Abstract. Accurate quantification of surface mass balance (SMB) in the Antarctic interior underpins ice sheet mass budget assessments and ice core interpretation. Stake measurements, however, systematically underestimate SMB because firn densification causes surface lowering unrelated to mass change. Here, we simulate firn compaction with a firn densification model and correct stake records from 2008-2024 at Dome Argus (Dome A), East Antarctica, thereby refining SMB estimates and their spatial variability. The mean annual corrected SMB is 24.14 kg m-2 yr-1, 8.8 % higher than the uncorrected value (22.19 kg m-2 yr-1). Over the stake array, the RACMO2.4p1 regional model yields lower and more spatially uniform SMB (17.50 kg m-2 yr-1). Using automatic weather station observations, we estimate annual sublimation of 2.34 mm w.e yr-1. and hoar deposition of 0.87 mm w.e. yr-1, indicating that the net vapor flux is equivalent to 5.7 % of the total mass input. This framework reduces densification induced bias in stake-derived SMB, provides an observational benchmark for evaluating regional climate models, and supports accurate dating of ice core climate records from Dome A.

Antarctic inland regions, as critical hubs for global climate change monitoring, suffer from a lack of reliable long-term greenhouse gas (GHG) observation systems due to extremely low temperatures, strong winds, and limited logistical/energy support. To address this gap, the CRUX-1.0 automatic observation system was developed and deployed at Taishan Station (inland Antarctic Plateau) during the 39th and 40th CHINARE (Chinese National Antarctic Research Expedition), targeting simultaneous monitoring of CO2 and surface ozone (O3). Integrating four core subsystems – analysis, calibration, temperature control, and data communication – the system is specifically engineered for harsh polar environments with low power consumption (<350 W) and autonomous operation capability. The operational analysis based on a 1-month continuous field experiment showed its stable performance: CO2 measurements achieved a coefficient of variation (CV) <5.6 % (nearing 0 % post-calibration), while O3 measurements maintained a CV <5.6 %. The average mixing ratios (CO2: 420.7 ± 0.7 ppm; O3: 20.1 ± 0.8 ppb) closely aligned with regional background levels and South Pole Station data, confirming high reliability. As an unattended system with synchronous CO2/O3 measurement, low-power temperature control and automatic calibration, CRUX-1.0 shows good potential for long-term deployment in data-scarce polar inland regions.

River ice is a key variable within the global climate observing system and exerts a substantial influence on the navigability of river basins. Monitoring river ice phenology provides a scientific basis for assessing basin-scale navigation potential. The Irtysh-Ob River is the only international river in China that flows into the Arctic Ocean. It traverses China, Kazakhstan, and Russia, with Semey (Semipalatinsk), Omsk, and Beloyarsk marking the upper, middle, and lower reaches, respectively. This river system serves as a natural corridor facilitating Sino-Russian cooperation in the Arctic region. Based on MODIS MOD09GQ Band 2 surface reflectance data from 2000 to 2024, this study integrated a dynamic thresholding method with visual interpretation to extract river ice phenology information for the Irtysh-Ob River basin. Three key indicators-freeze-up start (FUS), break-up end (BUE), and navigation duration (ND) were derived and their spatial-temporal variations were systematically analyzed. Furthermore, a linear regression model combined with ERA5 reanalysis data was employed to quantify the relationship between river ice phenology and key climatic factors, particularly mean monthly temperature. Using temperature projections from the ISIMIP3b dataset, future trends in river ND were projected. The study shows that during 2000-2024, FUS was delayed by 1.32 d per decade, BUE advanced by 3.55 d per decade, and ND increased by 5.34 d per decade. Statistically, FUS shows a significant positive correlation with mean monthly temperature (R = 0.80, p < 0.05), whereas BUE exhibits a significant negative correlation (R = -0.86, p < 0.05). By the end of the 21st century, ND in certain sections of the Irtysh-Ob River is projected to exceed eight months under the SSP585 emission scenario, with some areas approaching year-round navigability. This study provides important insights for evaluating the navigational capacity and potential of the Irtysh-Ob River system.

The state of the Antarctic stratospheric polar vortex (ASPV) in austral spring is a key source of predictability for Southern Hemisphere surface climate on subseasonal-to-seasonal timescales. However, the relationship between Antarctic sea ice and the ASPV remains insufficiently understood. Here, using reanalysis data and CMIP6 models, we investigate the asymmetric impacts of May-June sea ice concentration (SIC) anomalies in the Amundsen-Ross Seas on the September-November (subsequent spring) ASPV. Results show that a reduction in Amundsen-Ross SIC significantly weakens the polar vortex, while the effect of an increase in SIC can be negligible. The loss of Amundsen-Ross SIC enhances surface turbulent heat fluxes, moistens and warms the troposphere, reduces static stability, and enhances convection. These changes promote enhanced upward propagation of planetary waves, particularly stationary waves, into the stratosphere. The resulting anomalies in wavenumber 1 and wavenumber 2 geopotential heights constructively interfere with the climatological stationary waves, amplifying the upward wave-activity flux and ultimately weakening the polar vortex during the austral spring. However, an increase in Amundsen-Ross SIC cools the surface and suppresses air-sea interactions, confining its influence to the lower troposphere without a significant stratospheric response. These results underscore the critical role of regional Antarctic sea ice loss in driving stratospheric circulation and provide essential constraints for improving the representation of stratosphere-troposphere coupling in climate models.

Extreme cyclones from the mid-latitudes can transport water vapor and heat to the Arctic,affect the Arctic sea ice extent and the thickness of ocean mixing layer,and bring strong winds,low temperatures,rain and snow.Using ERA-5 reanalysis data at 6 h intervals during 1980-2021,extreme cyclones originating from the mid-latitudes of the North Atlantic and entering the Arctic during winter are objectively identified and tracked.In total 130 extreme cyclones are identified and classified.The generation mechanisms behind extreme cyclones with three different tracks,i.e.,west,middle and east,and the reasons for the differences in these tracks after the formation of extreme cyclones are explored.Results show that positive potential vorticity appearing in the lower stratosphere 5-6 d prior to the formation of the extreme cyclones and the downward intrusion of stratospheric positive potential vorticity into the upper troposphere that accelerates the polar front jet provide dynamic conditions favorable for the formation of extreme cyclones.When an extreme cyclone is generated,the upper and lower positive potential vorticity regions are connected,leading to rapid development of the cyclone.Additionally,it is found that the cyclone track after cyclogenesis primarily depends on the transport of warm advection in the lower troposphere.

The Arctic is a critical region for global climate change, where temperature variations profoundly influence sea ice dynamics and atmospheric circulation. Harsh conditions limit in-situ observations in the Arctic, making reanalysis datasets indispensable, while the reliability of these reanalysis products requires systematic validation. This study evaluates the performance of the China Meteorological Administration Global Atmospheric Reanalysis (CMA-RA) and the ECMWF Reanalysis v5 (ERA5) in representing 2-m air temperature (Ta) and surface temperature (Ts) against in-situ observations from a total of 1658 buoys of the International Arctic Buoy Programme (IABP) and Cold Regions Research and Engineering Laboratory of the United States (CRREL) during 2001–2024. The results demonstrate strong consistency between the two reanalysis products and buoy observations, with correlation coefficients (R) of ⩾ 0.94 for Ta and ⩾ 0.88 for Ts in reproducing seasonal and interannual variations. For Ta, CMA-RA outperforms ERA5 under extreme cold conditions but exhibits a cold bias in long-term simulations (−0.30 ± 1.50°C), whereas ERA5 shows a warm bias (1.13 ± 2.28°C). Both CMA-RA and ERA5 yield high correlations with buoy observations across Arctic subregions. For Ts, both CMA-RA (−4.15 ± 3.55°C) and ERA5 (−2.52 ± 3.21°C) display cold biases, with the largest deviations occurring in winter (< −4°C) and the smallest in summer (> −1.6°C). The relatively higher Ts observed by buoys reveals consistent cold biases in CMA-RA and ERA5, suggesting that model physics, surface parameterizations, and data assimilation strategies jointly contribute to these systematic discrepancies. This study provides a comprehensive spatial evaluation and a relatively long continuous temporal assessment of the performance of CMA-RA and ERA5 over the Arctic to date.

Intense surface melt and subsequent meltwater ponding are the key triggers for the disintegration of ice shelves in the Antarctic Peninsula (AP). Although a long-term decline in AP surface melt has been evident since the early 1990s, episodes of intense surface melt events have frequently been reported in recent years. Here, using 1979-2023 daily surface melt rates from regional climate models, we show that this declining trend has reversed, with November-February surface melt increasing significantly by 3% year-1 (p < 0.05) between 2009 and 2022. Decomposition of trends based on circulation classification indicates that changes in the frequency of atmospheric circulation patterns cannot account for this enhancement. Instead, the thermodynamics-linked to variations in the surface energy budget independent of atmospheric circulation contribute 80% of the positive trend in AP surface melt. Analysis of extreme surface melt events further supports the dominant thermodynamic contribution.

Precipitation phases are crucial input parameter in hydrological research because they determine the initial and boundary conditions of hydrological models. The paper primarily reviews recent advances on the change patterns of precipitation phases and their multifaceted impacts in the Tibetan Plateau (TP). Furthermore, we identify key future challenges and provide an outlook for continued research. Precipitation phases are modulated by multiple factors including near-surface air temperature, water vapor content, topography, atmospheric pressure, and static stability. However, the accuracy of current methods for observing the amount and precipitation phases remains too coarse to meet the research requirements. Nevertheless, a robust finding is that global warming has driven widespread shifts from snow to rain (SSR) across the TP, resulting in multifaceted impacts. Widespread decreases in both heavy and light snowfall events across most of the TP have jointly driven a declining snowfall-to-rainfall ratio, with rainfall becoming the dominant precipitation type over the TP since the mid-1990s. SSR can lead to decreased snow cover or increased snow melting, which results in lower land surface albedo and more solar radiation absorption, and further cause strengthened elevation-dependent warming and accelerated glacier ablation. SSR also increases the frequency of rain-on-snow events and surface snowmelt, triggering more frequent wet avalanches and elevating flood risk. Additionally, SSR could strengthen the "Tibetan Plateau sensible heat pump" effect, and further influence the seasonal atmospheric circulation. While for permafrost degradation and phenology, SSR has both positive and negative effects according to the certain environment. Owing to cascading uncertainties associated with the accuracy of measurement datasets, acquiring precise measurement datasets is essential for future precipitation phase research. One key challenge in current precipitation phase research is a theoretical upper accuracy limit for precipitation phase discrimination based solely on near-surface meteorological datasets. We therefore propose that future research should concentrate on combined processes that form precipitation, the observation of meteorological parameters in the upper atmosphere, remote sensing technology and advanced algorithms. Despite considerable efforts in studying precipitation phases, we also advocate anticipation of unforeseen impacts that may result from global warming.

Recently, rapid warming scenarios along with intensified climate extremes were observed in the Antarctic Peninsula (AP). Acting as a key indicator of a changing climate, the snowline refers to the lower limit where snow remains on the glacier surface at the end of the melting season. The snowline altitude (SLA) also approximately represents the equilibrium line altitude (ELA), which reflects glacier surface mass balance (SMB) dynamics. Unfortunately, unlike continuous SLA monitoring in the High Mountain Asia and circum-Arctic regions, there is a lack of precise SLA information due to the unavailability of methods in the AP. In this study, a novel workflow, namely SLAMU, which mainly consists of a stacking machine learning (ML) model and a U-Net network enhanced by CBAM modules, was proposed. The SLAMU workflow, for the first time, utilized both optical and SAR satellite imagery to identify snowlines. The stacking ML model achieved higher classification accuracy and Kappa coefficients (0.936, 0.903) than the random forest (RF) model (0.884, 0.833), thereby generating a more representative training label dataset. Based on the visually interpreted snowline, SLAMU results exhibit more robust consistency than results either from ML models or published algorithms. The comparisons illustrated that SLAMU could nicely capture minor differences between snow and ice by fully grasping various glacier land-cover characteristics, therefore precisely estimating SLA. A long-time-series SLA dataset in the AP based on the SLAMU workflow can be expected, which further serves as a baseline for better quantitatively investigating glacier SMB under climate change.

Against the backdrop of successive global temperature records in past years, polar climate has exhibited high interannual variability. Consequently, maintaining a timely understanding of recent polar climatic state is particularly important. In this study, integrating multi-source observations, the China meteorological administration first-generation global atmospheric reanalysis (CMA-RA), and satellite data, we report the detailed 2025 polar climate changes and anomalies. While polar warming persisted, 2025 exhibited distinct spatio-temporal shifts compared to 2024. CMA-RA shows that the Antarctic surface air temperature rapidly shifts from a ‘warm winter and cool summer’ in 2024 to a ‘cold winter and warm spring’ in 2025 and the warming hotspot shifts from the Queen Maud Land to the West Antarctica and Antarctic Peninsula. In the Arctic, mean annual sea ice extent (SIE) set a new lowest record (10.13 × 106 km2) since 1979, attributed primarily to an unprecedentedly lowest winter maximum SIE. Furthermore, the average freezing onset in regions north of 70°N is delayed by 5.2 d relative to the 2011–2025 average. Regional warming peaks in the Barents-Kara Sea surface temperature in the Arctic with a new historical warming record in August (+5.0 °C, relative to 1991–2010 average). Atmospheric monitoring revealed rising greenhouse gases, with sulfur hexafluoride reaching its highest interannual increase on record. Arctic total O3 concentration shows a reversal between 2024 and 2025. The record-low levels observed in 2025 are related to the strong polar vortex and low stratospheric temperatures, conducive to enhanced ozone loss. Conversely, the Antarctic ozone hole closed three weeks earlier than the average time. This assessment of the 2025 polar climate status will advance our understanding of climate variability in polar regions and cryosphere stability.

Firn refreezing over the Greenland Ice Sheet (GrIS) buffers surface mass loss by retaining meltwater. However, the spatial heterogeneity of long-term firn refreezing variability and its relationship with extreme melt events remain largely unclear. In this study, the Community Firn Model (CFM) is used to investigate refreezing processes at 13 firn sites across the GrIS, forced by automatic weather station (AWS) observations (2009‒2024) and the regional climate model MAR (1940‒2024). Taking the southwestern percolation-zone site KAN_U as an example, multiple parameterizations are evaluated by comparing simulated firn density and temperature with in-situ observations, and the Brils2022 (BRI) scheme is selected for subsequent simulations. The results show that the mean annual refreezing at KAN_U during 2009‒2024 is 207 mm w.e. (45.3% refreezing ratio on average). The CFM-BRI simulations show 21%‒24% lower mean refreezing ratios relative to MAR. Long-term simulations for 1940‒2024 show relatively stable refreezing capacity at northern sites, but a 30% decline in refreezing ratio at the southwestern percolation zone (KAN_U) since the 1990s. Extreme melt events have become more frequent at KAN_U (five events during 2010‒2024), extending firn recovery from one cold season to 2‒5 years and increasing runoff, which peaked at 1160 mm w.e. in 2012. The frequency of extreme melt events is negatively correlated with the refreezing rates (r = −0.72, p < 0.001), indicating a delayed refreezing response to extreme melting. These findings improve our understanding of the long-term variability of refreezing processes in the GrIS firn zone and its response to increasing extreme melt events.

Daily minimum solar zenith angle(SZA)≥80° during or near the period of polar night(May—July)at Zhongshan station of China(69.37°S,76.38°E)in Antarctic restricts ground-based observations of Total Ozone Column(TOC)by using direct solar light(DS),which limits further accurate understanding of TOC seasonality.To address this issue,the following four types of TOC observations at SZA≥80°:(1)Brewer ozone spectrophotometer DS,TOCDS≥80°,(2)focused sun-disk(FS),TOCFS≥80°,(3)focused moon disk(FM),TOCFM and(4)SAOZ spectrometer zenith twilight observations,TOCSAOZ,made from 2009 to 2023 are analyzed with reference to the Brewer DS observations within SZA of[72°,80°),i.e.,TOCDS[72,80°).The results show that,on average,TOCDS≥80° are lower by(5.5±9.5(1σ))DU or(2.1±4.1(1σ))%when SZA is[81°,81.5°)while TOCFS≥80° are higher by(2.8±4.3(1σ))DU or(1.75±4.3(1σ))%when SZA is[80°,84.5°).The fixed stratospheric ozone layer height(～22 km)in the air mass factor(μ)calculation causes a decreased μ with increasing SZA,which is the main reason for the higher TOCFS≥80°.On average,TOCFM is lower by(6.8±16.7(1σ))DU or(2.2±6.8(1σ))%while TOCSAOZ is lower by(12.1±12.9(1σ))DU or(4.4%±5.0(1σ))%on average.The longer optical path of twilight in the atmosphere together with the nature latitudinal distribution of TOC are the reasons for lower TOCSAOZ values.The significant diurnal variation of TOC during the"ozone hole"(TOC≤220 DU)period increases the differences between those observed TOC at SZA≥80° and the reference.It is confirmed that the annual"ozone hole"at Zhongshan station starts in August.The average TOC is within 270-290 DU while the minimum value can be～230 DU,indicating that ozone depletion has already occurred during the polar night when the polar vortex has been well developed.The secondary seasonal lower TOC in autumn(March),which are due to the influence of the nature stratospheric Brewer-Dobson circulation,is similar to the lowest TOC in autumn in the middle and high latitudes of the northern Hemisphere.FS observations should be preferentially applied when the SZA≥80°,and FM should be implemented because it is the only effective way during the polar night for routine TOC observations.

Complex interactions among the ocean, sea ice, and ice shelves in the Southern Ocean are critical for global climate, yet accurately simulating these processes remains challenging in climate models, such as those participating in the Coupled Model Intercomparison Project Phase 6, due to their coarse resolution and incomplete physical components. Therefore, the development of high-resolution circumpolar coupled ocean-sea ice-ice shelf models could improve our understanding of the evolution of the Southern Ocean. In this study, we use the c66m version of the Massachusetts Institute of Technology General Circulation Model, including a sea ice component and an ice shelf component, to configure the coupled Southern Ocean-Sea ice-Ice shelf Model (SOSIM v1.0). Adopting the Refined Topography dataset version 2 for the geometry of seafloor and ice draft, SOSIM features a horizontal resolution of similar to 5 km and 70 vertical layers. Forced by the European Centre for Medium-Range Weather Forecasts Reanalysis v5, a long-term integration of SOSIM is run forward from 1979 to 2022, with daily outputs for estimating the oceanic state, sea ice evolution, and basal mass balance of ice shelves. A comprehensive evaluation of the performance of SOSIM has been conducted against multiple observational and reanalysis datasets. Identified biases include an underestimated Antarctic Circumpolar Current transport, an overestimated Antarctic Slope Current, a warm drift in abyssal waters, an exaggerated seasonality of sea ice extent, and an underestimated total ice shelf mass loss. Despite these limitations, SOSIM still captures large-scale hydrographic structures, the annual variability of sea ice, and cross-slope exchanges over shelf seas. Furthermore, SOSIM is set to serve as the dynamical core for the next-generation Southern Ocean Ice Prediction System being developed in China.

The effects of initial soil temperature and moisture were explored by performing a series of 84-hour numerical simulations form 10 to 25 December 2023,using the WRF model with soil temperature and moisture initialized with CMA-GFS forecasts and the China Meteorological Administration Land Data Assimilation Sys-tem(CLDAS)analysis respectively.It showed that the relative humidity(RH2m)and the temperature(T2m)at 2 m were poorly during the first 21-hour integration and getting better during the following time integration ini-tialized with CLDAS than that with CMA-GFS,with a maximum root mean square error(RMSE)decrease of 8.3％and 10％respectively.Further diagonosis indicated that the first 21-hour integration usually a accompanied with more sensible and latent heat fluxes in case of the soil temperature and moisture initialized with CLDAS.It means that the model would take a longer spin-up time during which any satisfiable forecasted T2m and RH2m might not be gotten,due to the in consistanece in initial conditions which came from the different source datasets containing some more reliable variables although.Spatially,when the model was initialized with CLDAS,it rep-resented much more favourable with smaller negative deviation of RH2m and positive deviation of the daily max-imum T2m,which maximally decreased by 8％and 1.5 ℃ in Henan respectively,and unfavourable with larger positive deviation of the daily minimum T2m in the southern region of Shanxi and central Hebei.Whereas,it rep-resented pretty well performance of daily maximum and minimum T2m and bad performance of RH2m with larg-er negative deviation in the northern region of northern Shanxi and northern Hebei.Among groups of initial soil conditions,the moister and colder initial soil group had the best forecasting performance of T2m which is tightly closed to the observation,and the moister and warmer initial soil group has the worst although the T2m differ-ence between the simulations initialized with CLDAS and CMA-GFS is small.Compared with the initial soil tem-perature,the initial soil moisture has a greater impact on T2m.The drier initial soil would lead to a better fore-casting performance of daily minimum T2m,accompanied with larger sensible heat flux and smaller latent heat flux in the integration.

The Greenland Ice Sheet is losing mass at an accelerating rate. In situ observations are sparse due to its harsh environment, making reanalysis datasets an essential alternative. However, their accuracy over Greenland—particularly in high-altitude and inland regions—remains uncertain, necessitating a systematic evaluation. In this study, we comprehensively evaluate four major reanalysis products—ERA5, ERA5-Land, MERRA-2 and NCEP/DOE R2—using observational data from 51 automatic weather stations across the Greenland Ice Sheet. We analyse accuracy in five key atmospheric variables (2 m air temperature, surface pressure, 10 m wind speed, downwelling shortwave and longwave radiation) across three temporal resolutions: monthly, daily and hourly. The results show that over the evaluation period (2018–2022), ERA5 and MERRA-2 consistently outperform the other considered products. ERA5 performs the best in temperature and pressure, with monthly temperature and pressure biases below 2.5 °C and 6 hPa, respectively, and strong consistency across time scales; at the same time, MERRA-2 exhibits the best accuracy in shortwave radiation in certain seasons, with hourly downwelling shortwave radiation correlation coefficients exceeding 0.92 in all four seasons, mainly because its aerosol and radiation processes better capture seasonal variability in atmospheric clarity and solar energy reaching the surface. ERA5-Land, despite its finer resolution, systematically underestimates summer shortwave radiation levels and features inconsistent wind speed accuracy. NCEP/DOE R2 shows pronounced errors across all variables and is not recommended for use in modern climate studies. Spatial analyses further reveal that the considered reanalysis products show the best accuracy along the coast and lower accuracy in the high-elevation interior. These findings offer essential guidance for the selection of suitable reanalysis products in climate and surface mass balance studies on Greenland.

Total column water vapor (TCWV) is a crucial indicator of atmospheric processes in the troposphere and a key driver of climate change. However, the severe environmental conditions in Antarctica constrain research on spatiotemporal variability and its underlying driving mechanisms. Based on multi-source datasets including radiosonde, global navigation satellite system (GNSS), and reanalysis data, this study calculates and analyzes the spatiotemporal variations of water vapor over Antarctica and investigates the mechanisms behind these changes. Key findings indicate that Antarctic TCWV exhibits significant spatial heterogeneity, ranging from 0 to 6 mm annually, with the highest values occurring over the Antarctic Peninsula and coastal West Antarctica, decreasing sharply inland. Temporally, a weak overall drying trend (-9.91 x 10(-4) mm/decade) was observed, with a notable shift around 2015. Analysis further reveals that atmospheric circulation anomalies during 2009-2016 drove corresponding TCWV and precipitation anomalies in West Antarctica and the Antarctic Peninsula. Importantly, positive TCWV anomalies enhanced the surface energy budget, leading to elevated surface temperatures - most markedly over the Antarctic Peninsula, where increases reached similar to 1.8 K, and contributed to intensified surface melt. These results advance our understanding of TCWV dynamics in Antarctic climate and highlight its critical role in surface warming and ice-sheet melting, providing a valuable basis for improved climate and ice-sheet modeling in polar regions.

Abstract Antarctic springtime ozone reduction is spatially heterogeneous, making it essential to examine local and vertical ozone changes. However, the long‐term total column ozone (TCO) and vertical ozone structure changes in the coastal region of East Antarctica remain uncertain. This study investigates the TCO variability and vertical distribution of ozone, based on Zhongshan TCO observations (1993–2024), Davis ozonesondes (2003–2024), complemented by satellite and reanalysis data sets (SBUV, ERA5, MERRA2, and MSR2) from 1980 to 2024. TCO at stations is significantly correlated with the Antarctic regional (60°–90°S) mean ( R > 0.8) and most effectively reflects the TCO variations over the coastal sector of East Antarctica (about 61°–79°S, 34°–120°E; R > 0.9) from August to December. A positive TCO trend from September to December has emerged since 2003 at Zhongshan, although persistent ozone deficits since 2020 have partially offset this upward tendency. At Davis, springtime ozone deficit occurs mainly within 165–30 hPa. In 2019, unusually high column ozone (187.81 Dobson units (DU)) in this layer coincided with sudden stratospheric warming. Since 2003, September column ozone (165–30 hPa) has exhibited an upward inclination of 0.80 ± 0.75 DU/yr, and September ozone mixing ratio deficit rates from 2018 to 2022 were lower than in 2013–2017. However, ozone deficit after mid‐September state has intensified (0.86 ± 0.62 DU/yr), highlighting the role of late‐spring reduction. This study offers a complete view of the long‐term temporal and vertical variations in ozone over the coastal region of East Antarctica and provides additional insights and evidence for springtime Antarctic ozone layer recovery.

The Arctic has experienced rapid and profound changes due to its heightened sensitivity to global warming and growing regional human pressures. While past research has advanced our understanding of these transformations, a comprehensive assessment within a unified analytical framework is still needed to quantify the ecological impacts of human activity across this fragile region. In this study, we systematically assessed the expansion of human activity and its ecological effects across Arctic and sub-Arctic regions from 2000 to 2020. We combined satellite-based land-cover datasets, vegetation resilience indicator (i.e., lag-1 month temporal autocorrelation of remotely sensed greenness), and species distribution data to track and analyze these changes and impacts. Our findings show that areas affected by human activity-mainly cultivated lands and artificial surfaces-expanded by nearly 13,000 km2, equivalent to a rate of 1.8 % per decade. This growth was largely driven by the increase in artificial surfaces (similar to 77.2 %) and extended to higher latitude. As a result, natural habitats became increasingly fragmented, vegetation resilience declined, and risks of ecological tipping points rose. These impacts threatened the habitats of approximately 97.5 % of Arctic species, including 111 species listed as vulnerable or endangered. Our results highlight that, beyond the effects of climate change, the continued expansion of human activity is intensifying ecological risks in the Arctic. This underscores an urgent need for enhanced ecological protection and transformative social strategies to safeguard the region's future.