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Changes in the volume transport of Atlantic water into the Arctic Ocean can affect the heat and mass balance in the central Arctic Ocean. To understand the impacts of Arctic storms on the inflow through Fram Strait, we implemented the NEMO ocean model for the Arctic Ocean, to simulate the decadal variations of the water volume transport through Fram Strait. The simulations suggest that the water inflow tends to be weaker in the decades of the 1960 and 2010s but stronger in the 1980s. The decadal variation is associated with decadal variability of the storm density in the Greenland Sea. When there is an increased storm density near Fram Strait, the southerly wind anomalies dominate the Atlantic water pathway. As a response, there is an increased Atlantic inflow through Fram Strait. Plain Language Summary On decadal scales, Arctic storms near Fram Strait are highly correlated with the water volume transport into the Arctic Ocean through Fram Strait. When there are more storms near Fram Strait, the transport tends to increase. In addition, the heat flux associated with the water volume transport reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport. Key Points On a decadal scale, the storms in the Greenland Sea can affect the volume transport of Atlantic water inflow through Fram Strait Associated heat flux reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport

In July and August 2024, two consecutive stratospheric sudden warming (SSW) events (termed SW07 and SW08) occurred over Antarctic, both featuring a rapid 17°C temperature rise at 10 hPa and significant stratospheric polar vortex (SPV) deceleration. SW07 occurred at the earliest winter time of the year recorded in the satellite era (1979 to present). The study found that, strong blocking highs affected stratospheric warming via nonlinear planetary wave prior to SW07, and the substantial sea ice loss over Antarctic Ross Sea and Amundsen Sea likely created favorable conditions for the formation of these blocking highs. Furthermore, the stratospheric preconditioning significantly amplified the intensity of the planetary waves. A downward‐propagating negative Southern Annular Mode (SAM) signal after SW07 supported blocking highs, creating a favorable circulation for planetary wave perturbations prior to SW08. In addition, enhanced ozone transport from low latitudes to the pole during SW07 and SW08 contributed to ozone recovery. Plain Language Summary Sudden stratospheric warming (SSW) events are frequently observed over the Arctic but are exceptionally rare in the Southern Hemisphere. Two consecutive SSW events occurred over the Antarctic in July and August 2024, which is a highly unusual phenomenon. These two SSW events caused stratospheric temperatures to rise rapidly by 17°C within a short period and led to a significant weakening of the stratospheric polar vortex (SPV), breaking the historical record from 1979. The first event (SW07) occurred at the earliest winter time of the year observed in the satellite era (1979–present). We found that strong planetary waves originating in the troposphere, driven by blocking highs likely associated with sea ice loss in the Antarctic, were amplified in the stratosphere due to preconditioning of the stratosphere, thereby playing a major role in the early development of SW07. In addition, enhanced tropospheric planetary wave activity and increased ozone transport from low latitudes, triggered by SW07, contributed to the development of SW08. This study underscores the critical role of tropospheric strong blocking highs and stratospheric preconditioning in the onset of SW07, as well as emphasizes the subsequent impact of SW07 on the development of SW08. Key Points The Antarctic experienced its earliest and consecutive sudden stratospheric warming events on record during July and August 2024 since 1979 Significant loss of sea ice in the Ross and Amundsen Seas of Antarctica created favorable conditions for the formation of blocking highs Stratospheric preconditioning provided favorable conditions for planetary wave resonance preceding SW07

This paper focuses on the proof and application of discriminating between oil spills and seawater (including the “look-alikes”, named low wind areas) based on the polarization ratio. A new relative polarization ratio (PRr) method is proposed, which is based on the difference between the scattering mechanism and the dielectric constant for oil spills compared to that of seawater. The case study found that (1) PRr numerically amplifies the contrast between oil spills and seawater, reduces the difference between low wind areas and ordinary seawater, and exhibits better details of the image; (2) the threshold method based on Euclidean distance can obtain the highest classification overall accuracy within the allowable error range, and can be widely used in the study of different incidence angles and environmental conditions; and (3) the identification of oil spills and seawater by the proposed methods can largely avoid the misjudgment of low wind areas as oil spills. Considering visual interpretation as the reference ‘ground truth’, the overall classification accuracy of all cases is more than 95%; only the edge of the diffuse thin oil slick and oil–water mixture is difficult to identify. This method can serve as an effective supplement to existing oil spill detection methods.

The provision of reliable results from numerical wave models implemented over vast ocean areas can be considered as a time-consuming process. In this regard, the estimation of areas with maximum similarity in wave climate spatial areas and the determination of associated representative point locations for these areas can play an important role in climate research and in engineering applications. To deal with this issue, we apply a state-of-the-art clustering method, Geo-SOM, to determine geographical areas with similar wave regimes, in terms of mean wave direction (MWD), mean wave period (T0), and significant wave height (Hs). Although this method has many strengths, a weakness is related to detection and accounting of the most extreme and rare events. To resolve this deficiency, an initial preprocessing method (called PG-Geo-SOM) is applied. To evaluate the performance of this method, extreme wave parameters, including Hs and T0, are calculated. We simulate the present climate, represented as 1979 to 2017, compared to the future climate, 2060–98, following the Intergovernmental Panel on Climate Change (IPCC) future scenario RCP8.5 in the northwestern Atlantic Ocean. In this approach, the wave parameter data are divided into distinct groups, or clusters, motivated by their geographical positions. For each cluster, the centroid spatial point and the time series of data are extracted, for Hs, MWD, and T0. Extreme values are estimated for 5-, 10-, 25-, 50-, and 100-yr return periods, using Gumbel, exponential, and Weibull stochastic models, for both present and future climates. Results show that for parameter T0, the impact of climate change for the study area is a decreasing trend, while for Hs, in coastal and shelf areas up to about 1000 km from the coastline, increasing trends are estimated, and in open-ocean areas, far from the coast, decreasing trends are obtained.

The impacts of increased open water in the Beaufort Sea were investigated for a summer Arctic storm in 2008 using a coupled atmosphere‐ice‐ocean model. The storm originated in northern Siberia and slowly moved into the Beaufort Sea along the ice edge in late July. The maximum wind associated with the storm occurred when it was located over the open water near the Beaufort Sea coast, after it had moved over the Chukchi and Beaufort Seas. The coupled model system is shown to simulate the storm track, intensity, maximum wind speed and the ice cover well. The model simulations suggest that the lack of ice cover in the Beaufort Sea during the 2008 storm results in increased local surface wind and surface air temperature, compared to enhanced ice cover extents such as occurred in past decades. In addition, due to this increase of open water, the surface latent and sensible heat fluxes into the atmosphere are significantly increased. However, there were no significant impacts on the storm track. The expanded open water and the loss of the sea ice results in increases in the surface air temperature by as much as 8°C. Although the atmospheric warming mostly occurs in the boundary layer, there is increased atmospheric boundary turbulence and downward kinetic energy transport that reach to mid‐levels of the troposphere and beyond. These changes result in enhanced surface winds, by as much as ∼4 m/s during the 2008 storm, compared to higher ice concentration conditions (typical of past decades). The dominant sea surface temperature response to the storm occurs over open water; storm‐generated mixing in the upper ocean results in sea surface cooling of up to 2°C along the southern Beaufort Sea coastal waters. The Ekman divergence associated with the storm caused a decrease in the fresh water content in the central Beaufort Sea by about 11 cm. Key Points Decrease of Beaufort ice cover increases the sea surface temperature by ~6C Atmospheric responses to warmer SSTs are mainly limited to boundary layer Enhanced storm‐generated surface winds, by as much as ~4 m/s

Possible modifications to ocean temperature in the Barents Sea induced by climate change are explored. The simulations were performed with a coupled ice–ocean model (CIOM) driven by the surface fields from the Canadian Regional Climate Model (CRCM) simulations. CIOM can capture the observed water volume inflow through the Barents Sea Opening. The CIOM simulation and observations suggest an increase in the Atlantic water volume inflow and heat transport into the Barents Sea in recent decades resulting from enhanced storm activity. While seasonal variations of sea ice and sea surface temperature in CIOM simulations are comparable with observations, CIOM results underestimate the sea surface temperature but overestimate ice cover in the Barents Sea, consistent with an underestimated heat transport through the Barents Sea Opening. Under the SRES A1B scenario, the loss of sea ice significantly increases the surface solar radiation and the ocean surface heat loss through turbulent heat fluxes and longwave radiation. Meanwhile, the lateral heat transport into the Barents Sea tends to increase. Thus, changes in ocean temperature depend on the heat balance of solar radiation, surface turbulent heat flux, and lateral heat transport. During the 130-yr simulation period (1970–2099), the average ocean temperature increases from 0° to 1°C in the southern Barents Sea, mostly due to increased lateral heat transport and solar radiation. In the northern Barents Sea, ocean temperature decreases by 0.4°C from the 2010s to the 2040s and no significant trend can be seen thereafter, when the surface heat flux is balanced by solar radiation and lateral heat transport and there is no notable net heat flux change.

The Surface Water Ocean Topography (SWOT) mission significantly improves on the capabilities of current nadir altimeters by enabling two-dimensional mapping. Assimilating this advanced data into high-resolution models poses challenges. To address this, Observing System Simulation Experiments (OSSEs) were conducted to evaluate the effects of both simulated and actual SWOT data on the Regional Ice Ocean Prediction System (RIOPS). This study examines the OSSEs’ design, focusing on the simulated observations and assimilation systems used. The validity of the OSSE designs is confirmed by ensuring the deviations between the assimilation system and the Nature Run (NR) align with discrepancies observed between actual oceanic data and OSSE simulations. The study measures the impact of assimilating SWOT and two nadir altimeters by calculating root mean square forecast error for sea surface height (SSH), temperature, and velocities, along with performing wave-number spectra and coherence analyses of SSH errors. The inclusion of SWOT data is found to reduce RMS SSH errors by 16% and RMS velocity errors by 6% in OSSEs. The SSH error spectrum shows that the most notable improvements are for scales associated with the largest errors in the range of 200-400 km, with a 33% reduction compared to traditional data assimilation. Additionally, spectral coherence analysis shows that the limit of constrained scales is reduced from 280 km for conventional observations to 195 km when SWOT is assimilated as well. This study also represents our first attempt at assimilating early-release SWOT data. A set of Observing System (data denial) experiments using early-release SWOT measurements shows similar (but smaller) responses to OSSE experiments in a two nadir-altimeter context. In a six-altimeter constellation setup, a positive impact of SWOT is also noted, but of significantly diminished amplitude. These findings robustly advocate for the integration of SWOT observations into RIOPS and similar ocean analysis and forecasting frameworks.

This paper presents a first attempt to analyze C‐band RADARSAT‐2 measurements of the normalized radar cross sections (NRCS) in quad‐polarization acquisition mode (HH, VV, HV, and VH) over the ocean. NRCS in copolarizations and cross‐polarizations are found to be different; the latter is independent of radar incidence angles and wind directions, but is quite linear with respect to wind speeds. We also investigate the properties of the polarization ratio, denoted PR, and show that it is dependent on incidence angle and azimuth angle as well as wind speed. It also correlates well with wave steepness and significant wave height. Moreover, the polarization difference shows a linear relationship with wind speed. Two new analytical models are proposed to estimate PR; one is a function of incidence angle only, while the other has additional dependence on wind speed. Comparisons are presented with theoretical and empirical PR models from the literature; the new PR model which includes wind speed dependence is shown to best compare with observed RADARSAT‐2 data. An assessment of this PR model is given using different CMOD algorithms and RADARSAT‐2 images. Results show that the wind speeds retrieved from this PR model and CMOD5.N are in good agreement with buoy measurements (standard deviation, 1.37 m/s). This joint GMF‐PR approach constitutes a promising hybrid model for wind speed retrievals from HH‐polarized RADARSAT‐2 images. Key Points Quad‐polarization RADARSAT‐2 data New models proposed for the polarization ratio (PR) PR model with only incidence angle dependence

The authors explore possible temperature modifications of the Atlantic Water Layer (AWL) induced by climate change, performing simulations for 1970 to 2099 with a coupled ice–ocean Arctic model (CIOM). Surface fields to drive the CIOM were provided by the Canadian Regional Climate Model (CRCM), driven by outputs from the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) following the A1B climate change scenario. In the present climate, represented as 1990–2009, the CIOM can reliably reproduce the AWL compared to Polar Science Center Hydrographic Climatology (PHC) data. For the future climate, assuming the A1B climate change scenario, there is a significant increase in water volume transport into the central Arctic Ocean through Fram Strait due to the weakened atmospheric high pressure system over the western Arctic and an intensified atmospheric low pressure system over the Nordic seas. The AWL temperature tends to decrease from 0.36°C in the 2010s to 0.26°C in the 2060s. In the vertical, the warm Atlantic water core slightly expands before the 2030s, significantly shrinks after the 2050s, and essentially disappears by 2070–99, in the southern Beaufort Sea. The temperature decrease after 2030 is mainly due to the reduced heat fluxes in the Kara and Barents Seas. In the northeastern Barents and Kara Seas, the loss of sea ice increases the heat loss from the Atlantic water and reduces the water temperature near the bottom, contributing to decreased heat fluxes into the central Arctic Ocean, as well as decreased AWL temperature at central Arctic Ocean intermediate layers. In addition, the vertically integrated heat loss also plays an important role in the AWL cooling process.

In this study we examine the cross–seasonal effects of boreal winter sea surface temperature (SST) anomalies over the tropical central Pacific (Niño 4 region) on Antarctic stratospheric circulation and ozone transport during the subsequent austral winter using ERA5 reanalysis of 45 years (1980–2024). Our analyses show that warm (cold) SST anomalies in the Niño 4 region during December–February are associated with mid- and high-latitude stratospheric warming (cooling), a contracted (expanded) stratospheric polar vortex (SPV), and enhanced (suppressed) polar ozone concentrations in the subsequent July–September period. This delayed response is mediated by the Pacific–South America (PSA) teleconnection pattern, which excites planetary waves that propagate upward into the stratosphere, thereby modifying the Brewer–Dobson circulation and enhancing ozone poleward transport, ultimately warming polar stratosphere. In addition, as the influence of the Niño 4 SST anomalies on the PSA teleconnection pattern diminishes during July–September, surface heat feedback at mid- and high-latitude becomes critically important for planetary waves. For example, persistent southeastern Pacific SST warming and sea–ice loss over the Amundsen and Ross Seas reinforce planetary waves by releasing heat from ocean into atmosphere. A multivariate regression statistical model using factors of boreal winter Niño 4 SST and June PSA indices explains approximately 32 % of the variance in austral winter stratospheric temperatures. These findings highlight a previously underexplored pathway through which tropical Pacific SST anomalies modulate Antarctic stratospheric dynamics on cross-seasonal timescales.