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By observing well‐known sea surface temperature (SST) indices and outputs from Climate Forecast System version 2 (CFSv2) hindcasts and predictions, in this study, we developed a hybrid statistical downscaling prediction model (HSDPM) based on a timescale decomposition approach, which effectively improved the forecasting ability of summer (June–August) precipitation over Hainan Island (HNSP) in China; this precipitation presented multiple obvious timescale variabilities. We found that the interannual variability of the HNSP is closely related to the observed North Atlantic tripole SST anomalies in the preceding winter and the summer sea level pressure over the South China Sea by CFSv2 predicted in March. On the other hand, the interdecadal variability in the HNSP is linked to the prewinter Pacific Interdecadal Oscillation (PDO) according to the observations, the CFSv2 predictions of the summer surface air temperature over the tropical central‐east Pacific. On this basis, both the interannual and interdecadal components of the HNSP are effectively predicted using the corresponding predictors via multiple regression; thus, the HSDPM is ultimately established by combining the above two components. Compared with the original CFSv2 model, the HSDPM model achieves a considerable improvement in performance in predicting the HNSP. Specifically, the temporal correlation coefficient, ratio of root‐mean‐square error and anomaly sign consistency rate between the observed and HSDPM‐predicted HNSPs are 0.70, 17.4% and 80.5%, respectively, which are significantly greater than the above three forecasting index values of 0.23, 38.3% and 48.8%, respectively, obtained from the original CFSv2 predictions. The application of the HSDPM may be beneficial for drought and flood prevention and mitigation in Hainan Island. [ABSTRACT FROM AUTHOR]

Annual maximum 7-day precipitation has increased over South China since 1961. Ten CMIP6 climate models simulate either weaker increases in risk ratio than observed or nonsignificant changes. [ABSTRACT FROM AUTHOR]

In 2021, the Yangtze–Huaihe River Basin (YHRB) of China underwent normal precipitation during the classical Meiyu period in June–July but suffered extreme precipitation and severe floods in August. The present study revealed that the extreme heavy precipitation anomalies over the YHRB region were closely related to the combined effect of the strong western North Pacific anomalous anticyclone (WNPAC) and East Asian middle–high latitude circulation anomalies in August 2021. Moreover, the background of sea surface temperature (SST) anomalies was a strong eastern-Pacific La Niña event that rapidly decayed in spring and a second La Niña emerged in late summer, accompanied by a weak tropical Indian Ocean warming and a strong tropical Atlantic warming in summer. The rapidly decaying La Niña event and the weak tropical Indian Ocean warming alone seem to be insufficient to induce the strong WNPAC in August 2021. Observational evidence and numerical experiments suggest that the rapid tropical Atlantic warming from late spring to summer observably contributed to the enhancement and westward shift of the WNPAC, and the cold SST anomalies in the eastern tropical Pacific associated with the second La Niña event also provided favorable conditions for a strong WNPAC in August 2021. Overall, rapid tropical Atlantic warming and the development of the second La Niña contributed to the strong WNPAC in August 2021, while the maintenance mechanism of the East Asian middle–high latitude circulation anomalies that controlled cold air activity remains unclear. [ABSTRACT FROM AUTHOR]

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]

In this paper, the spatial and temporal characteristics of convective precipitation (CP) and large-scale precipitation (LSP) in southern China during 1980–2020 are analyzed using monthly mean precipitation data from MERRA-2. In addition, the possible effects of relative humidity on CP and LSP are explored. The results indicate the following. (1) The LSP dominates the proportion of total precipitation (TP). Both LSP and CP are more prevalent in the south and less prevalent in the north, but there is a difference in the regions of their maximum centers. (2) Significant interannual and seasonal variations are observed in precipitation. TP and LSP tended to be higher than average after the 1990s, while for the CP, a significant negative trend has dominated the past ten years. There are significant increasing trends for TP and LSP, with area-averaged linear trends of 78.1 mm/decade and 85.9 mm/decade, respectively, while that of CP is − 17.1 mm/decade. The increasing trends of LSP are mainly contributed by the precipitation of summer and autumn. (3) The variations of LSP are affected by relative humidity in the troposphere, while CP is only influenced by the changes in relative humidity due to air temperature or specific humidity. The trend of relative humidity is − 0.33%/decade, mainly due to rising temperature in the troposphere. (4) Changes in relative humidity caused by temperature or specific humidity alone act on large-scale precipitation through both interannual and interdecadal processes, causing large-scale precipitation to increase, and the convective precipitation is mainly affected by the interdecadal processes. [ABSTRACT FROM AUTHOR]

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 influence on society, yet its successful seasonal prediction remains a long-term scientific 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 1-month lead time (in June). The analysis of observations spanning 40 years (1963–2002) reveals three physically and synergistically influencing 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 Pacific SST, and (c) a positive tendency of the North Atlantic tripolar SST. These precursors enhance the anomalous low-level anticyclone over the western North Pacific and southerly anomalies over NEC in late summer, which are beneficial to enhancing NECR. An empirical prediction model built on these three predictors achieves a forecast temporal correlation coefficient (TCC) skill of 0.72 for 1961–2019, and a 17-year (2003–2019) independent forecast shows a significant TCC skill of 0.70. The skill is substantially higher than that of five 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 meaningful approach for the prediction of NECR, although the dynamical prediction of NECR has considerable room for improvement. [ABSTRACT FROM AUTHOR]

Persistent extreme heat events (PEHEs) exert a more negative impact on society, including agriculture, plant phenology, power production and human health, compared to general EHEs. The temporal and spatial characteristics of summer PEHEs in eastern China were analysed based on a daily maximum temperature dataset from 759 stations over the period of 1961–2018. The results show the following: Persistent distributions of PEHEs show that they are characterized by an exponential decay with a drop in the decay rate. In terms of spatial distribution, there is an apparent regional difference in the duration of PEHEs. North China is dominated by multi-frequency and short-duration EHEs, while South China is the opposite. PEHEs in North China and the Huanghuai region mainly occur in June-July but mostly in July and August in South China. Strongly responding to global warming, the frequency and duration of PEHEs in North China have increased since the 1990s. However, the frequency of PEHEs in North China and the Huanghuai region has shown opposite trends in June-July since the beginning of the twenty-first century. Affected by the atmospheric circulations, the regional differences in PEHE frequency are also apparent. Since the beginning of the twenty-first century, the PEHEs in North China and the Huanghuai area have shown an increasing trend in August. The short-term PEHEs in the middle and lower reaches of the Yangtze River and South China increased rapidly in the 2000s, while long-term PEHEs increased in the 2010s. This study implies that attention should be paid to not only the frequency of EH days but also to the persistence of EHE which is a key characteristic of damaging EH. [ABSTRACT FROM AUTHOR]

Have the onset dates of regional extreme hot events threatening human health been advancing? Based on the daily maximum temperature data from Chinese metrological stations and reanalysis datasets, we quantified the variations in the onset dates of the first regional extreme hot events (EHE-ODs) and revealed the early-onset characteristics of the regional EHEs in southeastern China. The results show that the EHE-ODs in southeastern China have a significant early-onset trend with an average advanced rate of 7.1 days/decade since 1987. The rate in the middle and lower reaches of the Yangtze River and South China exceeds 10.3 days/decade. The interannual variation in the sea ice over the Barents Sea (SICBS) in March and the snow depth over western Eurasia (SDWEA) in April are closely related to the first regional EHE-ODs in southeastern China, which both provide favorable atmospheric circulation patterns and significant descending motion for the occurrence of regional EHEs. The pathway of the physical process originates from the northern Eurasia propagating southeastward, and spreads to southeastern China, which can enhance the anticyclonic anomaly in southeastern China and favor the occurrence of regional EHEs in southeastern China in the early summer. Therefore, the SICBS in March might be a critical potential predictor for the onset of the regional EHEs in southeastern China. • The onset date of extreme hot events (EHE) in southeastern China has an early-onset trend. • The advanced rate of the early-onset trend of regional EHE exceeds 10.3 days/decade. • Barents Sea ice plays as a precursor for the onset date of EHE in eastern China. • Midlatitude Eurasian atmospheric wave train is related to the early onset of EHE. [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]