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Accurately assessing ice loads is a fundamental issue in the field of structural design for ships in ice-covered regions. In this paper, we conducted research on extreme ice load estimation for icebreaking ships, combining stochastic theory with numerical simulation. Firstly, using sea ice data from the Arctic region of the United States National Snow and Ice Data Center, a stochastic ice field model was established under Arctic sea ice conditions using non-parametric estimation and the rejection sampling method, and ice field data were generated stochastically. Then, based on the stochastic ice field data, a three-dimensional numerical model of the interaction between the ice field and the ship hull was established, and the reliability of the numerical model was verified by experimental results. Finally, based on the numerical model of the interaction between the ice field and the ship hull, asymptotic methods were used to study the extreme ice load estimation in different parts of the ship hull, revealing the variation law of the extreme ice load in different parts of the ship hull. This study provides basic theory and technical support for the structural design of ships in polar regions and has engineering application value.

The Puruogangri Ice Field (PIF) in the central Tibetan Plateau, known as the world’s Third Pole, is the largest modern ice field in the Tibetan Plateau and a crucial indicator of climate change. Although it was thought to be quiet, recent studies identified possible surging behaviors. But comprehensive velocity fields remain largely unknown. Here we present the first comprehensive and high spatiotemporal resolution 3D displacement field of the PIF from 2017 to 2024 using synthetic aperture radar (SAR) imaging geodesy. Using time-series InSAR and time-series pixel offset tracking and integrating ascending and descending Sentinel-1 SAR images, we invert the time-series 3D displacement over eight years. Our results reveal significant seasonal variations and three surging glaciers, with peak displacements exceeding 110 m in 12 days. Combined with ERA5 reanalysis and SAR backscatter coefficients analysis, we demonstrate that these surges are hydrologically controlled, likely initiated by damaged subglacial drainage systems. This study enhances our understanding of glacier dynamics in the central Tibetan Plateau and highlights the potential of using SAR imaging geodesy to monitor glacial hazards in High Mountain Asia.

Due to climate warming, the glaciers of the Tibetan Plateau have experienced rapid mass loss and the patterns of glacier changes have exhibited high spatiotemporal heterogeneity, especially in interior areas. As the largest ice field within the Tibetan Plateau, the Puruogangri Ice Field has attracted a lot of attention from the scientific community. However, relevant studies that are based on satellite data have mainly focused on a few periods from 2000–2016. Long-term and multiperiod observations remain to be conducted. To this end, we estimated the changes in the glacier area and mass balance of the Puruogangri Ice Field over five subperiods between 1975 and 2021, based on multisource remote sensing data. Specifically, we employed KH-9 and Landsat images to estimate the area change from 1975 to 2021 using the band ratio method. Subsequently, based on KH-9 DEM, SRTM DEM, Copernicus DEM and ZY-3 DEM data, we evaluated the glacier elevation changes and mass balance over five subperiods during 1975–2021. The results showed that the total glacier area decreased from 427.44 ± 12.43 km2 to 387.87 ± 11.02 km2 from 1975 to 2021, with a decrease rate of 0.86 km2 a−1. The rate of area change at a decade timescale was −0.74 km2 a−1 (2000–2012) and −1.00 km2 a−1 (2012–2021). Furthermore, the rates at a multiyear timescale were −1.23 km2 a−1, −1.83 km2 a−1 and −0.42 km2 a−1 for 2012–2015, 2015–2017 and 2017–2021, respectively. In terms of the glacier mass balance, the region-wide results at a two-decade timescale were −0.23 ± 0.02 m w.e. a−1 for 1975–2000 and −0.29 ± 0.02 m w.e. a−1 for 2000–2021, indicating a sustained and relatively stable mass loss over the past nearly five decades. After 2000, the loss rate at a decade timescale was −0.04 ± 0.01 m w.e. a−1 for 2000–2012 and −0.17 ± 0.01 m w.e. a−1 for 2012–2021, indicating an increasing loss rate over recent decades. It was further found that the mass loss rate was −0.12 ± 0.02 m w.e. a−1 for 2012–2015, −0.03 ± 0.01 m w.e. a−1 for 2015–2017 and −0.40 ± 0.03 m w.e. a−1 for 2017–2021. These results indicated that a significant portion of the glacier mass loss mainly occurred after 2017. According to our analysis of the meteorological measurements in nearby regions, the trends of precipitation and the average annual air temperature both increased. Combining these findings with the results of the glacier changes implied that the glacier changes seemed to be more sensitive to temperature increase in this region. Overall, our results improved our understanding of the status of glacier changes and their reaction to climate change in the central Tibetan Plateau.

We present the first comprehensive inventory and analysis of rock glaciers in the hydrographic Great Basin (GB), United States, documenting 842 features (mean 9.9 ha; range 0.1-201 ha) across thirty-two mountain ranges. These encompassed 8° latitude (from 36.5°N to 44.3°N) and 11° longitude (from −110.7°W to −121.4°W), and composed 83.1 km 2 , or 1.1 percent, of the cumulative area above the lowest rock glacier elevation. Forty-five percent of the features were mapped as intact (containing ice) and occurred across sixteen mountain ranges. Rock glaciers conservatively contained cumulative water volume of 0.8924 km 3 . We also mapped 237 persistent ice fields from thirteen GB ranges. Ice-field water equivalent was 0.0653 km 3 ; rock glaciers contributed 93 percent of the total water volume (rock glacier:icefield ratio, 14:1). Rock glaciers occurred on northerly aspects at high elevations (mean, 3,196 m) and had a mean annual air temperature of 1.7°C (range, 1.3-3.3°C). Contributions of water from rock-glacier springs and groundwater have not been included in GB hydrologic assessments, nor have rock glaciers been evaluated for their roles in supporting cold-adapted aquatic fauna and promoting vegetation communities and habitat for alpine terrestrial species. Rock glaciers provide hydrologic and ecologic refugia previously unrecognized in the GB with respect to warming future climates.

Ships sailing through cold regions frequently encounter floe ice fields. An air-bubble system that reduces friction between the hull and ice floes is thus considered useful for the reduction of ice-induced resistance. In this study, a numerical analysis procedure based on coupled finite volume method (FVM) and discrete element method (DEM) is proposed to simulate complicated hull-water-gas-ice interactions for ice-going ships installed with air-bubble systems. The simulations reveal that after turning on the air-bubble system ice floes in contact with the hull side wall are pushed away from the hull by the gas-water mixture, resulting in an ice-free zone close to the side hull. It is found that the drag reduction rate increases with the increase of ventilation, while the bow ventilation plays a deciding role in the overall ice-resistance reduction. The proposed procedure is expected to facilitate design of new generations of ice-going ships.

Glacier mass balance change is among the best indicators of glacier response to climate change. Due to its inaccessibility and limited observation, little is known about the change to the Dongkemadi Ice Field (DIF) in the Tanggula Mountains located in the source region of the Yangtze River in central Tibetan Plateau. Here, an enhanced temperature index-based glacier model considering glacier area change was applied to study the temporal-spatial variation in mass balance on the DIF from 1989 to 2012 and to assess its response to climate change. The model was forced by reconstructed temperature and precipitation from adjacent national meteorological stations and validated by comparing with field observations from the Xiao Dongkemadi Glacier (XDG). Results show that the simulated mass balance is in good agreement with the observations (R 2  = 0.75, p < .001), and the model can reasonably reproduce well the glacier mass change. Then the model was applied to twenty individual glaciers in DIF and forced by the high-resolution regional climate model (RegCM3) from 2013 to 2050 to project their further variation. In the future, the mass balance of glaciers in DIF shows a continuously negative trend with a linear rate of −0.16 m water equivalent (w.e.) a −1 in representative concentration pathway (RCP) 4.5 and −0.35 m w.e. a −1 in RCP 8.5. Most of the glaciers' equilibrium line altitudes (ELAs) will reach or exceed their maximum elevation after the 2030s. By coupling a modified volume-area scaling method with the mass balance model, results showed that areas of the individual glaciers in DIF will lose about 12.10 to 30.66 percent under RCP4.5 and 14.06 to 38.76 percent under RCP8.5, and the volume of the DIF will lose about 1.18 km 3 in RCP4.5 and 1.44 km 3 in RCP8.5 by the end of 2050. In addition, the terminuses of glaciers experienced the largest percentage losses and most of the glaciers' front position will reach ~5,520 m a.s.l. in RCP 4.5 and 5,570 m a.s.l. in RCP 8.5, the latter of which is nearly close to the DIF average ELA in 1989. The clearly increasing summer air temperature may be the main reason for glacier shrinkage in the DIF. If the warming trend continues, glaciers in DIF may further retreat with continued glacial melt or even mostly disappear by the end of the century.

This article contains the analytical model of the drift of a separate ice field under the action of wind and current, in which velocities and directions can vary over time. The model takes into account the mass of ice, added mass of seawater, and the effects of the wind and current on the ice field in forming the friction on its upper and underwater surfaces and the frontal resistance on its end (forward and backward) surfaces. Simulation of the wind drift of the ice field showed the drift velocity exceeds the considerable known velocity of a compact ice cover drift. A drifting ice field has a certain kinetic energy that should be released when a collision occurs with an unmovable obstacle, and spent on brittle breakdown of a quantity of the ice field. The volume of formed small ice pieces (fragments of ice field) was estimated by comparison of the specific energy of the sea ice brittle destruction and the kinetic energy of the drifting ice field. The article presents the results of the estimation of the possible volume of the ice pieces and the scales of formed piles as a result of a collision with an obstacle, depending on the initial dimensions of the ice field and wind speed. Developed models and the results of computer modeling can be used to estimate the ice pile sizes near the stationary platforms and terminals on the Arctic seas.

Ocean–sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent relatively well. However, the ensemble can not be used to get a robust estimate of recent trends in the Arctic sea ice volume. Biases in the reanalyses certainly impact the simulated air–sea fluxes in the polar regions, and questions the suitability of current sea ice reanalyses to initialize seasonal forecasts.

The current GFDL seasonal prediction system, the Seamless System for Prediction and Earth System Research (SPEAR), has shown skillful prediction of Arctic sea ice extent with atmosphere and ocean constrained by observations. In this study we present improvements in subseasonal and seasonal predictions of Arctic sea ice by directly assimilating sea ice observations. The sea ice initial conditions from a data assimilation (DA) system that assimilates satellite sea ice concentration (SIC) observations are used to produce a set of reforecast experiments (IceDA) starting from the first day of each month from 1992 to 2017. Our evaluation of daily sea ice extent prediction skill concludes that the SPEAR system generally outperforms the anomaly persistence forecast at lead times beyond 1 month. We primarily focus our analysis on daily gridcell-level sea ice fields. SIC DA improves prediction skill of SIC forecasts prominently in the June-, July-, August-, and September-initialized reforecasts. We evaluate two additional user-oriented metrics: the ice-free probability (IFP) and ice-free date (IFD). IFP is the probability of a grid cell experiencing ice-free conditions in a given year, and IFD is the first date on which a grid cell is ice free. A combined analysis of IFP and IFD demonstrates that the SPEAR model can make skillful predictions of local ice melt as early as May, with modest improvements from SIC DA.

Calving glaciers are highly sensitive to bedrock geometry near their terminus. To understand the mechanisms controlling rapid calving glaciers’ mass loss, we measured the lake topography in front of four lake-terminating glaciers in the southern Patagonian icefield. Using remotely sensed surface elevation data, we calculated flotation height and surface slope and compared those with changes in ice-front position, surface speed and surface elevation. Rapid retreat accompanied by rapid flow acceleration and ice surface steepening was observed at Glaciar Upsala from 2008–2011, and at O'Higgins and Viedma glaciers from 2016–present. Surface lowering in the lower part of Glaciar Upsala reached 30 m a−1 and was 18 m a−1 and 12 m a−1 at O'Higgins and Viedma glaciers, respectively. Near- or super-buoyant conditions were observed prior to these events, leading to gradual flow acceleration due to low effective pressure and decoupling from the bed. The super-buoyant condition and gradual acceleration imply full-thickness buoyant calving, which causes the ice front to retreat from the shallow bedrock topography with substantial flow acceleration. We conclude that the buoyancy force plays an important role in the rapid mass loss of lake-terminating glaciers in southern Patagonia.