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The September rainfall over Northern China (NC) in 2021 was the heaviest since 1961 and had unprecedented socioeconomic impacts. Holding the hypothesis that the drivers of extreme climate events usually contain extreme factors, we firstly propose the Ranking Attribution Method (RAM) to find the possible air–sea multi-factors responsible for this rainfall event. Via the atmospheric bridges of zonal-vertical circulation and Rossby wave energy propagation, the remote factors of warm sea surface temperature anomalies (SSTA) over the tropical Atlantic, cold SSTA over the tropical Pacific, Southern Annular Mode-like pattern in the Southern Hemisphere and North Pacific Oscillation-like pattern in the Northern Hemisphere jointly strengthened the Maritime Continent (MC) convection and Indian monsoon (IM). Through meridional-vertical circulation, the intensified MC convection enhanced the subtropical high over southern China and induced ascending motion over NC. The local factor of extreme air acceleration in the east Asian upper-level jet entrance region further anchored the location of the southwest-northeast rain belt. The strengthened IM and subtropical high over southern China induced considerable moisture transport to the rain belt via two moisture channels. The combined effect of these extreme dynamic and moisture conditions formed this unprecedented rainfall event. This study suggests that the RAM can effectively reveal the factors that contributed to this extreme rainfall event, which could provide a new pathway for a better understanding of extreme climate events. [ABSTRACT FROM AUTHOR]

Extreme climate events have exerted strong effects on permafrost environments over the past few decades. The occurrence of extreme warming events during the cold season can alter the hydrothermal dynamics of the active layer. Here, we used meteorological and observational soil hydrothermal data to investigate variations in extreme warming events and their impacts on the hydrothermal regimes of the active layer in three permafrost regions in China. The results indicated that the eight analyzed extreme warming indices showed statistically significant increasing trends with differing rates from 1962 to 2019. Prominent differences existed in the mean values and linear trend magnitudes not only among the three permafrost regions but also among the eight indices. Most recorded high-intensity extreme warming events occurred primarily in the past 15 years (2005–2019). The occurrence times of extreme events and the active layer freeze–thaw process codetermined the influential extents of the extreme events on the active layer hydrothermal conditions at the Tanggula permafrost Monitoring Site. Events that occurred from March to April could cause soil temperature to increase with a greater magnitude than that induced by events occurring from October to November. Different event types could also lead to distinct differences in their corresponding influential extents. [ABSTRACT FROM AUTHOR]

In recent decades, wave power (WP) energy from the ocean is one of the cleanest renewable energy sources associated with oceanic warming. In Indo-Pacific Ocean, the WP is significantly influenced by natural climate variabilities, such as El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO). In this study, the impact of major climate variability modes on seasonal extreme WP is examined over the period 1979–2019 using ERA5 reanalysis data and the non-stationary generalized extreme value analysis is applied to estimate the climatic extremes. Independent ENSO influence after removing the IOD impact (ENSO|IOD) on WP are evident over the northeast and central Pacific during December–February, and March–May, respectively, which subsequently shifts towards the western Pacific in June–August (JJA) and September–November (SON). The ENSO|PDO impact on WP exhibits similar yet weaker intensity year round compared to ENSO. Extreme WP responses due to the IOD|ENSO include widespread decreases over the tropical and eastern Indian Ocean, with localized increases only over South China and Philippine seas and Bay of Bengal during JJA, and the Arabian Sea during SON. Lastly, for the PDO|ENSO, the significant increases in WP are mostly confined to the Pacific, and most prominent in the North Pacific. Composite analysis of different phase combinations of PDO (IOD) with El Niño (La Niña) reveals stronger (weaker) influences year-round. The response patterns in significant wave height, peak wave period, sea surface temperatures, and sea level pressure help to explain the seasonal variations in WP. [ABSTRACT FROM AUTHOR]