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In the background of long‐term global warming, the northern hemisphere experienced an extremely hot summer in 2022 with the hottest on record for Europe and China, and the second‐hottest for North America and Asia. The hot summer concurred with a triple‐dip La Niña in the tropical Pacific. Given the extremity of the hot summer in East Asia in 2022, in this work, we examine the associated atmospheric circulation and assess the real‐time predictions from the North American Multimodel Ensemble (NMME). Also, we identify the contributions of long‐term warming trends, sea surface temperature (SST) forcing, and an atmospheric feedback to the hot summer. The hot summer in East Asia in 2022 is due to the extremely strong and westward expanded western Pacific subtropical high. That leads to cloud cover reduction and increases in net downward shortwave radiation at the surface, and further strengthens the positive surface air temperature (SAT) anomalies. In contrast, the seasonal‐interannual variation of SST has a minor impact. Thus, the hot summer is mainly associated with the long‐term trend and amplified by the positive feedback among the SAT, cloud cover, and net downward shortwave radiation. NMME with the initial conditions in May 2022 predicts positive SAT anomalies in most regions of East Asia, but does not capture the observed spatial distribution pattern and amplitudes. The failure implies the challenge of state‐of‐the‐art climate models in predicting such extreme events. Plain Language Summary: In the context of global warming, the northern hemisphere experienced an extremely hot summer in 2022 with the hottest on record for Europe and China. The hot summer concurred with a triple‐dip La Niña in the tropical Pacific during 2020–2023. In this work, we examine the causes and assess the real‐time predictions and predictability of the hot summer in East Asia. The hot summer in 2022 is due to the extremely strong and westward expanded western Pacific subtropical high. For the averages in the main hot summer region in East Asia in 2022, the largest contribution is from the long‐term trend (∼50%), and for the rest 50%, half of them is from the feedback among atmospheric circulation‐surface air temperature‐cloud cover‐net downward shortwave radiation. In contrast, the seasonal‐interannual components of the global sea surface temperatures play a secondary role. Multi‐model ensemble with the initial conditions in May 2022 predicts positive surface air temperature anomalies in most regions of East Asia, especially in August. However, compared with the observations, both the spatial distribution pattern of surface air temperature anomalies and their amplitudes have distinguished biases in the North American Multimodel Ensemble predictions. The failure implies the challenge of state‐of‐the‐art climate models in predicting such extreme events. Key Points: The hot summer in East Asia in 2022 is due to the extremely strong and westward expanded western Pacific subtropical highThe hot summer is caused by the long‐term trend and amplified by positive feedback among the surface air temperature (SAT), cloud, and downward shortwave radiationNorth American Multi‐model Ensemble does not capture the observed spatial distribution pattern and amplitudes of SAT anomalies [ABSTRACT FROM AUTHOR]

The Meiyu season is a typical rainy season in East Asia that is controlled by summer monsoon. Despite extensive research on its impact, it is unclear how urbanization modifies precipitation during the Meiyu season in the background of the monsoon influence. To address this gap, this study investigated the effects of urbanization and monsoon on the modification of precipitation during the Meiyu season (PDM) in the megacity of Shanghai, China. Through homogenization analysis of the original observational data, we assessed the temporal and spatial variation in PDM in Shanghai during two stages of urbanization. Our findings revealed that both total precipitation and extreme daily precipitation during the Meiyu season in Shanghai have significantly increased since 1961. The spatial heterogeneity of PDM has also enhanced during the rapid urban process that has occurred since 1986. The long-term trend of increasing precipitation in Shanghai showed a synchronous variation with the East Asian subtropical summer monsoon (EASM) in 1961–2021. Over the interannual time scale, the significant positive correlation between PDM and EASM during the slow urbanization period (Stage 1: 1961–1985) changed to a non-significant correlation during the rapid urbanization period (Stage 2: 1986–2021), which was associated with the enhanced convective precipitation in Shanghai during the Meiyu season. Urbanization induced more convective precipitation and further weakened the association between PDM and EASM over the central city and nearby areas during Stage 2. The rapid urbanization process also resulted in increased differences in near-surface wind between urban and non-urban areas, which facilitated more PDM over the central city due to the urban friction effect and wind shear in Stage 2. Furthermore, our analysis suggests that the increase in precipitation may be associated with the enhanced coupling of cold air intrusion with the warmer climate background due to the urban heat effect occurring in Stage 2. These findings contribute to a better understanding of how urbanization and monsoons affect PDM in East Asian megacities and serve as a unique reference for climate prediction in this region. [ABSTRACT FROM AUTHOR]

The sea-gale process (SGP) is a significant and disastrous weather event for the marine industry. However, the sub-seasonal predictability of SGP remains unclear. In this study, we investigate the influence of low-frequency oscillation on SGP in the Yangtze River estuary from November to April, and its implications for sub-seasonal prediction. We noted that SGPs have a close relationship with the 10~30 day low-frequency component of the 10-m wind speed in the Yangtze River estuary, and typically occur during the peak phase of the low-frequency oscillation. The 10~30 day low-frequency oscillation of 10-m wind was found to be linked to the eastward propagation of extratropical Rossby waves from the North Atlantic across Europe to East Asia. This Rossby wave leads to the low-frequency oscillation of the Siberian high pressure and Japan Sea low pressure, which is indicative of the 10~30 day low-frequency oscillations of the 10-m wind speed in the Yangtze River Estuary. A sea-gale process index (SGPI) was constructed based on the low-frequency oscillation of the Siberian high and the Japan Sea low in order to predict SGPs at the sub-seasonal time scale. Hindcast and real-time forecasts showed that 2/3 of SGPs can be predicted with a leading time of 10~30 days, and that good sub-seasonal predictions of SGPs are connected with strong low-frequency oscillations at the initial forecast time. Therefore, SGPI can be adopted for the sub-seasonal prediction of SGPs in the Yangtze River Estuary. [ABSTRACT FROM AUTHOR]

Following the description of the basic climatic characteristics of Meiyu in East Asia, we present a comprehensive review of multi–time scale variabilities of the Meiyu together with the long‐term change of extreme precipitation during the Meiyu in this paper. The dynamic prediction skills of the Meiyu on subseasonal to seasonal time scales are further described and illustrated by using present numerical prediction models. For the multi–time scale variabilities of the East Asian Meiyu, they are closely related with the impacts of both quasi‐biweekly and 30–60 day oscillation from both the tropics and the middle and high latitudes on intraseasonal time scale, the influences of El Niño–Southern Oscillation and the Tropospheric Biennial Oscillation on interannual time scale, the variations of East Asian summer monsoon on decadal time scale, and the continued impacts of global warming, Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation on interdecadal scale and long‐term trend. Under the background of the global warming and the influences of urbanization and aerosol effects, the Meiyu shows some specific characteristics including significantly weakened continuous rain, uneven spatial distribution of precipitation, and increased (decreased) number of strong (weak) precipitation days. Improvements of prediction on rain belt location, total precipitation amount, persistent heavy precipitation events, and low‐frequency variability oscillation during Meiyu season have been achieved with the improved dynamic models of the Beijing Climate Center since 2010. Key Points: Meiyu's variabilities are related with intraseasonal oscillation, interannual to multidecadal oscillation of ocean, and global warmingMeiyu impacted by global warming, urbanization, and aerosol effects exhibits stronger rainfall eventsImprovements of prediction of East Asian Meiyu on multi‐time scale have been achieved with the present operational climate models [ABSTRACT FROM AUTHOR]