Search Results (51)

In recent years, large-scale linear infrastructure developments have been developed across hundreds of kilometers of permafrost regions on the Qinghai–Tibet Plateau. The implementation of major engineering projects, including the Qinghai–Tibet Highway, oil pipelines, communication cables, and the Qinghai–Tibet Railway, has spurred intensified research into permafrost dynamics. Climate warming has accelerated permafrost degradation, leading to a range of geological hazards, most notably widespread thermokarst landslides. This study investigates the spatiotemporal distribution patterns and influencing factors of thermokarst landslides in Qinghai Province through an integrated approach combining field surveys, remote sensing interpretation, and statistical analysis. The study utilized multi-source datasets, including Landsat-8 imagery, Google Earth, GF-1, and ZY-3 satellite data, supplemented by meteorological records and geospatial information. The remote sensing interpretation identified 1208 cryogenic hazards in Qinghai’s permafrost regions, comprising 273 coarse-grained soil landslides, 346 fine-grained soil landslides, 146 thermokarst slope failures, 440 gelifluction flows, and 3 frost mounds. Spatial analysis revealed clusters of hazards in Zhiduo, Qilian, and Qumalai counties, with the Yangtze River Basin and Qilian Mountains showing the highest hazard density. Most hazards occur in seasonally frozen ground areas (3500–3900 m and 4300–4900 m elevation ranges), predominantly on north and northwest-facing slopes with gradients of 10–20°. Notably, hazard frequency decreases with increasing permafrost stability. These findings provide critical insights for the sustainable development of cold-region infrastructure, environmental protection, and hazard mitigation strategies in alpine engineering projects. Full article

Glaciers, often regarded as “frozen reservoirs”, play a crucial role in replenishing numerous rivers in arid regions, contributing to ecological balance and managing river flow. Recently, the rapid shrinkage of the glaciers in the East Tianshan Mountains has affected the water quantity in the Karez system. However, studies on glacier changes in this region are limited, and recent data are scarce. This study utilizes annual Landsat composite images from 1990 to 2022 obtained via the Google Earth Engine (GEE). It utilizes a ratio threshold approach in conjunction with visual analysis to gather the glacier dataset specific to the Turpan–Hami region. The Open Global Glacier Model (OGGM) is used to model the flowlines and mass balance of around 300 glaciers. The study analyzes the glacier change trends, distribution characteristics, and responses to climate factors in the Turpan–Hami region over the past 30 years. Additionally, future glacier changes through the end of the century are projected using CMIP6 climate data. The findings indicate that the following: (1) From 1990 to 2022, glaciers in the research area underwent considerable retreat. The total glacier area decreased from 204.04 ± 0.887 km² to 133.52 ± 0.742 km², a reduction of 70.52 km², representing a retreat rate of 34.56%. The number of glaciers also decreased from 304 in 1990 to 236 in 2022. The glacier length decreased by an average of 7.54 m·a⁻¹, with the average mass balance at −0.34 m w.e.·a⁻¹, indicating a long-term loss of glacier mass. (2) Future projections to 2100 indicate that under three climate scenarios, the area covered by glaciers could diminish by 89%, or 99%, or even vanish entirely. In the SSP585 scenario, glaciers are projected to nearly disappear by 2057. (3) Rising temperatures and solar radiation are the primary factors driving glacier retreat in the Turpan–Hami area. Especially under high emission scenarios, climate warming will accelerate the glacier retreat process. Full article

Precambrian tropical glaciation is an enigma of Earth’s climate. Overlooking fundamental difference of land/sea icelines, it was equated with a global frozen ocean, which is at odds with the sedimentary evidence of an active hydrological cycle, and its genesis via the runaway ice–albedo feedback conflicts with the mostly ice-free Proterozoic when its trigger threshold was well exceeded by the dimmer sun. In view of these shortfalls, I put forth two key hypotheses of the tropical glaciation: first, if seeded by mountain glaciers, the land ice would advance on sea level to be halted by above-freezing summer temperature, which thus abuts an open cozonal ocean; second, a tropical supercontinent would block the brighter tropical sun to cause the required cooling. To test these hypotheses, I formulate a minimal tropical/polar box model to examine the temperature response to a varying tropical land area and show that tropical glaciation is indeed plausible when the landmass is concentrated in the tropics despite uncertain model parameters. In addition, given the chronology of paleogeography, the model may explain the observed deep time climate to provide a unified account of the faint young Sun paradox, Precambrian tropical glaciations, and Phanerozoic glacio-epochs, reinforcing, therefore, the uniformitarian principle. Full article

In this research, a feedback nonlinear control law was designed and tested to perform acquisition and station-keeping maneuvers for a lunar navigation constellation. Each satellite flies an Elliptical Lunar Frozen Orbit (ELFO) and is equipped with a steerable and throttleable low-thrust propulsion system. Lyapunov stability theory was employed to design a real-time feedback control law, capable of tracking all orbital elements (including the true anomaly), expressed in terms of modified equinoctial elements (MEEs). Unlike previous research, control synthesis was developed in the complete nonlinear dynamical model, and allows for driving the spacecraft toward a time-varying desired state, which includes correct phasing. Orbit propagation was performed in a high-fidelity framework, which incorporated several relevant harmonics of the selenopotential, as well as third-body effects due to the gravitational pull of the Earth and Sun. The control strategy at hand was successfully tested through two Monte Carlo campaigns in the presence of nonnominal flight conditions related to estimation errors of orbit perturbations, accompanied by the temporary unavailability and misalignment of the propulsive thrust. Full article

The article addresses the issue of numerical modeling of the process of forming the temperature regime of earth dams, along with their foundations, built and operated in permafrost conditions. A large number of such structures have been constructed in the permafrost regions of the Earth to meet the needs of industry and population. The paper outlines the key principles of designing and constructing such structures. These principles were developed based on years of experience in hydrotechnical construction. Failure to follow these principles leads to structural failures, as confirmed by the presented statistics on accidents. It is essential to ensure the appropriate thermal condition of the structure and its foundation, either frozen or thawed. An unplanned transition of soils from one state to another may lead to an emergency situation. Temperature changes can cause phase transitions of water from liquid to solid (ice), which also affects the formation of the structure’s regime. Numerical methods of calculation allow for the most comprehensive consideration of the influencing factors and processes. The article presents the results of numerical modeling of the filtration-temperature regime of an earth dam with a foundation in permafrost conditions, using two computational programs. The first is based on a locally variational approach (Termic, authored by the researchers), while the second uses a classical linear equation system solution (PLAXIS 2D 2022 software). A comparison of the results obtained from both programs showed good qualitative and quantitative consistency. Under the influence of seepage flow, the zone of frozen ground degradation is spreading in the lower part of the earth dam and its foundation. By September of the 27th year of operation, the thawed ground zone reaches approximately the middle of the structure at the base. The temperature values along the screen axis at the base of the structure are +1.2 °C (according to the Termic program—ver. 1.1) and +1.06 °C (according to PLAXIS 2D PC). Recommendations and future research directions on this topic are also formulated. Full article

The period of freezing is an important phenological characteristic of lakes in the Northern Hemisphere, exhibiting higher sensitivity to regional climate changes and aiding in the detection of Earth’s response to climate change. This review systematically examines 1141 articles on seasonal frozen lakes from 1991 to 2021, aiming to understand the seasonal variations and control conditions of ice-covered lakes. For the former, we discussed the physical structure and growth characteristics of seasonal ice cover, changes in water environmental conditions and primary production, accumulation and transformation of CO₂ beneath the ice, and the role of winter lakes as carbon sources or sinks. We also proposed a concept of structural stratification based on the differences in physical properties of ice and solute content. The latter provided an overview of the ice-covered period (−1.2 d decade⁻¹), lake evaporation (+16% by the end of the 21st century), the response of planktonic organisms (earlier spring blooming: 2.17 d year⁻¹) to global climate change, the impact of greenhouse gas emissions on ice-free events, and the influence of individual characteristics such as depth, latitude, and elevation on the seasonal frozen lakes. Finally, future research directions for seasonally ice-covered lakes are discussed. Considering the limited and less systematic research conducted so far, this study aims to use bibliometric methods to synthesize and describe the trends and main research points of seasonal ice-covered lakes so as to lay an important foundation for scholars in this field to better understand the existing research progress and explore future research directions. Full article

Precipitation nowcasting, which involves the short-term, high-resolution prediction of rainfall, plays a crucial role in various real-world applications. In recent years, researchers have increasingly utilized deep learning-based methods in precipitation nowcasting. The exponential growth of spatiotemporal observation data has heightened interest in recent advancements such as denoising diffusion models, which offer appealing prospects due to their inherent probabilistic nature that aligns well with the complexities of weather forecasting. Successful application of diffusion models in rainfall prediction tasks requires relevant conditions and effective utilization to direct the forecasting process of the diffusion model. In this paper, we propose a probabilistic spatiotemporal model for precipitation nowcasting, named LLMDiff. The architecture of LLMDiff includes two networks: a conditional encoder–decoder network and a denoising network. The conditional network provides conditional information to guide the denoising network for high-quality predictions related to real-world earth systems. Additionally, we utilize a frozen transformer block from pre-trained large language models (LLMs) in the denoising network as a universal visual encoder layer, which enables the accurate estimation of motion trend by considering long-term temporal context information and capturing temporal dependencies within the frame sequence. Our experimental results demonstrate that LLMDiff outperforms state-of-the-art models on the SEVIR dataset. Full article

Due to the extensive utilization of liquid nature gas (abbreviated as LNG) resources and a multitude of considerations, LNG storage tanks are gradually transitioning towards smaller footprints and heightened safety standards. Consequently, underground LNG storage tanks are being designed and constructed. However, underground LNG storage tanks release a considerable quantity of cold into the ground under both accidental and normal conditions. The influence of cold results in the ground freezing, which further compromises the safety of the structure. Existing research has neglected to consider the effects of this. This oversight could potentially lead to serious safety accidents. In this work, a complete set of experiments using a novel LNG underground storage tank fluid-solid-thermal coupled cryogenic leakage scale model were conducted for the first time to simulate the effect of the tank on the soil temperature field, stress field, and displacement field and to analyze the development of the three fields and the results of the effect. This research helps the related personnel to better design, construct, and evaluate the LNG underground storage tanks to avoid the catastrophic engineering risks associated with cryogenic leakage and helps to improve the design process of LNG underground storage tanks. Full article

In future aviation surveillance, the demand for higher real-time updates for global flights can be met by deploying automatic dependent surveillance–broadcast (ADS-B) receivers on low Earth orbit satellites, capitalizing on their global coverage and terrain-independent capabilities for seamless monitoring. Specific emitter identification (SEI) leverages the distinctive features of ADS-B data. High data collection and annotation costs, along with limited dataset size, can lead to overfitting during training and low model recognition accuracy. Transfer learning, which does not require source and target domain data to share the same distribution, significantly reduces the sensitivity of traditional models to data volume and distribution. It can also address issues related to the incompleteness and inadequacy of communication emitter datasets. This paper proposes a distributed sensor system based on transfer learning to address the specific emitter identification. Firstly, signal fingerprint features are extracted using a bispectrum transform (BST) to train a convolutional neural network (CNN) preliminarily. Decision fusion is employed to tackle the challenges of the distributed system. Subsequently, a transfer learning strategy is employed, incorporating frozen model parameters, maximum mean discrepancy (MMD), and classification error measures to reduce the disparity between the target and source domains. A hyperbolic space module is introduced before the output layer to enhance the expressive capacity and data information extraction. After iterative training, the transfer learning model is obtained. Simulation results confirm that this method enhances model generalization, addresses the issue of slow convergence, and leads to improved training accuracy. Full article

The mechanical properties of frozen fissured rock masses are crucial considerations for engineering in frozen earth. However, there has been little research on the mechanical properties of frozen fissured sandstone, including its strength, deformation, and geometric parameters. In this study, sandstone samples with three open en echelon fissures were observed using high-speed photography and acoustic emissions during uniaxial compression tests. The aim was to investigate sandstone’s strength, deformability, and failure process in order to elucidate the effects of freezing on its mechanical properties. In the frozen-saturated and dried states, the uniaxial compression strength (UCS) initially decreases and then increases with an increase in fissure inclination angle. Conversely, the UCS of samples in the saturated state continuously increases. The UCS follows a decreasing trend, as follows: frozen-saturated state > dried state > saturated state. The initial crack angle decreases as the fissure inclination increases in all states, irrespective of temperature and moisture conditions. However, the initial crack stress and time show an increasing trend. The uniaxial compression strength (UCS) of frozen fissured sandstone is influenced by four mechanisms: (1) ice provides support to the rock under compression, (2) ice fills microcracks, (3) unfrozen water films act as a cementing agent under tension or shearing loads, and (4) frost damage leads to softening of the rock. Full article

The soil freeze/thaw (FT) state has emerged as a critical role in the ecosystem, hydrological, and biogeochemical processes, but obtaining representative soil FT state datasets with a long time sequence, fine spatial resolution, and high accuracy remains challenging. Therefore, we propose a decision-level spatiotemporal data fusion algorithm based on Convolutional Long Short-Term Memory networks (ConvLSTM) to expand the SMAP-enhanced L3 landscape freeze/thaw product (SMAP_E_FT) temporally. In the algorithm, the Freeze/Thaw Earth System Data Record product (ESDR_FT) is sucked in the ConvLSTM and fused with SMAP_E_FT at the decision level. Eight predictor datasets, i.e., soil temperature, snow depth, soil moisture, precipitation, terrain complexity index, area of open water data, latitude and longitude, are used to train the ConvLSTM. Direct validation using six dense observation networks located in the Genhe, Maqu, Naqu, Pali, Saihanba, and Shandian river shows that the fusion product (ConvLSTM_FT) effectively absorbs the high accuracy characteristics of ESDR_FT and expands SMAP_E_FT with an overall average improvement of 2.44% relative to SMAP_E_FT, especially in frozen seasons (averagely improved by 7.03%). The result from indirect validation based on categorical triple collocation also shows that ConvLSTM_FT performs stable regardless of land cover types, climate types, and terrain complexity. The findings, drawn from preliminary analyses on ConvLSTM_FT from 1980 to 2020 over China, suggest that with global warming, most parts of China suffer from different degrees of shortening of the frozen period. Moreover, in the Qinghai–Tibet region, the higher the permafrost thermal stability, the faster the degradation rate. Full article

In recent years, the number of expected missions to the Moon has increased significantly. With limited terrestrial-based infrastructure to support this number of missions, as well as restricted visibility over intended mission areas, there is a need for space navigation system autonomy. Autonomous on-board navigation systems in the lunar environment have been the subject of study by a number of authors. Suggested systems include optical navigation, high-sensitivity Global Navigation Satellite System (GNSS) receivers, and navigation-linked formation flying. This paper studies the interoperable nature and fusion of proposed autonomous navigation systems that are independent of Earth infrastructure, given challenges in distance and visibility. This capability is critically important for safe and resilient mission architectures. The proposed elliptical frozen orbits of lunar navigation satellite systems will be of special interest, investigating the derivation of orbit determination by non-terrestrial sources utilizing celestial observations and inter-satellite links. Potential orbit determination performances around 100 m are demonstrated, highlighting the potential of the approach for future lunar navigation infrastructure. Full article

The goal of this research is to define a lunar-orbiting system that provides power to the lunar surface through wireless power transmission. To meet the power demand of a lunar base, a constellation of satellites placed in stable orbits is used. Each satellite of this constellation consists of solar arrays and batteries that supply a power transmission system. This system is composed of a laser that transmits power to receivers on the lunar surface. The receivers are photonic power converters, photovoltaic cells optimized for the laser’s monochromatic light. The outputs of this work will cover the architecture of the system by studying different orbits, specifically analyzing some subsystems such as the laser, the battery pack and the receiver placed on the lunar ground. The study is conducted considering two different energy demands and thus two different receivers location: first, at the strategic location of the Artemis missions’ landing site, the Shackleton Crater near the lunar south pole; second, on the lunar equator, in anticipation of future and new explorations. The goal is to evaluate the possible configurations to satisfy the power required for a lunar base, estimated at approximately 100 kW. To do this, several cases were analyzed: three different orbits, one polar, one frozen and one equatorial (Earth–Moon distant retrograde orbit) with different numbers of satellites and different angles of the receiver’s cone of transmission. The main objective of this paper is to perform a comprehensive feasibility study of the aforementioned system, with specific emphasis placed on selected subsystems. While thermal control, laser targeting, and attitude control subsystems are briefly introduced and discussed, further investigation is required to delve deeper into these areas and gain a more comprehensive understanding of their implementation and performance within the system. Full article

Background: Understanding and countering the well-established negative health consequences of spaceflight remains a primary challenge preventing safe deep space exploration. Targeted/personalized therapeutics are at the forefront of space medicine strategies, and cross-species molecular signatures now define the ‘typical’ spaceflight response. However, a lack of direct genotype–phenotype associations currently limits the robustness and, therefore, the therapeutic utility of putative mechanisms underpinning pathological changes in flight. Methods: We employed the worm Caenorhabditis elegans as a validated model of space biology, combined with ‘NemaFlex-S’ microfluidic devices for assessing animal strength production as one of the most reproducible physiological responses to spaceflight. Wild-type and dys-1 (BZ33) strains (a Duchenne muscular dystrophy (DMD) model for comparing predisposed muscle weak animals) were cultured on the International Space Station in chemically defined media before loading second-generation gravid adults into NemaFlex-S devices to assess individual animal strength. These same cultures were then frozen on orbit before returning to Earth for next-generation sequencing transcriptomic analysis. Results: Neuromuscular strength was lower in flight versus ground controls (16.6% decline, p < 0.05), with dys-1 significantly more (23% less strength, p < 0.01) affected than wild types. The transcriptional gene ontology signatures characterizing both strains of weaker animals in flight strongly corroborate previous results across species, enriched for upregulated stress response pathways and downregulated mitochondrial and cytoskeletal processes. Functional gene cluster analysis extended this to implicate decreased neuronal function, including abnormal calcium handling and acetylcholine signaling, in space-induced strength declines under the predicted control of UNC-89 and DAF-19 transcription factors. Finally, gene modules specifically altered in dys-1 animals in flight again cluster to neuronal/neuromuscular pathways, suggesting strength loss in DMD comprises a strong neuronal component that predisposes these animals to exacerbated strength loss in space. Conclusions: Highly reproducible gene signatures are strongly associated with space-induced neuromuscular strength loss across species and neuronal changes in calcium/acetylcholine signaling require further study. These results promote targeted medical efforts towards and provide an in vivo model for safely sending animals and people into deep space in the near future. Full article

During the Advanced Plant Habitat experiment 2, radish plants were grown in two successive grow-outs on the International Space Station (ISS) for 27 days each. On days 10, 18, and 24, leaf punch (LP) samples were collected and frozen. At harvest, bulb tissue was sampled with oligo-dT functionalized Solid Phase Gene Extraction (SPGE) probes. The space samples were compared with samples from ground controls (GC) grown at the Kennedy Space Center (KSC) under the same conditions as on the ISS, with notably elevated CO₂ (about 2500 ppm), and from lab plants grown under atmospheric CO₂ but with light and temperature conditions similar to the KSC control. Genes corresponding to peroxidase (RPP), glucosinolate biosynthesis (GIS), protein binding (CBP), myrosinase (RMA), napin (RSN), and ubiquitin (UBQ) were measured by qPCR. LP from day 24 and bulb samples collected at harvest were compared with RNA-seq data from material that was harvested, frozen, and analyzed after return to Earth. The results showed stable transcription in LP samples in GC but decreasing values in ISS samples during both grow-outs, possibly indicative of stress. SPGE results were similar between GC and ISS samples. However, the RNA-seq analyses showed different transcription profiles than SPGE or LP results, possibly related to localized sampling. RNA-seq of leaf samples showed greater variety than LP data, possibly because of different sampling times. RSN and RPP showed the lowest transcription regardless of method. Temporal analyses showed relatively small changes during plant development in space and in ground controls. This is the first study that compares developmental changes in space-grown plants with ground controls based on a comparison between RNA-seq and qPCR analyses. Full article