Ice Content Research Articles

Technical note: Retrieval of the supercooled liquid fraction in mixed-phase clouds from Himawari-8 observations

Abstract. The supercooled liquid fraction (SLF) in mixed-phase clouds (MPCs) is an essential variable of cloud microphysical processes and climate sensitivity. However, the SLF is currently calculated in spaceborne remote sensing only as the cloud phase–frequency ratio of adjacent pixels, which results in a loss of the original resolution in observations of cloud liquid or ice content within MPCs. Here, we present a novel method for retrieving the SLF in MPCs based on the differences in radiative properties of supercooled liquid droplets and ice particles at visible (VIS) and shortwave infrared (SWI) channels of the geostationary Himawari-8. Liquid and ice water paths are inferred by assuming that clouds are composed of only liquid or ice, with the real cloud water path (CWP) expressed as a combination of these two water paths (SLF and 1-SLF as coefficients), and the SLF is determined by referring to the CWP from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The statistically relatively small cloud phase spatial inhomogeneity at a Himawari-8 pixel level indicates an optimal scene for cloud retrieval. The SLF results are comparable to global SLF distributions observed by active instruments, particularly for single-layered cloud systems. While accessing the method's feasibility, SLF averages are estimated between 74 % and 78 % in Southern Ocean (SO) stratocumulus across seasons, contrasting with a range of 29 % to 32 % in northeastern Asia. The former exhibits a minimum SLF around midday in summer and a maximum in winter, while the latter trend differs. This novel algorithm will be valuable for research to track the evolution of MPCs and constrain the related climate impact.

20-year permafrost evolution documented through petrophysical joint inversion, thermal and soil moisture data

This study investigates the ground characteristics of the high altitude (3410 m a.s.l.) permafrost site Stockhorn in the Swiss Alps using a combination of surface and subsurface temperature, soil moisture, electrical resistivity and P-wave velocity time series data including a novel approach to explicitly quantify changes in ground ice content. This study was motivated by the clear signal of permafrost degradation visible in the full dataset at this long-term monitoring site within the PERMOS (Permafrost Monitoring Switzerland) network. Firstly, we assess the spatio-temporal evolution of the ground ice and water content by a combined analysis of all available in situ thermal (borehole and ground surface temperature), hydrological (soil moisture) and geophysical (geoelectric and seismic refraction) data over two decades (2002–2022) regarding the driving factors for the spatially different warming. Secondly, we explicitly quantify the volumetric water and ice content and their changes in the subsurface from 2015 to 2022 using a time-consistent petrophysical joint inversion scheme within the open-source library pyGIMLi. The petrophysical joint inversion scheme has been improved by constraining the rock content to be constant in time for six subsequent inversions to obtain consistent changes in ice and water content over the monitoring period based on jointly inverted resistivity and traveltime data. All different data show a warming trend of the permafrost. The ice content modeled from the petrophysical joint inversion has decreased by about 15 vol.% between 2015 and 2022. Changes in ice content are first observed in the lower, south-facing part of the profile. As a result, resistivity and P-wave velocity have been decreasing significantly. Permafrost temperatures measured in the boreholes have increased between 0.5 °C and 1 °C in 20 years. Our study shows the high value of joint and quantitative analysis of datasets comprising complementary subsurface variables for long-term permafrost monitoring.

Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties

Abstract. Mixed-phase clouds are not well represented in climate and weather forecasting models, due to a lack of the key processes controlling their life cycle. Developing methods to study these clouds is therefore essential, despite the complexity of mixed-phase cloud processes and the difficulty of observing two cloud phases simultaneously. We propose in this paper a new method to retrieve the microphysical properties of mixed-phase clouds, ice clouds and supercooled water clouds using airborne or satellite radar and lidar measurements, called VarPy-mix. This new approach extends an existing variational method developed for ice cloud retrieval using lidar, radar and passive radiometers. We assume that the lidar attenuated backscatter β at 532 nm is more sensitive to particle concentration and is consequently mainly sensitive to the presence of supercooled water. In addition, radar reflectivity Z at 95 GHz is sensitive to the size of hydrometeors and hence more sensitive to the presence of ice particles. Consequently, in the mixed phase the supercooled droplets are retrieved with the lidar signal and the ice particles with the radar signal, meaning that the retrievals rely strongly on a priori and error values. This method retrieves simultaneously the visible extinction for ice αice and liquid αliq particles, the ice and liquid water contents IWC and LWC, the effective radius of ice re,ice and liquid re,liq particles, and the ice and liquid number concentrations Nice and Nliq. Moreover, total extinction αtot, total water content (TWC) and total number concentration Ntot can also be estimated. As the retrieval of ice and liquid is different, it is necessary to correctly identify each phase of the cloud. To this end, a cloud-phase classification is used as input to the algorithm and has been adapted for mixed-phase retrieval. The data used in this study are from DARDAR-MASK v2.23 products, based on the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) observations from the CALIPSO and CloudSat satellites, respectively, belonging to the A-Train constellation launched in 2006. Airborne in situ measurements performed on 7 April 2007 during the Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) campaign and collected under the track of CloudSat–CALIPSO are compared with the retrievals of the new algorithm to validate its performance. Visible extinctions, water contents, effective radii and number concentrations derived from in situ measurements and the retrievals showed similar trends and are globally in good agreement. The mean percent error between the retrievals and in situ measurements is 39 % for αliq, 398 % for αice, 49 % for LWC and 75 % for IWC. It is also important to note that temporal and spatial collocations are not perfect, with a maximum spatial shift of 1.68 km and a maximum temporal shift of about 10 min between the two platforms. In addition, the sensitivity of remote sensing and that of in situ measurements is not the same, and in situ measurement uncertainties are between 25 % and 60 %.

Mountain permafrost landslides: Experimental study investigating molard formation processes

Landslides triggered by degrading mountain permafrost pose an increasing risk to life and infrastructure in mountain regions due to current climate change trends. Because discontinous mountain permafrost is not directly detectable by remote sensing, permafrost molards offer a way of indirectly detecting its location and state. Permafrost molards are cones of loose debris that are associated with landslide deposits. They originate from ice-cemented blocks of sediment that are transported downslope with the landslide. These ice-cemented blocks are fragmented parts of the permafrost initially located in the landslide source area. Over time, these blocks degrade into conical mounds with diameters typically ranging from decimeters up to 40 m. They indicate the presence of an area of degrading permafrost at the level of the detachment zone. The physical processes that lead to the formation of molards from the ice-cemented blocks have not yet been studied in detail. Therefore, we perform an experimental study to recreate molards in a controlled laboratory environment and investigate the key formation processes. We downscale the molards to an initial cube side length of ~30 cm, and reduced the model's complexity by using two different types of gravel with a defined granulometry and lithology. We quantified the degradation phase by using a novel photogrammetric time-lapse system to detect changes in the digital elevation model between half-hourly time-steps. For the first time, we successfully recreated morphologies resembling molards under controlled laboratory conditions on a decimeter scale. We find the main processes to produce the final molard shape are cascades of grainfall for slightly cohesive sediment, and individual grainfall for non-cohesive sediment. Our experiments reveal three possible cross-section shapes (bell-shaped, triangular, trapezoidal) that correspond to molards that can be found in the field. Along with these field observations, we suggest that it may be possible to identify the cohesion of a molard's sediment based on its morphology. Together with future field data and experiments investigating the granulometry, ice and clay contents of the initial ice-cemented block, we aim to use molards as a record to better understand the landslide dynamics and state of the mountain permafrost.

Unraveling ice multiplication in winter orographic clouds via in-situ observations, remote sensing and modeling

Recent years have shown that secondary ice production (SIP) is ubiquitous, affecting all clouds from polar to tropical regions. SIP is not described well in models and may explain biases in warm mixed-phase cloud ice content and structure. Through modeling constrained by in-situ observations and its synergy with radar we show that SIP in orographic clouds exert a profound impact on the vertical distribution of hydrometeors and precipitation, especially in seeder-feeder cloud configurations. The mesoscale model simulations coupled with a radar simulator strongly support that enhanced aggregation and SIP through ice-ice collisions contribute to observed spectral bimodalities, skewing the Doppler spectra toward the slower-falling side at temperatures within the dendritic growth layer, ranging from −20 °C to −10 °C. This unique signature provides an opportunity to infer long-term SIP occurrences from the global cloud radar data archive, particularly for this underexplored temperature regime.

Application of multi-source data fusion on intelligent prediction of photovoltaic power

Accurate photovoltaic power prediction is crucial for reducing the uncertainty of photovoltaic systems in grid operation. Variations in cloud cover are one of the primary factors leading to fluctuations in photovoltaic power generation. However, clouds possess highly complex three-dimensional structures. Existing photovoltaic power prediction methods typically rely on two-dimensional cloud images, which are insufficient for fully capturing the impact of clouds on photovoltaic power generation. To address these challenges, this paper proposes a Multi-source data Photovoltaic power Prediction Model (MPPM) based on satellite cloud images and meteorological data. MPPM mainly includes SpatioTemporal feature Conditional Diffusion Model (STCDM), Attention Stacked LSTM network (ASLSTM) and Multidimensional Feature Fusion Module (MFFM). STCDM model utilizes a diffusion model to accurately forecast two-dimensional satellite cloud imagery. ASLSTM extracts the features of three-dimensional meteorological elements. MFFM module integrates the two-dimensional satellite cloud imagery features with the three-dimensional meteorological element features. The two-dimensional satellite cloud imagery reflects the visible aspect of cloud layers, while the three-dimensional meteorological data, which includes cloud water and ice content correlated with altitude, mainly captures the invisible aspect of cloud layers. These two sets of information complement each other, enabling a more comprehensive capture of the three-dimensional characteristics of clouds. Satellite cloud image prediction experiment and photovoltaic power prediction experiment are carried out on STCDM and MPPM model respectively. The experimental results demonstrate that the STCDM model achieved a Structural Similarity index (SSIM) of 0.909 for predicting satellite cloud imagery within 1 h and 0.789 within 24 h. Meanwhile, the MPPM model attained a pearson Correlation coefficient (CORR) of 0.945 for predicting PV power within 1 h and 0.856 within 24 h. These findings indicate that both the STCDM and MPPM models outperform other comparative algorithms in forecasting satellite cloud imagery and PV power.

Evaluating thermal conductivity of soil-rock mixtures in Qinghai-Tibet plateau based on theory models and machine learning methods

The thermal property of the scum layer (soil-rock mixtures) has dominant influence on the heat exchange efficiency between the lower rock layer and the upper environment in the open-pit mines of the cold regions. This paper presents a series of thermal conductivity tests (560 samples) on the scum particle to investigate the coupling effects of ice (moisture) content, temperature, and particle size distribution on the thermal properties. Previously reported models (47 empirical or theoretical models) were adopted to predicate the thermal conductivity of soil-rock mixtures in order to validate the evaluation ability of these models under the wide testing ranges. The comparison results indicate that the theoretical models, normalized model and linear/non-linear models all can not fully predict experimental results under the wide testing conditions. Three machine learning algorithms were used in the assessment presentation for the thermal properties of soil-rock mixtures. The performance of three machine learning algorithms were contrastively examined by using three important indexes (the coefficient of determination (R2), the root mean square error (RMSE) and the relative error (RE)). Based on the evaluation results, the performance ranking of three machine learning algorithms can be listed (GA-BP > SVR > RFR). This investigation is a beneficial attempt for the large data analysis to introduce the machine learning method into the determination of the thermal conductivity of soil-rock mixture under complex conditions.

Rate of permafrost thaw and associated plant community dynamics in peatlands of northwestern Canada

Abstract The most rapid climate warming is occurring in northern, permafrost environments. Peatlands of these regions are particularly sensitive to climate warming, with the high ground ice content of peat plateaux resulting in the formation of collapse scars as ground temperatures warm. To quantify the rates of permafrost thaw and associated vegetation changes, we sampled the plant and lichen communities in transects spanning actively thawing collapse scar margins at sites from mid‐Boreal to Low Subarctic conditions, within Canada's Northwest Territories. Seventeen transects were sampled in 2007/08 and 14 of these were resampled 10 years later. The rate of lateral permafrost thaw of collapse scar margins ranged from −6 to 63 cm year−1 (mean: 22.0 cm ± 4.7 cm year−1 (SE)); variability was high and no trends with respect to latitude or temperature gradients were detected. Plant communities displayed a clear gradient from lichen‐ and ericaceous shrub‐dominated peat plateaux, to collapse scars primarily characterized by Sphagnum mosses and graminoids. Both space‐for‐time (distance from collapsing margin) and direct measurement of 10‐year changes showed a successional sequence following permafrost thaw; floating mat communities characterized by Sphagnum riparium or S. balticum proceeded to lawn communities of S. angustifolium and, finally, to hummock communities with Mylia anomala or S. fuscum. This successional sequence was associated with increased water table depth and lower soil water content in plant communities farther from the actively collapsing front, illustrating that peat growth above the water table was driving plant community successional changes. The most rapid plant community succession occurred in recently thawed environments as peat growth propelled the ground surface above the water table while the slowest succession occurred in the collapse scar hummock communities located farthest from the actively collapsing peat plateau margin. Synthesis. In just 10 years, significant vegetation change was detected, in association with both permafrost thaw and subsequent plant community succession. These changes occurred across a broad climatic and latitudinal gradient, from mid‐Boreal to Low Subarctic and have implications for wildlife, global C cycle and indigenous communities who depend on this landscape for harvesting, spiritual and cultural practices.

Oven Design for In‐Situ Thermal Extraction of Volatiles From Lunar Regolith

AbstractExtracting volatiles from lunar regolith for analysis or utilization is one of the most important aspects of future lunar exploration. However, the low thermal conductivity of lunar regolith poses a challenge. Here, we conduct simulations to analyze the heat and mass transfer processes within the sample inside the oven. We identify three main factors affecting oven heat‐up rate: water ice content (WIC) in the regolith, oven diameter, and power supply. Taking these factors into account, we devise an oven design and apply it to three case studies: (a) assessing water ice and isotopic composition in Permanently Shadowed Regions, akin to Chang'e‐7 mini‐fly probe missions; (b) measuring noble gases, as Chang'e‐7 and Luna‐27 landers; and (c) large‐scale in‐situ resources utilization (ISRU). The simulation results indicate that water ice can be extracted using sufficiently high heating power without issues. However, the complete extraction of noble gases is challenging and may require alternative heating methods. For ISRU purposes, large ovens can be subdivided into smaller ones by adding internal structures, for example, honeycomb, to improve the heat‐up rate by at least 1.5 times. Additionally, we find that the oven can serve as a scientific payload for WIC measurement using the heating curve. A flowchart of this new WIC measurement method is provided, offering an alternative method to mass spectrometry or spectroscopy measurements.

On water freezing in slag-blended cementitious materials at early ages

Concretes casted in cold climate can be threatened by frost action from the initial stages of maturing. Hence, to secure their long-term functionality, it is essential to be acquainted with the material's early response to sub-zero temperatures. Addressing this challenge, the article concerned the resistance of young slag-blended cementitious materials against the early frost attack. An extensive experimental analysis covering both macro- and microscales was designed for this purpose. At first, development of the pore size distribution and ice content profile of the 100 % Portland cement and slag-blended pastes were evaluated from the early ages until maturing via mercury intrusion porosimetry and differential scanning calorimetry. It was reported that the distinction between gel pore and capillary pore is created after 3rd day for OPC and after 21st day for slag-blended paste. Next, the destructive impacts of a single freezing-thawing cycle on the mechanical properties of the young Portland cement and slag-blended mortars were measured. Subsequently, the strength development of the Portland cement and slag-blended concretes that experienced the frost exposure were evaluated and compared with each other. It was observed that the early freezing strengthen (up to 15 %) the OPC based concrete and weaken (up to 13 %) the slag-blended concrete. Additionally, the analysis was proposed to simulate the winter conditions at the building sites. The strength development of the Portland cement and slag-blended concretes that were cured at low temperatures and experienced an early freezing episode were assessed. The decrease of curing temperature caused the reduction of compressive strength of OPC-based concrete around 25 % and slag-blended concrete around 50 %. As a result, micro- and macrostructural requirements were proposed to secure the proper resistance of the slag-blended cementitious materials against the possible early frost damage.

A sustainable method to increase the strength of warm permafrost: Ice nucleation active bacteria-based

Ice nucleation active (INA) bacteria are capable of triggering ice formation close to 0 °C, but their ability of increasing ice content in warm permafrost remain unknown. Ice content is vital because it determines the bearing capacity of warm permafrost. Through nuclear magnet resonance and direct shear device, we found that adding INA bacterium Pseudomonas syringae with a concentration of 1 g/L in warm frozen soil can result in 64% increase in the shear strength, 113% increase in cohesion and 27% increase in ice content. The internal friction angle of warm frozen soil is less affected by P. syringae. Warm frozen soil with P. syringae exhibits brittle failure under normal stresses of 100 kPa to 300 kPa and plastic failure under 400 kPa. The shear strength increment can be regulated by the concentration of P. syringae which exponentially relates to ice content and linearly to shear strength. This emerging strategy reveals the importance of INA bacteria in cooling permafrost, and provides a sustainable and environment-friendly method for confronting permafrost degradation and the subsequent infrastructure instability.

Experimental study on the shear behavior of saw-toothed ice-rich debris–rock interface: effects of undulation, ice content, normal stress, and temperature

Experimental study on the shear behavior of saw-toothed ice-rich debris–rock interface: effects of undulation, ice content, normal stress, and temperature

Effects of the ice formation and its content on viscoelastic characteristics of wood exposure to low temperatures ranging from −125°C to 25°C

ABSTRACT The influence of ice formation and its content on the viscoelastic characteristics of wood were investigated in the temperature range between −125°C and 25°C. The stiffness and damping properties of the longitudinal (L), radial (R) and tangential (T) specimens were determined for different moisture content (MC) levels at or above the fiber saturation point (FSP) ranging from 25% to 300%. Results showed that the E′ value was correlated negatively with temperature for all specimens. Accompanied by the frozen free water inside the wood, the order of magnitude in E′ for specimens in the different anatomical directions trend toward an accord. The increment in E′ (ΔE′) of specimens was correlated positively with the ice content, and ΔE′ in the L direction was lower than those in the R and T directions at each MC level. The γ-relaxation ranged from −112.9°C to −94.8°C was observed for all orthotropic directions at 10 Hz, which was assigned to the reorientation of methylol groups and adsorbed water molecules in the wood cell walls. At each MC level, a lower peak temperature of γ-relaxation was observed in the L specimens compared to the transverse specimens. Notably, the γ-relaxation peak temperature in the E″ and tanδ spectrum showed obvious frequency-dependence, and the apparent activation energy (ΔH) of γ-relaxation over the measured MC range was about 38.08∼69.57 KJ/mol. The ΔH value was close for specimens in orthotropic grain orientations, indicating that this γ-relaxation phenomenon was not affected by its orthotropic structure and also related closely with the formation of ice in the wood cell lumens.

Sentinel-1 detection of ice slabs on the Greenland Ice Sheet

Abstract. Ice slabs are multi-meter-thick layers of refrozen ice that limit meltwater storage in firn, leading to enhanced surface runoff and ice sheet mass loss. To date, ice slabs have primarily been mapped using airborne ice-penetrating radar, which has limited spatial and temporal coverage. This makes it difficult to fully assess the current extent and continuity of ice slabs or to validate predictive models of ice slab evolution that are key to understanding their impact on Greenland's surface mass balance. Here, for the first time, we map the extent of ice slabs and superimposed ice facies across the entire Greenland Ice Sheet at 500 m resolution using dual-polarization Sentinel-1 (S-1) synthetic-aperture radar (SAR) data collected in winter 2016–2017. We do this by selecting empirical thresholds for the cross-polarized backscatter ratio and HV backscattered power that jointly optimize the agreement between airborne ice-penetrating radar data detections of ice slabs and the S-1 estimates of ice slab extent. Our results show that there is a strong correlation between C-band backscatter and the ice content of the upper ∼ 7 m of the firn column that enables ice slab mapping with S-1. Our new mapping shows that ice slabs are nearly continuous around the entire margin of the ice sheet. This includes regions in southwest Greenland where ice slabs have not been previously identified by ice-penetrating radar but where the S-1-inferred ice slab extent shows strong agreement with the extent of visible runoff mapped from optical imagery. The algorithm developed here lays the groundwork for the long-term monitoring of ice slab expansion with current and future C-band satellite systems and highlights the potential added value of future L-band missions for near-surface studies in Greenland.

Experimental Study on the Effect of Fine-Grained Soil Content on the Freezing Strength of Aeolian Sand-Cement Interface

In cold regions, understanding the freezing strength of the interface between soil and structure is crucial for designing frost-resistant foundations. To investigate how the content of cement powder in aeolian sand affects this strength, we conducted direct shear tests under various conditions such as different fine-grained soil content, normal stress, and initial moisture content of the soil. By analyzing parameters like soil properties, and volume of ice content, and using the Mohr-Coulomb strength theory to define interface strength, we aimed to indirectly measure the cementation strength of the interface. Our findings revealed that as the particle content increased, the interface stress-strain curves became noticeably stiffer. We also observed a positive linear relationship between freezing strength and silt content, while the initial moisture content of the soil did not significantly impact the strengthening effect of fine-grained soil on freezing strength. Moreover, we discovered that as the powder content increased, the force binding the ice to the interface decreased, while the friction angle at the interface increased. However, the cohesion force at the interface remained relatively unchanged. Overall, our analysis suggests that the increase in freezing strength due to fine-grained soil content is primarily due to the heightened friction between aeolian sand and the interface.

Contribution of fluorescent primary biological aerosol particles to low-level Arctic cloud residuals

Abstract. Mixed-phase clouds (MPCs) are key players in the Arctic climate system due to their role in modulating solar and terrestrial radiation. Such radiative interactions rely, among other factors, on the ice content of MPCs, which is regulated by the availability of ice-nucleating particles (INPs). While it appears that INPs are associated with the presence of primary biological aerosol particles (PBAPs) in the Arctic, the nuances of the processes and patterns of INPs and their association with clouds and moisture sources have not been resolved. Here, we investigated for a full year the abundance of and variability in fluorescent PBAPs (fPBAPs) within cloud residuals, directly sampled by a multiparameter bioaerosol spectrometer coupled to a ground-based counterflow virtual impactor inlet at the Zeppelin Observatory (475 m a.s.l.) in Ny-Ålesund, Svalbard. fPBAP concentrations (10−3–10−2 L−1) and contributions to coarse-mode cloud residuals (0.1 to 1 in every 103 particles) were found to be close to those expected for high-temperature INPs. Transmission electron microscopy confirmed the presence of PBAPs, most likely bacteria, within one cloud residual sample. Seasonally, our results reveal an elevated presence of fPBAPs within cloud residuals in summer. Parallel water vapor isotope measurements point towards a link between summer clouds and regionally sourced air masses. Low-level MPCs were predominantly observed at the beginning and end of summer, and one explanation for their presence is the existence of high-temperature INPs. In this study, we present direct observational evidence that fPBAPs may play an important role in determining the phase of low-level Arctic clouds. These findings have potential implications for the future description of sources of ice nuclei given ongoing changes in the hydrological and biogeochemical cycles that will influence the PBAP flux in and towards the Arctic.

Preconditioning of mountain permafrost towards degradation detected by electrical resistivity

Warming permafrost has been detected worldwide and is projected to continue during the next century by many modelling studies. In mountain regions, this can lead to potentially hazardous impacts on short time-scales by an increased tendency for slope instabilities. However, time scales of permafrost thaw and the role of the ice content are less clear, especially in heterogeneous mountain terrain, where ice content can vary between zero and supersaturated conditions over small distances. Warming of permafrost near the freezing point shows therefore complex inter-annual behaviour due to latent heat effects during thawing and the influence of the snow-cover, which is governed by highly non-linear processes itself. Here, we demonstrate a preconditioning effect within near-surface layers in mountain permafrost that causes non-linear degradation and accelerates thaw. We hypothesise that a summer heat wave, as has occurred in the Central European summers 2003, 2015 and 2022, will enhance permafrost degradation if the active layer and the top of the permafrost layer are already preconditioned, i.e. have reduced latent heat content. This preconditioning can already be effectuated by a singular warm year, leading to exceptionally strong melting of the ground ice. On sloping terrain this ice-loss can be considered as irreversible, as large parts of the melted water will drain during the process, and an equivalent build-up of ice in cold years does not happen on similar time-scales as the melting. We propose a simple geophysical approach based on electrical resistivity tomography surveys that can assess the state of preconditioning in the absence of boreholes. In addition, we will show that resistivity data from a total of 124 permafrost sites in the Andes, Europe, and Antarctic adhere to a distinct power law behaviour between unfrozen and frozen states, which confirms the consistent electrical behaviour of permafrost and active layer materials over a wide range of landforms and material composition.

Numerical simulation of mass and heat transfer for water extraction from icy lunar regolith

The confirmation of water ice’s existence in the permanent shadow area led to extensive research in the field of water ice mining from icy lunar regolith. A priori numerical simulation of water ice mining is necessary for guiding the development of lunar water ice mining schemes more reasonably. A 2D axisymmetric numerical simulation model capable of simulating the thermal extraction process about mining water ice from icy lunar regolith is constructed, which is executed in the COMSOL Multiphysics. The thermal extraction cases of lunar regolith with different initial water ice content and heating fluxes are simulated. The EER (energy efficiency ratio) is used to evaluate the efficiency of thermal extraction. The results show that the EER is higher as the initial water ice content is increased, which means more power is used to heat water and less power is used to heat the regolith. The icy lunar regolith with initial water ice content higher than 5.0 wt% is found to be more valuable, over which the EER at the end of thermal extraction will not increase much as the initial water ice content increases. However, the higher heating flux leads to the lower EER at the end of thermal extraction. The speed and economics of thermal extraction are suggested to be weighted before the mission’s implementation. The status of thermal diffusion (thermal transpiration) is studied, and the results indicate that thermal diffusion and advection both can be ignored in thermal extraction modeling, unless the average magnitude of temperature gradient and pressure gradient exceed the maximum of 75764 K/m and 11053 Pa/m in our calculation cases, respectively.

Study of hydrothermal characteristics of large‐scale water conveyance trunk canals in seasonally frozen ground regions under the influence of different initial water contents

AbstractIn seasonal frozen soil, freezing and thawing can change the physical and mechanical properties and affect slope stability. There are complex moisture conditions in the main water transfer canal. A study of the hydrothermal evolution of canals with different initial water contents under the action of freezing and thawing is of great importance for the prevention and control of canal slope slides. Hydrothermal coupling models are the key to revealing the canal's hydrothermal evolution. As some of the modeling parameters in the current hydrothermal coupling model are based on empirical values, particularly those in the van Genuchten equation, which are not necessarily related to soil properties, they are not suitable for analyzing the hydrothermal evolution of canals. This paper determines the soil‐water characteristic curve from the cumulative curve of particle gradation in the subsoil, and then determines the hydraulic parameters of the subsoil using the VG model, which then corrects the hydrothermal coupling model. The method of modifying the hydrothermal coupling model is original, which makes the model more realistically reflect drainage soil characteristics. During freezing and thawing of channel slopes with different initial water contents (21%, 25%, 29%, 33%, 37%, and 41%), temperature field, water field, and ice content distributions were investigated. Using the V‐G model, the optimal parameters for canal subsoil were a = 0.06, n = 1.2, and m = 0.17, and temperature distribution trends between canals with different water contents were basically similar. Water will accumulate at the bottom as the liquid water content increases at the canal boundary.

A cold laboratory hyperspectral imaging system to map grain size and ice layer distributions in firn cores

Abstract. The Greenland and Antarctic ice sheets are covered in a layer of porous firn. Knowledge of firn structure improves our understanding of ice sheet mass balance, supra- and englacial hydrology, and ice core paleoclimate records. While macroscale firn properties, such as firn density, are relatively easy to measure in the field or lab, more intensive measurements of microstructural properties are necessary to reduce uncertainty in remote sensing observations of mass balance, model meltwater infiltration, and constrain ice age – gas age differences in ice cores. Additionally, as the duration and extent of surface melting increases, refreezing meltwater will greatly alter firn structure. Field observations of firn grain size and ice layer stratigraphy are required to test and validate physical models that simulate the ice-sheet-wide evolution of the firn layer. However, visually measuring grain size and ice layer distributions is tedious, is time-consuming, and can be subjective depending on the method. Here we demonstrate a method to systematically map firn core grain size and ice layer stratigraphy using a near-infrared hyperspectral imager (NIR-HSI; 900–1700 nm). We scanned 14 firn cores spanning ∼ 1000 km across western Greenland’s percolation zone with the NIR-HSI mounted on a linear translation stage in a cold laboratory. We leverage the relationship between effective grain size, a measure of NIR light absorption by firn grains, and NIR reflectance to produce high-resolution (0.4 mm) maps of effective grain size and ice layer stratigraphy. We show the NIR-HSI reproduces visually identified ice layer stratigraphy and infiltration ice content across all cores. Effective grain sizes change synchronously with traditionally measured grain radii with depth, although effective grains in each core are 1.5× larger on average, which is largely related to the differences in measurement techniques. To demonstrate the utility of the firn stratigraphic maps produced by the NIR-HSI, we track the 2012 melt event across the transect and assess its impact on deep firn structure by quantifying changes to infiltration ice content and grain size. These results indicate that NIR-HSI firn core analysis is a robust technique that can document deep and long-lasting changes to the firn column from meltwater percolation while quickly and accurately providing detailed firn stratigraphy datasets necessary for firn research applications.