Ice Changes Research Articles

Arctic and Antarctic Sea Ice Thickness and Volume Changes From Observations Between 1994 and 2023

AbstractBoth Arctic and Antarctic sea ice are affected by climate change. While Arctic sea ice has been declining for several decades, Antarctic sea ice extent slowly increased until 2015, followed by a sharp drop in 2016. Quantifying sea ice changes is essential to assess their impacts on the ocean, atmosphere, ecosystems and Arctic communities. In this study, we combine sea ice thickness estimates from four satellite radar altimeters to derive the longest time series of homogeneous sea ice thickness for both hemispheres over 30 years (1994–2023). The record supports the rapid loss of sea ice in the Arctic for each month of the year and the heterogeneous changes in sea ice thickness in the Antarctic. The study confirms that most of the volume variability is due to the thickness variability, which holds true for both hemispheres. The sea ice thickness time series presented here offer new insights for models, in particular the possibility to evaluate sea ice reanalyses and to initialize forecasts, especially in the Antarctic, where the data set presented here has no equivalent in terms of spatial and temporal coverage.

Cold Season Cloud Response to Sea Ice Loss in the Arctic

Abstract Based on satellite observations, we investigate the cloud responses during the cold season, from October to the following March, to interannual fluctuations in Arctic sea ice concentrations during September and October. It is found that the cloud responses differ between the periods 2000-2018 and 1982-1999. From 2000-2018, increased Arctic Ocean cloud cover in October and November transitioned to significantly less cloud cover and cloud radiative forcing (CRF) from January to March, in response to lower sea ice concentrations in September and October. The lower CRF in January and March preconditions the sea ice and likely contributes to higher sea ice concentrations the following September. This suggests a negative cloud feedback on sea ice concentration, which may contribute to sea ice recovery after a dramatic decrease. In contrast, from 1982 to 1999, generally increased cloud cover and cloud radiative forcing persisted from October to March following lower sea ice concentrations in the preceding September and October. The cause of the different cloud responses to sea ice changes in these two time periods remains unclear and requires further investigation.

Comparison of Non-Contact Measurement Technologies Applied on the Underground Glacier—The Choice for Long-Term Monitoring of Ice Changes in Dobšiná Ice Cave

Comparison of Non-Contact Measurement Technologies Applied on the Underground Glacier—The Choice for Long-Term Monitoring of Ice Changes in Dobšiná Ice Cave

Exploring the Use of Fengyun-3 Meteorological Satellite for Monitoring Sea Ice to Provide Services for Polar Navigation

This paper explores the feasibility and effectiveness of using the Fengyun-3 meteorological satellite to monitor sea ice, providing services for ships navigating in polar regions. Firstly, it analyzes the impact of Arctic sea ice changes on ship navigation and the importance of sea ice monitoring in route planning. Next, it provides a detailed introduction to the data sources and processing methods of the Fengyun-3 satellite, including radiometric calibration, geometric correction, image registration, and cropping. Subsequently, it discusses the characteristics of sea ice in the visible spectrum and successfully extracts sea ice information using MERSI-II data with land, cloud, and seawater masking techniques. The study indicates that the comprehensive use of multi-spectral data and other observation methods can significantly enhance sea ice monitoring capabilities. In the future, integrating more advanced technologies is expected to achieve refined identification and short-term prediction of sea ice movement, thereby providing more scientific and efficient support for ships navigating in polar regions, enhancing navigation safety and efficiency, and offering a scientific basis for the development of Arctic shipping routes.

Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling

Melt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A novel melt pond parameterization scheme simulates the movement of meltwater under the influence of gravity over a realistic sea ice topography. We evaluated different melt pond parameterization schemes based on remote sensing observations. The absolute deviation of the maximum pond coverage simulated by the new scheme is within 3%, while differences among parameterization schemes exceed 50%. Errors were found to be primarily due to the calculation of macroscopic meltwater loss, which is related to sea ice surface topography. Previous studies have indicated that sea ice with a lower surface roughness has a larger catchment area, resulting in larger pond coverage during the melt season. This study has identified an opposing mechanism: sea ice with lower surface roughness has a larger catchment area connected to the macroscopic flaws of the sea ice surface, which leads to more macroscopic drainage into the ocean and thereby a decrease in melt pond coverage. Experimental simulations showed that sea ice with 46% higher surface roughness, resulting in 12% less macroscopic drainage, exhibited a 38% higher maximum pond fraction. The presence of macroscopic flaws is related to the fragmentation of sea ice cover. As Arctic sea ice cover becomes increasingly fragmented and mobile, this mechanism will become more significant.

Projected Antarctic sea ice change contributes to increased occurrence of strong El Niño

Current climate models suggested that Antarctic sea ice cover would decrease substantially under cumulative CO2 emission, but little is known whether large decrease in Antarctic sea ice can influence the occurrence of strong El Niño. Using time slice coupled and uncoupled model experiments, we show that in response to half reduction of Antarctic sea ice projected near the end of the 21st century, the frequency of strong El Niño would be increased by ~40%. It is contributed by enhanced thermocline, Ekman, and zonal advective positive feedbacks that are partly offset by enhanced thermodynamic damping. The strong warming and weakened westerly winds in the southeastern Pacific generate an anomalous Rossby wave propagating into the eastern subtropical and tropical Pacific, favoring stronger El Nino, and air-sea coupling and ocean feedbacks play a critical role in the teleconnection. Unexpectedly, compare to halved Antarctic sea ice, the ice-free Antarctic leads to a decrease in the frequency of strong El Niño, which is largely due to a substantial increase in thermodynamic damping. We also show that a large portion of the increase of strong El Niño events under greenhouse warming might be connected with Antarctic sea-ice loss, though increased greenhouse gas plays an important role.

Capacity of a set of CMIP6 models to simulate Arctic sea ice drift

Abstract Evaluating CMIP6 model performance helps to improve the prediction of future changes in Arctic sea ice. We analyze the seasonal cycles, distribution, and evolution of sea ice in different regions from 1979 to 2014. We compare the output from selected CMIP6 models with reference data for sea ice motion. We also discuss the correlations between sea ice motion(SIM) and sea ice thickness (SIT) in reference data, and how CMIP6 models explain them. We select EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, MPI-ESM1-2-HR, and NorESM2-LM for CMIP6 study. We compare outputs with reference data: Sea ice extent (SIE) from NSIDC; SIT from PIOMAS; and SIM from the IABP buoy data. Analytical techniques include Theil-Sen and Ordinary least squares (OLS) regression. Most selected CMIP6 models have seasonal cycles of SIM lagging behind IABP observations by 1-2 month and overestimate central Arctic SIM magnitude, with MPI-ESM1-2-HR having the highest discrepancy and NorESM2-LM lowest. The models show better simulation of SIM in the ice melting season than in the growing season. Models perform worse at capturing regional differences in SIM evolution and are overly conservative when simulating the increasing trend in ice motion, especially in coastal Arctic seas during summer. There is significant negative correlation between SIT and SIM in October.

Future Global River Ice in CMIP6 Models under Climate Change

Abstract River ice changes due to climate change significantly impact river hydrology, economies, and societies. This study employed the CMIP6 data and a river ice model to predict global river ice changes in response to climate change. Results indicate significant declines in global river ice due to global warming. With each 1°C increase in surface air temperature (SAT) in the future, river ice extent of ice-affected rivers decrease by 2.11 percentage points, and ice duration shorten by 8.4 days. Under the shared socioeconomic pathways 2-4.5 (SSP2-4.5) scenario, the long-term mean SAT is 1.2°–2.5°C higher than in the near term. This leads to a 1.9–4.4-percentage-point decrease in global river ice extent, a 6.8–15.1-day decrease in river ice duration, and ice-free rivers increasing by up to 4.02%. The SSP5-8.5 scenario predicts a warmer long-term mean SAT, leading to greater reductions in river ice. Geographically, river ice loss is most notable in North America, Europe, Siberia, and the Tibetan Plateau (TIB), particularly in peninsular, coastal, and mountainous regions due to the combined effects of initial temperatures and temperature increases. Overall, the eastern Europe (EEU) shows the greatest loss of river ice on average. Monthly analyses show the most substantial decreases from October to June, indicating pronounced seasonal variability. This study provides valuable insights for addressing challenges related to river ice changes in high-latitude and high-elevation regions. Significance Statement River ice has a significant impact on various aspects, including hydrology, ecology, and the economy. The ongoing global warming phenomenon has resulted in a decline in river ice. This ice acts as a barrier, affecting river gas exchange and influencing the metabolism of the river, which is crucial for regulating greenhouse gas (GHG) emissions. The primary objective of this research is to examine the response of river ice to future climate change. The outcomes of this study will play a role in estimating future GHG emissions and understanding river metabolism, as well as providing a valuable reference for tackling emerging challenges in resource acquisition in high-latitude and high-altitude regions.

Thermodynamic and Dynamic Variations in Sea Ice Thickness of the Ross Sea, Antarctica, Driven by Atmospheric Circulation

AbstractAtmospheric circulation has significant impacts on sea ice drifting patterns and mass balance, as wind drag induces pressure ridges and leads on the sea ice surface. In this study, the spatiotemporal distributions of these dynamic sea ice deformation features in the Ross Sea are examined using ICESat‐2 (IS2) ATL10 freeboard data (2019–2022). The temporal variation of the modal sea ice thickness (SIT), caused by thermodynamic ice growth and sea ice advection, varies from 0.7–1.0 m in April to 1.0–1.6 m in July–September and decreases thereafter in the northwest (NW) and northeast (NE) sectors. This temporal variation of modal SIT agrees with the air temperature (correlation coefficients >0.5). The southwest (SW) sector shows a consistently low modal SIT (<1.0 m) because of the production of new ice in polynyas and continuous northward sea ice drift. Meanwhile, the southeast (SE) sector shows the thickest ice in Octobers 2019 and 2020 because of the advection of thick ice from the Amundsen Sea, which was reduced in 2021 and 2022. In terms of dynamic sea ice deformation, the SE sector shows the largest deformation because of the wind‐driven convergence of sea ice movement. However, such intense deformation in the SE sector diminished in 2021 and 2022 due to the dominance of strong southerly wind associated with the Amundsen Sea Low (ASL). This study emphasizes the potential of IS2 sea ice products to assess the role of atmospheric driving forces on thermodynamic and dynamic sea ice changes.

Enhanced interannual variability of the May North Atlantic Oscillation and its impact on summer sea ice in the North Atlantic after the mid-2000s

Based on data diagnosis and numerical experiments, this study investigated the changes in the interannual properties of the May North Atlantic Oscillation (NAO) and their impact on summer (June–July) sea ice in the North Atlantic during 1979–2021. Results showed statistically significant increase in the interannual variability of the May NAO after the mid-2000s, which had remarkably enhanced impact on summer sea ice in the eastern Hudson Bay (EHB) and the western Labrador Sea (WLS). During 2005–2021, corresponding to a positive phase of the May NAO, anomalous surface westerly or northwesterly winds prevailed over the Hudson Bay and Labrador Sea in May. This led to statistically significant increase in sea ice in both the EHB and the WLS in May via dynamic processes (favoring southeastward movement of the sea ice) and thermal processes (changing surface turbulent heating and shortwave radiation). In comparison with the situation in May, the increase in sea ice in the EHB developed further during summer mainly via thermal processes (positive feedback between the increased sea ice and shortwave radiation). In contrast, amplitude of the increased sea ice in the WLS was comparable between May and summer. Dynamic processes (southeastward movement of sea ice), which was induced by a barotropic anomalous high in the troposphere centered over the Labrador Peninsula, favored the increase in sea ice in summer in the WLS. The tripole sea surface temperature anomalies in the North Atlantic and increased snowpack on the Labrador Peninsula in May, triggered by the positive phase of the May NAO, played an important role in the formation of the anomalous high. During 1979–2004, the surface wind, snowpack, and tripole sea surface temperature anomalies in May, triggered by the May NAO, were relatively weak, leading to statistically insignificant changes in summer sea ice in the EHB and WLS.

First Red List of Ecosystems assessment of a tropical glacier ecosystem to diagnose the pathways towards imminent collapse

Abstract Tropical glaciers are rapidly disappearing, particularly in isolated mountain peaks below 5,000 m elevation. These glaciers are fundamental substrates for unique cryogenic ecosystems in high tropical environments where the ice, melting water and rocky substrate sustain microbiological communities and other meso- and macro-biota. This study uses the Red List of Ecosystems guidelines to diagnose the collapse of the tropical glacier ecosystem of the Cordillera de Mérida, Venezuela. We undertook the assessment with existing estimates of glacier ice extent, indirect historical estimates of ice mass balance and global mechanistic models of future ice mass balance. We complemented these with additional statistical analysis of trends and bioclimatic suitability modelling to calculate and predict rates of decline and relative severity of degradation in selected ecosystem indicators. The evidence suggests an extreme risk of collapse (Critically Endangered) because of a prolonged and acute reduction in ice extent and changes in climatic conditions that are leading to the complete loss of ice mass. The ice substrate has declined 90% in the last 20 years, and observed acceleration of the rate of decline suggests it will probably disappear within the next 5 years. Loss of ice substrate will trigger an immediate loss of supraglacial, englacial and subglacial biotic compartments and initiate a decades-long succession of forefield vegetation. However, ongoing inventories of native biota and monitoring of ecosystem transitions can provide valuable insights and lessons for other ecosystems facing similar risks. The Red List of Ecosystems assessment protocol provides a useful framework for comparative analysis of cryogenic ecosystems.

Analysis of fast ice anomalies and their causes in 2023 in Prydz Bay, East Antarctica

In 2023, Antarctica experienced its lowest sea ice extent in the satellite era, with extreme polar events gaining widespread attention. Prydz Bay, where the Chinese Zhongshan Station is located, is the third largest embayment in Antarctica. Changes in sea ice, fast ice and polynyas directly affect local heat and mass exchanges between the ocean and atmosphere, as well as ecosystems and research activities. In 2023, substantial fast ice anomalies were observed in Prydz Bay: the extent of fast ice off Zhongshan Station (ZSFI) was anomalously low, while that within Barrier Bay (BaFI) was anomalously high. This study analysed the seasonal evolution and underlying main causes for the extreme conditions using ice charts, satellites and reanalysis data. From 2014 to 2022, the extent of ZSFI typically increased during the cold season, reaching a maximum of (9.41 ± 2.47) × 103 km2, whilst the Barrier Bay Polynya (BaP) persisted throughout this period. However, in 2023, ZSFI did not increase from June onwards, peaking at a maximum extent of only 5.49 × 103 km2, and the BaP closed in mid-winter, leading to the formation of extensive BaFI. Air temperature and wind speed continuously dropped in July, and these conditions persisted for approximately 1 month, leading to the closure of BaP. However, ZSFI did not expand further under these extreme meteorological conditions, indicating its independence from these factors. The limited expansion of ZSFI could be attributed to high ocean temperatures. Overall, this study provides valuable insights into the mechanisms driving extreme fast ice conditions.

Cloud Radiative Effects Slow Sea Ice Changes During Summer Arctic Dipole Anomaly

AbstractOver the past 30 years, the Arctic Dipole Anomaly (DA) has repeatedly led to record lows in summer sea ice extent, with cloud radiative effects (CRE) playing a crucial regulatory role. Here, we reveal the CRE variations between positive and negative DA events and elucidate the slowing impacts of CRE on sea ice thickness (SIT) changes. The DA triggers robust meridional winds and transpolar drift, markedly reducing SIT in the Beaufort Sea (BeS), Chukchi Sea (CS), and East Siberian Sea (ESS), while increasing it in the Greenland Sea (GS). CRE significantly slow SIT changes, contributing +14.4, +4.4, +16.4, and −26.7 cm to changes from June to August, against total changes of −55.9, −29.4, −39.8, and +42.8 cm in September over BeS, CS, ESS, and GS, respectively. This study underscores the key impacts of CRE on sea ice variation, emphasizing their significance in the polar climate system.

Ice algae contributions to the benthos during a time of sea ice change: a review of supply, coupling, and fate

Ice algae contributions to the benthos during a time of sea ice change: a review of supply, coupling, and fate

Future sea ice weakening amplifies wind-driven trends in surface stress and Arctic Ocean spin-up

Arctic sea ice mediates atmosphere-ocean momentum transfer, which drives upper ocean circulation. How Arctic Ocean surface stress and velocity respond to sea ice decline and changing winds under global warming is unclear. Here we show that state-of-the-art climate models consistently predict an increase in future (2015–2100) ocean surface stress in response to increased surface wind speed, declining sea ice area, and a weaker ice pack. While wind speeds increase most during fall (+2.2% per decade), surface stress rises most in winter (+5.1% per decade) being amplified by reduced internal ice stress. This is because, as sea ice concentration decreases in a warming climate, less energy is dissipated by the weaker ice pack, resulting in more momentum transfer to the ocean. The increased momentum transfer accelerates Arctic Ocean surface velocity (+31–47% by 2100), leading to elevated ocean kinetic energy and enhanced vertical mixing. The enhanced surface stress also increases the Beaufort Gyre Ekman convergence and freshwater content, impacting Arctic marine ecosystems and the downstream ocean circulation. The impacts of projected changes are profound, but different and simplified model formulations of atmosphere-ice-ocean momentum transfer introduce considerable uncertainty, highlighting the need for improved coupling in climate models.

Analysis of Arctic Sea Ice Concentration Anomalies Using Spatiotemporal Clustering

The dynamic changes of sea ice exhibit spatial clustering, and this clustering has characteristics extending from its origin, through its development, and to its dissipation. Current research on sea ice change primarily focuses on spatiotemporal variation trends and remote correlation analysis, and lacks an analysis of spatiotemporal evolution characteristics. This study utilized monthly sea ice concentration (SIC) data from the National Snow and Ice Data Center (NSIDC) for the period from 1979 to 2022, utilizing classical spatiotemporal clustering algorithms to analyze the clustering patterns and evolutionary characteristics of SIC anomalies in key Arctic regions. The results revealed that the central-western region of the Barents Sea was a critical area where SIC anomaly evolutionary behaviors were concentrated and persisted for longer durations. The relationship between the intensity and duration of SIC anomaly events was nonlinear. A positive correlation was observed for shorter durations, while a negative correlation was noted for longer durations. Anomalies predominantly occurred in December, with complex evolution happening in April and May of the following year, and concluded in July. Evolutionary state transitions mainly occurred in the Barents Sea. These transitions included shifts from the origin state in the northwestern margin to the dissipation state in the central-north Barents Sea, from the origin state in the central-north to the dissipation state in the central-south, and from the origin state in the northeastern to the dissipation state in the central-south Barents Sea and southeastern Kara Sea. Various evolutionary states were observed in the same area on the southwest edge of the Barents Sea. These findings provide insights into the evolutionary mechanism of sea ice anomalies.

Evaluating soil freezing characteristic curve models for predicting unfrozen water content in freezing soils

Frozen soil is widely distributed around the world, and the phase change and migration of ice and water contribute to various engineering and agricultural challenges. The Soil Freezing Characteristic Curve (SFCC), which elucidates the relationship between water and temperature in permafrost, serves as a crucial tool for studying permafrost and forms the foundational equation for coupled numerical simulations involving permafrost water-heat-force. Different choices of SFCC result in variations in the predicted values of unfrozen water, thereby affecting the accuracy of other issues or numerical simulations. Moreover, there is a lack of studies on the performance of SFCC models under diverse conditions. Therefore, we review and classify some existing SFCC models, selects 14 SFCC models according to functional form, derivation process, physical significance etc., and evaluates these models through published data and statistical indicator RMSE, Radj2 and BIC. The effects of functional form, soil type, cooling stage and initial water content on each model were analyzed using cluster analysis and other means. It is concluded that the SFCC model is affected by the function form, and the power and exponential functions need to be modified by more parameters. The nested soil water characteristic curve model also needs to be modified for the low water content section. Meanwhile, each model also shows sensitivity to the characteristics of datasets, and the performance under different conditions is not the same. Some models may not fit data features under certain conditions. Therefore, it is necessary to reasonably select the SFCC model in different use backgrounds and conditions.

Arctic sea ice loss warmed the temperate East Asian winter in the mid-Holocene

The recent colder winters in midlatitude Eurasia have been proposed to result from Arctic sea-ice decline. However, large uncertainties remain regarding this link in the present variable climate. Here, we present ice-rafted debris records from the eastern Arctic and geochemical data from the temperate East China Sea to reconstruct Holocene changes in sea ice and the East Asian winter monsoon. Our reconstructions and climate numerical simulations revealed enhanced Arctic sea-ice decline but warmer winters in East Asia in the mid-Holocene than in the late Holocene. In the warmer mid-Holocene, enhanced Arctic sea-ice loss transferred more heat from intensive summer solar insolation to the winter atmosphere, suppressing meridional heat transport; thus, less high-latitude cold air moved to lower latitudes in Asia due to the weakened winter monsoon. Our findings imply that the colder winters in East Asia may not change the long-term trend toward winter warming in the context of Arctic sea-ice decline.

Assessment of Arctic sea ice simulations in cGENIE model and projections under RCP scenarios

Simulating and predicting Arctic sea ice accurately remains an academic focus due to the complex and unclear mechanisms of Arctic sea ice variability and model biases. Meanwhile, the relevant forecasting and monitoring authorities are searching for models to meet practical needs. Given the previous ideal performance of cGENIE model in other fields and notable features, we evaluated the model’s skill in simulating Arctic sea ice using multiple methods and it demonstrates great potential and combined advantages. On this basis, we examined the direct drivers of sea-ice variability and predicted the future spatio-temporal changes of Arctic sea ice using the model under different Representative Concentration Pathways (RCP) scenarios. Further studies also found that Arctic sea ice concentration shows large regional differences under RCP 8.5, while the magnitude of the reduction in Arctic sea ice thickness is generally greater compared to concentration, showing a more uniform consistency of change.

Co-located OLCI optical imagery and SAR altimetry from Sentinel-3 for enhanced Arctic spring sea ice surface classification

The Sentinel-3A and Sentinel-3B satellites, launched in February 2016 and April 2018 respectively, build on the legacy of CryoSat-2 by providing high-resolution Ku-band radar altimetry data over the polar regions up to 81° North. The combination of synthetic aperture radar (SAR) mode altimetry (SRAL instrument) from Sentinel-3A and Sentinel-3B, and the Ocean and Land Colour Instrument (OLCI) imaging spectrometer, results in the creation of the first satellite platform that offers coincident optical imagery and SAR radar altimetry. We utilise this synergy between altimetry and imagery to demonstrate a novel application of deep learning to distinguish sea ice from leads in spring. We use SRAL classified leads as training input for pan-Arctic lead detection from OLCI imagery. This surface classification is an important step for estimating sea ice thickness and to predict future sea ice changes in the Arctic and Antarctic regions. We propose the use of Vision Transformers (ViT), an approach adapting the popular deep learning algorithm Transformer, for this task. Their effectiveness, in terms of both quantitative metric including accuracy and qualitative metric including model roll-out, on several entire OLCI images is demonstrated and we show improved skill compared to previous machine learning and empirical approaches. We show the potential for this method to provide lead fraction retrievals at improved accuracy and spatial resolution for sunlit periods before melt onset.