Search

Using the prediction data from the Global Seasonal Forecast version 5 (GloSea5) during the 1993–2016 period, the probabilistic prediction skills of the midsummer (July and August) surface air temperature (SAT) over the middle and lower reach of the Yangtze River valley (MLYR) are evaluated by the ranked probabilistic skill score. We found that the GloSea5 better predicts below-normal (BN) events than above-normal (AN) events at a long lead time, as well as the associated western Pacific subtropical high (WPSH) and circumglobal teleconnection (CGT) anomaly. This result reveals the asymmetry of the probabilistic prediction skills of the midsummer MLYR SAT, which is related to the asymmetric effect of predictability sources: the warm midsummer ENSO favors BN events via promoting the eastward retreat of the WPSH, whereas the cold midsummer ENSO exhibits weak effect on AN events due to the induced southwestward expansion of the WPSH; the warm mid-latitude North Atlantic (MNA) promotes AN events via projecting its influence onto the atmospheric teleconnections such as the CGT, but not vice versa. The GloSea5 exhibits strong response to both two predictability sources, but fails to reproduce the asymmetric effect of predictability sources especially for ENSO, which limits the prediction skills of AN events. On the other hand, the worse (better) simulations of the warm MNA (warm midsummer ENSO) lead to the lower (higher) prediction skills of AN (BN) events. These results are useful for better understanding the predictability of the midsummer SAT over the MLYR. [ABSTRACT FROM AUTHOR]

By using the hindcast and forecast data from the National Centers for Environmental Prediction Climate Forecast System version 2 (NCEP CFSv2) for the 1982–2018 period, we investigate the forecasting skills of the mid‐summer (July and August) surface air temperature (SAT) at interannual timescales in this study. Although CFSv2 predictions show a warm bias for the climatological mean SAT over the Yangtze River valley (25°–32°N, 105°–122°E), they show a consistent and great performance in predicting the interannual variability of the mid‐summer SAT over this region until 4 months in advance, where the linear correlation coefficient between the predicted and observed time series reaches +0.65, +0.51 and + 0.68 for 4, 2 and 0 months in advance, respectively. The CFSv2 predictions well simulate the linkage between the SAT anomalies over the Yangtze River valley and the anomalous atmospheric circulation aloft, including the circumglobal teleconnection and zonal extension of the Western Pacific Subtropical High. However, CFSv2 has trouble in simulating the associated vertical velocity, cloud cover and solar radiation anomalies, except for 0 months in advance. The persistent forecasting skills result from the accurate response of the circumglobal teleconnection and Western Pacific Subtropical High to the El Niño/Southern Oscillation and sea surface temperature (SST) anomalies over the mid‐latitude North Atlantic. Correspondingly, the forecasting skill, signal and signal‐to‐noise ratio are effectively improved in the years with strong mid‐summer SST anomalies over the tropical central‐eastern Pacific or mid‐latitude North Atlantic. These results are useful for understanding the predictability of the mid‐summer SAT over the Yangtze River valley. [ABSTRACT FROM AUTHOR]

By using the hindcast and forecast data from the National Centers for Environmental Prediction Climate Forecast System version 2 (NCEP CFSv2) for the 1982–2018 period, we investigate the forecasting skills of the mid‐summer (July and August) surface air temperature (SAT) at interannual timescales in this study. Although CFSv2 predictions show a warm bias for the climatological mean SAT over the Yangtze River valley (25°–32°N, 105°–122°E), they show a consistent and great performance in predicting the interannual variability of the mid‐summer SAT over this region until 4 months in advance, where the linear correlation coefficient between the predicted and observed time series reaches +0.65, +0.51 and + 0.68 for 4, 2 and 0 months in advance, respectively. The CFSv2 predictions well simulate the linkage between the SAT anomalies over the Yangtze River valley and the anomalous atmospheric circulation aloft, including the circumglobal teleconnection and zonal extension of the Western Pacific Subtropical High. However, CFSv2 has trouble in simulating the associated vertical velocity, cloud cover and solar radiation anomalies, except for 0 months in advance. The persistent forecasting skills result from the accurate response of the circumglobal teleconnection and Western Pacific Subtropical High to the El Niño/Southern Oscillation and sea surface temperature (SST) anomalies over the mid‐latitude North Atlantic. Correspondingly, the forecasting skill, signal and signal‐to‐noise ratio are effectively improved in the years with strong mid‐summer SST anomalies over the tropical central‐eastern Pacific or mid‐latitude North Atlantic. These results are useful for understanding the predictability of the mid‐summer SAT over the Yangtze River valley. [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]

In 2020 summer, the excessive rainfall over the Yangtze and Huaihe River valley (YHRV) broke the record held since 1961, and the induced flood disasters caused huge losses. The record-breaking rainfall was primarily attributed to the abnormally strong western Pacific subtropical high (WPSH), characterized by a westward expansion to southern China. The extreme northern India Ocean (NIO) warming and the rapid La Niña development were responsible for the abnormally strong WPSH via enhancing its two leading modes (EOF1 and EOF2), with the normalized principal components (PC1 and PC2) of +1.07 and +1.30 in 2020, respectively. Compared to the observations, the excessive rainfall over the YHRV and the abnormally strong WPSH was successfully predicted by the National Centers for Environmental Prediction Climate Forecast System version 2 (CFSv2) initialed in May. Although the CFSv2 can capture the influence mechanisms of two SST forcings on the WPSH, only the La Niña development provided a primary predictability source for the extreme 2020 summer. First, the above-normal PC2 was accurately predicted (+1.60) beneficial from the accurate simulation of the La Niña development, whereas the predicted PC1 (+0.43) was much weak due to the underestimation of the NIO warming. Second, owing to a stronger (weaker) linkage between the YHRV rainfall and the PC2 (PC1) in the CFSv2, the predicted YHRV rainfall exhibited a stronger (weaker) response to the La Niña development (NIO warming) in 2020 summer. Future model improvements need to more emphasize the role of the NIO SST in the summer YHRV rainfall. • The record-breaking rainfall over the Yangtze and Huaihe River valleyoccurred in 2020 summer. • The northern India Ocean warming and La Niña development were jointly responsible for the extreme 2020 summer. • The predictability of 2020 summer by the NCEP CFSv2 was dominantly originated from the La Niña development. [ABSTRACT FROM AUTHOR]

The Once‐in‐a‐Century extreme rainstorm event caused severe floods over Henan province during July 18–21, 2021, which resulted in large casualty and property losses. Although the rainstorm event occurred in Henan after July 18, the excessive rainfall had occurred to the east of Henan before July 18, with the 4‐day accumulated rainfall exceeding +130 mm during July 14–17, 2021. How the rainfall evolving westward and intensifying after July 18 remained a puzzle, which is the focus of this study. The prerainstorm stage (July 14–17) was related to the South Asian High (SAH) extending eastward and the western Pacific subtropical high (WPSH) extending northwestward, and a low vortex between the SAH and WPSH caused above‐normal rainfall to the east of Henan. The rainstorm stage (July 18–21) was associated with an inverted trough and excessive southerly and southeasterly water vapor transportation above Henan, which resulted from the combined effects of a deep trough in the upper troposphere and typhoon activities. Additionally, three subseasonal forecasting systems predicted this rainstorm event 3 days in advance, with the European Center for Medium Range Weather Forecasts (ECMWF) performing the best, which was related to a better prediction of the inverted trough and the water vapor transportation in the middle‐lower troposphere. These results advance our understanding of the extreme rainstorm event in July 2021 in Henan. [ABSTRACT FROM AUTHOR]

Using hindcast and forecast data from advanced prediction systems of NCEP CFSv2 and JMA/MRI CPSv2 for the winter 1982/1983–2017/2018, this study investigates the predictability of the climatology and dominant modes of winter-mean surface air temperature (SAT) over East Asia. Although the simulated climatological mean SAT has a large bias over most of the mainland China, both models show high forecasting skills for the principal components (PC1 and PC2) of the two major modes (northern and southern temperature modes) of the winter-mean SAT over East Asia 1 month in advance. In comparison, the MRI-CPSv2 performs better than the CFSv2 in simulating the spatial distribution of the northern temperature mode and the associated circulation anomalies aloft, but the CFSv2 has better performance than the MRI-CPSv2 in simulating the spatial distribution of southern temperature mode and its linkage to the Arctic Oscillation and Eurasian pattern. Furthermore, both models well simulate the impacts of the dipole sea surface temperature (SST) anomalies over the mid-latitude North Pacific and El Niño–Southern Oscillation on the northern and southern temperature modes, respectively. Accordingly, the forecasting skill and signal-to-noise ratio of the PC1 (PC2) are significantly improved in the years with strong SST anomalies over the mid-latitude North Pacific (tropical central-eastern Pacific), particularly for the CFSv2 (MRI-CPSv2) predictions. These results are beneficial for understanding the interannual predictability of the East Asian winter climate. [ABSTRACT FROM AUTHOR]

The driving mechanism of Arctic amplification (AA) is so complex that no consistent and definitive conclusion has been formed yet. In particular, the internally and externally driven trends of AA have not been distinguished using observation-based methods. Given that the Arctic is more sensitive than other regions to anthropogenic greenhouse gas increases and other external forcings, we focus on separating anthropogenically driven trends from the Arctic surface air temperature (SAT) changes during 1979–2017 to quantify the contribution of anthropogenic effects on AA, with detection and attribution converted to probability distribution functions. Results indicate that the Arctic coast of the Siberian Great Plains, from the Barents Sea to the Kara Sea and eastward to the Bering Strait, has been warming most significantly, and is mainly dominated by anthropogenically driven trends. From 1979 to 2017, the minimum anthropogenically driven warming in most parts of the Arctic Ocean exceeds 2℃, especially the Kara Sea area, where the anthropogenically driven warming is significant, reaching 4℃. In addition, the minimum anthropogenic contributions exceed 60% in most parts of the Arctic Circle and are more than 80% of the warming trend in (75–90° N, 150–180° W). In 140° W–140° E Arctic region, the anthropogenically driven trend is the most remarkable, at 0.82℃ / decade, accounting for 84.5% of the measured warming trend. Meanwhile, the anthropogenically driven trend accelerates most rapidly in this area (0–140° W, 60–90° N). [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]

The Asian‐Australian monsoon (AAM) region is characterized as abundant summer monsoon rainfall, which provides fresh water resources for high‐density population there. The research uses HadGEM3‐A‐N216 model simulations to compare the change of extreme rainfall intensity in the AAM region with and without anthropogenic influences. Although the anthropogenic forcing exerts a weak impact on the climatological mean distribution of the extreme precipitation, it significantly increases the extreme precipitation intensity at each degree in most parts of the AAM region, especially for the northern East Asia, the Bay of Bengal, and Australia. As the extreme degree increases from the 50–98%, the extreme precipitation intensity in the northern East Asia, the Bay of Bengal, and the Australia increase more and more rapidly, while that in the southern East Asia changes from a decreasing trend to an increasing trend. Overall, the stronger extreme precipitation is accompanied by a stronger growth trend under the anthropogenic forcing. [ABSTRACT FROM AUTHOR]

The record‐long 2020 Meiyu season since 1961 caused severe floods over the Yangtze and Huaihe River valleys (YHRV). Why the Meiyu duration doubled in 2020 remains a puzzle. We show that the long‐lasting Meiyu can be divided into three stages: advanced‐onset, strong‐persisting, and delayed‐withdrawal. The advanced‐onset was associated with an extremely negative‐phase East Atlantic/West Russia teleconnection. The strong‐persisting was attributed to a positive‐phase Pacific–Japan (PJ) pattern sustained by La Niña's rapid development. The delayed withdrawal was related to the combined effect of a positive PJ pattern and a mid‐troposphere "two ridge–one trough" pattern over Asia. Two subseasonal forecasting systems predicted the positive rainfall anomalies over the YHRV in the first two stages, but not the third stage, which may be associated with poor prediction of the two ridge–one trough pattern. These results highlight the role of subseasonal evolution in extreme climate events. Plain Language Summary: During the northward advance of the East Asian summer monsoon, the East Asian subtropical region is normally characterized by a quasi‐stationary rainband that persists from mid‐June to mid‐July, which is known as Meiyu in China and Baiu in Japan. Both the duration and the accumulated rainfall of the 2020 Meiyu set the highest record since 1961, which caused a severe flood and an enormous economic loss in the Yangtze and Huaihe River valleys (YHRV), central‐eastern China. We investigated the mechanism and predictions of this long‐lasting flood. The record‐long 2020 Meiyu can be divided into three stages: advanced‐onset, strong‐persisting, and delayed withdrawal. The advanced‐onset stage was mainly induced by the extratropical climate anomalies associated with the East Atlantic/West Russia teleconnection. In contrast, the strong‐persisting stage was due to the enhanced tropical forcing via triggering the Pacific–Japan pattern. The delayed withdrawal stage arises from the combined effect of tropical forcing and mid‐latitude teleconnection. The current advanced forecasting systems can predict the positive rainfall anomalies over the YHRV in the first two stages, but not the third stage. These findings advance our understanding of the extreme 2020 flood and help improve future extreme monsoon prediction. Key Points: The long‐lasting 2020 Meiyu season was characterized by three stages: advanced‐onset, strong‐persisting, and delayed withdrawalThe mid‐latitude teleconnection played a crucial role in the 2020 Meiyu onset and withdrawal, while tropical forcing's role is enhanced in the last two stagesAdvanced forecasting systems cannot predict the delayed withdrawal due to the failure in predicting the mid‐latitude teleconnection [ABSTRACT FROM AUTHOR]

In the context of global warming, determining to what extent natural variability and external forcing have an impact on climate change is crucial for formulating mitigation policies and adaptation plans. We quantifiably and effectively separate unnatural trends from the global land surface air temperature (SAT) changes during 1951–2015 by calculating the long‐term correlation exponent through detrended fluctuation analysis and applying mainly probability statistics methods. We provide effective discriminated evidence for whether the observed SAT change exceeds its natural internal variability. Furthermore, we search the range of SAT changes caused by unnatural trends, and identify their corresponding minimum contributions to warming relative trends in different regions. The unnatural warming of the mid‐ to high latitude inland areas of Eurasia and North America is basically high, and the warming responses to unnatural forcing are most intense in these areas. Compared to earlier detection, we find the minimum unnatural trend contributes more than 80% to the observed SAT change in North America, northern Greenland, eastern Africa, and the mid‐ to high latitudes of Eurasia. In addition, the temporal evolutions of unnatural trends in key areas are determined. In North Africa, Western Australia, the United States and Mexico, the unnatural impact became significant at the earliest. Meanwhile, the overall unnatural trend in North Africa is the most significant, followed by western Brazil, and grows most rapidly over time in the two key areas. [ABSTRACT FROM AUTHOR]

The occurrence of a Ural blocking (UB) event is an important precursor of severe cold air outbreaks in Siberia and East Asia, and thus is significant to accurately predict UB events. Using subseasonal to seasonal (S2S) models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Environment and Climate Change Canada (ECCC), we evaluated the predictability of a persistent UB event on 18 to 26 January 2012. Results showed that the ECCC model was superior to the ECMWF model in predicting the development stage of the UB event ten days in advance, while the ECMWF model had better predictions than the ECCC model for more than ten days in advance and the decaying stage of the UB event. By comparing the dynamic and thermodynamic evolution of the UB event predicted by the two models via the geostrophic vorticity tendency equation and temperature tendency equation, we found that the ECCC model better predicted the vertical vorticity advection, ageostrophic vorticity tendency, the tilting effect, horizontal temperature advection, and adiabatic heating during the development stage, whereas the ECMWF model better predicted the three dynamic and the two thermodynamic terms during the decaying stage. In addition, during both the development and decaying stages, the two models were good (bad) at predicting the vortex stretching term (horizontal vorticity advection), with the PCC between both the predictions and the observations larger (smaller) than +0.70 (+0.10) Thus, we suggest that the prediction of the persistent UB event in the S2S model might be improved by the better prediction of the horizontal vorticity advection. [ABSTRACT FROM AUTHOR]