, 1979–2022), monthly rainfall (GPCP v2.3, 2.5°×2.5°, 1979–2022), and SST (ERSSTv5, 2.0°×2.0°, 1854–2022) were analyzed. Midsummer conditions were July–August means. Anomalies were defined relative to 1979–2021 climatology; long-term trends were removed to minimize global warming influences. Heatwave definition: Heatwave days (HWDs) are days when daily maximum temperature exceeds the calendar-day 90th percentile threshold based on a 5-day window. Given strong SAT–HWD correlation over YRV, midsummer-mean SAT anomalies represented heatwave intensity. Statistical tools: Empirical orthogonal function (EOF) analysis, singular value decomposition (SVD), correlation and regression analyses were applied. Stationary wave activity flux (Takaya–Nakamura) diagnosed Rossby wave propagation. Statistical significance used two-tailed Student’s t-tests with n−2 degrees of freedom. Numerical experiments: The CAM6.0 atmosphere model (CESM v2.1; F_2000_climo, 192×288, 32 levels) with prescribed climatological SST/sea ice was used. Control (CTL): forced by monthly climatological SSTs for 25 years; last 20 years used for ensemble mean. Three 20-year sensitivity runs: (i) EXP_SST adds observed 2022 July–August SST anomalies over 15°S–15°N, 100°E–140°W to climatology (La Niña forcing); (ii) EXP_Q adds anomalous diabatic heating over Pakistan–NW India (15°N–35°N, 60°E–80°E) with specified vertical profile (zero below 900 hPa and above 100 hPa; peak double the regional-mean anomaly, tapering to edges); (iii) EXP_Q_SST includes both forcings. Added SST and heating anomalies were scaled by 1.5× 2022 observations to highlight impacts. Model responses assessed as EXP minus CTL ensemble means. Pre-industrial control: A 1000-year fully coupled CESM2 PI control (fixed 1850 forcings; f09_f09_mg17) assessed internal variability contributions and synchronization among CGT, La Niña, Pakistan rainfall, and YRV heatwaves without anthropogenic forcing.

- 2022 YRV heat extremes: Regionally averaged midsummer SAT anomaly was +2.42 K and heatwave days anomaly +23.12 days; HWDs exceeded climatology by 4 standard deviations; 2022 remained the hottest midsummer since 1979 even after detrending. - Circulation anomalies: A barotropic high from the western North Pacific (WNP) to northern India; WPSH 5880-gpm isopleth extended ~40° longitude westward; strengthened midlatitude westerlies near 45°N and SAH ridge stretched east to ~130°E, jointly controlling the YRV. - La Niña influence: The 2022 triple-dip La Niña showed enhanced and westward-shifted SST anomalies from winter to midsummer, yielding an equatorial western Pacific zonal SST gradient >2.0 SD (2nd strongest since 1979; stronger than 2020: 0.63 SD and 2021: 0.59 SD). The zonal SST gradient correlated strongly with the La Niña–forced WPSH mode (WPSH PC2) at r=0.78 (p<0.001). However, WPSH PC2 correlated only modestly with YRV SAT (r=0.44, p<0.01) and could not account for upper-reach YRV/eastern Tibet high pressure. - Pakistan rainfall and CGT: Pakistan’s July–August 2022 rainfall exceeded climatology by ~3 SD and set a historical record (>500 mm). Pakistan rainfall and YRV SAT were positively coupled interannually (r=0.55, p<0.001) and intraseasonally in 2022 (r=0.52). After removing ENSO, their correlation remained r=0.49 (p<0.01), indicating a largely ENSO-independent linkage. - Rossby waves and CGT: Upper-tropospheric anomalies in 2022 exhibited a CGT-like wave train with strong resemblance to the YRV-associated pattern (pattern correlation PCC=0.80). The CGT’s East Asia high center was closely tied to YRV heat (correlation 0.81, p<0.001). Diabatic heating over Pakistan–NW India reinforced the CGT downstream, extending the SAH northeastward and supporting WPSH westward expansion. - Modeling evidence: CAM6 experiments showed La Niña forcing reproduced the WNP anticyclone and strengthened low-level WPSH; Pakistan diabatic heating produced strong CGT action centers over West and East Asia, enhanced SAH and WPSH, and positive SAT anomalies over the YRV. CGT and SAT anomalies in EXP_Q (Pakistan heating) were stronger than in EXP_SST (La Niña), indicating Pakistan rainfall’s leading role. Combined forcing (EXP_Q_SST) further amplified CGT/SAH/WPSH and produced widespread warming (>0.6 K) from the Tibetan Plateau to YRV, though with a northward bias of the warm center. - Large-sample PI results: In 1000-year CESM2 PI, intense Pakistan rainfall was necessary to form the CGT wave train—especially the East Asia center—and to generate YRV heatwaves. La Niña with normal Pakistan rainfall produced a zonally symmetric seesaw pattern insufficient to explain extreme YRV heat. - Overall mechanism: An overlay of enhanced low-level WPSH (aided by La Niña) and intensified upper-level SAH/CGT (driven by Pakistan diabatic heating) sustained subsidence and increased surface solar radiation over the YRV, causing recurrent and unprecedented heatwaves.

The study set out to explain why YRV heatwaves in midsummer 2022 were unprecedented. Analyses demonstrate that while the triple-dip La Niña enhanced the zonal SST gradient and strengthened the low-level WPSH, it could not alone account for the extremity or for the upper-level anomalies spanning the entire YRV and eastern Tibetan Plateau. The decisive factor was the exceptional Pakistan rainfall and associated diabatic heating, which excited and reinforced a robust CGT wave train. This teleconnection displaced the jet northward, extended the SAH northeastward over East Asia, and—together with the westward-extended WPSH—produced a superposition of high-pressure systems over the YRV. The resulting persistent subsidence reduced cloud cover and increased downwelling solar radiation, directly intensifying heatwaves. Statistical relationships (strong Pakistan rainfall–YRV SAT coupling, robust CGT similarity, and independence from ENSO) and targeted CAM6 sensitivity experiments coherently support this mechanism. The findings refine the understanding of heatwave drivers in East Asia, emphasizing the joint roles of tropical Pacific SST gradients and South Asian monsoon diabatic heating, and highlight the predictive value of monitoring Pakistan/ISM rainfall and CGT activity in addition to ENSO state.

This work provides convergent observational, statistical, and modeling evidence that record-breaking Pakistan rainfall, together with an anomalously strong equatorial western Pacific SST gradient during the 2022 triple-dip La Niña, produced overlapping high-pressure systems (westward-extended WPSH and northeastward-stretched SAH under a reinforced CGT), leading to unprecedented YRV heatwaves. Pakistan rainfall played the leading role by exciting a strong CGT and extending the SAH; La Niña contributed by enhancing the low-level WPSH. Future directions include elucidating the drivers of the extreme 2022 Pakistan rainfall—potentially involving positive NAO forcing at the Atlantic jet exit, enhanced atmospheric rivers from the Arabian Sea, and feedbacks with CGT—assessing their predictability, and disentangling similarities and differences in mechanisms of heatwaves over the Tibetan Plateau versus the YRV. Model improvements to better represent the subtropical jet and teleconnections will further enhance predictive skill for East Asian heat extremes.

- Model bias: CAM6 control climate exhibits a northward-displaced subtropical westerly jet, leading to a northward shift of simulated East China warm anomalies relative to observations. - Forcing idealizations and scaling: Sensitivity experiments applied prescribed SST and idealized diabatic heating profiles, scaled to 1.5× observed 2022 anomalies to emphasize responses, which may affect amplitude and pattern realism. - Attribution of Pakistan rainfall: While Pakistan rainfall’s role is robust, its causes in 2022 (e.g., influence of NAO, atmospheric rivers, internal variability) are not fully resolved and warrant further study. - Trend removal: Long-term trends were removed to minimize global warming effects; while appropriate for isolating interannual mechanisms, this may omit interactions between anthropogenic warming and circulation anomalies affecting heatwave intensity.