Ice Growth Research Articles

On sea ice emission modeling for MOSAiC's L-band radiometric measurements

Abstract The retrieval of sea ice thickness using L-band passive remote sensing requires robust models for emission from sea ice. In this work, measurements obtained from surface-based radiometers during the MOSAiC expedition are assessed with the Burke, Wilheit and SMRT radiative transfer models. These models encompass distinct methodologies: radiative transfer with/without wave coherence effects, and with/without scattering. Before running these emission models, the sea ice growth is simulated using the Cumulative Freezing Degree Days (CFDD) model to further compute the evolution of the ice structure during each period. Ice coring profiles done near the instruments are used to obtain the initial state of the computation, along with Digital Thermistor Chain (DTC) data to derive the sea ice temperature during the analyzed periods. The results suggest that the coherent approach used in the Wilheit model results in a better agreement with the horizontal polarization of the in situ measured brightness temperature. The Burke and SMRT incoherent models offer a more robust fit for the vertical component. These models are almost equivalent since the scattering considered in SMRT can be safely neglected at this low frequency, but the Burke model misses an important contribution from the snow layer above sea ice. The results also suggest that a more realistic permittivity falls between the spheres and random needles formulations, with potential for refinement, particularly for L-band applications, through future field measurements.

Impact of ice growth on the physical and chemical properties of dense cloud cores

We investigated the effect of time-dependent ice growth on dust grains on the opacity and hence on the dust temperature in a collapsing molecular cloud core, with the aim of quantifying the effect of the dust temperature variations on ice abundances as well as the evolution of the collapse. To perform the simulations, we employed a one-dimensional collapse model that self-consistently and time-dependently combines hydrodynamics with chemical and radiative transfer simulations. The dust opacity was updated on the fly based on the ice growth as a function of the location in the core. The results of the fully dynamical model were compared against simulations run with different values of fixed ice thickness. We found that the ice thickness increases quickly and reaches a saturation value (as a result of a balance between adsorption and desorption) of approximately 90 monolayers in the central core (volume density ~104 cm−3), and several tens of monolayers at a volume density of ~103 cm−3, after only a few 105 yr of evolution. The results thus exclude the adoption of thin (approximately ten monolayer) ices in molecular cloud simulations except at very short timescales. However, the differences in abundances and the dust temperature between the fully dynamic simulation and those with a fixed dust opacity are small; abundances change between the solutions generally within a factor of two only. The assumptions on the dust opacity do have an effect on the collapse dynamics through the influence of the photoelectric effect on the gas temperature, and the simulations take a different time to reach a common central density. This effect is, however, small as well. In conclusion, carrying out chemical simulations using a dust temperature corresponding to a fixed opacity seems to be a good approximation. Still, although at least in the present case its effect on the overall results is limited – as long as the grains are monodisperse – ice growth should be considered to obtain the most accurate representation of the collapse dynamics. We have found in a previous work that considering a grain size distribution leads to a complicated ice composition that depends on the grain size nonlinearly. With this in mind, we will carry out a follow-up study where the influence of the grain size on the present simulation setup is investigated.

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.

Structural investigation, computational analysis, and theoretical cryoprotectant approach of antifreeze protein type IV mutants.

Antifreeze proteins (AFPs) have unique features to sustain life in sub-zero environments due to ice recrystallization inhibition (IRI) and thermal hysteresis (TH). AFPs are in demand as agents in cryopreservation, but some antifreeze proteins have low levels of activity. This research aims to improve the cryopreservation activity of an AFPIV. In this in silico study, the helical peptide afp1m from an Antarctic yeast AFP was modeled into a sculpin AFPIV, to replace each of its four α-helices in turn, using various computational tools. Additionally, a new linker between the first two helices of AFPIV was designed, based on a flounder AFPI, to boost the ice interaction activity of the mutants. Bioinformatics tools such as ExPASy Prot-Param, Pep-Wheel, SOPMA, GOR IV, Swiss-Model, Phyre2, MODFOLD, MolPropity, and ProQ were used to validate and analyze the structural and functional properties of the model proteins. Furthermore, to evaluate the AFP/ice interaction, molecular dynamics (MD) simulations were executed for 20, 100, and 500 ns at various temperatures using GROMACS software. The primary, secondary, and 3D modeling analysis showed the best model for a redesigned antifreeze protein (AFP1mb, with afp1m in place of the fourth AFPIV helix) with a QMEAN (Swiss-Model) Z score value of 0.36, a confidence of 99.5%, a coverage score of 22%, and a p value of 0.01. The results of the MD simulations illustrated that AFP1mb had more rigidity and better ice interactions as a potential cryoprotectant than the other models; it also displayed enhanced activity in limiting ice growth at different temperatures.

Modeling of Supercooled Large Droplet Physics in Aircraft Icing

This paper aims to investigate phenomena that are related to SLD conditions in aircraft icing including gravity, non-spherical droplets, droplet breakup and droplet splash using an in-house computational tool. The in-house computational tool involves four modules for the computation of the flow field, droplet trajectories, convective heat transfer coefficients and ice growth rates. Droplet trajectories are computed using the Lagrangian approach, while ice growth rates are calculated using the Extended Messinger Model. In order to extend the capabilities of the computational tool to include SLD-related phenomena, empirical models that represent SLD physics are implemented. An extensive study has been performed using MS317 and NACA0012 airfoils, that aims to bring out the relative importance of the SLD-related phenomena, particularly on water catch rates and ice formation. The results of the study pointed to some important new conclusions that may shed further light on SLD physics. For example, multiple droplet breakup has been observed under certain conditions and droplet breakup emerged as a more important effect than previously reported. It was also seen that droplet splash influences both the energy balance and the mass balance in the icing process, which has been shown to have an important effect on the final ice shape, especially for very large droplets.

Globular Antifreeze Protein-Inspired Nanoparticle-Based Large-Scale T-Cell Cryoprotection System for Lymphoma Immunotherapy.

Large-scale biosafe T-cell cryopreservation is required to bring T-cell therapies to the market, but it remains challenging due to the cytotoxicity of common cryoprotectants [e.g., dimethyl sulfoxide (DMSO)] and unavoidable ice injuries to cells. Herein, inspired by natural globular antifreeze proteins, we establish a biocompatible zwitterionic magnetic nanoparticle (ZMNP)-based cryoprotection system, achieving large-scale cryopreservation of T cells for lymphoma immunotherapy. ZMNPs could form a globular hydration shell to inhibit water molecule aggregation as well as ice growth, and the surficial hydration strength-antifreeze performance relationship of ZMNPs was investigated. During the thawing process, ZMNPs possessed a magnetic field-mediated nanowarming property that enabled rapid heating and also facilitated easy magnetic separation for cell recovery. These combined effects resulted in a high post-thaw viability (>80%) of large-scale T-cell cryopreservation (20 mL). Notably, post-thaw T cells exhibited similar transcript profiles to fresh cells, while up- or downregulation of 1050 genes was found in the DMSO group. In a mouse E.G7-OVA lymphoma model, ZMNP-system-cryopreserved T cells achieved a tumor suppression rate of 77.5%, twice as high as the DMSO group. This work holds great promise for the application of advanced cryopreservation techniques in the development of therapeutic cellular products.

Mechanisms, Applications, and Challenges of Utilizing Nanomaterials in Cryopreservation

Cryopreservation of biological samples, including cells, tissues, and organs, has become an essential component in various biomedical research and applications, such as cellular therapy, tissue engineering, organ transplantation, and conservation of endangered species. However, it faces critical challenges throughout the cryopreservation process, such as loading/unloading of cryoprotective agent (CPA), ice inhibition during cooling, and ultrafast and uniform heating during rewarming. Applying nanomaterials in cryopreservation has emerged as a promising solution to address these challenges in each step due to their unique properties. For instance, in order to deliver nonpermeating CPA into cells, some nanomaterials, such as polymeric nanocapsule, can carry nonpermeating CPA to penetrate into the cells, regulating the intracellular ice crystal. During cooling, some nanomaterials, such as graphene oxide, can bind to basal or prism planes of ice crystals, suppressing the ice growth. During rewarming, some nanomaterials, such as magnetic nanoparticles, can improve the heating performance, preventing devitrification and recrystallization during rewarming. However, challenges in nanomaterials‐assisted cryopreservation remain, including the need for comprehensive studies on nanomaterials toxicity and the development of scalable manufacturing processes for industrial applications. This review examines the role of nanomaterials in cryopreservation, focusing on their mechanisms, applications, and associated challenges.

Data-driven discovery of potent small molecule ice recrystallisation inhibitors

Controlling the formation and growth of ice is essential to successfully cryopreserve cells, tissues and biologics. Current efforts to identify materials capable of modulating ice growth are guided by iterative changes and human intuition, with a major focus on proteins and polymers. With limited data, the discovery pipeline is constrained by a poor understanding of the mechanisms and the underlying structure-activity relationships. In this work, this barrier is overcome by constructing machine learning models capable of predicting the ice recrystallisation inhibition activity of small molecules. We generate a new dataset via experimental measurements of ice growth, then harness predictive models combining state-of-the-art descriptors with domain-specific features derived from molecular simulations. The models accurately identify potent small molecule ice recrystallisation inhibitors within a commercial compound library. Identified hits can also mitigate cellular damage during transient warming events in cryopreserved red blood cells, demonstrating how data-driven approaches can be used to discover innovative cryoprotectants and enable next-generation cryopreservation solutions for the cold chain.

Inverse Relationship Between Ice Nucleation and Ice Growth Rates in Frozen Foods

Inverse Relationship Between Ice Nucleation and Ice Growth Rates in Frozen Foods

Repurposing weather modification for cloud research showcased by ice crystal growth.

The representation of cloud processes in models is one of the largest sources of uncertainty in weather forecast and climate projections. While laboratory settings offer controlled conditions for studying cloud processes, they cannot reproduce the full range of conditions and interactions present in natural cloud systems. To bridge this gap, here we leverage weather modification, specifically glaciogenic cloud seeding, to investigate ice growth rates within natural clouds. Seeding experiments were conducted in supercooled stratus clouds (at to C) using an uncrewed aerial vehicle, and the created ice crystals were measured 4-10 min downwind by in situ and ground-based remote sensing instrumentation. We observed substantial variability in ice crystal growth rates within natural clouds, attributed to variations in ice crystal number concentrations and in the supersaturation, which is difficult to reproduce in the laboratory and which implies faster precipitation initiation than previously thought. We found that for the experiments conducted at C, the ice crystal populations grew nearly linearly during the time interval from 6 to 10 min. Our results demonstrate that the targeted use of weather modification techniques can be employed for fundamental cloud research (e.g. ice growth processes, aerosol-cloud interactions), helping to advance cloud microphysics parameterizations and to improve weather forecasts and climate projections.

Temporal Evolution of Gaseous Mercury Across the Sea Ice‐Seawater Interface: A Mesocosm Study

AbstractIn the marine cryosphere, seasonal sea ice dynamics affect the behavior of gaseous mercury, yet the mechanism remains poorly understood. By carrying out an outdoor sea ice mesocosm study, we examine primarily the abiotic factors influencing mercury dynamics and show distinct behaviors of gaseous mercury across the sea ice‐seawater interface over the full growth‐melt cycle. The distribution of gaseous mercury in sea ice is influenced by entrapment of gaseous mercury from different sources into sea ice of different textures, transport schemes within sea ice, and in situ cryo‐processes that affect mercury speciation. In the growing sea ice sections where solar radiation penetrated, production of gaseous mercury was observed, supporting the occurrence of in‐ice cryo‐photoreduction of divalent mercury. In under‐ice seawater, concentrations of dissolved gaseous mercury decreased gradually during ice growth and increased rapidly to pre‐freezing levels as ice started to melt, suggesting that the atmosphere‐sea ice‐seawater exchange pathway of gaseous mercury could be re‐established through melting first‐year sea ice. Our results from this unique mesocosm study provide new insights on the dynamics of gaseous mercury in and around sea ice that are primarily driven by abiotic processes, assisting model parameterizations for mercury cycling in polar regions.

Winter Targeted Observing Periods during the Year of Polar Prediction in the Southern Hemisphere (YOPP-SH)

Abstract The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven targeted observing periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5–10-day duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed-phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high-time-resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The Sea Ice Prediction Network South (SIPN South) analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase.

Antifreeze Protein Activity: From Ice Binding to Ice Growth Inhibition

Antifreeze Protein Activity: From Ice Binding to Ice Growth Inhibition

Dehydration drives damage in the freezing of brittle hydrogels.

It is widely known that freezing breaks soft, wet materials. However, the mechanism underlying this damage is still not clear. To understand this process, we freeze model, brittle hydrogel samples, while observing the growth of ice-filled cracks that break these apart. We show that damage is not caused by the expansion of water upon freezing or the growth of ice-filled cavities in the hydrogel that exert pressure on the surrounding material. Instead, local ice growth dehydrates the adjacent hydrogel, leading to drying-induced fracture. This dehydration is driven by the process of cryosuction, whereby undercooled ice sucks nearby water toward itself, feeding ice growth. Our results highlight the strong analogy between freezing damage and desiccation cracking, which we anticipate being useful for developing an understanding of both topics. Our results should also give useful insights into a wide range of freezing processes, including cryopreservation, food science, and frost heave.

Phase Transition of Cubic Ice to Hexagonal Ice during Growth and Decomposition.

Ice, one of the most enigmatic materials on Earth, exhibits diverse polymorphism, with research mainly focusing on the most commonly observed phases: hexagonal ice (Ih), cubic ice (Ic), and stacking-disordered ice (Isd). While their formation or structural changes are crucial for advancements in cloud science, climate modeling, and cryogenic technology, the molecular mechanisms driving these phenomena remain unexplored. Herein, utilizing cryogenic transmission electron microscopy, we investigate the formation of ice at two different temperatures, demonstrating a size-dependent phase shift from Ic to Isd. Furthermore, a relatively metastable cubic phase in Isd transitions to a hexagonal phase under electron beam radiation. This transition, facilitated by crystal defects, contrasts with perfect crystalline Ic, which maintains its original phase, emphasizing the importance of defects in polymorphic phase transitions. Our findings provide novel insights on phase control during the ice growth processes and polymorphic phase transitions from the cubic-to-hexagonal phases.

Investigation of anchor ice evolution in rivers and the impact of hydrometeorological conditions

The evolution of anchor ice during river freeze-up is known to significantly influence sediment transport, fish habitats, and river hydrology during winter. It may also lead to the formation of anchor ice dams and the generation of anchor ice waves that can cause flooding. Many of the previous field studies of anchor ice focused on the conditions leading to its formation and release, its crystal structure and properties, and the evaluation of its impacts. However, direct measurements of the temporal variation of anchor ice in rivers are rare, which has limited our understanding of this important and dynamic ice form. In this study, six anchor ice events were measured on two Canadian rivers using an underwater camera system, accompanied by comprehensive measurements of weather and hydraulic data and frazil ice concentrations. The temporal evolution of anchor ice was observed to occur in one of three stages: growth, stable, or decay. The direction (i.e., upward or downward) and trend of the net air–water heat flux reliably indicated the timing of these three stages. Anchor ice growth in the majority of events was through a combination of frazil accretion and in-situ crystal growth, resulting in event-averaged growth rates from 0.48 to 1.77 cm/h. Anchor ice grew solely through frazil accretion when snowfall occurred, with event-averaged growth rates from 1.64 to 3.53 cm/h. Anchor ice decay occurred through the thermal thinning of accumulations at an average decay rate of −0.48 to −2.52 cm/h. Anchor ice release was controlled by thermal factors and always occurred after the end of supercooling. Frazil accretion rates were estimated using measurements of anchor ice growth rates and suspended frazil concentrations and ranged from 2.6 × 10−3 to 6.0 × 10−3 m/s.

Assessing the Environmental Impact of Aircraft/Engine Integration with Respect to Contrails

Abstract In recent years, the radiative forcing of aircraft contrails and aircraft-induced contrail cirrus have been highlighted as a serious short-term climate impact of the aviation industry. Greater understanding of factors influencing contrail properties are required if routes to mitigation are to be explored. In the current work, a parametric turbofan powered aircraft model has been created to study the impact that aircraft design, in particular the interaction between the jet and wingtip vortex, can have on ice crystal formation, growth, and dynamics within a contrail. To investigate this, a contrail microphysics module has been developed and integrated within Rolls-Royce in-house Hydra CFD code. Three-dimensional Reynolds-Averaged Navier-Stokes simulations are conducted over the jet and early vortex regime, covering an area which is often simplified in most contrail modelling approaches. It is found that the position of the engine along the wing of an aircraft can impact the formation of the wingtip vortex, altering the contrail properties and distribution downstream of the aircraft. The effect of multi-engine architecture is also assessed and shown to influence the magnitude of exhaust entrainment into the vortex.

Synergistic atmosphere-ocean-ice influences have driven the 2023 all-time Antarctic sea-ice record low

Antarctic sea ice extent (SIE) reached a new record low in February 2023. Here we examine the evolution of the coupled ocean-atmosphere-sea ice system during the 12 months preceding the record. The impact of preceding conditions is assessed with observations, reanalyses, and output from the regional ocean-sea ice coupled model NEMO3.6-LIM3. We find that the 2022-2023 sea ice annual cycle was characterized by consistently low SIE throughout the year, anomalously rapid sea ice retreat in December 2022, and nearly circumpolar negative SIE anomalies in February 2023. While advection-induced positive air temperature anomalies inhibited the sea ice growth in most regions, strong southerly winds in the Amundsen-Ross Sea caused by an anomalously deep Amundsen Sea Low in spring transported notable volumes of sea ice northward, triggering an unusually active ice-albedo feedback onshore and favoring accelerated melt towards the minimum. This study highlights the impacts of multifactorial processes during the preceding seasons to explain the recent summer sea ice minima.

Icings as sentinels and modifiers of water flow through winter landscapes: An exploration of physico‐chemical processes on the lake‐dominated, discontinuous permafrost Taiga Shield

AbstractThe winter hydrological period is in transition across the Canadian subarctic, as climate warming is shifting precipitation regimes, thawing permafrost, and altering active layer dynamics, and thus increasing the overall amount, and variability, of winter streamflow. Effects of these changes are poorly understood on the Taiga Shield, which comprises ~20% of North America's permafrost‐covered area, and is characterized by a unique ‘fill‐and‐spill’ hydrology whereby runoff generation requires the exceedance of lake basin storage thresholds. Here, we assessed lake hydrostatic levels and used trail camera images of icings, which are sheet‐like masses of layered ice that are common manifestations of wintertime flow on the Taiga Shield, to understand landscape controls on winter water movement in this region. We further used paired geochemical measurements to explore how source water characteristics affect icing chemistry, and the degree to which icings may modify the chemical composition of active winter flow. We undertake this work over 2 years, and across watersheds of different sizes and lake basin characteristics. We show that icing growth is driven by hydroclimatic controls that include fill‐and‐spill hydrologic constraints and winter air temperatures, and that pre‐freshet pulses of water flow are common within this landscape. Across winters with variable antecedent precipitation levels, a larger catchment was able to support icing growth via continued runoff generation, while small catchments were not. Icings were often chemically dilute compared with source waters, indicating that solute exclusion may actively enrich geochemical concentrations in flowing water. Across icings, chemical variation appeared related to source water type (groundwater versus lake; lake size) and apparent redox conditions. These results highlight that streamwater hydrology and biogeochemistry can be dynamic during the understudied winter period, and illustrate that icings may alter the composition of wintertime flow as it moves through fluvial networks.

ICESat-2 Shows Sea Ice Leads Have Little Overall Effects on the Arctic Cloudiness in Cold Months

Abstract The effect of leads in Arctic sea ice on clouds is a potentially important climate feedback. We use observations of clouds and leads from the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) to study the effects of leads on clouds. Both leads and clouds are strongly forced by synoptic weather conditions, with more clouds over both leads and sea ice at lower sea level pressure. Contrary to previous studies, we find that the overall lead effect on low-level cloud cover is −0.02, a weak cloud dissipating effect in cold months, after the synoptic forcing influence is removed. This is due to compensating contributions from the cloud dissipating effect by newly frozen leads under high pressure systems and the cloud enhancing effect by newly open leads under low pressure system. The lack of proper representation of lead effect on clouds in current climate models and reanalyses may impact their performance in winter months, such as in sea ice growth and Arctic cyclone development.