Search Results (355)

The intense changes in glaciers in the southeastern Tibetan Plateau (SETP) have essential impacts on regional water resource management. In order to study the seasonal fluctuations of glaciers in this region and their relationship with climate change, we focus on the Yigong Zangbo River Basin in the SETP, extract the annual and seasonal variations of glaciers in the basin during 2018–2023, and analyze their spatio-temporal characteristics through the seasonal-trend decomposition using the LOESS (STL) method. Finally, combining the Extreme Gradient Boosting (XGBoost) model and the Shapley additive explanations (SHAP) model, we assess the comprehensive impact of meteorological factors such as temperature and snowfall on glacier changes. The results indicate that glaciers in the Yigong Zangbo River Basin experienced remarkable mass loss during 2018–2023, with an average annual melting rate of −0.83 ± 0.12 m w.e.∙yr⁻¹. The glacier mass exhibits marked seasonal fluctuations, with increases in January–March (JFM) and April–June (AMJ) and noticeable melting in July–September (JAS) and October–December (OND). The changes over these four periods are 2.12 ± 0.04 m w.e., 0.93 ± 0.15 m w.e., −1.58 ± 0.19 m w.e., and −1.32 ± 0.17 m w.e., respectively. Temperature has been identified as the primary meteorological driver of glacier changes in the study area, surpassing the impact of snowfall. This study uses advanced altimetry data and meteorological data to monitor and analyze glacier changes, which provides valuable data for cryosphere research and also validates a set of replicable research methods, which provides support for future research in related fields. Full article

In recent years, there has been growing concern about the condition of snow leopards. The snow leopard (Panthera uncia), an apex predator of alpine ecosystems, is essential for the structural and functional stability of ecosystems. Monitoring of snow leopards’ activity patterns based on camera traps in the Qilian Mountain National Park (Qinghai area) between August 2020 to October 2023 was performed. The results showed that autumn is the peak period of snow leopard activity, especially in September when the frequency of activity is the highest, and there is one peak in the frequency of snow leopard daily activity in the time period of 18:00–22:00, while the highest overlap of the daily activity curves of snow leopards in different months was from spring to autumn (Δ = 0.97), and there were significant differences in diurnal activity rhythm between spring and autumn (p = 0.002). Snow leopards prefer sunny days, and they tend to be active at temperatures of −10–9 °C. Our research aimed to uncover the activity patterns of snow leopards at different scales within the study area and provide data for further studies on snow leopards and other wildlife by researchers. This study can be used to gain a comprehensive understanding of the ecological characteristics of snow leopards and to assess their habitats, and it will also serve as a reference for the local wildlife management authorities in formulating snow leopard conservation measures. Full article

Virtual learning environments (VLEs) in physical geography education offer significant potential to aid students in acquiring the essential skills for the environmental interpretation of glacial and periglacial environments for geoscience careers. Simulated real-world field experiences aim to help the student evaluate landscapes for natural hazards, assess their intensity, and translate and communicate this information to various stakeholders in human systems. The TREE-PG framework and VRUI model provide a philosophical and practical foundation for VLE architects, aiming to cultivate students’ knowledge, skills, and identity as geoscientists, specifically as physical geographers and geomorphologists. These frameworks emphasize the importance of translating scientific knowledge from physical features into engaging, accessible online lessons, exemplified by landscapes like those in Glacier National Park, Montana. Open-source software and open educational resources (OERs) can broaden access and incorporate diverse perspectives in these experiences, which are necessary to address the impacts of vulnerable communities to global deglaciation. Designing and creating virtual proxies of field-based education may help address issues associated with inclusion and belonging within geoscience disciplines to connect all students with dynamic physical environments beyond the classroom. Ethical AI approaches and discipline-specific repositories are needed to ensure high-quality, contextually accurate VLEs. AI’s tendency to produce output necessitates using domain-specific guardrails to maintain relevance and precision in virtual educational content. Full article

Permafrost-affected regions in the Russian Arctic are a critical study area for studying the sources of metal elements (MEs) in soils originating from geological/pedogenic processes or from anthropogenic sources via atmospheric transport. In the Nadym region of the Yamalo-Nenets Autonomous District, we investigated the contents of soil organic carbon (SOC), total nitrogen (TN), and MEs across different soil types and horizons, explored the source apportionment of MEs, and assessed local ecological risks of potentially toxic elements (PTEs). The results showed that (1) the contents of SOC and TN in Histic Cryosols (8.59% and 0.27%) were significantly higher than in Plaggic Podzols (Arenic, Gelic, and Turbic) (2.28% and 0.15%) and in Ekranic Technosols (Umbric) (1.32% and 0.09%); (2) the concentrations of MEs in the Nadym region were lower than in other Arctic regions; (3) the primary sources of MEs were identified as geological processes (36%), atmospheric transport (23%), agricultural activities (21%), and transportation (20%); and (4) the permafrost-affected soils in the Nadym region exhibited low ecological risks from PTEs. These results underscore the critical role of geological and anthropogenic factors in shaping soil conditions and highlight the relatively low ecological risk from PTEs, providing a valuable benchmark for future environmental assessments and policy development in Yamal permafrost regions. Full article

Climate change and aridification have increased the risk of salinization and organic carbon loss in dryland soils. Enrichment using biochar and organic fertilizers has the potential to reduce salt toxicity and soil carbon loss. However, the effects of biochar and organic fertilizers on CO₂ and CH₄ emissions from saline soils in dryland areas, as well as their microbial mechanisms, remain unelucidated. To clarify these issues, we performed a 5-month incubation experiment on typical soda-type saline soil from the western part of the Songnen Plain using five treatments: control treatment (CK), 5% urea (U), straw + 5% urea (SU), straw + 5% urea + microbial agent (SUH), and straw + 5% urea + biochar (SUB). Compared with the SU treatment, the SUH and SUB treatments reduced cumulative CO₂ emissions by 14.85% and 35.19%, respectively. The addition of a microbiological agent to the SU treatment reduced the cumulative CH₄ emissions by 19.55%, whereas the addition of biochar to the SU treatment increased the cumulative CH₄ emissions by 4.12%. These additions also increased the relative abundances of Proteobacteria, Planctomycetes, and Ascomycota. Overall, the addition of biochar and organic fertilizer promoted CO₂ emissions and CH₄ uptake. This was mainly attributed to an improved soil gas diffusion rate due to the addition of organic materials and enhanced microbial stress due to soil salinity and alkalinity from the release of alkaline substances under closed-culture conditions. Our findings have positive implications for enhancing carbon storage in saline soils in arid regions. Full article

Global warming leads to the melting of permafrost, affects changes in soil microbial community structures and related functions, and contributes to the soil carbon cycle in permafrost areas. Located at the southern edge of Eurasia’s permafrost region, the Greater Khingan Mountains are very sensitive to climate change. Therefore, by analyzing the bacterial community structure, diversity characteristics, and driving factors of soil profiles (active surface layer, active deep layer, transition layer, and permafrost layer) in this discontinuous permafrost region, this research provides support for the study of the carbon cycling process in permafrost regions. The results show that the microbial diversity (Shannon index (4.81)) was the highest at 0–20 cm, and the Shannon index of the surface soil of the active layer was significantly higher than that of the other soil layers. Acidobacteria and Proteobacteria were the dominant bacteria in the active layer soil of the permafrost area, and Chloroflexi, Actinobacteria, and Firmicutes were the dominant bacteria in the permafrost layer. Chloroflexi made the greatest contribution to the bacterial community in the permafrost soil, and Bacteroidota made the greatest contribution to the bacterial community in the active surface soil. The structure, richness, and diversity of the soil bacterial community significantly differed between the active layer and the permafrost layer. The number of bacterial species was the highest in the active layer surface soil and the active layer bottom soil. The difference in the structure of the bacterial community in the permafrost soil was mainly caused by changes in electrical conductivity and soil–water content, while that in the active layer soil was mainly affected by pH and soil nutrient indices. Soil temperature, NO₃⁻-N, and pH had significant effects on the structure of the bacterial community. The active layer and permafrost soils were susceptible to environmental information processing and genetic information processing. Infectious disease: the number of bacterial species was significantly higher in the surface and permafrost layers than in the other layers of the soil. In conclusion, changes in the microbial community structure in soil profiles in discontinuous permafrost areas sensitive to climate change are the key to soil carbon cycle research. Full article

The Arctic and boreal regions are experiencing a rapid increase in temperature, resulting in a changing cryosphere, increasing human activity, and potentially increasing high-latitude methane emissions. Satellite observations from Sentinel-5P TROPOMI provide an unprecedented coverage of a column-averaged dry-air mole fraction of methane (XCH₄) in the Arctic, compared to previous missions or in situ measurements. The purpose of this study is to support and enhance the data used for high-latitude research through presenting a systematic evaluation of TROPOMI methane products derived from two different processing algorithms: the operational product (OPER) and the scientific product (WFMD), including the comparison of recent version changes of the products (OPER, OPER rpro, WFMD v1.2, and WFMD v1.8). One finding is that OPER rpro yields lower XCH₄ than WFMD v1.8, the difference increasing towards the highest latitudes. TROPOMI product differences were evaluated with respect to ground-based high-latitude references, including four Fourier Transform Spectrometer in the Total Carbon Column Observing Network (TCCON) and five EM27/SUN instruments in the Collaborative Carbon Column Observing Network (COCCON). The mean TROPOMI–TCCON GGG2020 daily median XCH₄ difference was site-dependent and varied for OPER rpro from −0.47 ppb to 22.4 ppb, and for WFMD v1.8 from 1.2 ppb to 19.4 ppb with standard deviations between 13.0 and 20.4 ppb and 12.5–15.0 ppb, respectively. The TROPOMI–COCCON daily median XCH₄ difference varied from −26.5 ppb to 5.6 ppb for OPER rpro, with a standard deviation of 14.0–28.7 ppb, and from −5.0 ppb to 17.2 ppb for WFMD v1.8, with a standard deviation of 11.5–13.0 ppb. Although the accuracy and precision of both TROPOMI products are, on average, good compared to the TCCON and COCCON, a persistent seasonal bias in TROPOMI XCH₄ (high values in spring; low values in autumn) is found for OPER rpro and is reflected in the higher standard deviation values. A systematic decrease of about 7 ppb was found between TCCON GGG2014 and GGG2020 product update highlighting the importance of also ensuring the reliability of ground-based retrievals. Comparisons to atmospheric profile measurements with AirCore carried out in Sodankylä, Northern Finland, resulted in XCH₄ differences comparable to or smaller than those from ground-based remote sensing. Full article

Investigating the changes in snow cover caused by climate change is extremely important and has attracted increasing attention in cryosphere and climate research. Optimal remote sensing-based snow datasets can provide long-term daily and global spatial-temporal snow-cover distribution at regional and global scales. However, the application of these snow-cover products is inevitably limited because of the space–time discontinuities caused by cloud obscuration, which poses a significant challenge in snowpack-related studies, especially in High Mountain Asia (HMA), an area that has high-elevation mountains, complex terrain, and harsh environments and has fewer observation stations. To address this issue, we developed an improved five-step hybrid cloud removal strategy by integrating the daily merged snow-cover probability (SCP) algorithm, eight-day merged SCP algorithm, decision tree algorithm, temporal downscaling algorithm, and optimal threshold segmentation algorithm to produce a 21-year, daily cloud-free snow-cover dataset using two daily MODIS snow-cover products over the HMA. The accuracy assessment demonstrated that the newly developed cloud-free snow-cover product achieved a mean overall accuracy of 93.80%, based on daily classified snow depth observations from 86 meteorological stations over 10 years. The time series of the daily percentage of binary snow-cover over HMA was analyzed during this period, indicating that the maximum snow cover tended to change more dramatically than the minimum snow cover. The annual snow-cover duration (SCD) experienced an insignificantly increasing trend over most of the northeastern and southwestern HMA (e.g., Qilian, eastern Kun Lun, the east of Inner Tibet, the western Himalayas, the central Himalayas, and the Hindu Kush) and an insignificant declining trend over most of the northwestern and southeastern HMA (e.g., the eastern Himalayas, Hengduan, the west of Inner Tibet, Pamir, Hissar Alay, and Tien). This new high-quality snow-cover dataset will promote studies on climate systems, hydrological modeling, and water resource management in this remote and cold region. Full article

Against the backdrop of climate change and the “dual carbon” goals, enhancing the ecological efficiency of cryospheric tourism is crucial not only for the high-quality development of the tourism industry itself but also for the protection of the ecological environment and the promotion of green sustainable development in the cryospheric region. In light of this, this study, taking climate change as its background and based on the perspective of carbon emission constraints, integrates multidimensional factors such as “climate change, carbon emission constraints, and cryospheric resources” into a unified measurement framework to construct a model for evaluating the ecological efficiency of tourism in the cryosphere. Specifically, the model considers inputs, expected outputs, and unexpected outputs. Subsequently, employing the super-efficiency slack-based measure (SBM) model, this study measures the tourism ecological efficiency (TEE) of three provinces (Xinjiang, Qinghai, Tibet) in the cryosphere from 2013 to 2021 and utilizes the Malmquist–Luenberger index and gray correlation model to reveal their dynamic changes, efficiency decomposition, and influencing factors. The results indicate that: (1) The overall mean of TEE in the cryosphere is between 0.2428 and 1.2142, Over the study period, the average annual growth rate and corresponding confidence interval were 14.74%, (−8.61%, 64.23%), showing a significant fluctuating growth trend. Among them, Xinjiang stands out, with its mean scores ranging from 0.2418 to 1.6229, surpassing the overall average level of the cryosphere. (2) During the study period, the overall dynamic efficiency of tourism ecology in the cryosphere increased by 21.54%, driven by the synergy of technological progress (TC), pure technical efficiency (PET), and scale efficiency (SE). For each province, the dynamic efficiency of tourism ecology has improved, but to varying degrees. (3) Regarding the driving factors of TEE in the cryosphere, each driving factor is closely related to TEE, ranked from large to small as follows: carbon emission structure, level of economic development, infrastructure, intensity of technological input, industrial structure, resource endowment, and environmental regulation. This article holds theoretical and practical significance for promoting the high-quality development of polar tourism and achieving synergistic progress between the economy and environment. Full article

Understanding the distribution of rock glaciers provides key information for investigating and recognizing the status and changes of the cryosphere environment. Deep learning algorithms and red–green–blue (RGB) bands from high-resolution satellite images have been extensively employed to map rock glaciers. However, the near-infrared (NIR) band offers rich spectral information and sharp edge features that could significantly contribute to semantic segmentation tasks, but it is rarely utilized in constructing rock glacier identification models due to the limitation of three input bands for classical semantic segmentation networks, like DeeplabV3+. In this study, a dual-encoder DeeplabV3+ network (DEDNet) was designed to overcome the flaws of the classical DeeplabV3+ network (CDNet) when identifying rock glaciers using multispectral remote sensing images by extracting spatial and spectral features from RGB and NIR bands, respectively. This network, trained with manually labeled rock glacier samples from the Qilian Mountains, established a model with accuracy, precision, recall, specificity, and mIoU (mean intersection over union) of 0.9131, 0.9130, 0.9270, 0.9195, and 0.8601, respectively. The well-trained model was applied to identify new rock glaciers in a test region, achieving a producer’s accuracy of 93.68% and a user’s accuracy of 94.18%. Furthermore, the model was employed in two study areas in northern Tien Shan (Kazakhstan) and Daxue Shan (Hengduan Shan, China) with high accuracy, which proved that the DEDNet offers an innovative solution to more accurately map rock glaciers on a larger scale due to its robustness across diverse geographic regions. Full article

In this study, we utilized a feature optimization method combining texture and topographical factors with the random forest (RF) approach to identify changes in the extent of the debris cover around the Tianshan Tomur Peak between 1989 and 2022. Based on Sentinel-1 image data, we extracted glacier flow velocities using an offset tracking method and conducted a long-term analysis of flow velocities in combination with existing datasets. The debris identification results for 2022 showed that the debris-covered area in the study region was 409.2 km², constituting 22.8% of the total glacier area. Over 34 years, the area of debris cover expanded by 69.4 km², reflecting a growth rate of 20.0%. Analysis revealed that glaciers in the Tomur Peak area have been decelerating at an overall rate of −4.0% per decade, with the complexity of the glacier bed environment and the instability of the glacier’s internal structure contributing to significant seasonal and interannual variability in the movement speeds of individual glaciers. Full article

Understanding changes in runoff due to climate variations in glacier-dominated headwaters is key to managing water resources and dryland watersheds effectively and rationally. The continuous glacier shrinkage caused by climate warming has significantly impacted the water supply and ecological systems in the vast arid regions of Central Asia, attracting extensive public concern. The study results indicate an increase in total runoff at the Urumqi River source region during both the baseline (1997–2016) and mid-century (2040–2059) periods, encompassing rain, glacier meltwater, and snowmelt components. Compared to the baseline period, the temperature increases by the mid-century under the three climate scenarios (SSP1−26, SSP2−45, and SSP5−85) range from 0.98 to 1.48 °C. In this region, during the period from 1997 to 2016, glacier meltwater was the dominant component of runoff, comprising 42.10–43.79% of the total, followed by snowmelt at 29.64–30.40% and rainfall contributions of 26.56–27.49%. Additionally, glacier storage in this typical catchment responds quickly to temperature fluctuations, significantly impacting runoff. The Urumqi River source region’s runoff exhibits heightened sensitivity to these temperature shifts compared to precipitation effects. We hypothesized three glacier coverage scenarios: unchanged at 100% glaciation, reduced by half to 50%, and fully retreated to 0% glaciation. Analysis of these scenarios demonstrated that glaciers are pivotal in runoff formation. Under the SSP1−26, SSP2−45, and SSP5−85 climate scenarios, glaciers contributed additional runoff increases of 51.61%, 57.64%, and 62.07%, respectively. Generally, glaciers play a critical role in supplying water in dry areas. Thus, accurately forecasting future water resource shifts in high-altitude glacier regions is crucial for downstream water resource management and utilization. Full article

The VIIRS instrument on the JPSS-2 (renamed NOAA-21 upon reaching orbit) spacecraft was launched in November 2022, making it the third sensor in the VIIRS series, following those onboard the SNPP and NOAA-20 spacecrafts, which are operating nominally. As a multi-disciplinary instrument, the VIIRS provides the worldwide user community with high-quality imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans. This study provides an early assessment of the calibration stability and radiometric consistency of the NOAA-21 VIIRS RSBs using the latest NASA SIPS C2 L1B products. Vicarious approaches are employed, relying on reflectance data obtained from the Libya-4 desert and Dome C sites, deep convective clouds, and simultaneous nadir overpasses, as well as intercomparison with the first two VIIRS instruments using MODIS as a transfer radiometer. The impact of existing band spectral differences on sensor-to-sensor comparison is corrected using scene-specific a priori hyperspectral observations from the SCIAMACHY sensor onboard the ENVISAT platform. The results indicate that the overall radiometric performance of the newly launched NOAA-21 VIIRS is quantitatively comparable to the NOAA-20 for the VIS and NIR bands. For some SWIR bands, the measured reflectances are lower by more than 2%. An upward adjustment of 6.1% in the gain of band M11 (2.25 µm), based on lunar intercomparison results, generates more consistent results with the NOAA-20 VIIRS. Full article

In this paper, we used data from 42 soil temperature observation sites in permafrost regions throughout the Northern Hemisphere to analyze the characteristics and variability in soil temperature. The observation data were used to evaluate soil temperature simulations at different depths from 10 CMIP6 models in the permafrost region of the Northern Hemisphere. The results showed that the annual average soil temperature in the permafrost regions in the Northern Hemisphere gradually decreased with increasing latitude, and the soil temperature gradually decreased with depth. The average soil temperatures at different depths were mainly concentrated around 0 °C. The 10 CMIP6 models performed well in simulating soil temperature, but most models tended to underestimate temperatures compared to the measured values. Overall, the CESM2 model yielded the best simulation results, whereas the CNRM-CM6-1 model performed the worst. The change trends in annual average soil temperature across the 42 sites ranged from −0.17 °C/10a to 0.41 °C/10a from 1900 to 2014, the closer to the Arctic, the faster the soil warming rate. The rate of soil temperature change also varied at different depths between 1900–2014 and 1980–2014. The rate of soil temperature change from 1980 to 2014 was approximately three times greater than that from 1900 to 2014. Full article

Lake ice thickness (LIT) is a sensitive indicator of climate change, identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic-aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow–ice and ice–water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LIT and FFSAR_LIT retracker, respectively. We found that LIT retrievals from Sentinel-6 high-resolution SAR data at different posting rates are fully consistent with the LIT estimations obtained from thermodynamic lake ice model simulations and from low-resolution mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, demonstrating the continuity between LRM and SAR LIT retrievals. By comparing the Sentinel-6 SAR LIT estimates to optical/radar images, we found that the Sentinel-6 LIT measurements are fully consistent with the evolution of the lake surface conditions, accurately capturing the seasonal transitions of ice formation and melt. The uncertainty in the LIT estimates obtained with Sentinel-6 UFSAR data at 20 Hz is in the order of 5 cm, meeting the GCOS requirements for LIT measurements. This uncertainty is significantly smaller, by a factor of 2 to 3 times, than the uncertainty obtained with LRM data. The FFSAR processing at 140 Hz provides even better LIT estimates, with 20% smaller uncertainties. The LIT retracker analysis performed on data at the higher posting rate (140 Hz) shows increased performance in comparison to the 20 Hz data, especially during the melt transition period, due to the increased statistics. The LIT analysis has been performed over two representative lakes, Great Slave Lake and Baker Lake (Canada), demonstrating that the results are robust and hold for lake targets that differ in terms of size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions. Full article