Barents Kara Seas Research Articles

Atmospheric warming during rapid sea ice loss over the Barents–Kara seas in winter

AbstractThe atmospheric temperature change associated with rapid sea ice loss events over the Barents–Kara Seas (BKS) is explored. Rapid sea ice loss events are defined as periods with a tendency for sea ice concentration averaged over BKS to be below the fifth percentile of the probability density function distribution during the winters of 1979–2020 for at least three consecutive days. Composite analysis shows that there is a significantly positive bottom‐amplified temperature anomaly ahead of the rapid sea ice loss, which is closely associated with a wave train composed of a Ural blocking and an upstream positive phase of the North Atlantic Oscillation. This structure is favorable for the transport of warm and moist air into the BKS, and therefore, the tropospheric temperature, including the surface air temperature, increases through horizontal warm‐temperature advection, specifically through warm advection of the climatological temperature by the anomalous wind. The cooling over the BKS due to the adiabatic effect and vertical mixing opposes the horizontal warm‐temperature advection above and below about 900 hPa, respectively. However, an increase in skin temperature prominently results from enhanced downward long‐wave radiation, which is also the main contributor to the rapid sea ice loss.

The cooperative effects of November Arctic sea ice and Eurasian snow cover on the Eurasian surface air temperature in January–February

AbstractDue to their significant influence on large‐scale atmospheric circulation and climate anomalies, the variability of Arctic sea ice and Eurasian snow cover during late autumn and their combined effects have garnered increasing attention. This study aims to investigate the physical mechanism underlying the covariation among the Barents‐Kara Seas (BKS) sea ice concentration (SIC), Eurasian snow cover extent (SCE) and the ensuing winter Eurasian surface air temperature (SAT). The statistics results of singular value decomposition suggest a significant linkage between the decreased BKS SIC, zonal “negative–positive” dipole SCE anomalies over Eurasia in November and cold Eurasian SAT in January–February (JF). Observational diagnosis analyses about the meridional moisture, heat transport and surface heat flux demonstrate that subpolar Eurasian anticyclonic circulation plays a crucial role in connecting the predominant modes of SIC and SCE. Furthermore, the BKS SIC and Eurasian SCE anomalies can jointly excite upward‐propagating planetary waves into the stratosphere, while simultaneously reducing the subpolar meridional temperature gradient. This results in westerly wind deceleration and favours the continuous planetary wave propagation. Consequently, the stratospheric polar vortex is significantly weakened, along with negative Northern Annular Mode anomalies propagating downward from the stratosphere to troposphere. Negative‐phase Arctic Oscillation anomalies correspondingly develop during JF, resulting in widespread cold anomalies over the Eurasian continent. These results are further confirmed by numerical sensitivity experiments from the Community Atmosphere Model forced by the above mentioned SIC and SCE anomalies. The empirical hindcast model analyses further suggest that the prediction skill of JF Eurasian SAT is enhanced when both the November BKS SIC and Eurasian SCE signals are considered.

Dominant features of phasic evolutions in the winter Arctic-midlatitude linkage since 1979

Abstract Over the past decades, the Arctic-midlatitude linkage has been extensively explored. Recent studies have suggested that the characteristics of phasic evolutions in the relationship between the Arctic warming and midlatitudes remain elusive. Therefore, this study systematically investigates this issue by using running empirical orthogonal function (EOF) and moving correlation, and the results show a phasic alternation process in the relationship between the tropospheric thickness over the Barents-Kara Seas (BKS) and East Asian temperature, characterized by a phasic weak (P1: 1979-2000)–strong (P2: 2001-2011)–weak (P3: 2012-2021) connection. Our results highlight that since the winter of 2010, despite the Arctic sea ice being in an exceptionally reduced phase and continuous Arctic warming, the Arctic-midlatitude connection has not exhibited sustained strengthening relative to P2 phase. Moreover, it is found that changes of the connection between the BKS warming and the East Asian winter Monsoon may contribute to this phasic evolution, and the Arctic Oscillation (AO) plays an important role in modulating their phasic evolutions. The conclusions of this study help to deepen our understanding of the evolution of the strength and weakness of the relationship between Arctic warming and climate variations in midlatitudes.

Relative sea-level sensitivity in the Eurasian region to Earth and ice-sheet model uncertainty during the Last Interglacial

Fingerprinting the source and rate of the melt of polar ice sheets during the Last Interglacial is a key research challenge. This is reliant on high-quality relative sea-level constraints, and the correction of this data for the effects of glacial isostatic adjustment driven by ice sheet cover changes prior to the interglacial. However, both the spatial and temporal evolution of past ice sheets and the Earth’s rheological structure that serve as inputs to glacial isostatic adjustment predictions are significantly uncertain. This study sets out to determine the relative influence of each of these inputs on modelled values of Last Interglacial relative sea levels and how this influence varies spatially. To answer this question, we use a palaeo ice-sheet model and a gravitationally consistent glacial isostatic adjustment model. We develop new numerical tools to generate plausible ice-sheet extent and histories, quantify relative sea-level uncertainty, and perform a Sobol sensitivity analysis facilitated by the use of Gaussian process emulation. We find that Earth model parameters are the dominant contributors to relative sea-level uncertainty in most Eurasian regions, but that relative sea-level values in the Barents-Kara Sea are most influenced by ice-sheet loading, while the timing of the deglaciation has the greatest impact in the Baltic Sea. Our results show that the magnitude and rate of relative sea-level change is relatively insensitive to the specific timing of ice-sheet retreat, as well as the configuration of the far-field North American ice sheet. Overall, our work suggests that the coastlines of the southern North Sea and the English Channel are least influenced by relative sea-level uncertainty and are the most suitable for future data collection studies aiming to limit the influence of glacial isostatic adjustment.

Storylines of summer Arctic climate change constrained by Barents–Kara seas and Arctic tropospheric warming for climate risk assessment

Abstract. While climate models broadly agree on the changes expected to occur over the Arctic with global warming on a pan-Arctic scale (i.e. polar amplification, sea ice loss, and increased precipitation), the magnitude and patterns of these changes at regional and local scales remain uncertain. This limits the usability of climate model projections for risk assessments and their impact on human activities or ecosystems (e.g. fires and permafrost thawing). Whereas any single or ensemble mean projection may be of limited use to stakeholders, recent studies have shown the value of the storyline approach in providing a comprehensive and tractable set of climate projections that can be used to evaluate changes in environmental or societal risks associated with global warming. Here, we apply the storyline approach to a large ensemble of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models with the aim of distilling the wide spread in model predictions into four physically plausible outcomes of Arctic summertime climate change. This is made possible by leveraging strong covariability in the climate system associated with well-known but poorly constrained teleconnections and local processes; specifically, we find that differences in Barents–Kara sea warming and lower-tropospheric warming over polar regions among CMIP6 models explain most of the inter-model variability in pan-Arctic surface summer climate response to global warming. Based on this novel finding, we compare regional disparities in climate change across the four storylines. Our storyline analysis highlights the fact that for a given amount of global warming, certain climate risks can be intensified, while others may be lessened, relative to a “middle-of-the-road” ensemble mean projection. We find this to be particularly relevant when comparing climate change over terrestrial and marine areas of the Arctic which can show substantial differences in their sensitivity to global warming. We conclude by discussing the potential implications of our findings for modelling climate change impacts on ecosystems and human activities.

Projection of a winter ice-free Barents-Kara Sea by CMIP6 models with the CCHZ-DISO method

The winter sea ice over the Barents-Kara Sea (BKS) is reducing at an alarming rate, which impacts the Arctic shipping routes and the local ecosystems as well as the climate system across other regions. Consequently, it is imperative to project the winter ice-free state in this region to adequately prepare for future climate change and its impacts. However, most models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) show higher climatological values, weaker decreasing trends, and lower interannual variabilities in winter BKS sea ice concentration compared to observation. Additionally, it can be also seen that there exist great uncertainties in the projections of different models on whether the BKS region will be ice-free in future winters and the ice-free period, which spans almost the entire 21st century. Therefore, the study adopts two approaches developed from distance between indices of simulation and observation (DISO) method to project the winter ice-free period of the BKS under different emission scenarios. The results indicate that under SSP1–2.6, the winter BKS will not be ice-free by 2100. For SSP2–4.5, SSP3–7.0, and SSP5–8.5, the winter BKS is projected to be ice-free during 2076–2086, 2063–2068, and 2049–2061, respectively. By employing the DISO method, the projection uncertainty is reduced and the results highlight the urgency of reducing greenhouse gas emissions to delay the winter ice-free period over the BKS. These projections are intended to provide a reference for policymakers.

Significant contribution of internal variability to recent Barents–Kara sea ice loss in winter

The Arctic has experienced a rapid sea ice loss in the Barents and Kara Seas in winter over the satellite era. Such sea ice loss has been modulated by anthropogenic forcing and internal variability, but a precise estimate of their relative contribution remains unclear. Here, using large ensemble simulations and machine-learning techniques, we successfully reproduce wintertime Barents-Kara sea ice trends as the joint impact of anthropogenic and internal variability components. Over the whole satellite period, anthropogenic forcing contributes about 70% to the Barents-Kara sea ice loss, with internal variability contributing to the remainder. However, internal variability is more important in explaining varying sea ice trends over shorter periods (~20 years), including the accelerated sea ice loss up to 2017, consistent with an extreme, unforced atmospheric circulation dipole trend in the Euro-Atlantic sector. Overall, this study highlights that internal variability plays a more important role in shaping recent winter Arctic sea ice loss than previously thought, and has implications for Arctic sea ice projections and the use of machine learning methods in future attribution studies.

Influence of Regional Sea Ice Loss on the Arctic Stratospheric Polar Vortex

AbstractBased on multi‐model large‐ensemble experiments provided by Polar Amplification Model Intercomparison Project (PAMIP), we investigate the influence of the projected sea ice loss in Barents‐Kara Seas (BKS) and Sea of Okhotsk (SOK) on the Arctic stratospheric polar vortex (SPV). Results show that future BKS sea ice reduction leads to a weakened SPV during November‐February by enhancing the upward‐propagating planetary wave 1, which is more pronounced during Quasi‐Biennial Oscillation (QBO) easterly than westerly phase. Through weakening the upward‐propagating planetary wave 2, future SOK sea ice reduction is favorable for a strengthened SPV during January‐April. Inter‐model spread in the magnitudes of SPV responses to BKS sea ice reduction can be largely explained by the divergent planetary wave responses, but less so for SOK sea ice reduction. Results from a linearized baroclinic model further validate the importance of the planetary‐scale wave responses in explaining the differing SPV responses to sea‐ice loss over the two regions.

Mechanism for compound daytime-nighttime heatwaves in the Barents–Kara Sea during the boreal autumn and their relationship with sea ice variability

The frequency of heatwaves in the Arctic is on the rise under global warming. These occurrences not only profoundly impact the local ecological environment but also exert remote effects on East Asia and even the global climate. Yet, there exists a noticeable dearth of research focus on Arctic compound daytime-nighttime heatwaves, limiting our comprehension of Arctic climate dynamics. We investigated the occurrence and extinction mechanism for compound daytime-nighttime heatwaves in the Barents–Kara Sea (BKS) during the boreal autumn and explored their association with the sea ice variability. Our results show that a significant dipole pattern appears in the geopotential height two days before the occurrence of compound daytime-nighttime heatwaves in the BKS during autumn, characterized by a negative anomaly centered over Greenland and a positive anomaly centered over the BKS. A robust southerly anomaly in the middle of this dipole pattern facilitates the continuous inflow of warm, moist air from the Atlantic Ocean to the BKS. Both the strong intrusion of moisture and the transport of heat (positive temperature advection) driven by the large-scale atmospheric circulation increase downward latent heat flux, sensible heat flux and net longwave radiation. These factors collectively increase the near-surface temperature over the BKS, ultimately leading to the occurrence of compound daytime-nighttime heatwaves in this region of the Arctic. The extinction of compound daytime-nighttime heatwaves in the BKS is a result of the weakening of the transport of heat and intrusion of water vapor caused by changes in the large-scale circulation. The intrusion of water vapor and the transport of heat significantly reduce the sea ice concentration in most of the BKS. This reduction in sea ice persists for an additional day after the termination of compound daytime-nighttime heatwaves in the BKS. A process of positive atmospheric temperature feedback on a sub-monthly scale may potentially influence the maintenance of compound daytime-nighttime heatwaves in the BKS during the boreal autumn.

Subseasonal variability of sea level pressure and its influence on snowpack over mid-high-latitude Eurasia during boreal winter

The atmospheric circulation significantly influences the snowpack over mid-high-latitude Eurasia. This study examines the characteristics of the leading subseasonal variability mode of boreal winter sea level pressure (SLP) with 20-80-day period and its relationship with snowpack over mid-high-latitude Eurasia, using the fifth generation of European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) data and different snowpack datasets. The SLP leading mode, characterized by a monopole pattern with a strong surface anomalous high centered near the Ural Mountains, exhibits a barotropic structure and extends from the surface to the tropopause. Above SLP and geopotential height anomalies propagate southeastward from the Barents-Kara Sea to East Asia. This leading SLP mode contributes to surface air temperature (SAT) and snowfall circulation anomalies over mid-high-latitude Eurasia. The latter two both directly influence on snowpack anomalies in situ. Over high latitude region, snowfall circulation anomaly is the dominant factor to control the snow depth anomaly. Over middle latitude region, both SAT and snowfall circulation anomalies lead to the snowpack anomaly. Furthermore, the response of snow depth to the leading subseaonal SLP mode occurs 2–5 days earlier than the response of snow cover to the same mode over middle latitude region. In addition, it is suggested that the Arctic Oscillation (AO), East Atlantic/West Russia (EAWR) and Polar/Eurasia (PEU) pattern may contribute to the development of the leading SLP mode and subsequently influence snowpack anomalies.

The recent increasing frequency of strong cooling event in Southwest China in February

AbstractA strong cooling event refers to a sharp change in the average temperature over a short period. The rapid change of temperature has important effect on human health and is highly concerned recent years. Based on the observed temperature data set from stations in Southwest China (SWC) from 1979 to 2017, this paper analyses the characteristics of the strong cooling event (SCE). The result shows that SCE occurs with the highest frequency during the time from February to May. Among them, the frequency of SCE in February exhibits an abrupt change before and after 2005 with a significant increase. Further study reveals that the change of SCE frequency in February is associated with the large‐scale background circulation patterns. After 2005, there is a cyclonic circulation anomaly in Northeast Asia and an anticyclonic circulation anomaly in the Tibet Plateau (TP). This pattern provides a favourable condition for the southward movement of cold air mass, thereby increasing the frequency of SCE in SWC. Furthermore, it is revealed that there is a strong correlation between the variation of SCE frequency in February and sea surface temperatures (SST) in the Northwest Pacific in January before 2005. The cold SST anomaly could favour the occurrence of extreme TD events in SWC through vertical circulation. After 2005, the correlation between SCE and Northwest Pacific SST is not significant. The sea ice in the northern Barents Sea and Kara Sea becomes the dominant impact factor. The abnormally low sea ice concentration is conducive to strengthen the meridional circulation over East Asia, leading to an increasing frequency of SCE in SWC.

Physical and Unphysical Causes of Nonstationarity in the Relationship Between Barents‐Kara Sea Ice and the North Atlantic Oscillation

AbstractThe role of internal variability in generating an apparent link between autumn Barents‐Kara sea (BKS) ice and the winter North Atlantic Oscillation (NAO) has been intensely debated. In particular, the robustness and causality of the link has been questioned by showing that BKS‐NAO correlations exhibit nonstationarity in both reanalysis and climate model simulations. We show that the lack of ice observations means nonstationarity cannot be confidently assessed using reanalysis prior to 1961. Model simulations are used to corroborate an argument that forced nonstationarity could result from ice edge changes due to global warming. Consequently, the observed change in BKS‐NAO correlations since 1960 might not be purely a result of internal variability and may also reflect that the ice edge has moved. The change could also reflect the availability of more accurate ice observations. We discuss potential implications for analysis based on coupled climate models, which exhibit large ice edge biases.

Can seasonal prediction models capture the Arctic mid‐latitude teleconnection on monthly time scales?

AbstractThis study explores Arctic warming's effect on Eurasia's temperature variability, notably the warm Arctic–cold Eurasia (WACE) pattern, and assesses seasonal prediction models' accuracy in capturing this phenomenon and its monthly variation. Arctic warming events are categorized into deep Arctic warming (DAW), shallow Arctic warming (SAW), warming aloft (WA), and no Arctic warming (NOAW), based on the temperatures at 2 m and 500 hPa in the Barents–Kara Sea. It is revealed that DAW events are significantly correlated with monthly cold temperature anomalies in East Asia, predominantly occurring in January–February, excluding December. This study evaluates two primary capabilities of seasonal prediction models: their proficiency in forecasting these Arctic warming events, particularly DAW, and their ability to replicate the spatial patterns associated with DAW. Some models demonstrated notable predictive skill for DAW events, with enhanced performance in January and February. Regarding spatial pattern reproduction, models showed limited alignment with the reference dataset over the Northern Hemisphere (above 25° N) in December, whereas a higher degree of concordance was observed in January–February. This indicates their capability in capturing the atmospheric circulation patterns associated with DAW, pointing to areas where model performance can be enhanced.

Connections between low- and high- frequency variabilities of stratospheric northern annular mode and Arctic ozone depletion

Previous studies have demonstrated a dynamical linkage between the ozone and stratospheric polar vortex strength, but only a few have mentioned the persistence of the anomalous vortex. This study uses the complete ensemble empirical mode decomposition with adaptive noise to decompose the winter stratospheric northern annular mode (NAM) variabilities into relatively low frequencies (>4 months) and high frequencies (<2 months) (denoted as NAML and NAMH) and investigates their relationship with the Arctic ozone concentration in March. A closer relationship is found between the Arctic ozone and the NAML, i.e. a persistently strong stratospheric polar vortex in winter (especially February–March) is more critical than a short-lasting extremely strong vortex in contributing to Arctic ozone depletion. We find that a negative NAMH or major stratospheric sudden warming event in early winter could be a precursor for the anomalous depletion of Arctic ozone in March. The NAML changes are further related to the warm North Pacific sea surface temperature (SST) anomalies and ‘central-type’ El Niño-like or La Niña-like SST anomalies in early winter months, as well as cold North Atlantic SST anomalies and higher sea ice concentration in the Barents–Kara Sea from late-autumn to early-spring.

The linkage between wintertime sea ice drift and atmospheric circulation in an Arctic ice-ocean coupled simulation

By analyzing an Arctic ice-ocean coupled simulation, we study the linkage between wintertime sea ice drift and atmospheric circulation, and interpret the driving force terms in the sea ice dynamic equation. Sea ice drift anomaly is featured by an anticyclonic (cyclonic) gyre when regulated by negative (positive) phase of Arctic Oscillation with positive (negative) phase of Arctic Dipole, and a quasi-meridional stream from Chukchi-Beaufort (Barents-Kara) Seas to Barents-Kara (Chukchi-Beaufort) Seas when regulated by positive (negative) phase of Arctic Oscillation with positive (negative) phase of Arctic Dipole. Sea ice drift anomaly, when regulated by the mode alone, resembles spatial pattern of leading atmospheric mode. Decomposing sea ice dynamical equation shows that wind-ice stress dominates sea ice drift in areas away from islands and continental coastlines, ocean-ice stress acts as a resistant power to partly cancel the wind-ice stress in these areas, while in the coastal areas such as the thick multiyear ice zone north of the Canadian Arctic Archipelago, the wind-ice and ocean-ice stresses are small, the balance exists between sea surface height potential gradient and internal ice stress divergence. Developing more sophisticated internal ice stress expression in ice model is of great important to correctly project future sea ice change for the ice modeling community.

Differing roles of North Atlantic oceanic and atmospheric transports in the winter Eurasian Arctic sea-ice interannual-to-decadal variability

In recent decades, winter Arctic sea-ice concentration (SIC) has experienced a most prominent decline over Barents-Kara Seas (BKS). However, what regulates the time scale and spatial structure of the SIC variability over the Eurasian Arctic is unclear. Here, we find that the SIC variability over the Eurasian Arctic exhibits two major modes: decadal dipole mode with antiphase variation between the BKS and East Greenland (EG), and interannual monopole mode with in-phase variation between the BKS and EG. This decadal mode mainly results from interdecadal changes in ocean heat transports (OHTs) through Barents Sea Opening (BSO) and EG, lagging the Atlantic Multidecadal Oscillation by 7–16 years. The positive SIC dipole mode with a decrease over the BKS and an increase over the EG is also tied to the negative Arctic Oscillation comprised of Ural blocking and the negative North Atlantic Oscillation (NAO). However, the SIC loss of the interannual monopole mode mainly stems from the positive Arctic dipole comprised of Ural blocking and positive NAO through interannual changes in the BSO OHT and atmospheric moisture or heat transport. We further highlight that interannual atmospheric transports and BSO OHT associated with the Arctic dipole contribute to ~66% and ~34% of the interannual variability of the Eurasian Arctic SIC during 1960-2017, respectively. On decadal timescales, the relative contributions of atmospheric transports associated with Arctic Oscillation and OHT to the Eurasian Arctic SIC variability are ~19% and ~81%, respectively. Especially, the contribution of decadal atmospheric transports is significantly intensified during 2000–2017.

Two distinct declining trend of autumn Arctic sea ice concentration before and after 2002

This study investigates the Arctic sea ice concentration trend during 1979–2021 and explores why the autumn Arctic sea ice loss is accelerated after 2002 and its trend declining center shifts from the Chukchi Sea to the Barents-Kara-Laptev Seas. Attribution analysis reveals that the enhanced summer sea ice concentration negative trend in large part explains the autumn sea ice concentration accelerating reduction, whereas it is the trend center shift of increased downward longwave radiation that accounts for mostly of the autumn sea ice concentration decline center shift. Further analysis suggests the downward longwave radiation trend is closely related to large-scale atmospheric circulation changes. A tendency towards a dipole structure with an anticyclonic circulation over Greenland and the Arctic Ocean and a cyclonic circulation over Barents-Kara Seas enhances (suppresses) the downward longwave radiation over Western (Eastern) Arctic by warming and moistening (cooling and drying) the lower troposphere during 1979–2001. In comparison, a tendency towards a stronger Ural anticyclone combined with positive phase of the North Atlantic Oscillation pattern significantly promotes the increase of downward longwave radiation over Barents-Kara-Laptev Seas during 2002–2021. Our results set new insights into the Arctic sea ice variability and deepen our understanding of the climate change.

The linkage between autumn Barents-Kara sea ice and European cold winter extremes

While the Arctic's accelerated warming and sea ice decline have been associated with Eurasian cooling, debates persist between those attributing this to sea ice retreat and those to internal variability. Our study examines the association between autumn sea ice variability over the Barents-Kara Seas and extreme cold winters in Europe. Using the observational data and composite analysis, we explore the interannual variability and the potential linkage between sea ice and atmospheric circulation patterns. It reveals a correlation with shifts toward a negative phase of North Atlantic Oscillation and more frequent episodes of the atmospheric blocking over Greenland and the North Atlantic. Furthermore, the negative phase of the North Atlantic Oscillation and enhanced blocking are closely related and mutually reinforcing, shaping the spatial distribution of cold anomalies over much of the European continent. Our results suggest a link between the unusual decrease in Barents-Kara Sea ice during autumn and the occurrence of intense European weather extremes in subsequent winter months, emphasizing the need for delving deeper into this relationship on monthly time scales to enhance our predictive capabilities for midlatitude extreme events.

Regime shift of the leading mode of winter surface wind speed in northwest China in 2003/04 and its possible link with Barents–Kara sea ice

AbstractUsing the ERA‐5 reanalysis datasets, NCEP/NCAR sea ice concentration (SIC) and observed winter surface wind speed (WSWS) in northwest China during 1979–2020, this study examined the regime shift of the leading mode of observed WSWS in northwest China and investigated its possible link with the winter Barents–Kara Sea (BKS) SIC. The leading mode of observed WSWS in northwest China showed negative anomalies in southern and northeastern Xinjiang, Gansu, western and northern Shaanxi Provinces, and positive anomalies in northwestern and middle Xinjiang, Qinghai and Ningxia Provinces. The signs of WSWS in the leading mode is generally opposite to their trends during 1979–2020. Leading principal component (PC1) of observed WSWS in northwest China underwent an obvious decreasing regime shift in 2003/04, as well as the winter BKS SIC. There are significant correlations between PC1 and BKS SIC on both interdecadal and interannual timescales. Decadal decrease of BKS SIC is accompanied with a positive phase of Scandinavia pattern (SP) with positive anomalies of 500‐hPa geopotential height over subtropical North Atlantic, Arctic‐Ural region and southern Asia, and negative anomalies over northern North Atlantic‐West Europe and Siberia regions. BKS SIC and SP significantly influenced the Northern China Wind Index (NCWI) at 200 hPa on interdecadal timescale, which was related to the PC1 on both interdecadal and interannual timescales after removing the signal of Arctic Oscillation. Meridional configuration of Siberian cyclonic anomaly and southern Asian anticyclonic anomaly associated with the winter BKS SIC could enhance the intensity of NCWI, which favoured the increase of observed WSWS in northwest China and thereby may contribute to the regime shift in 2003/04 of the leading mode. However, there were still some stations showing decreasing regime shift, which mainly located at the region of steeping terrain. These decreasing changes of WSWS may be related to circumfluence effect of terrain, urbanization and local microclimate, and these reasons still need further detailed study.

Intensified gradient La Niña and extra-tropical thermal patterns drive the 2022 East and South Asian “Seesaw” extremes

In July and August 2022, a notable “seesaw” extreme pattern emerged, characterized by the “Yangtze River Valley (YRV) drought” juxtaposed with the “Indus Basin (IB) flood”, leading to enormous economic and human losses. We observed that the “seesaw” extreme pattern concurs with the second-strongest sea surface temperature (SST) gradient between the equatorial central and western Pacific caused by the triple-dip La Niña and western Pacific warming. The convergent statistical and numerical evidence suggested that the enhanced SST gradients tend to amplify the western Pacific convection and the descending Rossby responses to the La Niña cooling, promoting the “seesaw” extreme pattern through the westward expansion of the western Pacific subtropical high (WPSH). Further investigation demonstrated that the magnitude of the YRV surface temperature and IB rainfall exhibited a reversed change from July to August. The persistent cooling of the southern Indian Ocean induced by the triple-dip La Niña increases the cross-equatorial moisture transport, which played a significant role in the record-breaking IB rainfall during July. By contrast, the historic YRV surface temperature occurred in August with a decrease in IB rainfall. The Barents-Kara Sea warming extended the downstream impact of the North Atlantic Oscillation via local air-sea interaction that enhanced the WPSH and the YRV extreme surface temperature by emanating an equatorward teleconnection wave train. The overlay of the tropical thermal conditions and extra-tropical forcings largely aggravated the severity of the “YRV drought and IB flood”.