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Based on the meteorological observational data over Qinghai-Xizang （Tibetan） Plateau and atmospheric reanalysis dataset during 1961 to 2020， the snowfall variation characteristics over the Qinghai-Xizang （Tibetan） Plateau and its related corresponding circulation system were analyzed in this paper.Main conclusions are drawn as following： the spatial distribution of snowfall shows a uniformity with less in the northwest and more in the southeast.The characteristics of interannual and interdecadal variability are very evident.The interannual variability of the snowfall over Qinghai-Xizang Plateau was strong.The first mode of Qinghai-Xizang （Tibetan） Plateau snowfall anomalies is regional uniformity.In terms of the key circulation systems that affect Qinghai-Xizang （Tibetan） Plateau snowfall， when the snowfall over Qinghai-Xizang （Tibetan） Tibetan Plateau is more， the upper troposphere corresponds to the positive phase of the southern Eurasian （SEA） teleconnection， characterized as positive anomalies over the southwestern Europe， the Arabian Sea， and the northeast Asia， and negative anomalies over the Middle East and the Qinghai-Xizang （Tibetan） Plateau， while the Middle East jet is stronger； the positive （negative） phase of North Atlantic Oscillation （NAO） is conducive to more （less） snowfall over Tibetan Plateau， via modulating the SEA teleconnection and key circulation systems such as the Middle East jet stream.

Abstract Unprecedentedly extreme precipitation occurred in Pakistan (PAK), and mega heat waves persisted along the Yangtze River Valley (YRV) from July to August 2022. Using the advanced multiscale window transform-based canonical transfer attribution framework, we quantitatively delineated intra-scale and inter-scale interactions leading to record-breaking spatially concurrent extremes in 2022 and comprehensively revealed differences in dynamic processes affecting extreme events in July and August. The basic flow scale window lost the available potential energy (APE), and through APE canonical transfers to the intraseasonal-scale and synoptic-scale windows, the inter-scale dynamic processes and barotropic instability of the basic flow scale preserved the concurrent extreme in July. In August, the eruptive synoptic-scale kinetic energy convergence provided dynamic conditions for the sinking motion of the YRV and its advection to PAK from the Indian Ocean. Consequently, the interaction between high- and low-frequency processes drove atmospheric circulation in summer, but the high-frequency process in August played a vital role in extreme events. Additionally, the heat source in the tropical western-central Pacific is considered one of the key drivers for localized repetitive bursts of energy. This study emphasizes both the interactions between multiple scales of atmospheric dynamics and reveals the driving mechanisms behind the impacts of warming on extreme events, linking the external forcing issue with the free problem of atmospheric internal instability.

Abstract In August 2022, an unprecedented compound heatwave and drought event (CHDE) lasting 24 days occurred in the Yangtze River valley (YRV), leading to a severe reduction of the crop, fresh water, and power supply. We constructed a joint cumulative probability distribution of heatwave and drought intensity, and found that the lowest probability-based index (PI) of 0.06 in 2022 was estimated as a 1-in-662-year event over the 1961–2022 climate. We then detected the fingerprint of greenhouse gas forcing to the observed PI in a generalized extreme value framework, but not the aerosol forcing, suggesting the leading contribution of greenhouse gas forcing on such extreme CHDE. Furthermore, anthropogenic influence had increased the probability of such CHDE by more than 10 times compared to the counterfactual climate. Also, the PI decreased from about 0.30 at the present climate to about 0.14 at the 3 °C global warming level, indicating that CHDE will become more extreme over YRV.

Abstract Unlike prior researches focusing on interannual or interdecadal changes of the Northwest Pacific subtropical high (NWPSH), this paper emphasizes the interdecadal changes in the relationship between May‐June and July‐August NWPSH. The correlation coefficients between them are 0.66 (passing the 99.9% confidence level) and 0.12 during 1979–2002 and 2003–2023. Therefore, the May‐June NWPSH has a strong connection with July‐August East Asian precipitation during 1979–2002, but not during 2003–2023. The interdecadal variations in the relationship of NWPSH are due to interdecadal changes of ENSO. During 1979–2002, the eastern‐type ENSO in prior winter, having longer durations, can influence May‐June and July‐August NWPSH and the North Indian Ocean. However, the central‐type ENSO in prior winter only persists it's influence until May‐June, and changes into a Pacific Dipole pattern in July‐August during 2003–2023. Despite the North Indian Ocean continually warms during 2003–2023, the tropical Pacific Dipole offsets its impacts on the NWPSH.

Abstract This study identified four patterns of regional extreme precipitation events (REPEs) in Central Asia (CA) and their crucial synoptic systems and multiscale interactions. Four patterns with distinct spatial distributions were identified in: northern Kazakhstan, southern Xinjiang, western CA, and the Tianshan Mountains. Focusing on the three most frequent REPEs, the kinetic energy (KE) cross‐scale transfer from the basic‐to synoptic‐scale windows exhibited a zonal dipole, resulting in the development and enhancement of REPEs in northern Kazakhstan. The available potential energy (APE) cross‐scale transfer exhibited opposing patterns between the upper and lower troposphere, indicating baroclinic instability in the lower troposphere and barotropic instability of the basic flow in the upper troposphere. Both mechanisms enhanced the Central Asian vortices (CAVs) in southern Xinjiang and induced REPEs. Conversely, the energy budgets exhibited baroclinic instability of the basic flow throughout the entire region when the Tianshan Mountains REPEs occurred, providing energy for prevalent CAVs.

In this work, the LiTi2(PO4)3 (LTP) flakes have been prepared by employing a template method for lithium-ion batteries with high capacity. The 2D layered structure of LTP offers large aspect ratio and rich active sites, which not only create the large contact area between the electrolyte and electrode, but also promote the diffusion kinetics of Li+. As a result, the Li+ diffusion coefficient of lamellar LTP anode is 3.12 × 10−8 cm2 s−1, while it is only 5.01 × 10−10 cm2 s−1 for granular LTP anode. Further, the lamellar LTP anode delivers a high initial discharge capacity of 986.8 mAh·g−1 at 0.1 A g−1, and remains at 231.1 mAh·g−1 after 100 cycles, which is higher than that of the granular LTP anode (340.5 mAh·g−1 at 1st cycle, 169.3 mAh·g−1 at 100th cycles). Thus, the lamellar LTP should be recommended as a potential anode for high-performance LIBs due to the fast charge-discharge performance and superior cycling stability.

Abstract Heteroatom‐doped porous carbons have stable structures, high electron/ion transport efficiencies, and rich electroactive sites, which are of great significance to energy storage devices. The potential synergistic effects arising from the multi‐element doping benefit to improve the electrochemical behavior of porous carbon. In this paper, a facile doping strategy has been proposed to prepare the (N, Co, Zr, P) tetra‐doped porous carbon spheres (PCS) for enhanced lithium‐ion batteries (LIBs). The metal‐organophosphine framework (MOPF) as precursor is synthesized by utilizing riboflavin sodium phosphate as organic ligand coordinating with cobalt and zirconium ions. Through carbonizing MOPF, the (N, Co, Zr, P) tetra‐doped PCS can be obtained. As the anode for LIBs, the (N, Co, Zr, P) tetra‐doped PCS exhibits highly reversible capacity of 761 mAh g−1 at 0.1 A g−1 after 100 cycles, excellent rate performance of 126 mAh g−1 even at a high current density of 2 A g−1. The results feature that the unique 3D structure and superior local electron transport properties of (N, Co, Zr, P) tetra‐doped PCS promote the Li+ diffusion and adsorption, which improve the electrochemical properties. Moreover, the mechanism analysis realizes that the Li+ storage of (N, Co, Zr, P) tetra‐doped PCS is determined by the capacitive behavior at high scan rate, highlighting the significance of the heteroatom doping. Therefore, the (N, Co, Zr, P) tetra‐doped PCS should be considered as prominent candidate for high‐performance LIBs anodes.

Abstract In July-August 2022, Yangtze River Valley (YRV) experienced unprecedented hot summer, with the number of heatwave days exceeding climatology by four standard deviations. The heatwaves and associated severe droughts affected about 38 million people and caused devastating economic losses of about five billion US dollars. Here we present convergent empirical and modelling evidence to show that the record-breaking Pakistan rainfall, along with the 2022 tripe-dip La Niña, produces anomalous high pressure over YRV, causing intense heatwaves. The La Niña-induced second-highest sea surface temperature gradient in the equatorial western Pacific suppresses western Pacific convection and extends the subtropical high westward. More importantly, the tremendous diabatic heating associated with the unprecedented Pakistan rainfall reinforces the downstream Rossby wave train, extending the upper-level South Asia High eastward and controlling the entire YRV. The overlay of the two high-pressure systems sustains sinking motion and increases solar radiation reaching the ground, causing recurrent heat waves.

Vegetation plays a crucial role in maintaining the balance between nature, water and soil resources. However, understanding its impact mechanisms in arid and semi-arid areas remains limited. This study aims to analyze the spatial–temporal characteristics of the vegetation leaf area index (LAI) and climate elements in typical regions of northwest China and the correlations between LAI and climate elements; it also aims to explore the influence of regional vegetation growth on climate change. The results reveal significant correlations between LAI and various climate elements. Specifically, within the same region, surface temperature, precipitation, vegetation transpiration, and total evaporation show positive correlations with the LAI, whereas surface albedo shows a negative correlation. Vegetation may affect climate through both heat and water exchange between the land and atmosphere. Increased vegetation leads to the enhanced absorption of solar radiation by the land surface, elevating surface temperature. Increased levels of vegetation also increase vegetation transpiration and total evaporation, increasing the water vapor content in the atmosphere and thus leading to increased surface precipitation. Therefore, vegetation distribution plays a role in climate change, and ecological restoration projects in the northwest region hold significant potential for addressing ecological challenges in its arid and semi-arid areas.

Abstract Compared to interannual and interdecadal variations, inadequate attention has been given to intraseasonal changes in the summer northwest Pacific subtropical high (NWPSH). During 1981–2005, the north Indian Ocean (NIO) and NWPSH exhibit significant relationships from June to August, while the influences of the Boreal Summer Intraseasonal Oscillation 1 (BSISO1) in June and August differ from its impacts in July, resulting in a significant correlation between the NWPSH in June and August. The models capture NIO's roles but underestimate BSISO1's influences, leading to an underestimation (overestimation) of the relationship between NWPSH in June and August (adjacent two months). A dynamical‐statistical approach based on the close relationship between June and August NWPSH is proposed to improve models' prediction capabilities. Improved results show the mean correlation coefficients (root mean square errors) between prediction and observation for August precipitation and geopotential height increase by 57% and 21% (decrease by 0.27 mm/day and 1.61 m).

Abstract The Siberian storm track is one of the drivers of the East Asian extreme weather events. Using the daily JRA‐55 reanalysis data from 1980 to 2021, this study examines roles of eddy generation and jet characteristics in setting the annual cycle of Siberian storm track. It is found that there are two peaks of Siberian storm track intensity in boreal spring and autumn. The possible reason for such an annual cycle is explored by analyzing the maximum Eady growth rate over the Siberian region and jet characteristics. The stronger Siberian Eady growth rate in boreal spring and autumn, favoring a stronger baroclinic eddy generation, could contribute to the stronger intensity of Siberian storm tracks in these two seasons. Furthermore, the Siberian jet stream cores during boreal spring and autumn are located north of 50° N and resembles more an eddy‐driven jet. While in winter, the subtropical jet stream enhanced and the eddy‐driven jet becomes relatively weaker, which is less efficient to generate midlatitude baroclinic eddies. Besides, the eddy‐driven jet can modulate the horizontal wave propagations from upstream, which also plays a role in amplifying the spring and autumn Siberian storm tracks.

Abstract The precipitation in the Qilian (QMA) and Tienshan (TMA) mountain areas is one of the main sources of subsurface and surface water in northwestern China (NWC). Based on two datasets, CN05.1 and station‐observed daily precipitation, we found that summer precipitation in 1979–2020 exhibited an increasing trend in NWC. The results of rotation empirical orthogonal function (REOF) analysis also separated the increased precipitation patterns in the QMA and TMA from the other REOF modes; the proportion of the precipitation of these areas to the total NWC summer precipitation substantially increased (0.12%⋅year−1 and 0.03%⋅year−1, respectively). According to the moisture budget, the evaporation changes in the QMA and TMA were coherently coupled with precipitation, which suggested the feedback between increasing evaporation and precipitation with the recently warming climate. The precipitation increase was larger than that of evaporation, indicating a net wetting trend in the QMA and TMA. The increase in zonal horizontal and vertical moisture advection terms contributed more to the increased precipitation in the QMA. The increase in meridional moisture advection contributed more to the increased precipitation in the TMA. We concluded comprehensive frameworks of the water vapor transport in climate change in mountain areas in NWC which aimed to contribute to the understanding of arid region hydrology.

Abstract 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.

Climatic changes worsen concurrent extreme climate events. In July and August of 2022 and 2020, respectively, unexpected concurrent extreme events occurred in mid-latitude Asia. The sudden and severe consequences highlight the importance of a thorough understanding of the drivers of such extreme events, which is crucial for improving predictions and implementing preventive measures to mitigate future risks. By applying multi-scale window transform methodology, a unique mechanism of multi-scale zonal wind resonance is identified, which manifests as a quasi-stationary co-coupling with low-frequency zonal winds. This resonance leads to barotropic instability, triggering abnormal low-frequency Rossby wave behavior in the entrance and exit regions of the quasi-stationary jet stream. Simultaneously, the intensified meridional wind, coupled with adiabatic atmospheric warming, amplifies baroclinic instability, resulting in an enhanced wave pattern and the high concurrence events of 2022. Under long term future global warming levels of 4 °C, the concurrence, strengthened by multi-scale zonal wind resonance, is expected to persist. The mechanism evident in 2022 plays a broader and more significant role in concurrent events compared to the mechanism in 2020. Under the process of warming, resonance phenomena, as observed in 2022, are projected to become more frequent.

The 2022 floods in Pakistan resulted in severe losses and garnered global attention. This study aims to enhance the understanding of extreme precipitation (EP) events in Pakistan by examining the characteristics and mechanisms behind the persistent EP during summer, utilizing daily precipitation data from the Climate Prediction Center (CPC). Results showed that the monsoon precipitation in 2010, 2020 and 2022 are the highest three years on record. Notably, these peak events in 2010 (concentrating in the north) and 2022 (concentrating in the south) spanned from July through August. Conversely, the extreme precipitation in August 2020 was concentrated in northern Pakistan. For the circulation patterns, the intensification of the South Asian High and the western Pacific subtropical high with a strong Indian monsoon is a unifying feature, but the Iranian high and monsoon low-pressure system on the south of Pakistan was different. Additionally, the EP in July 2010 and August 2022 were also influenced by the teleconnection associated with European Blocking. La Niña events and the negative-phase Indian Ocean Dipole (IOD) also played a role in affecting summer EP, with the strongest La Niña occurring in 2010 and a notable triple-dip La Niña coinciding with a significant negative IOD phase in 2022. La Niña contributed to the formation of an anomalously strong anticyclone over the northwest Pacific and easterly winds along the southern Himalayas, impacting moisture transport to Pakistan. Conversely, the negative IOD phase amplified EP in Pakistan by enhancing the northward movement of convective systems and westerly winds over the Indian Ocean. Furthermore, reduced snow cover on the Tibetan Plateau in the springs of 2010 and 2022 likely induced a stronger thermal dynamical effect, acting as a heat source in summer and increasing precipitation in Pakistan.

The Yangtze River Valley (YRV) experienced record-breaking extreme high temperature and weakened rainfall events in August 2022, which resulted in severe disasters and large socioeconomic losses. The importance of the intensification and westward movement of the western Pacific subtropical high (WPSH) with abnormal subsidence has been emphasized in previous studies. However, the source of the abnormal subsidence remains unknown. This study investigates the source of the abnormal subsidence over the YRV and discusses its possible causes by adopting the three-pattern decomposition of the atmospheric circulation (3P-DGAC). Meridional circulation (MC) was the main contributor to the abnormal vertical velocity (114%), while the contribution of zonal circulation (ZC) was negative (–14%). Additionally, the negative rainfall anomaly over the YRV can be explained mainly by the MC. The anomalous MC was characterized as a ‘negative-positive-negative-positive-negative’ quintuple distribution with sinking motion over the YRV. Anomalous MC is closely related to the sea surface temperature anomaly (SSTA) over the three oceans. The negative phase of the Indian Ocean dipole (IOD) and La Niña SSTA leads to an anomalous rising motion of the ZC over the Maritime Continent, favoring the existence of the rising motion of the MC by the coupling effect. The positive phase of the North Atlantic triple (NAT) SSTA results in an anomalous Rossby wave train, which further leads to a sinking motion over the YRV.

Xinjiang is a typical arid and semi-arid Mountain basin system, which make the regional ecosystem extremely fragile. Studying the influence of climate on vegetation is conducive to qualitatively analyze the change trend of vegetation coverage in this region. Therefore, utilizing vegetation coverage and main meteorological elements (temperature, precipitation, relative humidity, sunshine hours) data in Xinjiang province, this paper carried out the influence of multiple meteorological elements on vegetation coverage changes, and constructed a model of the impact of multiple meteorological elements on the growing season vegetation coverage based on random forest. The model can better simulate the vegetation coverage in 2017 and 2018, with an average error of 0.027, in consequence it can well forecast whether the vegetation is high-density or low-density in this area. Correlation analysis and variable importance show that the critical meteorological factors affecting vegetation cover change are relative humidity and sunshine hours, accounting for 73% of the vegetation coverage area. The results are helpful to understand how meteorological factors affect the vegetation coverage, and then provide a theoretical reference for the construction of ecological security in Xinjiang.

The characteristics and related mechanisms of the interannual variability of late summer (August) extreme precipitation in West China (WC) were investigated from 1961 to 2021. Precipitation and extreme precipitation (defined as the 99th percentile) generally decreased in the southeast-northwest direction, with a maximum in the Sichuan Basin. The non-linear trends in extreme precipitation have increased since the 1980s. Therefore, we further found that the interannual increase in extreme precipitation in the WC was significantly related to the eastward-strengthened South Asian high, western-stretched Western Pacific Subtropical high, enhanced westerly jet, anomalous cyclone in Mongolia, and anomalous anticyclone in the western Pacific. The anti-cyclonic anomaly is a Gill-type response to increase the sea surface temperature in the western Pacific. A mid-high latitude barotropic Rossby-wave train can be induced and has essential effects on the above key circulation patterns, further cooperating with the strong updrafts rather than strengthening and maintaining extreme precipitation in the WC.

Synoptic circulation patterns over the midlatitudes play a pivotal role in regional precipitation changes; however, the synoptic circulation patterns over eastern Asia (35°–60° N, 105°–145° E) and their effects on extreme precipitation events in the North China Plain (NCP) and northeastern China (NEC) remain unclear. The summer daily 500 hPa geopotential height anomaly fields for 1979–2021 are classified into six synoptic circulation patterns using self-organizing map (SOM) cluster analysis. The SOM1 pattern, characterized by a high-pressure ridge over the north of eastern Asia and a trough near the Korean Peninsula, yields decreased precipitation in NEC. The SOM2 pattern reveals a robust high ridge over eastern Asia, resulting in a higher incidence of regional extreme precipitation events (REPEs) of approximately 24% in the NCP. Under the SOM3 pattern, the anomalous cyclonic circulation over eastern Asia leads to above-average precipitation in the NCP. The SOM4 pattern yields the highest incidence of REPEs in NEC, with the lowest incidence of REPEs in the NCP, as the anomalous cyclonic circulation over eastern Asia moves southeastward compared to the SOM3 pattern. The SOM5 pattern presenting an anticyclone–cyclone dipole reduces precipitation in the NCP and NEC, and the anticyclonic circulation near eastern China associated with the SOM6 pattern causes above-average precipitation in the NCP. On interannual time scales, the SOM2 pattern occurrence with an increasing trend tends to induce an increasing summer precipitation trend in the NCP. The SOM3 pattern occurrence is negatively correlated with the summer precipitation in NEC. Overall, classifying the synoptic circulation patterns helps to improve precipitation forecasting and provides insights into the synoptic circulation patterns dominating the occurrences of REPEs.

In order to enhance the prediction accuracy and computational efficiency of chaotic sequence data, issues such as gradient explosion and the long computation time of traditional methods need to be addressed. In this paper, an improved Particle Swarm Optimization (PSO) algorithm and Long Short-Term Memory (LSTM) neural network are proposed for chaotic prediction. The temporal pattern attention mechanism (TPA) is introduced to extract the weights and key information of each input feature, ensuring the temporal nature of chaotic historical data. Additionally, the PSO algorithm is employed to optimize the hyperparameters (learning rate, number of iterations) of the LSTM network, resulting in an optimal model for chaotic data prediction. Finally, the validation is conducted using chaotic data generated from three different initial values of the Lorenz system. The root mean square error (RMSE) is reduced by 0.421, the mean absolute error (MAE) is reduced by 0.354, and the coefficient of determination (R2) is improved by 0.4. The proposed network demonstrates good adaptability to complex chaotic data, surpassing the accuracy of the LSTM and PSO-LSTM models, thereby achieving higher prediction accuracy.

China has emerged as one of the global leaders in greening, achieved through human land use management practices, particularly afforestation projects. However, accurately calculating the energy balance processes of vegetated areas remains challenging because of the complexity of physical mechanisms, parameterization schemes, and driving dataset used in current research. In this study, we address these challenges by employing moving window methods in space inspired by “space-for-time”. This approach allows us to eliminate the influence of climate signals on vegetation development over long periods and determine the sensitivity of seasonal contributions of Land Surface Temperature (LST) to Leaf Area Index (LAI) in China from 2001 to 2018. Our findings reveal that the sensitivity of LST to LAI in the climatology period is approximately −0.085 K·m2·m−2, indicating a cooling effect. Moreover, the climatological trend remains negative, suggesting that Chinese vegetation greening is playing an increasingly important role in cooling the land surface. Considering the energy balance equation, we further investigate the underlying mechanisms. It is observed that the radiative feedback consistently contributes positively, while the non-radiative feedback always exerts a negative influence on the sensitivity. These results provide valuable insights into the complex interactions between vegetation greening and land surface temperature in China, providing informed land management and climate adaptation strategies. Understanding these trends and mechanisms is essential for sustainable and effective environmental planning and decision making.

During the “Dragon Boat Water” season in 2022, record-breaking anomalous rainfall occurred over South China (SC). In this study, the causes of anomalous rainfall are investigated by using the novel moisture budget equation of three-pattern circulations. The results show that the anomalous rainfall over SC caused by the horizontal, meridional, and zonal circulations was −10 mm, 168 mm, and 45.3 mm, which contribute −5%, 86%, and 23% of the actual rainfall anomaly (195.1 mm), respectively, suggesting that the meridional circulation contributes most to anomalous rainfall, followed by zonal circulation, and horizontal circulation contributes negatively. Further analysis based on the three-pattern decomposition of the global atmospheric circulation shows that the spatial configuration of the anomalous horizontal circulation and vertical vorticity provides the background for generating the anomalous divergence and convergence of meridional and zonal circulations and further anomalous vertical velocity of the meridional and zonal circulations, ultimately resulting in anomalous rainfall.

In this study, we compared two anomalous wet February periods in 2021 and 2022 in China. The same anomalies appeared in the spatial distribution of precipitation, with anomalous precipitation centered over the southeast coast. However, temperature discrepancies appeared in most of China, with anomalously high temperatures in 2021 and lower temperatures in 2022. Both instances of increased precipitation were attributed to warm and moist advection from the south, with transport in 2021 being partly enhanced by the South China Sea cyclone, whereas transport in 2022 was mainly due to the subtropical western North Pacific anticyclone. Therefore, in this study, we aimed to compare and analyze temperature and precipitation anomalies in February 2021 and 2022 using the self-organizing map method. Warm events in East Asia and cold events in Siberia and the Tibetan Plateau types were obtained by mode 1, which contained 2021. Mode 6 exhibited opposite warm types in Siberia and cold types in southern Asia, including February temperature and precipitation anomalies in 2022. Based on the results of this study, we can conclude that precipitation anomalies in February 2021 and 2022 occurred under different temperature and circulation anomalies, and both were influenced by La Niña events. Autumn sea ice loss in the Barents Sea contributed significantly to warm and rainy events in February 2021. However, the cold and rainy events of February 2022 were closely related to the strengthening of the Siberian High.

Global dryland areas are vulnerable to climate change and anthropogenic activities, making it essential to understand the primary drivers and quantify their effects on vegetation growth. In this study, we used the Time Series Segmented Residual Trends (TSS-RESTREND) method to attribute changes in vegetation to CO2, land use, climate change, and climate variability in Chinese and American dryland areas. Our analysis showed that both Chinese and American drylands have undergone a greening trend over the past four decades, with Chinese greening likely linked to climatic warming and humidification of Northwest China. Climate change was the dominant factor driving vegetation change in China, accounting for 48.3%, while CO2 fertilization was the dominant factor in American drylands, accounting for 47.9%. However, land use was the primary factor resulting in desertification in both regions. Regional analysis revealed the importance of understanding the drivers of vegetation change and land degradation in Chinese and American drylands to prevent desertification. These findings highlight the need for sustainable management practices that consider the complex interplay of climate change, land use, and vegetation growth in dryland areas.

The unprecedented and long-lasting abnormal monsoon rainfall attacked Pakistan in the summer of 2022, causing severe flooding. This study investigated the sub-seasonal characteristics and mechanisms of this distinctively extreme precipitation event. The historical rainfall in July and August and extreme precipitation mainly occurred in northern Pakistan. Both the monthly rainfall in July and August 2022 and the extreme precipitation during the summer were far exceeding the historical record and involved unique spatial distribution. The rainfall in July 2022 is nationwide and mainly located in northern Pakistan, while the rainfall in August and extreme precipitation occurred in southern Pakistan. Different physical processes are responsible for the precipitation in July and August 2022. In July, the South Asian high (SAH) and Iranian high extended eastward. Meanwhile, the anticyclonic circulation anomalies occurred in northwestern Pakistan and the easterly winds enhanced in the south side of the Tibetan Plateau (TP), which strengthened water vapor transporting from the Bay of Bengal and cooperated with the cyclonic system over the Arabian Sea to enhance the precipitation over Pakistan. In August, the SAH further extended eastward and the Western Pacific Subtropical High extended westward to the TP. Meanwhile, the European blocking (EB) developed, and a deep trough appeared over northwestern Pakistan. This weakened the easterly flow along southern TP but enhanced the southerly flow accompanying the cyclone over the Bay of Bengal and the Arabian Sea, and thus guided the water vapor transporting to southern Pakistan and enhanced the precipitation. The extreme precipitation in July was mainly attributed to the unusually strong Indian monsoon, while the extreme precipitation in August was the result of a combination of the Indian monsoon and EB. The study provided important information about extreme precipitation in Pakistan, which will help policymakers take measures to deal with the effects of flooding.

We report the observation of a large anisotropic magnetoresistance (AMR) and planar Hall effect (PHE) in a topological superconducting candidate Cu0.05PdTe2. The AMR and PHE data in Cu0.05PdTe2 can be well explained by the semiclassical theory, confirming that the magneto-transport behaviors of the Cu0.05PdTe2 superconductor are related to its topological nature. The AMR ratio in Cu0.05PdTe2 is one order of magnitude larger than those in traditional ferromagnetic metals. The present results suggest that Cu0.05PdTe2 is a promising material in future magnetoresistive devices with low power consumption.

Anomalous subsidence over the western part of the western Pacific subtropical high (WPSH) caused record-breaking precipitation anomalies over the Yangtze-Huaihe River catchment in early summer 2020 (June–July 2020). The meridional circulation (MC) made a positive contribution to this anomalous subsidence, while the zonal circulation (ZC) made a negative contribution. The quantitative contributions of the MC and ZC to this anomalous subsidence were approximately 110% and –10% in June, 130% and –30% in July, and 120% and –20% for the mean of June and July, respectively, suggesting that the MC played a dominant role in the anomalous subsidence of the western part of the WPSH. The anomalous MC, with a rising branch located at the Maritime Continent and a descending branch located over South China, was forced by the warming of the northern tropical Indian Ocean and the rapidly developed La Niña event, which further resulted in the intensification and southwestward expansion of the WPSH and thus in heavy rainfall over the Yangtze River region.

Pattern structures are usually used to describe the spatial and temporal distribution characteristics of individuals. However, the corresponding relationship between the pattern structure and system robustness is not well understood. In this work, we use geostatistical method–semivariogram to study system robustness for different pattern structures based on three dynamical models in different fields. The results show that the structural ratio of different pattern structures including the mixed state of spot and stripe, cold spot, stripe only, and hot spot are more than 75%, which indicated those patterns all have strong spatial dependence and heterogeneity. It was revealed that the systems corresponding to the mixed state of spot and stripe or cold spot are more robust. This article proposed a method to characterize the robustness of the system corresponding to the pattern structure and also provided a feasible approach for the study of “how structures determine their functions.”

Using daily precipitation data of national meteorological stations in Qinghai Province and reanalysis data, the main patterns of autumn continuous rain (ACR) are extracted, and key SST areas and circulation factors are searched for to analyze the possible effects on the seasonal and sub-seasonal predictability of ACR in Qinghai Province. The factors with strong precursors mainly include sea surface temperature (SST), Arctic vortex, and subtropical high. The influence of oceanic factors on ACR is relatively independent, while there is an interaction between atmospheric circulation factors. The precursors in spring are from the equatorial east-central Pacific for the main pattern with consistent precipitation distribution, and the Indian Ocean for the pattern with “saddle type” distribution. SST anomalies from the Pacific and Indian Oceans force different circulation patterns that can enhance meridional circulation over Europe-Asia and lead to different precipitation pattern of ACR. The signals from the Arctic vortex and subtropical high in June to July are indicative for ACR. The southward, westward and strong Arctic vortex, together with the south-westward extension of subtropical high over the Atlantic and Pacific can promote more ACR in Qinghai Province. Under the SST forcing and configuration of high and low latitude circulation, the meridional circulation continues to be weak, and the latitudinal circulation to be enhanced over the Eurasia in the early period, and the circulation pattern changes from type-W to type-C, which lead to positive anomaly of ACR in Qinghai Province.

Intensifying global climate change has a significant influence on the vegetation, which is the basis of most of Earth’s ecosystems. It is urgent to identify the critical meteorological elements of vegetation coverage changes to address the problems induced by climate change. Many studies, ranging from theoretical advances to data-driven analyses, have been devoted to investigating meteorological elements’ roles in changing vegetation coverage. However, little has been considered in the aspect of the meteorological elements’ seasonal scale in data-driven studies. Herein, taking China as an example, we collected satellite-derived vegetation coverage data from 2000 to 2020. We then analyzed the meteorological elements, on a seasonal scale, that affect the vegetation coverage change in terms of temperature, precipitation, and solar radiation. We revealed that the critical meteorological elements facilitating vegetation coverage area change differ in both time and space and gave a detailed analysis in line with such findings. Moreover, an apparent seasonal delay effect of meteorological elements on the vegetation coverage change is uncovered.

Arid ecosystems are known to be sensitive to climate change. The Jornada Basin in the USA, as one representative of arid land, has suffered from land degradation in recent decades. In order to disentangle the climate–vegetation feedback, we analyzed the vegetation dynamics under the effects of climate change via a mathematical model based on the reaction–diffusion mechanism. Using this model, we conducted a sensitive analysis of climate factors and concluded that the ecosystem might experience a catastrophic shift with the climatic deterioration. We considered the non-local interaction term to explain the competition among plants. Additionally, the PLR (power law range) metric was used to quantify the extent of the degradation and to compare the results of the vegetation patterns from the remote sensing data and the simulations. From the results, this model could simulate the trends of land degradation in this area. We found that the land degradation could be mainly attributed to climate changes in recent years. This approach suggests that vegetation patterns can provide hints as to whether the ecosystem is approaching desertification. These results can help with mapping vulnerable arid areas around the world through model simulation and satellite images.

The oceanic absorption of atmospheric CO _2 acidifies seawater, which accelerates CaCO _3 dissolution of calcifying organisms, a process termed dissolution effect. Promoted CaCO _3 dissolution increases seawater ALK (alkalinity), enhancing ocean carbon sink and mitigating ocean acidification. We incorporate different parameterizations of the link between CaCO _3 dissolution and ocean acidification into an Earth System Model, to quantify the feedback of the dissolution effect on the global carbon cycle. Under SRES A2 CO _2 emission scenario and its extension with emissions of 5,000 PgC in ∼400 years, in the absence of the dissolution effect, accumulated ocean CO _2 uptake between year 1800 and 3500 is 2,041 PgC. The consideration of the dissolution effect increases ocean carbon sink by 195–858 PgC (10%–42%), and mitigates the decrease in surface pH by 0.04–0.17 (a decrease of 10%–48% in [H ^+ ] (hydrogen ion concentration)), depending on the prescribed parameterization scheme. In the epipelagic zone, relative to the Arc-Atlantic Ocean, the Pacific-Indian Ocean experiences greater acidification, leading to greater dissolution effects and the resultant stronger feedbacks on ocean carbon sink and acidification in the Pacific-Indian Ocean. Noteworthy, the feedback of dissolution effect on ocean carbon sink can be comparable with or stronger than the feedback from CO _2 -induced radiative warming. Our study highlights the potentially critical role played by CaCO _3 dissolution effect in the ocean carbon sink, global carbon cycle and climate system.

Herein, we investigated the characteristics and mechanisms of interannual variability of extreme summer precipitation in northwest China (NWC). The four high-resolution precipitation predicting products under assessment indicated that both the accumulation of summer daily precipitation ≥95th percentile, and the summer maxima of daily precipitation generally decreased in a southeast—northwest direction, while relatively high values were observed in the Tienshan and Qilian Mountain areas. In turn, the Tropical Rainfall Measuring Mission (TRMM) satellite dataset underestimated extreme precipitation in mountainous areas, while Asian precipitation highly—resolved observational data integration towards evaluation (APHRODITE) and Climate Prediction Center (CPC) captured the characteristics of extreme precipitation in NWC. AMIP-type simulations of the interannual variability of extreme summer precipitation in NWC were quite unsuccessful. However, all of them can capture the increasing trends. Therefore, we further found that the interannual increase in extreme precipitation in NWC is strongly correlated with the weakened South Asian high, strengthened Western Pacific Subtropical high, the enhanced westerly jet, and the mid- to high-latitude Rossby wave trains, whose formation and sustenance can be traced back to sea surface temperature-anomalies in the western Pacific in May, June, and July. An increased sea surface temperature promotes convection and induces diabatic heating, which stimulates anticyclonic anomalies that disturb the enhanced westerly jet, resulting in a barotropic Rossby wave train via the Gill-type response. Additionally, it guides more water vapor convergence to NWC and enhances upward motion via anticyclonic anomalies over western Europe and Eastern Asia, and cyclonic anomalies over Central Asia.

The abnormal characteristics of extremely warm early summer (EWES) in North China under different decadal backgrounds were contrastively analyzed. Their relationships with upper- and lower-level atmospheric circulation and global sea surface temperature anomalies (SSTAs) are also discussed. Results show that temperature anomalies of EWES in North China are overall higher than normal in both cold (1961–1993) and warm (1994–2019) periods, but the anomalies of the latter are much higher than that of the former. EWES in North China is directly related to the circulation lying between 40° and 50°N in the middle troposphere, which leads to positive temperature anomalies occurring from the bottom to the upper level of the troposphere together with a high anomaly trend tilting northward. The persistent and strong Eurasian continental high (ECH) and weak Northeast China cold vortex (NECV) activity, together with the strong western Pacific subtropical high (WPSH) are major factors that directly lead to EWES in North China. ECH and WPSH are stronger and larger, and NECV are weaker and more northward in the warm period than in the cold period. In addition, the positive SSTAs in the tropical Indian Ocean and the Kuroshio area are favorable for the stronger and larger ECH and WPSH as well as the weaker and more northward NECV, causing strong anticyclonic and downward circulation system controlling North China, resulting in the extremely warm temperatures there. The joint impact of the positive tropical Indian Ocean SSTAs and the Kuroshio region SSTAs is more significant during warm than cold periods, resulting in much stronger EWES in North China during warm periods.

The interannual variation of snowfall over the Tibetan Plateau (TP) in early winter (November–December) and its related atmospheric attribution are clarified. Meanwhile, the influence of tropical sea surface temperatures (SSTs) on TP snowfall is investigated by diagnostic analyses and Community Atmosphere Model (CAM5) simulations. The leading mode of TP snowfall in early winter features a spatially uniform pattern with remarkable interannual variability. It is found that the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) are main external forcing factors for TP snowfall. Positive IOD with positive ENSO and positive IOD with neutral ENSO cases both have remote impact on motivating Southern Eurasia (SEA) pattern, which can induce an anomalous cyclone around the TP. The corresponding anomalous ascending motion and cold air in the mid-upper troposphere provide the dynamical and thermal conditions for heavy snowfall. The low-level southwesterly winds are enhanced over the Arabian Sea and Bay of Bengal, bringing abundant water vapor into the TP for excessive snowfall. Furthermore, CAM5 simulation experiments forced by IOD- and ENSO-related SST anomalies are performed to verify their combined and independent effects on TP snowfall in early winter. It is confirmed that either positive IOD or El Niño has certain impacts on motivating circulation anomalies favorable for snowfall over the TP. However, IOD plays a leading role in producing the excessive snowfall-related atmospheric conditions, and there is an asymmetric influence of ENSO and IOD on the TP snowfall.

Extreme rainfall may cause meteorological disasters and has tremendous impact on societies and economics. Assessing the capability of current dynamic models for rainfall prediction, especially extreme rainfall event prediction, at sub-seasonal to seasonal (S2S) scale and diagnosing the probable reasons are quite important topics in the current climate study field. This study analyzes the formation mechanisms of the extreme rainfall event during 18–22 July 2021 in Henan Province and introduces the Tanimoto Coefficient (TC) to evaluate the prediction performance of S2S models. The results show that confrontation between low-latitude typhoon “In-Fa” and subtropical highs leads to sufficient water vapor transporting to Henan, and that remarkable upward air motion causes strong convergence of water vapor, thereby providing atmospheric conditions for this extreme rainfall event. Furthermore, five S2S models showed limited capability in predicting this extreme rainfall event 20 days in advance with the TCs of four models being below 0.1. Models could capture this event signal 6 days ahead with most TCs above 0.2. The performances of model prediction for this extreme rainfall event were closely related to the fact that the water vapor convergence, vertical movements, relative vorticity, and geopotential height predicted by the NCEP model 20 days ahead were close to the actual situation, in contrast to the other four models 6 days in advance. This study implies that S2S model predictions for this extreme rainfall event show obvious differences, and the application of S2S models in the prediction of extreme events needs to fully consider their prediction uncertainties. The capability of the models to properly reproduce local water vapor convergence and vertical motions is also shown to be crucial for correctly simulating the extreme event, which might provide some hints for the further amelioration of models.

The analysis of actual evapotranspiration (ETa) changes is of great significance for the utilization and allocation of water resources. In this study, ETa variability in northern China (aridity index < 0.65) is investigated based on the average of seven datasets (GLEAM, GLASS, a complementary relationship-based dataset, CRA-40, MERRA2, JRA-55, and ERA5-Land). The results show that ETa increases significantly from 1982 to 2017. Limited by water supply, ETa is significantly correlated with precipitation (R = 0.682), whereas the increase in precipitation is insignificant (p = 0.151). Spatially, the long-term trend of ETa is also not completely consistent with that of precipitation. According to a singular value decomposition (SVD) analysis, the trend of ETa is mainly related to the first four leading SVD modes. Homogeneous correlation patterns indicate that more precipitation generally leads to high ETa; however, this relationship is modulated by other factors. Overall, positive potential evapotranspiration anomalies convert more surface water into ETa, resulting in a higher increase in ETa than in precipitation. Specifically, ETa in the northern Tibetan Plateau is associated with meltwater generated by rising temperatures, and ETa in the Badain Jaran Desert is highly dependent on the wet-day frequency. Under global warming, the inconsistency between ETa and precipitation changes has a great impact on water resources in northern China.

Abstract 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.

Actual evapotranspiration (AE) is a crucial processes in terrestrial ecosystems. Global warming is expected to increase AE; however, various AE estimation methods or models give inconsistent trends. This study analyzed AE variability in China during 1982–2015 based on the Budyko framework (AE_Budyko), a complementary-relationship-based product (AE_CR), and the weighted average of six reanalyses (AE_WAR). Because the response of AE to driving factors and the performances of AE datasets are both scale-dependent, China has been categorized into six distinct climatic areas. From a regional perspective, the X-12-ARIMA method was used to decompose monthly AE into the trend, seasonal, and irregular components. We examined the main characteristics of these components and the relationships of climate factors with AE. The results indicate that the trend component of AE increased from the mid-1990s to the early 2000s and more recently in the hyper-arid and arid areas. Increasing AE was observed from 1982 to the early 1990s in the semi-arid and dry sub-humid areas. AE increased significantly and had substantial interannual variability for the entire period in the sub-humid and humid areas. Increased precipitation and water supply from terrestrial water storage contributed significantly to increasing AE in the drylands. The simultaneous occurrence of increasing precipitation and wet-day frequency caused increasing AE in the dry sub-humid area. Increased AE could be explained by the increased energy supply and precipitation in the sub-humid and humid areas. Precipitation had the strongest influence on the irregular component of AE in drylands. AE and potential evapotranspiration had a strong positive correlation in the sub-humid and humid areas. Regarding data availability, a discrepancy existed in the trend component of AE_CR because soil moisture was not explicitly considered, whereas the irregular component of AE_Budyko contained distinct variations in humid and sub-humid areas.

Snow cover over the Tibetan Plateau plays a vital role in the regional and global climate system because it affects not only the climate but also the hydrological cycle and ecosystem. However, high-quality snow data are hindered due to the sparsity of observation networks and complex terrain in the region. In this study, a nonlinear time series analysis method called phase space reconstruction was used to obtain the Tibetan Plateau snow depth by combining the FY-3C satellite data and in situ data for the period 2014–2017. This method features making a time delay reconstruction of a phase space to view the dynamics. Both of the grids and their nearby in situ snow depth time series were reconstructed with two appropriate parameters called time delay and embedding dimension. The values of the snow depth for grids were averaged over the in situ observations and retrieval of the satellite if their two parameters were the same. That implies that the two trajectories of the time series had the same evolution trend. Otherwise, the snow depth values for grids were averaged over the in situ observation. If there were no in situ sites within the grids, the retrieval of the satellite remained. The results show that the integrated Tibetan Plateau snow depth (ITPSD) had an average bias of –1.35 cm and 1.14 cm, standard deviation of the bias of 3.96 cm and 5.67 cm, and root mean square error of 4.18 cm and 5.79 cm compared with the in situ data and FY-3C satellite data, respectively. ITPSD expressed the issue that snow depth is usually overestimated in mountain regions by satellites. This is due to the introduction of more station observations using a dynamical statistical method to correct the biases in the satellite data.

Droughts have more impact on crops than any other natural disaster. Therefore, drought risk assessments, especially quantitative drought risk assessments, are significant in order to understand and reduce the negative impacts associated with droughts, and a quantitative risk assessment includes estimating the probability and consequences of hazards. In order to achieve this goal, we built a model based on the three-dimensional (3D) Copula function for the assessment of the proportion of affected farmland areas (PAFA) based on the idea of internally combining the drought duration, drought intensity, and drought impact. This model achieves the “internal combination” of drought characteristics and drought impacts rather than an “external combination.” The results of this model are not only able to provide the impacts at different levels that a drought event (drought duration and drought intensity) may cause, but are also able to show the occurrence probability of impact at each particular level. We took Huize County and Mengzi County in Yunnan Province as application examples based on the meteorological drought index (SPI), and the results showed that the PAFAs obtained by the method proposed in this paper were basically consistent with the actual PAFAs in the two counties. Moreover, due to the meteorological drought always occurring before an agricultural drought, we can get SPI predictions for the next month or months and can further obtain more abundant information on a drought warning and its impact. Therefore, the method proposed in this paper has values both on theory and practice.

Based on ERA5 from 1980 to 2018, we compare and analyze the trend and interdecadal variation of evaporation anomalies over the tropical Indian Ocean by the evaporation decomposition method. This method mainly decomposes the evaporation anomalies into the Newtonian cooling, stability, relative humidity, wind speed, and transfer coefficient terms. The annual mean evaporation anomalies show an increasing trend (0.083 mm/d/decade). The Newtonian cooling term (0.026 mm/d/decade), the relative humidity term (0.032 mm/d/decade), and the wind speed term (0.026 mm/d/decade) play a major role in the increasing trend. The interdecadal variation of evaporation anomalies shows decreases in the 1980s and after the early 2000s, and an increase in the 1990s. The decreased evaporation anomalies in the 1980s are affected by the transfer coefficient term, which is associated with the North Atlantic Oscillation (NAO). The increased evaporation anomalies in the 1990s and the decreased evaporation anomalies since the early 2000s are largely controlled by the wind speed term, which are dominated by the Atlantic Multidecadal Oscillation (AMO). The Pacific Decadal Oscillation (PDO) may have important impacts on the interdecadal increase of evaporation anomalies by affecting the wind speed in the 1990s.

The intraseasonal variations of summer precipitation anomalies in the Meiyu area of East Asia are analyzed by applying a combined empirical orthogonal function (CEOF) of the latest meteorological reanalysis data ERA5 of European Center for Medium-Range Weather Forecasts for the period from 1991 to 2020, and the circulation structures and sources of variability of CEOF are also investigated. The first mode of the intraseasonal variations shows an in-phase pattern over the Meiyu area in June, July, and August, accounting for 22.2% of the total variance in the intraseasonal variations of summer precipitation anomalies. The positive (negative) CEOF1 is accompanied by the negative (positive) East Asia/Pacific pattern, including strong westerly wind anomalies in the upper troposphere and southwest monsoon in the lower troposphere, and the Western Pacific Subtropical High extending westward and its ridge line slightly south. The positive CEOF1 is preceded by decay of El Niño episodes, including the abnormal warm sea surface temperature anomalies (SSTAs) in the equatorial Central-Eastern Pacific in spring and warm SSTAs in the equatorial Indian Ocean in summer. The second mode shows an opposite precipitation anomaly in June and July, and the distribution in August is not significant. The corresponding geopotential height circulation of positive CEOF2 shows the large negative anomaly in the region north of 40° N and a positive anomaly over Japan in June, whereas the pattern reverses in July. At the same time, there is a radical reversion from abnormal eastly to westly wind in the upper troposphere. The structure of CEOF2 is somewhat induced by local SSTAs over the Northern Indian Ocean and South China Sea.

This paper presents a definition of bifurcation-type abrupt changes based on the bifurcation features of Lorenz trajectories. These abrupt changes are the result of the transition behavior of dynamical system trajectories among different equilibrium regions. We demonstrate that these bifurcation-type jumps can better reflect the nature of abrupt change. In analyzing the features of Lorenz equation trajectories, a dynamical method for detecting bifurcation-type abrupt changes is presented. A numerical solution of the Lorenz equation is adopted, using a curve integral or vector product to construct a time series of positive and negative values. Changes in the sign of this time series accurately determine whether the trajectory is in the right or left equilibrium region, and the points at which the time series is equal to zero are the times at which the trajectory jumps between different equilibrium regions, that is, the occurrence times of bifurcation-type abrupt changes. This method is completely dependent on the dynamical characteristics of the system. A theoretical approach for detecting abrupt climate changes based on the dynamical characteristics of the atmospheric model is described. Compared with the original method of identifying abrupt climate changes, this method has dynamic significance and can detect abrupt changes in multi-dimensional time series. Although this method can be applied theoretically, applications to real atmospheric data first require the data to be smoothed.

Atmospheric blocking (‘blocking’) in the Northern Hemisphere (NH) is a crucial driver of extreme cold spells in winter. Here we investigate the anthropogenic influence on the NH blocking and its impact on surface air temperature (SAT) during the winter 1960/1961–2012/2013 using two HadGEM3-GA6-N216 simulations with 15 ensemble members: (a) with anthropogenic and natural forcing (All-hist) and (b) with natural forcing only (Nat-hist). Compared to the Nat-hist run, the blocking frequency in the All-hist run decreases in the Euro-Atlantic, the Urals and the western Pacific, whereas it increases in the eastern Pacific and Greenland. These responses can be explained by the response of planetary waves and storm tracks. On the other hand, the decrease in SAT downstream of the blocking regions in the All-hist run is more pronounced than the Nat-hist run, especially in Europe and the Urals. Correspondingly, the proportion of cold days during all blocking days in these sectors is higher in the All-hist run than the Nat-hist run. These responses can be explained by the wind response associated with blocking. Overall, the spatiotemporal characteristics of blocking is crucial for evaluating the impact of blocking on extreme weather, and their response to anthropogenic forcing should be investigated by more models.

Using the four-times daily and monthly-mean reanalysis datasets of NCEP/NCAR for the 1958 to 2018 period, we investigate the interannual variability of the June-July-August (JJA)–mean water vapor source and sink over the tropical eastern Indian Ocean-Western Pacific (TEIOWP) and the underlying mechanism. It is found that the two major modes (EOF1 and EOF2) of the water vapor source and sink anomalies over the TEIOWP present a southwest-northeast oriented dipole and a southwest-northeast oriented tripole. Specifically, when the western maritime continent shows an anomalous water vapor source, the northwestern Pacific is characterized by anomalous water vapor sink and source in EOF1 and EOF2 modes, respectively. The EOF1 and EOF2 modes are primarily driven by a single and a double meridional cell anomaly, which corresponds to the in-phase and out-of-phase linkage between evaporation anomalies over the western maritime continent and precipitation anomalies over the northwestern Pacific, respectively. Furthermore, the EOF1 mode is regulated by the quick transition of the El Niño-Southern Oscillation (ENSO) phase, whereas the EOF2 mode probably originates from internal atmospheric variability. Considering that the standard deviation of PC1 is much higher during ENSO years than that during non-ENSO years, it is probable that the water source and sink anomalies over the TEIOWP tend to be dominant by EOF1 mode during ENSO years. In contrast, the EOF2 mode may play an important role in the water source and sink anomalies over the TEIOWP during non-ENSO years. Accordingly, the water vapor source and sink anomalies over the TEIOWP may be well predicted based on the ENSO state in the previous December-January-February. These results are useful for understanding the predictability of water vapor source and sink anomalies over the TEIOWP.

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.

Based on the analysis of the feature of Asian continent becoming cold in the early 21st century winter under the background of global warming, the Asian Warming Hole (AWH) index is proposed in this paper to measure the intensity during the cold events process. Result shows that the Asian continent is indeed experiencing a cold stage in the early 21st century winter, but it is just in a cold phase and will become warmer in the future. In recent years the activity of the winter cold events has an obvious quasi-four-year cycle, which can be reflected by atmospheric circulation, and AO (Arctic Oscillation) may play a very important role. It is credible that Asian surface temperature will be higher in the coming 3-4 years compared with 2011 winter, signifying that the precipitation may increase correspondingly.

The three summer drought patterns of the middle-lower reaches of the Yangtze River basin (MLRYRB) and their associated atmospheric circulation were investigated before and after 1980. For the whole-basin wide drought pattern during 1961–1979, the anomalous high ridge over Japan blocked the northerly flow from Siberia to southern China. Further, the western Pacific subtropical high (WPSH) was weaker than normal and shifted eastward. For the southern drought and northern flood pattern during 1961–1979, the zonal circulation was straight and an anomalous anticyclonic circulation was located over Japan. Less moisture was transported to southern China associated with the weakened WPSH. During 1980–2013, the WPSH extended westward and controlled the southern part of the MLRYRB, and an anomalous cyclonic circulation was centered over Japan. For the southern flood and northern drought pattern during 1961–1979, the meridional circulation was obvious, and the WPSH was weaker than normal. The anomalous southwesterly moisture transport appeared to southern China. However, during 1980–2013 the continental high pressure impacted northern China. The WPSH shifted eastward and the anomalous northeasterly moisture transport presented over eastern China.