Onset Of Freezing Research Articles

Role of Molecular Water Layer State on Freezing Front Propagation Rate and Mode Studied with Thermal Imaging.

In this work, we study the relationship between the molecular water layer (MWL) and frost freezing onset and propagation. The progression of frost has been reported to be governed by various localized icing phenomena, including interdroplet ice bridging, dry zones, and frost halos. Reports studying the state of water on surfaces have revealed the presence of a thin nanometer water layer on a range of surfaces. Regardless of further investigations that show environmental humidity, temperature, and surface energy to affect the thickness of the MWL on surfaces, the influence of the MWL on frost nucleation and propagation has not yet been previously addressed in the literature. To study the effect of the MWL on surface freezing events, a range of surface-functionalized glass substrates were prepared. In situ monitoring of freezing events with thermal imaging allowed studying the effect of surface chemistry and environmental relative humidity (RH) on the thickness and continuity of the MWL. We argue that the observed icing nucleation and propagation kinetics are directly related to the presence and continuity of the MWL, which can be manipulated by controlling the environmental humidity and surface chemistry.

Analysis of Heat Transfer of Molten Salts Startup Flow in Cold Pipes Avoiding Freezing in Solar and Nuclear Energy Systems

Abstract Molten salts are employed as the heat transfer fluid to carry the thermal energy from a solar receiver or a nuclear reactor for delivering to thermal storage systems or thermal power plants for power generation. For the startup operation, molten salts need to be pumped to flow into the pipes which may have lower temperature than the freezing point of molten salt due to the cold ambient temperature overnight or over the suspension of operation. Preventing the freezing of molten salt in cold pipes becomes a critical issue to the safe operation of a concentrating solar thermal power plant or a molten salt nuclear power plant. This study conducted a basic heat transfer analysis of the transient heat transfer from flowing molten salt to a cold pipe to determine the length from entrance to the onset of freezing of the fluid. From our modeling and analytical solution using method of characteristics, the correlation of the location of onset of freezing of molten salt with respect to the flow velocity, heat capacities of molten salt and pipes, dimension of the pipes, and the initial temperatures of salts and pipes, have been understood clearly. The modeling and computational tool can fundamentally help engineers to design a system to avoid freezing and clogging at cold startup when molten salt is applied as a heat transfer fluid.

Non-intrusive temperature measurements for transient freezing in laminar internal flow using laser induced fluorescence

This work presents two color LIF temperature measurements for the transient freezing in a square channel under laminar flow conditions. This is the first time non-intrusive temperature measurements were performed within the thermal boundary layer during the transient growth of an ice layer in internal flow. A combination of a local outlier factor algorithm and a smoothing operation was used to remove the top to bottom striations and reduce the other measurement noise. The temperature uncertainty in our measurements was between σ=0.3∘C and σ=0.5∘C. For the largest temperature difference between the bulk and the melting point of 14.6 °C, good results were obtained. As such, the current campaign demonstrates the potential of LIF as a non-intrusive temperature measurement technique for solid–liquid phase change experiments. However, some artefacts were present within the vicinity of the ice-layer due to the scattering of the laser light, especially near the inlet of the channel where the ice-layer is curved instead of flat. LIF measurements taken within a short time span prior to the onset of ice freezing showed approximately 2 °C of subcooling, consistent with previous findings. In addition, an anomalous behavior within the thermal boundary layer was observed, with a much smaller temperature gradient within the first few mm above the cold plate and a point of inflection in the temperature profile. The anomalous temperature behavior is possibly attributed to enhanced natural convection as a result of the subcooling at the cold plate surface.

Monitoring of Lake Ice Phenology Changes in Bosten Lake Based on Bayesian Change Detection Algorithm and Passive Microwave Remote Sensing (PMRS) Data.

Lake ice phenology (LIP), hiding information about lake energy and material exchange, serves as an important indicator of climate change. Utilizing an efficient technique to swiftly extract lake ice information is crucial in the field of lake ice research. The Bayesian ensemble change detection (BECD) algorithm stands out as a powerful tool, requiring no threshold compared to other algorithms and, instead, utilizing the probability of abrupt changes to detect positions. This method is predominantly employed by automatically extracting change points from time series data, showcasing its efficiency and accuracy, especially in revealing phenological and seasonal characteristics. This paper focuses on Bosten Lake (BL) and employs PMRS data in conjunction with the Bayesian change detection algorithm. It introduces an automated method for extracting LIP information based on the Bayesian change detection algorithm. In this study, the BECD algorithm was employed to extract lake ice phenology information from passive microwave remote sensing data on Bosten Lake. The reliability of the passive microwave remote sensing data was further investigated through cross-validation with MOD10A1 data. Additionally, the Mann-Kendall non-parametric test was applied to analyze the trends in lake ice phenology changes in Bosten Lake. Spatial variations were examined using MOD09GQ data. The results indicate: (1) The Bayesian change detection algorithm (BCDA), in conjunction with PMRS data, offers a high level of accuracy and reliability in extracting the lake ice freezing and thawing processes. It accurately captures the phenological parameters of BL's ice. (2) The average start date of lake ice freezing is in mid-December, lasting for about three months, and the start date of ice thawing is usually in mid-March. The freezing duration (FD) of lake ice is relatively short, shortening each year, while the thawing speed is faster. The stability of the lake ice complete ice cover duration is poor, averaging 84 days. (3) The dynamic evolution of BL ice is rapid and regionally distinct, with the lake center, southwest, and southeast regions being the earliest areas for ice formation and thawing, while the northwest coastal and Huang Shui Gou areas experience later ice formation. (4) Since 1978, BL's ice has exhibited noticeable trends: the onset of freezing, the commencement of thawing, complete thawing, and full freezing have progressively advanced in regard to dates. The periods of full ice coverage, ice presence, thawing, and freezing have all shown a tendency toward shorter durations. This study introduces an innovative method for LIP extraction, opening up new prospects for the study of lake ecosystem and strategy formulation, which is worthy of further exploration and application in other lakes and regions.

Sea ice heat and mass balance measurements from four autonomous buoys during the MOSAiC drift campaign

As part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), four autonomous seasonal ice mass balance buoys were deployed in first- and second-year ice. These buoys measured position, barometric pressure, snow depth, ice thickness, ice growth, surface melt, bottom melt, and vertical profiles of temperature from the air, through the snow and ice, and into the upper ocean. Observed air temperatures were similar at all four sites; however, snow–ice interface temperatures varied by as much as 10°C, primarily due to differences in snow depth. Observed winter ice growth rates (November to May) were <1 cm day−1, with summer melt rates (June to July) as large as 5 cm day−1. Air temperatures changed as much as 2°C hour−1 but were dampened to <0.3°C hour−1 at the snow–ice interface. Initial October ice thicknesses ranged from 0.3 m in first-year ice to 1.2 m in second-year ice. By February, this range was only 1.20–1.46 m, due in part to differences in the onset of basal freezing. In second-year ice, this delay was due to large brine-filled voids in the ice; propagating the cold front through this ice required freezing the brine. Mass balance results were similar to those measured by autonomous buoys deployed at the North Pole from 2000 to 2013. Winter average estimates of the ocean heat flux ranged from 0 to 3 W m−2, with a large increase in June 2020 as the floe moved into warmer water. Estimates of average snow thermal conductivity measured at two buoys during periods of linear temperature profiles were 0.41 and 0.42 W m−1 °C−1, higher than previously published estimates. Results from these ice mass balance buoys can contribute to efforts to close the MOSAiC heat budget.

Gas storage of peat in autumn and early winter in permafrost peatland

The carbon (C) balance of permafrost peatlands in autumn and winter, which affects the annual C budget estimation, has become a hotspot of studies on peatlands C cycle. This study combined the static chamber method, in situ soil profile measurements, and incubation experiments to investigate release and storage of C during autumn and early winter in a permafrost peatland in the Da Xing'an Mountains, Northeast China. Our results showed that the peak values of CH4 fluxes (30 August 2016) lagged behind those of CO2 fluxes (24 July 2016). At the onset of soil freezing, CH4 fluxes slightly increased, while CO2 fluxes decreased. During soil freezing in autumn, gases were found to be mainly stored in the soil as dissolved CH4 and CO2 and dissolved C concentrations (CH4, CO2, and DOC (dissolved organic carbon)) increased with depth. DOC concentrations were closely related to dissolved C gases, implying that the stored dissolved C gases might be derived from DOC decomposition. The CO2: CH4 ratio decreased sharply from the freezing of the surface layer to the total freezing of the soil, indicating larger CH4 storage in totally frozen soil. The incubation experiments also showed larger CH4 storage in the frozen soils and the stored C gases could influence the assessment of C emissions during thawing. These findings have important implications for clarifying the gas storage of permafrost peatland in autumn and early winter. The results may also clarify the key link of C emissions between the growing season and the nongrowing season.

Energy-efficient anti-icing performance of a hybrid superhydrophobic and electrothermal coating on metallic substrates

This paper reports the development of a hybrid anti-icing coating consisting of a thin-film electric heater and a superhydrophobic top coating. The coating was applied to a stainless steel substrate by a simple multi-layered spray coating process. The heating film consists of a layer of copper-based epoxy, insulated between layers of a polydimethylsiloxane (PDMS) elastomer. The heating film had a fast thermal response and showed excellent thermal stability at temperatures up to 100 °C. The SiO2-PDMS superhydrophobic top coating demonstrated an average static contact angle of 164° and hysteresis of 3° for water. The icephobic properties of the hybrid coating were investigated by a series of experiments conducted in a cold chamber. The hybrid coating reduced the ice adhesion strength by 83% and delayed the onset of droplet freezing when compared to the untreated substrate. Under continuous spray of 5 °C water at −20 °C chamber temperature, complete anti-icing of the hybrid coating was achieved with a minimum surface power density of 0.34 W/cm2. Water droplets rolled off the 45° inclined superhydrophobic surface before freezing, resulting in 37% less energy consumption for anti-icing. The superhydrophobic heating film has potential for industrial applications due to its simple fabrication process and energy-efficient anti-icing performance.

Temperature dependence of the viscoelastic properties of a natural gastropod mucus by Brillouin light scattering spectroscopy.

Brillouin spectroscopy was used to probe the viscoelastic properties of a natural gastropod mucus at GHz frequencies over the range -11 °C ≤ T ≤ 52 °C. Anomalies in the temperature dependence of mucus longitudinal acoustic mode peak parameters and associated viscoelastic properties at T = -2.5 °C, together with the appearance of a peak due to ice at this temperature, suggest that the mucus undergoes a phase transition from a viscous liquid state to one in which liquid mucus and solid ice phases coexist. Failure of this transition to proceed to completion even at -11 °C is attributed to glycoprotein-water interaction. The temperature dependence of the viscoelastic properties and the phase behaviour suggest that water molecules bind to glycoprotein at a temperature above the onset of freezing and that the reduced ability of this bound water to take on a configuration that facilitates freezing is responsible for the observed freezing point depression and gradual nature of the liquid-solid transition.

Estimation of the permafrost thickness of the New Siberia Island based on geothermal data and numerical modeling

The current ideas about the permafrost thickness on the New Siberia Island are very ambiguous both in terms of forming factors and in its magnitude (from 240 to 370 m), and in general are based on the assumption of the Pliocene beginning of rock freezing. In the last 20 years, new data have been obtained on the history of the region’s development in the Neopleistocene. They include the long existence of the New Siberia Island in marine conditions, which excluded the rocks freezing at that time, as well as the development of glaciation in the Middle Neopleistocene. These data indicate a significantly later onset of freezing of the island, which correlates with the nonstationarity of the temperature field of the frozen strata. The authenticity of the data is debated. The article is devoted to assessing the thickness of permafrost in accordance with three possible scenarios, allowing to take into account different points of view on the geological development of the region. The assessment is made using numerical modeling of the formation of frozen strata over the past 200 thousand years. One scenario includes the existence of glaciation during the Middle Neopleistocene, while in the other two it is absent. The last two scenarios differ in the stratigraphic schemes used. The reliability of the scenarios is assessed based on a comparison of the modeling results for each of them with geothermal data in a well on the island of New Siberia, obtained in the 1970s. The comparison results show that only the version with the existence of a glacier is consistent with the geothermal data. According to the data obtained, freezing of the island began under the glacier at the end of the Middle Neopleistocene, which existed in coastal-marine conditions. The most active increase in the frozen strata thickness dates back to the late Neopleistocene due to the drainage of the island. The obtained result is in agreement with new data on the age of the main geological bodies of the region, as well as with the idea of the glaciotectonic nature of dislocations in the Cretaceous - Middle Neopleistocene rocks.

Predicting the Onset of Freezing of Gait Using EEG Dynamics

Freezing of gait (FOG) severely incapacitates the mobility of patients with advanced Parkinson’s disease (PD). An accurate prediction of the onset of FOG could improve the quality of life for PD patients. However, it is imperative to distinguish the possibility of the onset of FOG from that of voluntary stopping. Our previous work demonstrated the neurological differences between the transition to FOG and voluntary stopping using electroencephalogram (EEG) signals. We employed a timed up-and-go (TUG) task to elicit FOG in PD patients. Some of these TUG tasks had an additional voluntary stopping component, where participants stopped walking based on verbal instruction to “stop”. The performance of the convolutional neural network (CNN) in identifying the transition to FOG from normal walking and the transition to voluntary stopping was explored. To the best of our knowledge, this work is the first study to propose a deep learning method to distinguish the transition to FOG from the transition to voluntary stop in PD patients. The models, trained on the EEG data from 17 PD patients who manifested FOG episodes, considering a short two-second transition window for FOG occurrence or voluntary stopping, achieved close to 75% classification accuracy in distinguishing transition to FOG from the transition to voluntary stopping or normal walking. Our results represent an important step toward advanced EEG-based cueing systems for smart FOG intervention, excluding the potential confounding of voluntary stopping.

A dataset of 10-year regional-scale soil moisture and soil temperature measurements at multiple depths on the Tibetan Plateau

Abstract. Soil moisture and soil temperature (SMST) are important state variables for quantifying the exchange of heat and water between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements are scarce on the Tibetan Plateau (TP), with even fewer are available for multiple soil depths. Tibet-Obs is such a long-term, regional-scale SMST observatory in the TP that has been established 10 years ago and includes three SMST monitoring networks, i.e. Maqu, Naqu, and Ngari (including Ali and Shiquanhe), located in the cold humid area covered by grassland, the cold semiarid area dominated by tundra, and the cold arid area dominated by desert, respectively. This paper presents a long-term (∼ 10 years) SMST profile dataset collected from the Tibet-Obs, which includes the original in situ measurements at a 15 min interval collected between 2008 and 2019 from all the three networks and the spatially upscaled data (SMups and STups) for the Maqu and Shiquanhe networks. The quality of the upscaled data is proved to be good, with errors that are generally better than the measured accuracy of adopted SMST sensors. Long-term analysis of the upscaled SMST profile data shows that the amplitudes of SMST variations decrease with increasing soil depth, and the deeper soil layers present a later onset of freezing and an earlier start of thawing and, thus, a shorter freeze–thaw duration in both the Maqu and Shiquanhe networks. In addition, there are notable differences between the relationships of SMups and STups under freezing conditions for the Maqu and Shiquanhe networks. No significant trend can be found for the SMups profile in the warm season (from May to October) for both networks that is consistent with the tendency of precipitation. A similar finding is also found for the STups profile and air temperature in the Shiquanhe network during the warm season. For the cold season (from November to April), a drying trend is noted for the SMups above 20 cm in the Maqu network, while no significant trend is found for those in the Shiquanhe network. Comparisons between the long-term upscaled data and five reanalysis datasets, including the ECMWF reanalysis v5 (ERA5), Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), Global Land Data Assimilation System version 2 Catchment Land Surface Model (GLDAS-2.1 CLSM), GLDAS-2.1 Noah, and GLDAS-2.1 variable infiltration capacity (GLDAS-2.1 VIC), indicate that none of the current model-based products can reproduce the seasonal variations and interannual trend changes in the measured SMST profile dynamics in both networks. All the products underestimate the STups at every depth, leading to an earlier onset of freezing and a later onset of thawing, which essentially demonstrates that the current models are not able to adequately simulate winter conditions on the TP. In short, the presented dataset would be valuable for evaluation and improvement in long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/20141567.v1 (Zhang et al., 2022).

Hemispherically lateralized rhythmic oscillations in the cingulate-amygdala circuit drive affective empathy in mice

Observational fear, a form of emotional contagion, is thought to be a basic form of affective empathy. However, the neural process engaged at the specific moment when socially acquired information provokes an emotional response remains elusive. Here, we show that reciprocal projections between the anterior cingulate cortex (ACC) and basolateral amygdala (BLA) in the right hemisphere are essential for observational fear, and 5-7Hz neural oscillations were selectively increased in those areas at the onset of observational freezing. A closed-loop disruption demonstrated the causal relationship between 5-7Hz oscillations in the cingulo-amygdala circuit and observational fear responses. The increase/decrease in theta power induced by optogenetic manipulation of the hippocampal theta rhythm bi-directionally modulated observational fear. Together, these results indicate that hippocampus-dependent 5-7Hz oscillations in the cingulo-amygdala circuit in the right hemisphere are the essential component of the cognitive process that drives empathic fear, but not freezing, in general.

Arrested Dynamics of Droplet Spreading on Ice.

We investigate the arrested spreading of room temperature droplets impacting flat ice. The use of an icy substrate eliminates the nucleation energy barrier, such that a freeze front can initiate as soon as the droplet's temperature cools down to 0 °C. We employ scaling analysis to rationalize distinct regimes of arrested hydrodynamics. For gently deposited droplets, capillary-inertial spreading is halted at the onset of contact line freezing, yielding a 1/7 scaling law for the arrested diameter. At low impact velocities (We≲100), inertial effects result in a 1/2 scaling law. At higher impact velocities (We>100), inertio-viscous spreading can spill over the frozen base of the droplet until its velocity matches that of a kinetic freeze front caused by local undercooling, resulting in a 1/5 scaling law.

Seasonality and timing of sea ice mass balance and heat fluxes in the Arctic transpolar drift during 2019–2020

Sea ice growth and decay are critical processes in the Arctic climate system, but comprehensive observations are very sparse. We analyzed data from 23 sea ice mass balance buoys (IMBs) deployed during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020 to investigate the seasonality and timing of sea ice thermodynamic mass balance in the Arctic Transpolar Drift. The data reveal four stages of the ice season: (I) onset of ice basal freezing, mid-October to November; (II) rapid ice growth, December–March; (III) slow ice growth, April–May; and (IV) melting, June onward. Ice basal growth ranged from 0.64 to 1.38 m at a rate of 0.004–0.006 m d–1, depending mainly on initial ice thickness. Compared to a buoy deployed close to the MOSAiC setup site in September 2012, total ice growth was about twice as high, due to the relatively thin initial ice thickness at the MOSAiC sites. Ice growth from the top, caused by surface flooding and subsequent snow-ice formation, was observed at two sites and likely linked to dynamic processes. Snow reached a maximum depth of 0.25 ± 0.08 m by May 2, 2020, and had melted completely by June 25, 2020. The relatively early onset of ice basal melt on June 7 (±10 d), 2019, can be partly attributed to the unusually rapid advection of the MOSAiC floes towards Fram Strait. The oceanic heat flux, calculated based on the heat balance at the ice bottom, was 2.8 ± 1.1 W m–2 in December–April, and increased gradually from May onward, reaching 10.0 ± 2.6 W m–2 by mid-June 2020. Subsequently, under-ice melt ponds formed at most sites in connection with increasing ice permeability. Our analysis provides crucial information on the Arctic sea ice mass balance for future studies related to MOSAiC and beyond.

Predicting the onset of freezing of gait in Parkinson’s disease

BackgroundFreezing of gait is a debilitating symptom of Parkinson’s disease associated with high risks of falls and poor quality of life. While productive therapy for FoG is still underway, early prediction of FoG could help high-risk PD patients to take preventive measures. In this study, we predicted the onset of FoG in de novo PD patients using a battery of risk factors from patients enrolled in PPMI cohort.MethodsBaseline characteristics were compared between subjects who developed FoG (68 patients, 37.2%, pre-FoG group) during the five-year follow up and subjects who did not (115 patients, 62.8%, non-FoG group). A multivariate logistic regression model was built based on backward stepwise selection of factors that were associated with FoG onset in the univariate analysis. ROC curves were used to assess sensitivity and specificity of the predictive model.ResultsAt baseline, age, PIGD score, cognitive functions, autonomic functions, sleep behavior, fatigue and striatal DAT uptake were significantly different in the pre-FoG group relative to the non-FoG group. However, there was no difference in genetic characteristics between the two patient sets. Univariate analysis showed several motor and non-motor factors that correlated with FoG, including PIGD score, MDS-UPDRS part II score, SDMT score, HVLT Immediate/Total Recall, MOCA, Epworth Sleepiness Scale, fatigue, SCOPA-AUT gastrointestinal score, SCOPA-AUT urinary score and CSF biomarker Abeta42. Multivariate logistic analysis stressed that high PIGD score, fatigue, worse SDMT performance and low levels of Abeta42 were independent risk factors for FoG onset in PD patients.ConclusionsCombining motor and non-motor features including PIGD score, poor cognitive functions and CSF Abeta can identify PD patients with high risk of FoG onset.

Chemical characteristics of freezing rain observed at Mount Heng in southern China

Freezing rain usually occurs when snow falls into an above-freezing layer aloft where it melts before reaching the sub-freezing surface as supercooled water. Although the occurrence of freezing rain is uncommon, it can produce extremely costly impacts. To date, field chemical observations of supercooled drops that form freezing rain are lacking. In this study, we collected 101 precipitation (freezing rain/rain/snow) samples on Mt. Heng in southern China for 7 years in the winters between 2015 and 2021. The winter precipitation collected at Mt. Heng was mostly acidic with pH values lower than 5. Acidity, contributed from NO3− and SO42−, was neutralized by NH4+ and Ca2+, indicating the additional contribution from organic acids. The major ions were NH4+, Ca2+, SO42− and NO3−, with concentrations of 135.7, 86.3, 72.5 and 61.8 μeq L−1, respectively. In general, the total ionic concentrations of freezing rain were, in comparison with mountain-based observations elsewhere, lower than those in cloud water but higher than those in rain. The higher concentrations of major ions in freezing rain would depress the freezing point of supercooled water drops and act to reduce the likelihood of freezing with effects increasing with concentration. This process would be countered by the presence of ice nuclei that is acting to freeze supercooled drops. These opposing processes complicate the understanding of the onset of freezing and consequently the occurrence of freezing rain. This study highlighted that additional model simulations and laboratory experiments are needed to validate the relationship between air pollution and freezing rain.

Kinetics of arsenic and antimony reduction and oxidation in peatlands treating mining-affected waters: Effects of microbes, temperature, and carbon substrate

Arsenic (As) and antimony (Sb) from mining-affected waters are efficiently removed in two treatment peatlands (TPs) in Northern Finland. However, the exact mechanisms behind this removal are not well resolved. Thus, the present study combines results from microcosm experiments and pilot-scale TPs on the effects of microbes, temperature, and carbon substrate to elucidate the role of peat microorganisms in As and Sb removal. The main As and Sb species in TP inflow water are arsenate and antimonate. In peat microcosms, they were quantitatively reduced, however, at rates about 20–400 times lower than previously reported from pure cultures, likely due to excess of other terminal electron acceptors, such as nitrate and sulfate. Addition of the microbial inhibitor sodium azide inhibited reduction, indicating that it is indeed microbially mediated. Arsenite and antimonite (re)oxidation, which is in situ likely limited to upper, oxic peat layers, was likewise observed in peat microcosms. Only for antimonite, oxidation also occurred abiotically, likely catalyzed by humic acids or metals. Process rates increased with increasing temperature, but all processes occurred also at low temperatures. Monitoring of pilot-scale TPs revealed only minor effects of winter conditions (i.e., low temperature and freezing) on arsenic and antimony removal. Formation of methylated oxyarsenates was observed to increase As mobility at the onset of freezing. From different carbon substrates tested, lactate slightly enhanced arsenate reduction and antimonate reduction was stimulated by acetate, lactate, and formate. However, a maximum rate enhancement of only 1.8 times indicates that carbon substrate availability is not the rate-limiting factor in microbial arsenate or antimonate reduction. The collective data indicate that microorganisms catalyze reduction and (re)oxidation of As and Sb species in the TPs, and even though temperature is a major factor controlling microbial As and Sb reduction/(re)oxidation, low inflow concentrations, long water residence times, and the presence of unfrozen peat in lower layers allow for efficient removal also under winter conditions.

Multi-thermals and high concentrations of secondary ice: a modelling study of convective clouds during the Ice in Clouds Experiment – Dust (ICE-D) campaign

Abstract. This paper examines the mechanisms responsible for the production of ice in convective clouds influenced by mineral dust. Observations were made in the Ice in Clouds Experiment – Dust (ICE-D) field campaign which took place in the vicinity of Cape Verde during August 2015. Measurements made with instruments on the Facility for Airborne Atmospheric Measurements (FAAM) aircraft through the clouds on 21 August showed that ice particles were observed in high concentrations at temperatures greater than about −8 ∘C. Sensitivity studies were performed using existing parameterization schemes in a cloud model to explore the impact of the freezing onset temperature, the efficiency of freezing, mineral dust as efficient ice nuclei, and multi-thermals on secondary ice production by the rime-splintering process. The simulation with the default Morrison microphysics scheme (Morrison et al., 2005) that involved a single thermal produced a concentration of secondary ice that was much lower than the observed value of total ice number concentration. Relaxing the onset temperature to a higher value, enhancing the freezing efficiency, or combinations of these increased the secondary ice particle concentration but not by a sufficient amount. Simulations that involved only dust particles as ice-nucleating particles produced a lower concentration of secondary ice particles, since the freezing onset temperature is low. The simulations implicate that a higher concentration of ice-nucleating particles with a higher freezing onset temperature may explain some of the observed high concentrations of secondary ice. However, a simulation with two thermals that used the original Morrison scheme without enhancement of the freezing efficiency or relaxation of the onset temperature produced the greatest concentration of secondary ice particles. It did so because of the increased time that graupel particles were exposed to significant cloud liquid water in the Hallett–Mossop temperature zone. The forward-facing camera and measurements of the vertical wind in repeated passes of the same cloud suggested that these tropical clouds contained multiple thermals. It is possible of course that several mechanisms, some of them only recently discovered, may be responsible for producing the ice particles in clouds. This study highlights the fact that the dynamics of the clouds likely play an important role in producing high concentrations of secondary ice particles in clouds.

Terrestrial or marine – indications towards the origin of ice-nucleating particles during melt season in the European Arctic up to 83.7° N

Abstract. Ice-nucleating particles (INPs) initiate the primary ice formation in clouds at temperatures above ca. −38 ∘C and have an impact on precipitation formation, cloud optical properties, and cloud persistence. Despite their roles in both weather and climate, INPs are not well characterized, especially in remote regions such as the Arctic. We present results from a ship-based campaign to the European Arctic during May to July 2017. We deployed a filter sampler and a continuous-flow diffusion chamber for offline and online INP analyses, respectively. We also investigated the ice nucleation properties of samples from different environmental compartments, i.e., the sea surface microlayer (SML), the bulk seawater (BSW), and fog water. Concentrations of INPs (NINP) in the air vary between 2 to 3 orders of magnitudes at any particular temperature and are, except for the temperatures above −10 ∘C and below −32 ∘C, lower than in midlatitudes. In these temperature ranges, INP concentrations are the same or even higher than in the midlatitudes. By heating of the filter samples to 95 ∘C for 1 h, we found a significant reduction in ice nucleation activity, i.e., indications that the INPs active at warmer temperatures are biogenic. At colder temperatures the INP population was likely dominated by mineral dust. The SML was found to be enriched in INPs compared to the BSW in almost all samples. The enrichment factor (EF) varied mostly between 1 and 10, but EFs as high as 94.97 were also observed. Filtration of the seawater samples with 0.2 µm syringe filters led to a significant reduction in ice activity, indicating the INPs are larger and/or are associated with particles larger than 0.2 µm. A closure study showed that aerosolization of SML and/or seawater alone cannot explain the observed airborne NINP unless significant enrichment of INP by a factor of 105 takes place during the transfer from the ocean surface to the atmosphere. In the fog water samples with −3.47 ∘C, we observed the highest freezing onset of any sample. A closure study connecting NINP in fog water and the ambient NINP derived from the filter samples shows good agreement of the concentrations in both compartments, which indicates that INPs in the air are likely all activated into fog droplets during fog events. In a case study, we considered a situation during which the ship was located in the marginal sea ice zone and NINP levels in air and the SML were highest in the temperature range above −10 ∘C. Chlorophyll a measurements by satellite remote sensing point towards the waters in the investigated region being biologically active. Similar slopes in the temperature spectra suggested a connection between the INP populations in the SML and the air. Air mass history had no influence on the observed airborne INP population. Therefore, we conclude that during the case study collected airborne INPs originated from a local biogenic probably marine source.

Post‐Translational Modifications Regulate Lipid Remodeling Enzyme During Freezing Stress

As winter approaches, plants acclimate to the cold and begin to induce physiological and metabolic changes that are necessary for survival. While we know much about the signaling pathways that induce metabolic changes at the onset of cold and early freezing, less is known about signaling during severe freezing. One such signaling pathway is the activation of the cryoprotective enzyme Sensitive to Freezing 2 (SFR2). Even though SFR2 is constitutively expressed, it only becomes active as the plant experiences subzero temperatures. The function of SFR2 is to recognize these freezing temperatures and induce membrane remodeling to produce oligogalactolipids, lipids containing two or more galactose molecules as a head group. Because of its ability to sense freezing, many cold-tolerant species including the model plant Arabidopsis thaliana, require SFR2 activity to survive more severe freezing temperatures. However, the signaling pathway that enables SFR2 to determine when temperatures reach freezing and to become active remains unknown. Here we show that SFR2 activity is regulated by post-translational modifications, specifically phosphorylations, and that these are the mechanism by which SFR2 can sense a freezing stress. To determine this, we took two complementary approaches. The first used Arabidopsis thaliana exposed to control, cool or freezing conditions. Following temperature treatment, SFR2 was immunoprecipitated and mass spectrometry measurements were taken. From this, we were able to determine a unique phosphorylation pattern on SFR2 at each temperature analyzed. To assess the importance of phosphorylations on the residues of interest we used site-directed mutagenesis on SFR2 to systematically change the amino acids we found to be phosphorylated to alanine. The effect of these mutations was measured using our second approach, a heterologous expression system in which SFR2 is always active. Functional assays of the SFR2 mutants in this system showed that the residues identified via mass spectrometry were only a portion of those needed for activity. We confirmed this by designing two unique non-phosphorylatable SFR2s. This was accomplished with in silico modeling of likely phosphorylatable residues, followed by mutagenesis to alanine. Heterologous protein synthesis and function analysis of these non-phosphorylatable SFR2s suggest these mutants are unable to synthesize oligogalactolipids and are currently being assessed in planta. Using both the Arabidopsis and heterologous expression data we will identify the specific residues required for SFR2 activation and the kinases responsible by determining recognition motifs surrounding the residues. By understanding how metabolic signals change during freezing stress, we can elucidate the dynamics surrounding low-temperature enzyme activation and direct research for increased cold tolerance in crops.