This study investigates the interdecadal variability of the leading mode of summer persistent extreme precipitation (PEP) over Southwest China (SWC) and its associated mechanisms using observational diagnostics and numerical simulations. The leading mode of summer SWC PEP exhibits a north-south dipole pattern, with a shift from a north-negative-south-positive pattern to a north-positive-south-negative pattern around 2003. An anomalous cyclone over Northeast to North China and an anticyclone over southern China in the lower troposphere trigger the PEP pattern by inducing moisture convergence (divergence) over northern (southern) SWC. Meanwhile, the Rossby wave train along the subtropical westerly jet over Eurasia provides favorable dynamic conditions for the dipole pattern. The moisture budget diagnostics indicate the importance of the interaction between dynamic and thermodynamic processes in the formation of north-south difference in SWC PEP variability. Such atmospheric circulation anomalies are closely related to southern European soil moisture, BarentsKara Sea (BKS) sea ice concentration (SIC) and thermal feedback over the eastern Tibetan Plateau (TP). On one hand, reduced summer soil moisture over southern Europe enhances the meridional temperature gradient and atmospheric baroclinicity to its north, intensifying synoptic-scale transient eddy activity. The resulting transient eddy forcing favors the development of a quasi-barotropic positive geopotential height anomaly over Europe, which subsequently favors the formation of the eastward-propagating wave train that modulates the anomalous circulation associated with SWC PEP. On the other hand, the summer BKS SIC reduction weakens the meridional temperature gradient over the mid-to-high latitude Eurasia, inducing local anomalous easterlies and promoting the formation of the above-mentioned European positive geopotential height anomaly and Rossby wave train. In addition, the thermal feedback over the eastern TP triggered by the Rossby wave train, reinforces the anomalous atmospheric pattern that favors the dipole PEP over SWC.

The Sichuan Basin experienced a persistent extreme heatwave event from 20 August to 28 September 2024, with the regional-mean surface air temperature reaching its highest value for the same period since 1979. This study investigated its spatiotemporal characteristics, underlying mechanisms, and predictability. The results show that an anomalous quasi-barotropic high pressure over East Asia-western North Pacific (AHPEW), with the center located over Northeast Asia, which was induced by the record-breaking enhancement and movement of the western North Pacific subtropical high and the South Asian high, directly contributed to this extreme heatwave event via anomalous adiabatic heating and diabatic heating at the near-surface. Further analyses reveal that anomalously enhanced convective activity over the South China Sea and low soil moisture over central Europe, with record-breaking intensities (since 1979), favored the maintenance and reinforcement of the AHPEW by triggering local meridional circulation anomalies and an extreme negative phase of the Silk Road pattern, respectively. In addition, locally positive soil moisture-evaporation-temperature feedback over the Sichuan Basin further intensified the extreme heatwave. CFSv2 (Climate Forecast System, version 2) reasonably predicts the month-to-month characteristics of the surface air temperature over the Sichuan Basin in August and September 2024 one month in advance, but the predicted intensity is weaker than that observed. This bias is mainly due to the weak prediction of the AHPEW, which is further closely linked to the underestimated intensity of the negative phase of the Silk Road pattern, reduced soil moisture over central Europe, and other related aspects.

Through k-means clustering analysis, this study identified three dominant anomalous patterns of autumn rainfall over West China: (1) a region-wide positive anomalies in precipitation, (2) a south-positive-north-negative dipole pattern, and (3) a west-positive-east-negative dipole pattern. The first two patterns account for most of the explained variance annually. The first pattern is influenced primarily by a strengthened and westward-extended western Pacific subtropical high and an intensified East Asian subtropical jet (EAJ), driven mainly by negative sea surface temperature (SST) anomalies in the tropical central-eastern Pacific. Reduced snow cover over the Tibetan Plateau also plays a moderating role by altering the thermal forcing that affects the EAJ. The second pattern is associated mainly with an anomalous anticyclone over the South China Sea and a weakened, southward-shifted EAJ, which are closely linked to El Nino-like SST anomalies in the tropical central-eastern Pacific and cold SST anomalies in the eastern North Atlantic. The above mechanisms were verified using the Linear Baroclinic Model and the ECHAM5 model.

During August 2020, record-breaking precipitation occurred over the Sichuan Basin (SCB), the highest since 1979, exceeding both the historical August average and the rainfall of July 2020. This observed inter-month precipitation evolution contrasts with the typical climatological pattern, in which precipitation rises from July to August. During this period, two extreme rainfall episodes occurred-11 to 13 August (E1) and 15 to 18 August (E2)-and E2 exhibited a more northerly-located precipitation center and higher precipitation compared to E1. These two extreme precipitation episodes accounted for 60.1 % of the total rainfall in August 2020. This study investigates the causes of inter-monthly precipitation anomalies in the SCB during July-August 2020 from the perspective of the inter-monthly difference (August minus July) and further reveals the causes of two extreme precipitation episodes. Compared to July, the enhanced and eastward-shifted South Asian High (SAH) and the northeastward-shifted Western Pacific Subtropical High (WPSH) collectively contributed to the record-breaking precipitation over the SCB in August. The enhanced western Pacific convection and suppressed Indian Ocean convection influence precipitation through its effects on WPSH and SAH indirectly. During both extreme episodes (E1 and E2), abundant water vapor was transported from the tropical western Pacific to the SCB by the intensified WPSH. Concurrently, more moisture from the Indian Ocean resulted in more precipitation in E2. Moreover, non-adiabatic heating anomalies on the Tibetan Plateau facilitated the development of a southwest vortex, which enhanced upward motion over the SCB. All key processes can be validated by the Linear Baroclinic Model.

The changes in the interannual impact of the May North Atlantic Oscillation (NAO) on May Eurasian surface air temperature (SAT), extreme warm days (EWD), and extreme cold days (ECD) during 1979-2021, along with the underlying mechanisms involved, were investigated in this study based on observation, reanalysis, and numerical experiments. Results showed that since the late 1990s, the response of May SATs, EWDs, and ECDs over the mid- and high-latitudes of Eurasia to the May NAO changed from a southwest-northeast-oriented dipole to a zonal tripole. During 1979-1998 (2000-2021), the May NAO led to northeastward- and southeastward-propagating (eastward-propagating) Rossby waves in May over the region and a resultant dipole (tripole) pattern of atmospheric circulation anomalies with a barotropic structure, which favored a dipole (tripole) pattern of SAT/lower-tropospheric air temperature anomalies, mainly via anomalous horizontal temperature advection (anomalous vertical adiabatic heating/cooling and horizontal temperature advection). From 1979 to 1998 to 2000-2021, the changes in Rossby wave activity induced by the May NAO were caused by the enhancement of atmospheric circulation anomalies in May around Iceland in response to the May NAO. The enhanced response of May atmospheric circulation around Iceland was partly attributed to the enhancement and southward movement of the mid- and upper-tropospheric northern action center of the May NAO, which was located west of Greenland, and the changes in the atmospheric mean state around Iceland.

Based on a normalized difference vegetation index (NDVI) dataset for 1982-2021, we found statistically significant variations in summer NDVI in eastern Siberia in the mid-1990s, i.e., summer-averaged NDVI increased substantially after 1997. Further analysis showed that summer North Atlantic sea surface temperature (NASST) increased markedly in period 2 (P2) (1997-2021) compared with that in period 1 (P1) (1982-96). Correspondingly, summer NASST warming affected the propagation of Rossby waves by altering the intensity of transient wave activity. Subsequently, eastward propagation of Rossby waves induced "negative-positive-negative-positive" circulation anomalies in the upper troposphere extending from the North Atlantic to Eurasia, corresponding to anomalous surface high pressure and southwesterly winds over eastern Siberia. This pattern is beneficial to higher 2-m temperatures, higher soil temperatures, and greater vapor pressure deficit in summer, which are conditions favorable for vegetation growth in eastern Siberia. The ECHAM5 numerical experiments reasonably reproduced the above physical processes. Additionally, under the influence of the snow cover-air temperature positive feedback process during May in eastern Siberia, May soil temperature in eastern Siberia was markedly higher in P2 than in P1. Moreover, May soil temperature anomalies can persist into summer, further favoring growth of summer vegetation. Therefore, the observed abrupt transition in summer NDVI was driven mainly by the combined effect of summer NASST and May land-atmosphere interaction in eastern Siberia. The two physical processes affecting summer NDVI are relatively independent, and they contributed approximately 42% and 8%, respectively, to the observed increase in summer NDVI.

A pronounced dipole anomaly of blocking days (BDD) between the eastern North Atlantic (ENA) and Ural occurred in January 2008, representing the strongest positive phase in recent decades, marked by considerably increased (decreased) Ural (ENA) blocking days. The background circulation exhibits a positive North Atlantic Oscillation phase, with diminished (strengthened) westerly winds and meridional potential vorticity gradients over Ural (ENA), which enhances (suppresses) blocking days. Under the combined anomalies of strong North Atlantic warming, robust La Ni & ntilde;a and substantial Barents-Kara newly formed sea ice reduction, along with their joint effects inducing significant atmospheric wave responses, the notable BDD is facilitated. Over the North Atlantic, enhanced surface turbulent heat fluxes excite upward-propagating Rossby waves and increase atmospheric baroclinicity, favoring local quasi-barotropic low-pressure anomalies that modulate background flow through downstream Rossby wave energy dispersion, thereby influencing the BDD. Over the Pacific, La Ni & ntilde;a-associated cooling suppresses convection, triggering a Gill-type response that strengthens anomalous easterly winds. In combination with reduced baroclinicity over the North Pacific, this enhances the subtropical anticyclone and initiates a downstream Rossby wave train that promotes the BDD. Moreover, declined Barents-Kara newly formed sea ice increases local turbulent heat fluxes and modulates mid-to-high-latitude circulation over Eurasia through altered transient eddy activity and Rossby wave propagation, thus reinforcing the BDD. Numerical experiments using the ECHAM5 model and LBM simulations confirmed the atmospheric responses to these SST and sea ice anomalies. Additionally, BDD-related circulation anomalies trigger widespread temperature and precipitation extremes and may contribute to compound extreme events.

Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotem-poral distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables as-sociated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC com-pared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.

In 2021, an exceptionally intense autumn rainfall event occurred in West China (WC), breaking historical precipitation records since 1961. A notable northward migration of rainfall center was observed during the season. This study utilized real-time forecast data from the ECMWF (European Centre for Medium-Range Weather Forecasts) and CMA (China Meteorological Administration) models under the S2S (Subseasonal-to-Seasonal Prediction) project to examine the subseasonal predictability of the extreme ARWC event and its associated systems, providing a theoretical basis for forecasting extreme autumn rainfall. The results showed that both models underestimated the observed anomalous precipitation, however, ECMWF was able to predict the spatial distribution and intensity of different phases of the event up to 8 days in advance, while the CMA model exhibited poor skill. ECMWF and CMA both successfully predicted the intraseasonal northward migration of the rainfall 8 days and 5 days in advance, respectively. Further analysis revealed that ECMWF and CMA can reproduce the mid-high-latitude wave patterns associated with the intraseasonal variations in the EAWJ at lead times of 1-10 days, contributing to better predictions of the intraseasonal northward migration of the rainfall. Their ability to predict the tropical convection differed, with ECMWF more accurately reproducing the anomalous dipole tropical convection activities over the Indo-Pacific Warm Pool and the central-eastern Pacific 1-22 days in advance, and the characteristic that the convection eventually weakens over the maritime continent. This led to better predictions of the intraseasonal variations of the WPSH, giving the ECMWF model a higher forecasting skill for both periods of the extreme ARWC in 2021 compared to the CMA model.

Based on observational datasets during 1980-2021 and the simulations from the PAMIP (Polar Amplification Model Intercomparison Project), this paper indicates that the eastern North Atlantic-Ural blocking days in December-January is characterized by a zonal dipole pattern which undergoes an interdecadal variation around 2008. Specifically, the blocking days in Ural (eastern North Atlantic-western Europe) regions increases (decreases) after 2008. Further research shows that the variation in the blocking days dipole (BDD) pattern is closely associated with the changes in the simultaneous background atmospheric circulation field including westerly winds, vertical shear of zonal winds, and meridional potential vorticity gradient over the eastern North Atlantic-Urals region. Moreover, after 2008, the positive North Atlantic Oscillation-like phase intensifies, a quasistationary eastward-propagating Rossby wave from the North Atlantic is excited, and a quasi-barotropic "-, +, -" tripole circulation anomaly in the eastern North Atlantic-Central Siberia is formed in the mid-upper troposphere. It is also found that, since 2008, there is a remarkable negative correlation between the Barents-Kara sea-ice concentration (SIC) and the BDD. After 2008, the rapid decrease in Barents-Kara SIC, dominated by newly formed SIC, is conducive to an increased local upward surface turbulent heat flux, further exciting Rossby waves and favoring the tripole circulation anomaly. Additionally, the atmospheric internal dynamical processes excited by the tripole circulation anomaly have positive feedback effects on it, contributing to strengthening (weakening) of the local background circulation field in the eastern North Atlantic-western Europe (Urals) region, thereby causing the blocking days to decrease (increase). The responses of the main physical processes to the Arctic sea ice reduction in the PAMIP models are roughly in agreement with the observations.

Accurately forecasting the Pan-Arctic sea-ice extent (SIE) in September is crucial for understanding climate change impacts and ensuring safe Arctic navigation. This study introduces the SWR DY-method, a novel prediction approach that combines the stepwise regression (SWR) and interannual increment methods and applies it to predictive performance. The model identifies grid points significantly correlated to September SIE using the temporal correlation coefficients between various monthly climate variables and the Pan-Arctic SIE in September. A database of potential predictors was established, from which SWR and long short-term memory (LSTM) neural networks were used to develop single-predictor models with monthly initializations from January to September. These single-predictor models were then ensemble-averaged to create multi-predictor ensemble prediction models. Evaluation of the models from 2014 to 2022 was carried out, comparing the performances of the SWR DY-method and LSTM DY-method. Results indicated that the SWR DY-method had higher single-predictor prediction skill than the LSTM DY-method. Multi-predictor models using the SWR DY-method demonstrated lower mean absolute errors and higher predictive skill for January to September initializations, outperforming the LSTM and the SIO (Sea Ice Outlook) median predictions. This study presents a new and effective strategy for improving seasonal predictions of Pan-Arctic SIE.摘要精准预测9月北极海冰范围对理解气候变化的影响与保障北极航道安全至关重要. 基于逐步回归和年际增量预测方法(SWR-DY), 本文研制了一种9月北极海冰范围预测新模型.该模型基于各月气候变量与9月北极海冰范围的时间相关系数, 筛选具有统计显著性的预测因子, 建立潜在预测因子库. 在此基础上, 分别采用SWR和长短期记忆神经网络(LSTM)构建1 − 9月逐月起报的单因子预测模型, 并通过集合平均得到多因子集合预测模型. 本文通过对比了不同模型对2014−2022年9月北极海冰范围的预测效能. 结果表明:SWR DY方法的单因子预测能力普遍优于LSTM DY方法; 其多因子模型在1 − 9月起报时均表现出更低的平均绝对误差和更高的预测能力. 新方法对2014−2022年9月北极海冰范围的预测效能也高于国际海冰预测网络活动多模型预测结果中位数的预测效能. 本研究为9月北极海冰范围预测提供了新方法.

Previous studies have demonstrated significant modulation of stratospheric polar vortex (SPV) on the northern annular mode (NAM) during winter, whereas the specific processes are not fully understood. This study investigates how the SPV prolongs the persistence of the NAM on the subseasonal timescales during winter. Our results suggest that the quasi‐geostrophic refractive index (RI) at the high latitudes of mid‐to‐upper troposphere (HL‐MTUT) may serve as a critical mediator in this process. Specifically, the preestablished SPV anomaly can persistently alter the RI at HL‐MTUT through directly modifying the vertical curvature of zonal wind in this region. The RI anomaly at HL‐MTUT, which reflects changes in the waveguide properties of zonal flow, can affect the meridional propagation of tropospheric eddies and is a key factor in the eddy‐zonal flow interactions associated with the NAM. Acting as a mediator, the HL‐MTUT RI will transmit the persistent anomalous signal of the SPV, which has a longer timescale compared to tropospheric variability, into the intrinsic dynamic processes of NAM. Consequently, the SPV will prolong the persistence of NAM. The above mechanism is further supported by a comparison of active‐SPV and inactive‐SPV years: In active‐SPV years, a greater persistence of the NAM is accompanied by a correspondingly greater persistence in both the vertical curvature of zonal wind and the RI at HL‐MTUT.

It has been a challenge to identify the impact of Arctic sea-ice loss on the intensity and position of the winter North Atlantic jet stream (NAJS) and the related mechanisms due to the uncertain effects of atmospheric internal variability. This study investigates the response of the winter NAJS to Arctic sea-ice loss and roughly estimates the contribution of internal variability in Arctic sea ice (ArcSIC) after the pre-industrial period, based on reanalysis dataset (referred to as observation here), the Coupled Model Inter-comparison Project phase 6 (CMIP6) and the Polar Amplification Model Inter-comparison Project (PAMIP). The results indicate that the majority of PAMIP models display robust but weak equatorward shift of the NAJS response to Arctic sea-ice loss, as well as robust NAJS-related circulation anomalies. Further analysis shows that the ability of models to reproduce observed NAJS response is primarily associated with tropospheric baroclinic wave activity and the troposphere-stratosphere coupling. Based on 20th-Century reanalysis data and CMIP6 historical simulations, we further estimate the relative contributions of external forcing and internal variability (including reduced ArcSIC) to NAJS latitude and speed variability. Compared to the pre-industrial period, the recent winter NAJS at 850 hPa has accelerated and shifted poleward. By calculating the ratio of the difference in NAJS speed (latitude) between the present-day and pre-industrial in CMIP6 multi-model ensemble mean to the difference in observation, this study approximately estimates that the external forcing contributes about 40 % of NAJS acceleration with minimal influence on its shift. The remaining acceleration and poleward shift are mainly attributed to internal variability. The difference between the present-day and pre-industrial PAMIP ensemble mean is considered as the "pure" forcing of Arctic sea-ice loss. Most models indicate that reduced ArcSIC tends to slow down the acceleration and pole- ward shift of winter NAJS, but show quantitively a wide range of uncertainty.

This study investigated the interannual relationship between July and August Beaufort Sea ice (BSIC) and August southern Greenland precipitation (SGP). Additionally, underlying mechanisms were explored using the ECHAM5 model. During 2008-2023, the interannual correlation between July and August BSIC and August SGP increased significantly compared to 1990-2007, with correlation coefficients of 0.70 and 0.51 for two precipitation datasets, both passing the significance test at the 95% confidence level. Further analysis indicated that, after 2008, the BSIC decreased significantly. The proportion of first-year ice increased, while sea ice thickness declined. These changes contributed to enhancing interannual variability in sea ice and strengthened the interannual correlation between BSIC and SGP. In terms of the mechanism, when BSIC decreased, it was accompanied by rising sea-air temperature and specific humidity differences. The upward sensible and latent heat fluxes increased. The reduction in sea ice triggered eastward-propagating Rossby waves, causing circulation anomalies in the North Atlantic resembling a negative phase of the summer North Atlantic Oscillation. Such circulation patterns inhibited moisture transport from the southwestern direction of the Labrador Sea and enhanced subsidence through cold advection, leading to reduced SGP. Conversely, when BSIC increased, the opposite effect occurs. Since 2008, the significant interdecadal decline in BSIC has become a key driver of the interdecadal decrease in SGP, although the latter is also influenced by the complex interactions within the climate system. Simulations using the ECHAM5 model confirmed these possible physical mechanisms behind the relationship.

Based on a normalized difference vegetation index (NDVI) dataset for 1982-2021, this work investigates the principal modes of interannual variability in summer NDVI over eastern Siberia using the year-to-year increment method and empirical orthogonal function (EOF) analysis. The first three principal modes (EOF1-3) of the yearto-year increment of summer NDVI (NDVI_DY) exhibit a regionally consistent mode, a western-eastern dipole mode, and a northern-southern dipole mode, respectively. Further analysis shows that sea surface temperature (SST) in the tropical Indian Ocean in February-March and western Siberian soil moisture in April could influence EOF1. EOF2 is modulated by April Northwest Pacific SST and western Siberian soil moisture in May. May North Atlantic SST and sea ice in the Kara Sea in the preceding October significantly affect EOF3. Using the year-to-year increment method and multiple linear regression analysis, prediction schemes for EOF1-3 are developed based on these predictors. To assess the predictive skill of these schemes, one-year-out cross-validation and independent hindcast methods are employed. The temporal correlation coefficients between observed EOF1-3 and the cross-validation results are 0.62, 0.46, and 0.37, respectively, exceeding the 95 % confidence level. In addition, reconstructed schemes for summer NDVI are developed using predicted NDVI_DY and the observed principal modes of NDVI_DY. Independent hindcasts of NDVI anomalies during 2019-2021 also present consistent distributions with the observed results.

The sea ice growth (SIG) in the Kara Sea plays a crucial role in the Arctic climate system. Many studies have examined its long‐term trend, but whether its variability has changed is less clear. Using observations and reanalysis data, we observe an intensified interannual variability of the Kara Sea SIG during boreal late winter (December–March) since 2004/2005. This arises from the retreat of active ice production zones in response to the strengthened modulation of the westward‐shifted North Atlantic Oscillation (NAO). Using a sea ice concentration budget, we quantitatively partition the NAO's contribution to total SIG variability post‐2004 (∼63.3%), revealing comparably dominant roles of thermodynamic and dynamic processes. During this period, the negative NAO‐associated surface winds concurrently cool sea surface and export sea ice from the Kara Sea, thereby injecting freshwater into the lower latitudes. Our study advances the understanding of the regional air‐ice‐ocean climate feedbacks in recent Arctic.

Southwest China (SWC) experienced a persistent extreme drought event from January to May 2023, with extensive and severe drought conditions peaking in January, April, and May. During these peak months, the standardized precipitation evapotranspiration index anomalies exceeded −1.5 standard deviations, indicating the extreme seasonal drought. Analysis revealed that anomalous descending motion and suppressed moisture transport resulted in precipitation deficit and enhanced potential evapotranspiration, further causing the prolonged drought. Specifically, in January 2023, reduced snow cover in southern Europe induced mid‐upper tropospheric high‐pressure anomalies over the Tibetan Plateau and SWC and enhanced Ural blocking high, contributing to anomalous northerly cold winds and subsidence. Simultaneously, cold sea surface temperature (SST) anomalies in the tropical western Indian Ocean weakened the south branch trough (SBT), further limiting moisture supply. These factors resulted in cold and dry conditions across SWC. In April, decreased snow cover in northern Europe excited upper‐level Rossby waves, favoring positive geopotential height anomalies and anomalous descending motions over SWC. These conditions, combined with a weakened SBT linked to warm SST anomalies in the Arabian Sea, suppressed precipitation in SWC. Additionally, strong local land‐atmosphere interactions and subsidence‐induced diabatic warming increased surface air temperature, exacerbating high temperature and drought conditions in April. In May, mid‐upper tropospheric high‐pressure anomalies over SWC linked to dry soil moisture in western Siberia and a weakened SBT associated with southern Indian Ocean SST anomalies, together with local land‐atmosphere coupling, sustained dry and hot conditions in SWC. Numerical experiments further confirmed the above physical mechanism.

Extreme easterly wind stress anomalies were observed in the equatorial Pacific in 2022, yet the underlying dynamics causing the easterly anomalies remain unclear. Moreover, it was still under debate that easterly anomalies in which period played the dominant role in the development of the 2022 La Ni & ntilde;a. Based on ERA5 reanalysis, we found that the annual-mean equatorial easterly wind stress anomalies in 2022 reached record highs since 1982, with the influence mainly from the strengthened trade winds over the past four decades (30.71%), cold sea surface temperature (SST) anomalies in the central equatorial Pacific (36.22%), cold SST anomalies in the southeastern tropical Pacific (21.26%), and two sets of easterly wind surges (EWSs) near the date line (7.65%). A strong convective Madden-Julian oscillation and a series of intense synoptic anticyclonic eddies in South Pacific were found as the main drivers of the EWSs. By forcing a coupled model with the equatorial zonal wind anomalies in different periods in 2022, we found that the easterly anomalies from January to mid-February and from mid-March to mid-June played the critical role in the development of 2022 La Ni & ntilde;a. While the two sets of EWSs cooled the equatorial central-eastern Pacific after their appearance, they did not significantly influence the intensity of 2022 La Ni & ntilde;a in boreal winter. Our findings imply that multiscale processes from synoptic to secular scales collectively contributed to the equatorial Pacific cooling in 2022 and further the genesis of the 2020-23 triple-dip La Ni & ntilde;a event.

Winter temperature variations in Siberia significantly influence climate anomalies and seasonal predictions across East Asia. While Bering Sea ice (BS_SIC) has emerged as an increasingly important factor in mid‐latitude climate, its connection to Siberian winter extremes remains poorly understood. Using observations, reanalysis data sets and ECHAM5 simulations, this study examines the influence of December BS_SIC on January extreme cold days (ECDs) in Siberia and the associated mechanisms. Results show that the interannual variability of BS_SIC is significantly correlated ( r = 0.49) with Siberian ECDs during 2000/01–2020/21, whereas no significant correlation is found during 1979/80–1997/98. The enhanced BS_SIC variability after 2000 strengthens eddy‐mean flow interaction, generating a Rossby wave that propagates from Alaska to Eurasia. Energy conversion at the North Atlantic jet exit enables this wave train to extract energy from the mean flow, leading to a northward shift of the East Asian polar front jet and a reduction in Siberian ECDs.