Search

Thundersnow is a special kind of thunderstorm that combines snowfall and lightning. A 10‐year thundersnow climatology over China was obtained based on observations during 2008–2017. Our results show that thundersnows are widely distributed in China, and most of the high‐frequency areas are located in the Tibetan Plateau and northeastern China. The average frequency of thundersnow decreases with decreasing altitude, and thundersnow usually occurs at low‐altitude stations once every 10 years. Thundersnow, which likely induces great total snowfall depths, appears mostly in spring, autumn and late winter and can occur in high‐altitude areas in summer. The blizzard probability on a thundersnow day is 12.7%. The percentage of positive cloud‐to‐ground lightning of winter thundersnow is approximately 20.7%, which is lower than those in other seasons. The negative phase of the Arctic Oscillation and anomalous western North Pacific anticyclone are favorable background conditions for thundersnow events. Plain Language Summary: Though the snowfall process is different from common rainfall processes that are accompanied by lightning, it can also occasionally produce lightning. This special type of thunderstorm is called thundersnow. It can induce heavy snowfall, which results in partial paralysis of modern cities. Electrified winter clouds may pose an aviation hazard. Although the frequency of thundersnow is low, it is widely distributed in China. Thundersnow can occur throughout the year, mainly in February‐May and October‐November. Thundersnow events increase the probability of blizzards, especially in the Shandong Peninsula in spring, North China and the Changbai Mountain in autumn, and the middle and lower reaches of the Yangtze River basin and Bohai Rim in winter. The variations of the thundersnow number are closely associated with extratropical atmospheric circulation anomalies. The climatological and atmospheric conditions of thundersnow in China that are revealed by this study help establish an important basis for thundersnow forecasting. Key Points: A 10‐year climatology of thundersnow in China was revealed for the first timeThe high‐frequency areas of thundersnow are mainly located in the Tibetan Plateau and northeastern ChinaThundersnow is significantly influenced by the Arctic Oscillation and associated with the anomalous western North Pacific anticyclone [ABSTRACT FROM AUTHOR]

Using precipitation data from weather stations in China and reanalysis data from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), the inter‐annual and inter‐decadal variability of early‐summer (May–June) and late‐summer (July–August) precipitation (hereinafter referred to as MJP and JAP, respectively) over northeast China (NEC) and their background circulation during 1951–2016 were analysed. The following new findings have been highlighted: (a) There are significantly different inter‐annual and inter‐decadal variability characteristics between MJP and JAP over NEC. The inter‐annual variability of MJP is independent from that of JAP, while the inter‐decadal variability of the former is opposite to that of the latter. A significant shift to more MJP (less JAP) occurred in the early 2000s (late 1990s). (b) In terms of the inter‐annual timescale, the large‐scale atmospheric circulations‐associated MJP is notably different from JAP over NEC. The variation in MJP is mainly dominated by the northeast China low (NECL) and the Okhotsk blocking high (OBH), while JAP is mainly influenced by the western Pacific subtropical high (WPSH), the NEC south wind (NESW), and the NECL. (c) On the inter‐decadal timescale, MJP is associated with the inter‐decadal variation of the East Asia/Pacific (EAP) teleconnection, while JAP is closely related to the inter‐decadal variation of the NECL and NESW. When the EAP is in a positive phase, MJP is more than average. Furthermore in late summer, the strong NECL and NESW are both of benefit to the convergence of water vapour from the tropical southwest and East Asian subtropical westerlies over NEC, which contributes to the more JAP than average. [ABSTRACT FROM AUTHOR]

By using the one-month‑lead predictions from the Climate Forecast System version 2 (CFSv2), this study evaluates the predictability of the unprecedented heatwaves hitting the Yangtze River Valley (YRV) and Tibetan Plateau (TP) in 2022 late summer. CFSv2 successfully reproduces the central China heatwaves, but shows distinct performances between the YRV and TP. Specifically, CFSv2 exhibits stronger ability to capture TP heatwaves that is close to the highest historical prediction record, whereas the predicted extremity of the YRV heatwaves is underestimated compared to the observations. The accurate simulation of the intense upper-level circumglobal teleconnection (CGT) pattern, particularly for the East Asia CGT center (CGT EA), is essential for the success predictions of high temperature anomalies, due to the strong and accurate linkage between CGT EA and YRV/TP heatwaves in CFSv2. The intense CGT pattern is associated with a stronger model response to developing La Niña in CFSv2, quite different from the observed leading contribution from the unprecedented Pakistan rainfall. The impacts of developing La Niña and Pakistan rainfall on the intense CGT pattern are significantly overestimated and underestimated by CFSv2, respectively. Additionally, the La Niña-forced enhancement of lower-level western Pacific subtropical high (WPSH) plays another important role in YRV heatwaves, but the reproduction of WPSH intensity is unable to reflect YRV heatwaves in CFSv2 due to the southeastward shift of the predicted WPSH location, which should be responsible for the underestimated YRV heatwaves. The model improvements in aspect of the Pakistan rainfall, El Niño-Southern Oscillation–CGT linkage and lower-level WPSH location should help effectively predict the central China heatwaves in the future. • CFSv2 successfully predicts the central China heatwaves in 2022 late summer. • The accurately predicted CGT is essential for the reproduction of heatwaves. • La Niña leads to the intense CGT in CFSv2 rather than Pakistan rainfall in observation. [ABSTRACT FROM AUTHOR]