Sea Ice Extent Research Articles

The Arctic: A New Theater of Great Power Competition

The Arctic warms at four times the global average, reducing summer sea ice extent by 40% since 1979, unlocking previously inaccessible resources, and shipping corridors. By 2025, the Northern Sea Route (NSR) offers seasonal commercial viability, cutting Asia-Europe transit times by 40% compared to Suez routes. This shift has sparked intense competition among great powers, including Russia, China, America and NATO member states, as they seek to assert their influence, secure resources, and gain strategic advantages in the region. This study provides an in-depth examination of the strategies employed by these nations in the Arctic, with a particular focus on the militarization of Arctic trade routes and the role of indigenous communities in shaping regional security policies. By analyzing the actions and motivations of these key players, this research aims to shed light on the complex dynamics at play in the Arctic and the implications for regional stability and global security. Our findings indicate that the Arctic is rapidly becoming a contested region, with nations striving for control over resources, trade routes, and strategic territories. The militarization of Arctic trade routes, such as the Northern Sea Route, has become a critical aspect of this competition, with nations seeking to assert their dominance and protect their interests. The study also highlights the importance of indigenous communities in the Arctic, who have traditionally inhabited the region and possess valuable knowledge and perspectives. However, their role in regional security policies remains limited, and their interests are often overlooked in the face of great power competition. This paper aims to analyze the emerging competition in the Arctic through the lens of these actors, discussing their strategic objectives, capabilities, and challenges. Given the region’s dynamic nature and its implications for international stability, understanding these competing interests is vital for policymakers, security analysts, and environmental stakeholders.

Improving short-term forecasts of sea ice edge and marginal ice zone around Svalbard

Sea ice is a major threat to marine operations around Svalbard, and accurate short-term (1–5 days) forecasts of sea ice edge (SIE) and marginal ice zone (MIZ) are crucial for safe marine operations. In this paper, we investigate the effects of assimilating the AMSR2 sea ice concentration (SIC), the Norwegian sea ice chart, and the OSTIA sea surface temperature (SST) on the short-term forecasts of SIE and MIZ around Svalbard. The used model, Barents-LAON, is based on the coupled ROMS-CICE model with the Local Analytical Optimal Nudging (LAON) for data assimilation. The assimilation effects are evaluated through seven model experiments, from Free run to the full assimilation of OSTIA SST, AMSR2 SIC, and ice chart. The results show that the Free run of Barents-LAON contains a large cold bias, which significantly overestimates the sea ice extent and underestimates the SST. Assimilation of SST mildly improves the analyses of SIE and MIZ, and additional assimilations of AMSR2 SIC and ice chart considerably improve the analyses and forecasts. We show that 1–3 days of forecasts of SIE and MIZ with assimilations of both SIC and SST outperform the CMEMS operational forecasts TOPAZ5 and neXtSIM, the US Navy GOFS3.1 system, and the Norwegian Meteorological Institute’s Barents-EPS. The assimilation of both ice chart and OSTIA SST is shown to have the largest improvement for MIZ analysis and forecasts. All the Barents-LAON short-term SIE forecasts with assimilations of SIC and SST outperform the sea ice chart persistence forecasts after the first day. However, all the MIZ forecasts, regardless of using the operational models or the current model experiments, are shown to have lower skills than the sea ice chart persistence. This suggests two possible defects: 1) the present AMSR2 SIC is not sufficiently accurate for separating MIZ from dense pack ice, and 2) some important physical processes may be lacking for the transformation between dense pack ice and MIZ in the present coupled ocean and sea ice models.

Modelling the influence of environmental factors on the acoustic presence of blue whale populations in the southern Indian Ocean

Blue whales in the Indian Ocean have been severely depleted by previous extensive commercial whaling. A good understanding of their spatio-temporal distribution is crucial for conservation. The songs of three blue whale acoustic populations - Antarctic blue whales (Balaenoptera musculus intermedia, ANT BW) and pygmy blue whales (B. musculus brevicauda) from the Southeast (SEIO PBW) and Southwest Indian Ocean (SWIO PBW) - were analyzed using 13 years of passive acoustic recordings from 10 sites in the southwest Indian Ocean. Although blue whale vocalizations comprise both songs and non-song calls (e.g., D-calls), the present study concentrates on the examination of songs. Generalized additive models (GAMs) were used to relate acoustic presence, measured by the number of positive minutes per day (averaged weekly), to environmental drivers such as sea surface temperature (SST), chlorophyll-a concentrations, and sea ice extent. These models allowed predictions of blue whale acoustic presence across the region. Empirical orthogonal functions (EOFs) were applied for dimensionality reduction to identify key habitats, including the Kerguelen Plateau and Madagascar Basin, which may serve as important feeding and resting zones based on acoustic presence and environmental data. Antarctic blue whales were predominantly detected in austral winter and spring, associated with lower SST and higher chlorophyll-a. In contrast, SEIO and SWIO pygmy blue whales were more frequent in summer and autumn, with some overlap suggesting ecological interactions. These findings lay the groundwork for targeted conservation efforts to protect critical blue whale habitats in a rapidly changing ocean.

Northern Hemisphere ice sheet and ocean interactions during the last glacial period in a coupled ice sheet–climate model

Abstract. This study examines the interactions between the Northern Hemisphere ice sheets and the ocean during the last glacial period. Using the iLOVECLIM climate model of intermediate complexity and the GRISLI ice sheet model, we explore the consequences of an amplification of the melt rates beneath ice shelves on ice sheet dynamics and the associated feedbacks. First, the amplification of oceanic basal melt rates leads to significant freshwater release from both increased calving and basal melt fluxes. Grounding line retreat and dynamic thinning occur over the Eurasian and Iceland ice sheets, while the oceanic perturbation fails to trigger a grounding line migration over the coasts of Greenland and the eastern part of the Laurentide ice sheet. Second, similar to hosing experiments with no coupling between the climate and the ice sheets, the influx of fresh water temporarily increases sea-ice extent; reduces convection in the Labrador Sea; weakens the Atlantic meridional overturning circulation; lowers surface temperatures in the Northern Hemisphere, especially over the North Atlantic Ocean; and increases the subsurface temperatures in the Nordic Seas. Third, the freshwater release and latent heat effect on ocean temperatures lead to a decrease in ice sheet discharge (negative feedback) for the Greenland and Eurasian ice sheets. The Laurentide ice sheet does not feature significant volume variations in the experiments. On the one hand, the amplification of the shelf melt rates produces a weak perturbation due to low background temperatures and salinity at shelf drafts in Baffin Bay and the Labrador Sea according to the model. On the other hand, the Laurentide ice sheet in the fully coupled model may be overly stable. We show that we are able to force a grounding line retreat and a North American ice sheet volume decrease by imposing ad hoc constant oceanic melt rates. However, in both sets of perturbation experiments, the Hudson Strait ice stream does not exhibit the past dynamic instability indicated by the presence of Laurentide-origin ice-rafted debris in the North Atlantic sediment records. This suggests the possibility that the model is too stable, specifically in the Hudson Bay region. Different ice sheet geometries or modeling choices regarding the basal dynamics beneath the ice sheet could help address this issue. In summary, this study found that an episode of subsurface warming may trigger dynamical instabilities and ice discharges along the coasts of the Nordic Seas but subsequent ocean–ice sheet interactions may be characterized by negative feedback thus dampening ice discharges. This study also emphasizes the need for further research using fully coupled models to explore the triggering mechanisms of massive iceberg discharges and to clarify the role of the ocean in these events.

Unveiling the Hidden Eddy Field of the Southern Ocean

Abstract Observational and modeling studies indicate that mesoscale and submesoscale eddies are important circulation features within ice shelf cavities on the Antarctic continental slope and in the open ocean. Not only are eddies a pathway for warm water to impinge on ice shelves but their dynamic interaction at the ice‐ocean boundary also increases basal melting. By combining observational data and model output, Kosty et al. (2025), https://doi.org/10.1029/2024JC021781 provides an important first characterization of the subsurface eddy field in the seasonally ice‐covered Southern Ocean. Their analysis reveals distinct spatial variability between cyclones and anticyclones, which could affect heat and salt fluxes, water column stability, and the seasonal extent of sea ice. With recent Southern Ocean studies indicating warming subsurface waters, eddy‐ice interactions are potentially poised to exert a substantial influence on the Southern Ocean cryosphere.

Toward a marginal Arctic sea ice cover: changes to freezing, melting and dynamics

Abstract. As the summer Arctic sea ice extent has retreated, the marginal ice zone (MIZ) has been widening. The MIZ is defined as the region of the ice cover that is influenced by waves and for convenience here is defined as the region of the ice cover between sea ice concentrations (SIC) of 15 % to 80 %. The MIZ is projected to become a larger percentage of the summer ice cover, as the Arctic transitions to ice-free summers. Using numerical simulations, we explicitly compare, for the first time, individual processes of ice volume gain and loss in the ice pack (SIC > 80 %) to those in the MIZ to establish and contrast their relative importance and examine how these processes change as the summer MIZ fraction increases over time. We use an atmosphere-forced, physics-rich, sea-ice-mixed layer model based on CICE, that includes a joint prognostic floe size and ice thickness distribution (FSTD) model including brittle fracture and form drag. We demonstrate that this model is realistic using satellite observations of sea ice extent and PIOMAS (the Pan-Arctic Ice Ocean Modeling and Assimilation System) estimates of thickness. A comparable setup has also been compared to floe size distribution (FSD) observations in prior studies. The MIZ fraction of the July sea ice cover, when the MIZ is at its maximum extent, increases by a factor of 2 to 3, from 14 % (20 %) in the 1980s to 46 % (50 %) in the 2010s in NCEP (HadGEM2-ES) atmosphere-forced simulations. In a HadGEM2-ES forced projection, the July sea ice cover is almost entirely MIZ (93 %) in the 2040s. Basal melting accounts for the largest proportion of melt in regions of pack ice and MIZ for all time periods. During the historical period, top melt is the next largest melt term in pack ice, but in the MIZ, top melt and lateral melt are comparable. This is due to a relative increase of lateral melting and a relative reduction of top melting by a factor of 2 in the MIZ compared to the pack ice. The volume fluxes due to dynamic processes decrease due to the reduction in ice volume in both the MIZ and pack ice. For areas of sea ice that transition to being MIZ in summer, we find an earlier melt season: in the region that was pack ice in the 1980s and became MIZ in the 2010s, the peak in the total melt volume flux occurs 20(12) d earlier. This continues in the projection where melting in the region that becomes MIZ in the 2040s shifts 14 d earlier compared to the 2010s. Our analysis shows that a different balance of processes controls the volume budget of the MIZ versus the pack ice. We also find that the balance of processes is different for the MIZ in the 2040s compared to the 1980s, and conclude that we cannot understand the disposition between basal, lateral and top melt in a future Arctic solely based on increased MIZ fraction, since changes in surface energy balance remain a strong control on these behaviours.

Atlantic water recirculation in the northern Barents Sea affects winter sea ice extent

Over the past 50 years, Arctic sea ice has declined in all seasons, with particularly pronounced winter reductions in the Barents Sea. While temperature changes in the Atlantic Water inflow and atmospheric-driven melt have been identified as key drivers of this decline, the role of the return-flow of Atlantic Water in the northern Barents Sea Opening, linked to its recirculation back into the Nordic Seas, has remained largely unrecognized. Using a global ocean and sea ice model, we find that the volume transport of the Atlantic Water return-flow is strongly correlated with the sea ice area in the Barents Sea. In addition, we find that, over the past 40 years, the return-flow has steadily weakened without a corresponding change in inflow. Here, we show that reduced Atlantic Water removal by a weakened return-flow contributes to both interannual variability and the sustained loss of Barents Sea sea ice.

Spatiotemporal dynamics of sea ice volume and their potential drivers in Liaodong Bay, China, using Sentinel-3 data over five ice seasons

Global sea ice extent has notably decreased in recent decades due to climate warming. In non-polar seas, sea ice predominantly consists of first-year ice that exhibits complex spatiotemporal variability and heightened sensitivity to meteorological and geographical influences. This study examined the spatiotemporal dynamics of sea ice volume (SIV) using 72 Sentinel-3 images of Liaodong Bay, China over five ice seasons (2018/19–2022/23). The SIV ranged from 3.94 × 107 m3 to 5.59 × 108 m3 with peak values occurring in the second half of January or the first half of February. Although inter-annual variation in SIV showed no consistent pattern, the SIV in the second half of February remained consistently high, exceeding 2.7 × 108 m3 each year. Over 90% of the sea ice occurred in the northeast Liaodong Bay, while the SIV in the southern regions was notably low. Furthermore, the SIV was significantly correlated with sea surface temperature, sunlight duration, offshore distance and water depth according to linear and quadratic polynomial regression models. These findings provide valuable insights into the SIV change patterns in a non-polar sea and offer a basis for future research and management related to sea ice in the Liaodong Bay and comparable non-polar regions.

End-of-21st century changes on the Antarctic continental shelf under mid- and high-range emissions scenarios

Abstract Dense Shelf Water (DSW) formation on the Antarctic shelf plays a crucial role in our global climate system. However, possible end-of-21st century changes to ocean circulation and temperature under different climate scenarios are poorly constrained. Here we force a 0.1° global ocean-sea ice model with spatially variable anomalies derived from a multi-model mean of 22 CMIP6 models to investigate the impact of mid- (SSP2-4.5) and high-range (SSP5-8.5) emissions on Antarctic margin circulation at the end of this century. We perform these simulations with and without future freshwater contributions from the Antarctic Ice Sheet to assess changes in the presence and absence of meltwater. In the experiments without anomalous meltwater, the Antarctic continental shelf warms and freshens, becoming increasingly stratified with reduced sea ice extent across all months. Reduced sea ice growth leads to freshening over the continental shelf which drives an acceleration of the upper ocean Antarctic Slope Current (ASC), even in the absence of future meltwater contributions. Incorporating future projections of meltwater significantly amplifies these responses, with a complete shutdown of DSW formation and export under both mid- and high-range scenarios. However, even under a mid-range emissions scenario without additional meltwater forcing, substantial changes in Antarctic continental shelf circulation and hydrography are anticipated by the end of this century, including a 35% reduction in DSW formation. Our results further suggest that the temperature response around the Antarctic margins is sensitive to the magnitude of future freshwater forcing, highlighting a need for better constraints on projections of meltwater contributions from the Antarctic Ice Sheet under different climate scenarios.

THE COUPLING OF CNN AND TCN MODELS FOR ARCTIC SEA ICE PREDICTION

The Arctic is warming faster than anywhere else on the planet, and as a result, sea ice in the Arctic Ocean is decreasing. In this study, we developed a coupling of Convolutional Neural Network (CNN) and Temporal Convolutional Network (TCN) models to simulate the spatiotemporal evolutions of Artic sea ice on a monthly scale. Comparative analysis demonstrated that the proposed CNN–TCN model outperforms existing methods in predicting both sea ice concentration and sea ice extent.

High Protistan Parasite Occurrence During Fall in a Warm, Low Sea Ice Year in the Eastern Bering Sea.

Marine protists in the eastern Bering Sea (EBS) are understudied despite being a critical component of the productive subarctic ecosystem. Climate change, and particularly the loss of sea ice, is rapidly altering this ecologically vulnerable and economically important system. In this study, the EBS protist community was characterized across recent years with drastic differences in sea ice extent. In 2019, when the extent of sea ice was anomalously low and retreat occurred early, increased fall water temperatures and surface salinities were observed, and the protist community was dominated by apicomplexan parasites. In contrast, 2017 had more typical winter sea ice conditions and in the fall, water temperatures and surface salinities were lower and protist communities were more diverse, with a larger ratio of primary producer to consumer protists compared to 2019. Surface water temperature was identified as a key predictor of apicomplexan compositional abundance and may be important in the life histories of parasites and their hosts. The interannual variability observed here indicates that the transfer of energy and biomass through the EBS ecosystem can differ drastically across years with differential sea ice influence and highlights the need to monitor protist communities and explore the impacts of protistan parasites.

Mean ocean temperature change and decomposition of the benthic δ18O record over the past 4.5 million years

Abstract. We use a recent reconstruction of global mean sea surface temperature change relative to preindustrial (ΔGMSST) over the last 4.5 Myr together with independent proxy-based reconstructions of bottom water (ΔBWT) or deep-ocean (ΔDOT) temperatures to infer changes in mean ocean temperature (ΔMOT). Three independent lines of evidence show that the ratio of ΔMOT / ΔGMSST​​​​​​​, which is a measure of ocean heat storage efficiency (HSE), increased from ∼ 0.5 to ∼ 1 during the Middle Pleistocene Transition (MPT, 1.5–0.9 Ma), indicating an increase in ocean heat uptake (OHU) at this time. The first line of evidence comes from global climate models; the second from proxy-based reconstructions of ΔBWT, ΔMOT, and ΔGMSST; and the third from decomposing a global mean benthic δ18O stack (δ18Ob) into its temperature (δ18OT) and seawater (δ18Osw) components. Regarding the latter, we also find that further corrections in benthic δ18O, probably due to some combination of a long-term diagenetic overprint and to the carbonate ion effect, are necessary to explain reconstructed Pliocene sea-level highstands inferred from δ18Osw. We develop a simple conceptual model that invokes an increase in OHU and HSE during the MPT in response to changes in deep-ocean circulation driven largely by surface forcing of the Southern Ocean. Our model accounts for heat uptake and temperature in the non-polar upper ocean (0–2000 m) that is mainly due to wind-driven ventilation, while changes in the deeper ocean (> 2000 m) in both polar and non-polar waters occur due to high-latitude deepwater formation. We propose that deepwater formation was substantially reduced prior to the MPT, effectively decreasing HSE. We attribute these changes in deepwater formation across the MPT to long-term cooling which caused a change starting ∼ 1.5 Ma from a highly stratified Southern Ocean due to warm SSTs and reduced sea-ice extent to a Southern Ocean which, due to colder SSTs and increased sea-ice extent, had a greater vertical exchange of water masses.

Long-term variations in sea ice extent can influence trends in maximum sea level in the northeastern Baltic Sea

Long-term variations in sea ice extent can influence trends in maximum sea level in the northeastern Baltic Sea

CMIP6 models overestimate sea ice melt, growth and conduction relative to ice mass balance buoy estimates

Abstract. With the ongoing decline in Arctic sea ice extent, the accurate simulation of Arctic sea ice in coupled models remains an important problem in climate modelling. In this study, the substantial Coupled Model Intercomparison Project Phase 6 (CMIP6) model spread in Arctic sea ice extent and volume is investigated using a novel, process-based approach. An observational dataset derived from the Arctic ice mass balance buoy (IMB) network is used to evaluate fluxes of melt, growth and conduction produced by a subset of CMIP6 models, to better understand the model processes that underlie the large-scale sea ice states. Due to the sparse nature of the IMB observations, the evaluation is performed by comparing distributions of modelled and observed fluxes in the densely sampled regions of the North Pole and Beaufort Sea. We find that all fluxes are routinely biased high in magnitude with respect to the IMB measurements by nearly all models, with too much melt in summer and too much conduction and growth in winter, even as a function of ice thickness. We also show that fluxes vary in ways which are physically consistent with the thermodynamic parameterisations used and that these effects likely modulate the large-scale relationship between ice thickness and ice growth and melt in the CMIP6 models.

Historical catch records of humpback whales and the assessment of early 20th century sea ice edge in climate models

Abstract Assessment of historical environmental conditions in the Southern Ocean is limited by sparse oceanographic records prior to remote-sensing data. Whale catch data, particularly from humpback whales, can help fill this gap, as these whales inhabit waters near the sea ice edge. This study combines historical whale catch data with sea-ice model simulations from CMIP6 to assess the performance in the decade 1930–1939. The models were ranked based on their ability to simulate satellite-observed sea ice seasonality. The high-ranking models locate the sea-ice edge north of historical humpback whale catch regions, indicating higher sea-ice extent at the start of the 20th century, especially in November and December. It is recommended that models be tuned towards these early 20th century conditions while running the pre-industrial simulations. This interdisciplinary approach suggests that using only satellite-era data for model calibration may lead to overestimates of historical sea-ice extent, affecting future predictions.

SICNetseason V1.0: a transformer-based deep learning model for seasonal Arctic sea ice prediction by incorporating sea ice thickness data

Abstract. The Arctic sea ice suffers dramatic retreat in summer and fall, which has far-reaching consequences for the global climate and commercial activities. Accurate seasonal sea ice predictions significantly infer climate change and are crucial for planning commercial activities. However, seasonal prediction of the summer sea ice encounters a significant obstacle known as the spring predictability barrier (SPB): predictions made later than the date of melt onset (roughly May) demonstrate good skill in predicting summer sea ice, while predictions made during or earlier than May exhibit considerably lower skill. This study develops a transformer-based deep learning model, SICNetseason (V1.0), to predict the Arctic sea ice concentration on a seasonal scale. Including spring sea ice thickness (SIT) data in the model significantly improves the prediction skill at the SPB point. A 20-year (2000–2019) test demonstrates that the detrended anomaly correlation coefficient (ACC) of September sea ice extent (sea ice concentration >15 %) predicted by our model during May and April is improved by 7.7 % and 10.61 %, respectively, compared to the ACC predicted by the state-of-the-art dynamic model SEAS5 from the European Centre for Medium-Range Weather Forecasts (ECMWF). Compared with the anomaly persistence benchmark, the mentioned improvement is 41.02 % and 36.33 %. Our deep learning model significantly reduces prediction errors in terms of September's sea ice concentration on seasonal scales compared to SEAS5 and the anomaly persistence model (Persistence). The spring SIT data are key in optimizing the predictions around the SPB, contributing to an enhancement in ACC of more than 20 % in September's sea ice extent (SIE) for 4- to 5-month-lead predictions. Our model achieves good generalizability in predicting the September SIE of 2020–2023.

Increased exposure of the shores of Hornsund (Svalbard) to wave action due to a rapid shift in sea ice conditions

Negative trends in sea ice extent in polar regions lead to increasing exposure of the coasts to wind-generated waves and thus to wave-induced erosion. In the Northern Hemisphere, a region undergoing particularly rapid changes is the Barents Sea, contributing nearly one-fourth of the total sea ice loss in the Arctic. This work concentrates on the westernmost edge of that area: the Hornsund fjord, located in the southwestern part of Spitsbergen (Svalbard). Long-term (1979–2023) variability in sea ice and waves offshore and in the coastal zone was analyzed based on sea ice reanalysis data, wave observations at three coastal locations, and a spectral wave model. We found that sea ice concentration at the entrance to Hornsund underwent a “regime shift” in 2005, from winters with frequent compact-ice occurrence in the period 1979–2005 to almost ice-free winters in the period 2006–2023. Results of simulations with a spectral wave model calibrated to observations in ice-free periods show large biases during compact-ice events (strongly overestimated wave height and energy flux, slightly underestimated peak and energy period), suggesting significant influence of ice-related attenuation on wave conditions nearshore. These biases, combined with the sea ice and wave data, were then used to estimate the mean seasonal cycles of nearshore wave conditions in the two periods 1979–2005 and 2006–2023. The results show that the lack of sea ice in the recent two decades has led to a substantial increase in wave energy reaching the coastal zone (up to 100% between February and April), and to a shift of the seasonal maximum of that energy from late autumn (November–December) to winter (December–March). Overall, these changes indicate an increased exposure of the coasts to wave-induced erosion and sediment transport.

Strong impact of the rare three-year La Niña event on Antarctic surface climate changes in 2021–2023

From 2021 to 2023, satellite records reveal that February Antarctic sea ice extent reached record lows in 2022 and 2023. Simultaneously, the Antarctic ice sheet experienced a transient mass gain and rebounded temporarily from a decadal decline since 2002. The reasons behind these dramatic changes are unknown. Here, we show that the triple-dip La Niña event during 2021–2023 (referred to as TD_LN2023) played a major role in these changes. Compared to a previous triple-dip La Niña event (1999–2001), the tropical-Antarctic teleconnections during TD_LN2023 were stronger. A more pronounced southward shift of the Ferrel Cell was identified as a key driver for the enhanced tropical-Antarctic teleconnections during TD_LN2023 against the background of intensified westerly winds and tropical expansion. The poleward increase, which facilitated poleward atmospheric heat and moisture transport, contributed to the sea ice extent decline and the ice sheet mass growth. Additionally, this southward shift strengthened the Rossby wave train, which, sustained by enhanced stratosphere-troposphere coupling, amplified the Pacific-South American pattern, and further promoted regional sea ice decline. Finally, this southward shift, associated with the southward shift of the westerly jet, enhanced Ekman suction, bringing subsurface warm water to the surface and contributing to pan-Antarctic low sea ice. The physical processes outlined in the case study are further validated through empirical orthogonal function and regression analysis. Under global warming, multi-year La Niña events are projected to occur more frequently. The evolving tropical-Antarctic teleconnections in the context warrant close attention.

Contribution of shorter-term radiative forcings of aerosols and ozone to global warming in the last two decades

This paper reports observations of regional and global upper stratosphere temperature (UST) and surface temperature, as well as various climate drivers, including greenhouse gases (GHGs), ozone, aerosols, solar variability, snow cover extent, and sea ice extent (SIE). We strikingly found warming trends of 0.77(±0.57) and 0.69(±0.22) K/decade in UST at altitudes of 35–40 km in the Arctic and Antarctic, respectively, and no significant trends over non-polar regions since 2002. These UST trends provide fingerprints of decreasing and no significant trends in total GHG effect in polar and non-polar regions, respectively. Correspondingly, we made the first observation of surface cooling trends in both the Antarctic since 2005 and the Arctic since 2016 once the SIE started to recover. However, surface warming remains at mid-latitudes, which caused the recent rise in global mean surface temperature (GMST). These temperature changing patterns are consistent with the characteristics of the cosmic-ray-driven electron reaction (CRE) mechanism of halogen-containing GHGs (halo-GHGs) with larger destruction rates at higher latitudes. Moreover, the no-parameter physics model of warming caused by halo-GHGs closely reproduces the observed GMSTs from 2000 to 2024, including the pause in warming during 2000–2012 and the significant warming by 0.2–0.3 °C during 2013–2023, of which 0.27 °C was calculated to arise from the net radiative forcing of aerosols and ozone due to improved air quality. The results also show that the physics model captures 76% of the variance in the observed GMSTs, exhibiting a warming peak in October 2023 and predicting a gradual GMST reversal thereafter.

Will the declining sea ice extent in the Arctic cause a reversal of net benthic-pelagic exchange directions?

Will the declining sea ice extent in the Arctic cause a reversal of net benthic-pelagic exchange directions?