Extreme Ice Research Articles

On the safety threshold of trains running on Sichuan-Tibet Railway bridges under the influence of floating ice

To investigate the running safety threshold of trains on the Sichuan-Tibet Railway bridges under the floating ice impact loads, a train-track-bridge dynamics model is established based on the theory of the train-track-bridge dynamic interaction and the design method of tuned mass damper (TMD), which uses the fluid-structure coupling method to calculate the floating ice impact loads. Taking a 5 × 32 m typical simply-supported beam bridge on the Sichuan-Tibet Railway as an example, the critical train speeds corresponding to floating ice impact loads of varying intensity are evaluated, and the effect of TMD on the running safety of the trains under extreme ice loads is investigated. The results show that the fluid effect has a significant influence on the impact loads of ice hitting the bridge pier, which cannot be ignored in the calculation. The ice impact intensities significantly reduce the train's safe speeds. Under the action of floating ice impact loads, the TMD attached to the bridge can effectively reduce the train's derailment factor and wheel unloading rate. The greater the TMD mass ratio, the more pronounced the vibration control effect.

Understanding the Forecast Skill of Rapid Arctic Sea Ice Loss on Subseasonal Time Scales

Abstract The predictability of sea ice during extreme sea ice loss events on subseasonal (daily to weekly) time scales is explored in dynamical forecast models. These extreme sea ice loss events (defined as the 5th percentile of the 5-day change in sea ice extent) exhibit substantial regional and seasonal variability; in the central Arctic Ocean basin, most subseasonal rapid ice loss occurs in the summer, but in the marginal seas rapid sea ice loss occurs year-round. Dynamical forecast models are largely able to capture the seasonality of these extreme sea ice loss events. In most regions in the summertime, sea ice forecast skill is lower on extreme sea ice loss days than on nonextreme days, despite evidence that links these extreme events to large-scale atmospheric patterns; in the wintertime, the difference between extreme and nonextreme days is less pronounced. In a damped anomaly forecast benchmark estimate, the forecast error remains high following extreme sea ice loss events and does not return to typical error levels for many weeks; this signal is less robust in the dynamical forecast models but still present. Overall, these results suggest that sea ice forecast skill is generally lower during and after extreme sea ice loss events and also that, while dynamical forecast models are capable of simulating extreme sea ice loss events with similar characteristics to what we observe, forecast skill from dynamical models is limited by biases in mean state and variability and errors in the initialization. Significance Statement We studied weather model forecasts of changes in Arctic sea ice extent on day-to-day time scales in different regions and seasons. We were especially interested in extreme sea ice loss days, or days in which sea ice melts very quickly or is reduced due to diverging forces such as winds, ocean currents, and waves. We find that forecast models generally capture the observed timing of extreme sea ice loss days. We also find that forecasts of sea ice extent are worse on extreme sea ice loss days compared to typical days, and that forecast errors remain elevated following extreme sea ice loss events.

A Comparison of Factors That Led to the Extreme Sea Ice Minima in the Twenty-First Century in the Arctic Ocean

Abstract The extreme Arctic sea ice minima in the twenty-first century have been attributed to multiple factors, such as anomalous atmospheric circulation, excess solar radiation absorbed by open ocean, and thinning sea ice in a warming world. Most likely it is the combination of these factors that drives the extreme sea ice minima, but how the factors rank in setting the conditions for these events has not been quantified. To address this question, the sea ice budget of an Arctic regional sea ice–ocean model forced by atmospheric reanalysis data is analyzed to assess the development of the observed sea ice minima. Results show that the ice area difference in the years 2012, 2019, and 2007 is driven to over 60% by the difference in summertime sea ice area loss due to air–ocean heat flux over open water. Other contributions are small. For the years 2012 and 2020 the situation is different and more complex. The air–ice heat flux causes more sea ice area loss in summer 2020 than in 2012 due to warmer air temperatures, but this difference in sea ice area loss is compensated by reduced advective sea ice loss out of the Arctic Ocean mainly caused by the relaxation of the Arctic dipole. The difference in open water area in early August leads to different air–ocean heat fluxes, which distinguishes the sea ice minima in 2012 and 2020. Further, sensitivity experiments indicate that both the atmospheric circulation associated with the Arctic dipole and extreme storms are essential conditions for a new low record of sea ice extent.

Characteristics of Arctic Summer Inversion and Its Correlation with Extreme Sea Ice Anomalies

Low tropospheric temperature inversion is very common in the Arctic region. Based on the hyperspectral Atmospheric Infrared Sounder (AIRS) profiles from 2002 to 2020, this study provides a comprehensive analysis of the characteristics and anomalies for low tropospheric inversions in the entire Arctic, especially during the summer period. Three types of inversion are classified here, representing the inversions under the clear-sky condition (“clear” inversion), under the cloudy condition with clouds under the inversion layer top (“cloud-I” inversion), and without clouds under the inversion layer top (“cloud-II” inversion). Obvious seasonality is revealed in these three types of inversion, which is stronger in winter than in summer, as per previous studies. We further found that a “summer” peak of inversions occurs in the Arctic, notably in July. Averaged over the study region (60−90° N, 180° W−180° E), the frequencies of “cloud-I” and “cloud-II” inversions peak in July with values of about 22.1% and 34.6%, respectively. Moreover, the three inversion types all display a small “July” peak of inversion strength, ranging from 2.14 to 3.19 K. The result reveals that when the frequency and strength of summer inversions are both with high positive anomalies, there would be a drop in sea ice concentration in September. This implied that the high positive anomalies, both in inversion frequency and strength in summer, might be a predicted signal for the extreme low sea ice event in September. It is also noted that during the extreme low sea ice events in 2007 and 2020, the summer inversion has a strong positive anomaly. However, the summer inversion in 2012, when the sea ice extent also broke the low record, was not extreme as in 2007 and 2020. Further study needs to be supported by follow-up models and observations to evaluate the impact of the inversions on the sea ice.

Dynamic Simulation of Power Systems Considering Transmission Lines Icing and Insulators Flashover in Extreme Weather

Global climate deterioration caused by excessive carbon emissions poses a severe threat to the stable operation of power systems. In extreme snow and ice weather, complex faults, such as ice-covered line breakage and insulator flashover, may be triggered. Hybrid simulations to reveal the influence mechanism and dynamic interaction process between extreme weather and power systems have become a research focus. Relationship models between meteorological conditions and grid failure were constructed in ice accretion and insulator flashover scenarios. Based on the above two models, a multi-variable and multi-time scale hybrid simulation of the meteorological process and power system, considering line icing and insulator flashover, was realized. An example was provided to verify the feasibility of the proposed simulation scheme.

A goal-based approach for selecting a ship's polar class

Following the International Code for Ships Operating in Polar Waters (Polar Code), ships operating in ice-covered polar waters must comply with an appropriate Polar Class (PC) or equivalent ice class standard. For the selection of an appropriate Polar Class, ship designers and operators are encouraged to use the Polar Operational Limit Assessment Risk Indexing System (POLARIS). A limitation of POLARIS is that it does not consider the extent to which a ship operates in various ice conditions, and thus also not the probabilistic nature of ice loading. To address this limitation, this article outlines a goal-based approach that is intended to complement POLARIS when selecting a ship's Polar Class. Following the proposed approach, the appropriateness of a ship's minimum required Polar Class as determined using POLARIS is evaluated by assessing the ship's long-term extreme ice loads, and by relating these to the design loads behind the considered Polar Class standard. To account for the probabilistic nature of ice loading, the approach calculates a ship's long-term extreme ice loads considering its intended operating profile and expected ice exposure. This is achieved by synthesising a modified version of the so-called event-maximum method, discrete-event simulations, and satellite ice data. The utility of the proposed approach is demonstrated through a case study, in which it is used as a complement to POLARIS to select an appropriate Polar Class for a double-acting ship intended for year-round independent operations along the northeast coast of Canada.

Molecular dating of the blood pigment hemocyanin provides new insight into the origin of animals.

The Neoproterozoic included changes in oceanic redox conditions, the configuration of continents and climate, extreme ice ages (Sturtian and Marinoan), and the rise of complex life forms. A much-debated topic in geobiology concerns the influence of atmospheric oxygenation on Earth and the origin and diversification of animal lineages, with the most widely popularized hypotheses relying on causal links between oxygen levels and the rise of animals. The vast majority of extant animals use aerobic metabolism for growth and homeostasis; hence, the binding and transportation of oxygen represent a vital physiological task. Considering the blood pigment hemocyanin (Hc) is present in sponges and ctenophores, and likely to be present in the common ancestor of animals, we investigated the evolution and date of Hc emergence using bioinformatics approaches on both transcriptomic and genomic data. Bayesian molecular dating suggested that the ancestral animal Hc gene arose approximately 881Ma during the Tonian Period (1000-720Ma), prior to the extreme glaciation events of the Cryogenian Period (720-635Ma). This result is corroborated by a recently discovered fossil of a putative sponge ~890Ma and modern molecular dating for the origin of metazoans of ~1,000-650Ma (but does contradict previous inferences regarding the origin of Hc ~700-600Ma). Our data reveal that crown-group animals already possessed hemocyanin-like blood pigments, which may have enhanced the oxygen-carrying capacity of these animals in hypoxic environments at that time or acted in the transport of hormones, detoxification of heavy metals, and immunity pathways.

The contribution of melt ponds to enhanced Arctic sea-ice melt during the Last Interglacial

Abstract. The Hadley Centre Global Environment Model version 3 (HadGEM3) is the first coupled climate model to simulate an ice-free Arctic during the Last Interglacial (LIG), 127 000 years ago. This simulation appears to yield accurate Arctic surface temperatures during the summer season. Here, we investigate the causes and impacts of this extreme simulated ice loss. We find that the summer ice melt was predominantly driven by thermodynamic processes: atmospheric and ocean circulation changes did not significantly contribute to the ice loss. We demonstrate these thermodynamic processes were significantly impacted by melt ponds, which formed on average 8 d earlier during the LIG than during the pre-industrial control (PI) simulation. This relatively small difference significantly changed the LIG surface energy balance and impacted the albedo feedback. Compared to the PI simulation: in mid-June, of the absorbed flux at the surface over ice-covered cells (sea-ice concentration > 0.15), ponds accounted for 45 %–50 %, open water 35 %–45 %, and bare ice and snow 5 %–10 %. We show that the simulated ice loss led to large Arctic sea surface salinity and temperature changes. The sea surface temperature and salinity signals we identify here provide a means to verify, in marine observations, if and when an ice-free Arctic occurred during the LIG. Strong LIG correlations between spring melt pond and summer ice area indicate that, as Arctic ice continues to thin in future, the spring melt pond area will likely become an increasingly reliable predictor of the September sea-ice area. Finally, we note that models with explicitly modelled melt ponds seem to simulate particularly low LIG sea-ice area. These results show that models with explicit (as opposed to parameterised) melt ponds can simulate very different sea-ice behaviour under forcings other than the present day. This is of concern for future projections of sea-ice loss.

Prediction method for plastic dynamic response of hull plate subjected to ice floe impact

Objectives Polar ships are often subjected to ice floe impact during navigation, particularly, hull plates may suffer permanent plastic deformation under extreme ice impact loads, affecting the safety and working performance of the ship, and greatly increasing the maintenance costs. Therefore, it is necessary to propose a method to predict the dynamic plastic response of hull structure under ice floe impact loads. Methods This paper analyzes the energy sharing mechanism of ice-hull interaction based on the energy analysis method and rigid-plastic theoretical method to predict the plastic dynamic response of hull plates. An analytical formula for the dynamic response of a hull plate under ice floe impact is proposed, and comparisons between the analytical and numerical results are made. Results The comparisons show that the presented analytical method is reliable, this simplified theoretical analysis method can provide designers with rapid prediction regarding the maximal plastic deformation and collision force of a hull plate under ice floe impact. Conclusions The research has giving it great significance for engineering applications.

Seasonal Arctic sea ice forecasting with probabilistic deep learning

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss.

Physical model testing I for investigating the effects of managed ice-field characteristics on a dynamic positioning vessel

This paper presents details of an extensive physical model testing program for evaluating the performance of a dynamic positioning (DP) controlled vessel in different realistic managed ice environments. It describes the model vessel, the preparation of the ice-field, the procedure of the model tests, the methodologies of data analysis, and highlights of the measurements. A simplified generic drillship model at 1:40 scale was tested in multiple managed ice configurations. A total of 372 test runs were carried out in 17 ice sheets to evaluate the thruster forces and motion responses of the vessel in various ice conditions. The physical and mechanical characteristics of the ice-field were modelled by controlling ice concentration, thickness, floe size, flexural strength, and the ice drift speed and direction. The ice concentration ranged from a light condition (7/10th) to a heavy condition (9/10th+) with multiple ice floe sizes ranging between 25 m to 100 m. Also, multiple ice thicknesses ranging between 0.60 m to 2.0 m and multiple ice drift speeds (0.2 knots, 0.5 knots, and 1.2 knots) with various moderate to extreme ice drift angles were investigated. The thruster forces on the model vessel along the surge and sway directions and the yawing moment were measured. Besides, the vessel model's 6-DOF motions and accelerations were recorded. Multiple cameras were used to capture the global and local ice-structure interactions placed in different above-water locations. All reported values presented in the paper are in full-scale unless otherwise specified.The time series of thruster forces and yawing moments are presented along with the vessel's positioning capabilities in various managed ice conditions. Results and discussions on the effects of various managed ice-field parameters on the time-averaged thruster forces and moment are offered. Generally, the analysis reveals that each of the ice parameters under investigation had a moderate to strong effect on global thruster force in the surge direction. The measurements and the videos showed complex and highly stochastic ice-vessel-basin wall interactions and different ice failure modes. Overall, the DP system used in the testing demonstrated the vessel's capabilities in maintaining the station for the majority of test head-on test cases and the oblique ice tests not exceeding 10°. The program generated a large dataset and video recordings to evaluate and improve understanding of the dynamic ice-vessel interactions and provided sufficient information for developing novel ice force models for real-time applications.

Research on fault scenario prediction and resilience enhancement strategy of active distribution network under ice disaster

Active distribution network (ADN) will encounter severe large-scale blackouts under extreme ice disaster. Different from the passive resilience restoration method after the real fault occurs, an information entropy model-based resilience enhancement strategy is proposed in this paper, which is dedicated to enhancing resilience before failure occurs. The vulnerability rate model is used to improve the situational awareness of the power system under severe weather. Typical scenario selection model (TSSM) is proposed by information entropy. Proactive defense plan with network reconfiguration at its core is the key to resilience enhancement. Implementation of repair by matching resources and faults, which is a means of resilience enhancement after the disaster has ended. The proposed resilience evaluation model considers the impact of economic factors on resilience enhancement. Different strategies and different evaluation metrics are adopted to evaluate the performance of resilience enhancement. Finally, the practical and simulated disaster testings are acted on the simplified real grid system to verify the method proposed in this paper.

The Ice-resistant Performance Analysis of Cable Pipe for Offshore Booster Station

In order to verify the ice-resistant performance of offshore booster station and its cable pipe. Taking a wind farm in Bohai as an an example, the response of offshore booster station and its cable pipe under the condition of sea ice once in 100 years is analyzed by numerical simulation. The results show that the platform and its cable pipe of the booster station have certain anti ice performance, but under extreme ice load, the vibration response of the upper part of the platform is large, so the safety operation of the facilities and cable pipes should be protected.

Risk hedging strategies for electricity retailers using insurance and strangle weather derivatives

With the increase of extreme weather events and the penetration of distributed energy resources, electricity retailers will encounter more risks at both transmission and distribution levels during the business operation process. For risks at the transmission level, huge damages to the transmission lines and towers caused by extreme events, like bushfires, ice storms, and flooding, will lead to power shortage. For risks at the distribution level, demand variations in accordance with temperature change will result in energy procurement difficulty for the retailers. In this paper, besides the normal bilateral contract, the insurance, the strangle weather derivatives, and the energy storage system are implemented to hedge the risks at both the transmission and distribution levels. Simulation results show that the proposed model ensures higher profits for the retailers in summer and winter compared to the conventional model when there are no extreme events occurring. When there are extreme events in both summer and winter, the proposed model incurs lower reduction of profits than that of the conventional model. In brief, the overall profits of the retailer using the proposed hedging model are higher than the convention model, and the overall profit variation of the conventional model is about 26% higher than the proposed model. Furthermore, when the budget of the retailer is sufficient, all three hedging tools can be invested. Whereas when the budget of the retailer is limited, the investment order should be insurance the first, strangle weather derivatives the second, and energy storage system the third.

High‐Frequency Sea Ice Variability in Observations and Models

AbstractWe characterize high‐frequency variability of sea ice extent (HFVSIE) in observations and climate models. We find that HFVSIE in models is biased low with respect to observations, especially at synoptic timescales (<20 days) in the Arctic year‐round and at monthly timescales (30–60 days) in Antarctica in winter. Models show large spread in HFVSIE, especially in Antarctica. This spread is partly explained by sea ice mean‐state while model biases in sea level pressure (SLP) and wind variability do not appear to play a major role in HFVSIE spread. Extreme sea ice extent (SIE) changes are associated with SLP anomaly dipoles aligned with the sea ice edge and winds directed on‐ice (off‐ice) during SIE loss (gain) events. In observations, these events are also associated with distinct ocean wave states during the cold season, when waves are greater (smaller) and travel toward (away from) the sea ice edge during SIE loss (gain) events.

A Decommissioned Wind Blade as a Second-Life Construction Material for a Transmission Pole

This paper demonstrates the concept of adaptive repurposing of a portion of a decommissioned Clipper C96 wind turbine blade as a pole in a power transmission line application. The current research program is aimed at creating a path towards sustainable repurposing of wind turbine blades after they are removed from service. The present work includes modelling and analysis of expected load cases as prescribed in ASCE 74 and NESC using simplified boundary conditions for tangent pole applications. Load cases involving extreme wind, concurrent ice and wind, extreme ice, differential ice, broken conductor, and broken shield have been analyzed and governing load cases for bending, shear, and torsion have been examined. Relative stiffnesses of different parts forming the wind blade’s cross section (i.e., shell, web, and spar cap) are determined. The corresponding stresses associated with each part under the governing loads are compared to allowable strength values which are determined from composite laminate theory and modelling of the known laminate structure of the E-Glass FRP material. Stresses and deflections obtained are compared with governing reliability-based design criteria and code requirements. The results of the structural analysis indicate that the wind blade can resist the expected loads with reasonable safety factors and that the expected deflections are within permissible limits. Recommendations are provided for detailing and modification of the wind blade for a power pole application in which crossarm and davit connections are highlighted, and foundation details are emphasized.

Experimental investigation on the performance degradation of helicopter rotor due to ice accretion

Helicopter rotor performance can be significantly altered by ice accretion which directly degrades the handling qualities and safety during flight. To obtain understanding into the effect of ice accretion on a helicopter rotor in forward flight under different icing environments, an experimental campaign was conducted in an icing wind tunnel using a rotor model with diameter at 2 m. Research was emphasized on revealing effect of liquid water content and static temperature on the rotor performance degradation. The dynamic thrust and torque of the rotor were measured by a six-component balance. Ice shape of the airfoils at specific rotor blade spanwise locations was obtained through the ice cutting process; meanwhile, the entire ice topology on the blade was scanned by means of the three-dimensional scanning technique. Results showed that ice was mainly accreted on the leading edge and lower surface of the blade. The static temperature of a icing cloud has a noticeable effect on the regime of accreted ice. The ice formation was transparent glaze at −8°C and transformed to milky rime when changed the static temperature to −20°C. Comparing to rime ice, the glaze ice on the blade is more influential to the rotor performance degradation. Particular attention is given to the fact that under extreme icing conditions, over 30% degradation of transient rotor thrust was observed.

Role of Intense Arctic Storm in Accelerating Summer Sea Ice Melt: An In Situ Observational Study

AbstractIntense storms have been more frequently observed in the Arctic during recent years, in coincidence with extreme sea ice loss events. However, it is still not fully understood how storms drive such events due to deficient observations and modeling discrepancies. Here we address this problem by analyzing in situ observations acquired during an Arctic expedition, which uniquely captured an intense storm in summer 2016. The result shows a pronounced acceleration of sea ice loss during the storm process. Diagnostic analysis indicates a net energy loss at the ice surface, not supporting the accelerated melting. Although the open water surface gained net heat energy, it was insufficient to increase the mixed‐layer temperature to the observed values. Dynamic analysis suggests that storm‐driven increase in ocean mixing and upward Ekman pumping of the Pacific‐origin warm water tremendously increased oceanic heat flux. The thermal advection by the Ekman pumping led to a warmed mixed layer by 0.05°C–0.12°C and, in consequence, an increased basal sea ice melt rate by 0.1–1.7 cm day−1.

Extreme melt season ice layers reduce firn permeability across Greenland

Surface meltwater runoff dominates present-day mass loss from the Greenland Ice Sheet. In Greenland’s interior, porous firn can limit runoff by retaining meltwater unless perched low-permeability horizons, such as ice slabs, develop and restrict percolation. Recent observations suggest that such horizons might develop rapidly during extreme melt seasons. Here we present radar sounding evidence that an extensive near surface melt layer formed following the extreme melt season in 2012. This layer was still present in 2017 in regions up to 700 m higher in elevation and 160 km further inland than known ice slabs. We find that melt layer formation is driven by local, short-timescale thermal and hydrologic processes in addition to mean climate state. These melt layers reduce vertical percolation pathways, and, under appropriate firn temperature and surface melt conditions, encourage further ice aggregation at their horizon. Therefore, the frequency of extreme melt seasons relative to the rate at which pore space and cold content regenerates above the most recent melt layer may be a key determinant of the firn’s multi-year response to surface melt.

Key barriers to the commercial use of the Northern Sea Route: View from China with a fuzzy DEMATEL approach

The unprecedented reduction in the Arctic sea ice may lead to shipping shortcuts through the Arctic region. Among these, the Northern Sea Route (NSR) linking Europe and Asia has received wide attention because of its potential to save time and energy compared with the conventional southerly transit. However, limited by various factors, the NSR has not witnessed sustained commercial operation, that is, no shipping companies have started regular services there. By reviewing existing literature, we classify 10 factors that have influenced NSR development into four categories: natural conditions, commercial costs, service support, and political considerations. We evaluate the interdependent relationships among these factors through a fuzzy decision-making trial and evaluation laboratory model (DEMATEL), an effective approach in identifying the cause–effect chain in an uncertain and complex decision-making environment. The most critical elements restricting Arctic NSR development include extreme climate, political considerations, and sea ice condition based on expert inputs. This study discusses relations among these factors as well as their policy implications, which could contribute to the decision making of shipping companies and policy focus of the government.