We evaluated the morphology, geomorphic settings, and micrometeorological controls of sorted polygons, stripes, lobate patterns, and turf-banked terraces in two summit areas of Daisetsu Mountain, Japan, using orthophoto images and digital surface models generated from unmanned aerial vehicle observations and structure-from-motion techniques and in situ records of air temperature, wind speed/direction and ground temperatures. The sorted polygons on flat terrain are equiform and large (3.5 m in mean length), but on gentle slopes, they are elliptical and small (2.9 m). Sorted stripes and lobate patterns occur on slope steeper than 3.5 degrees-4.5 degrees. The form transition of sorted patterned grounds is considered due to activities of frost heave and thaw settlement, gelifluction, and frost creep, as well as the spatial pattern of soil wetness. In the windward slopes steeper than 3.5 degrees-4.5 degrees, the ground materials move downslope, forming lobate patterns and sorted stripes. On the flat surfaces and leeward slopes, snow accumulation prevents soils from cooling in winter, provides snowmelts to the soils, and thus thickens the seasonal thawing during summer, allowing sorting at greater depths and enlarging the diameters of the frost patterned forms. Snow redistribution and snowmelt infiltration produce locally moist soils, creating favorable environments for plant growth on leeward, that is, eastward sides of microtopography. Soil movements along slopes are dammed on the slope covered with dense vegetation cover where risers of turf-banked terrace are formed. This is the explanation why the turf-banked terraces are typically facing slightly eastward from principal slope direction.

Targets for ecosystem restoration have been made at global, regional, and national scales, but monitoring of progress remains challenging. Differences in definitions, goals, and practices among restoration initiatives, linked to policy drivers and funding sources, add complexity. We evaluate the current state of ecological restoration activity in Colombia, where, since 2012, legal requirements to compensate for environmental damage may be driving widespread restoration efforts, alongside a long history of government and private restoration initiatives. We systematically searched several public databases, and circulated an online survey, to collect records of 675 terrestrial and coastal restoration projects initiated between 1963 and 2021, capturing data on: location, funding, monitoring, ecosystem type and actors. Location was reported for 613 projects at municipality level, and 261 projects at point level. Restoration aims included recovery of ecological processes, hydrological processes, soil erosion, and natural resources. Only 24 % reported any monitoring, with just 2 % monitoring effectiveness. Forty-one percent of projects were enacted under environmental compensation laws. Funding was mostly from within Colombia, with minimal international funding. This work highlights major gaps in the monitoring needed to achieve effective implementation of restoration targets. Enhancing coordination among institutions, and enhancing monitoring, will now be crucial to achieving restoration goals.

The demand for seed-based restoration and revegetation of degraded drylands has intensified with increased disturbance and climate change. Invasive plants often hinder the establishment of seeded species; thus, they are routinely controlled with herbicides. Herbicides used to control invasive plants may maintain soil activity and cause non-target damage to seeded species. Activated carbon (AC), which has a high adsorption of many herbicides, has been incorporated into seed pellets and coatings (seed technologies) to limit herbicide damage. Though various AC seed technologies have been examined in numerous laboratory and field studies, questions remain regarding their effectiveness and how to improve it, and what causes variation in results. We synthesized the literature on AC seed technologies for dryland restoration and revegetation to attempt to answer these questions. AC pellets compared to seed coatings were more thoroughly tested in the field and generally provide strong herbicide protection. However, greater amounts of AC in seed coatings appear to increase their effectiveness. Seed coatings show more potential for use than pellets because they are less logistically challenging to use compared to pellets, but need more field testing and refinement. Results often differ between laboratory and field studies, suggesting that field studies are critical in determining realized effects. However, seedling establishment failures from other barriers make it challenging to evaluate the effectiveness of AC seed technologies in the field. AC seed technologies are an innovative tool that with continued refinement, especially if other barriers to seedling establishment can be overcome, may improve the restoration and revegetation of degraded drylands.

Black carbon is a short-lived climate warming agent and serves as a crucial factor influencing the climate. Numerous models, observations, and laboratory studies have been conducted to quantify black carbon's direct or indirect impacts on the climate. Here, we applied bibliometric analysis to identify research trends and key topics on black carbon in the climate field. Based on the Web of Science (WOS) Core Collection database, a total of 4903 documents spanning the period from 2000 to 2023 were retrieved and screened, focusing on the topic of black carbon in the climate field, resulting in the Black-Carbon Climate Local (BCL) dataset. Our study examines the influence and trends of major countries, institutions, and authors in this field. The results show that China and the United States hold leading positions in terms of the number of publications. Based on keyword networks, the BCL dataset is segmented into six distinct research directions, and representative keywords of each direction include biomass burning, radiative forcing, air pollution, aerosol optical depth, optical properties, and biochar. This study helps to identify the current research status and trends of black carbon in the climate, highlighting main research directions and emerging topics.

This research paper presents a systematic literature review on the use of remotely sensed and/or global datasets in distributed hydrological modelling. The study aims to investigate the most commonly used datasets in hydrological models and their performance across different geographical scales of catchments, including the micro-scale (1000 km(2)). The analysis included a search for the relation between the use of these datasets to different regions and the geographical scale at which they are most widely used. Additionally, co-authorship analysis was performed on the articles to identify the collaboration patterns among researchers. The study further categorized the analysis based on the type of datasets, including rainfall, digital elevation model, land use, soil distribution, leaf area index, snow-covered area, evapotranspiration, soil moisture and temperature. The research concluded by identifying knowledge gaps in the use of each data type at different scales and highlighted the varying performance of datasets across different locations. The findings underscore the importance of selecting the right datasets, which has a significant impact on the accuracy of hydrological models. This study provides valuable insights into the use of remote sensed and/or global datasets in hydrological modelling, and the identified knowledge gaps can inform future research directions.

The second-generation Modern-ERA Retrospective analysis for Research and Applications (MERRA-2) land surface temperature (LST) dataset has been widely used for permafrost mapping in specific areas; however, its accuracy and application need to be evaluated over China. In this study, the MERRA-2 LST was evaluated against meteorological observations and three other reanalysis datasets including the first-generation MERRA, Japanese 55-year Reanalysis (JRA-55), and European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), using multiple statistical methods over the period from 1980 to 2018. The results revealed that the MERRA-2 LST generally exhibited cold bias compared to meteorological observations while performing better than the JRA55, ERA-Interim, and MERRA datasets in China, particularly in high-altitude permafrost regions. The comparison indicated that the time series trends for the MERRA-2 LST was consistent with that observed until 2000, and noticeably amplified cold bias, particularly for the period after 2005, was observed. Moreover, two correction methods were proposed and compared to reduce the error range for the MERRA-2 dataset, which was caused by the difference in elevation and land cover types. Calibrated results demonstrated that the linear regression method (Method1) between the elevation difference and mean bias error (MBE) for the LST performed well with root mean square error (RMSE) ranged from 2.15 to 5.97 ?C to 1.09-2.53 ?C. Moreover, in comparison with the MODIS LST dataset, the results showed that the adjusted MERRA-2 LST was in good agreement with smaller RMSEs against the observations. The surface frost number model was used for mapping the permafrost distribution over China based on the daily adjusted MERRA-2 LST dataset. According to the simulation results, the permafrost extent had a slightly continued degradation trend with a rate of 3-5% per decade over the past 39 years. The simulated permafrost area over China for the years 2010-2018 was approximately 1.63 x 106 km2, which accounts for 16.9% of mainland China. Thus, the adjusted MERRA-2 LST with high spatial-temporal consistency is the optimal choice to investigate permafrost distribution on a large scale.

Thermal conduction control is important for retarding permafrost degradation and mitigating of frost geohazards. Similar to a thermodiode, high thermal conductivity contrast (HTCC) materials can serve as good thermal insulators. A preferred HTCC material for ground cooling is larger in thermal resistance in summer and smaller in winter. Because of contrasting thermal conductivity under frozen and thawed states, organic soil is blessed with such a property. This study quantified and reported the HTCC effects on a range of soil organic matter concentrations (SOMC) and soil moisture saturation degree (SMSD). Using the COMSOL, influences of different SOMC and SMSD on ground temperatures were simulated and compared with laboratory-measured properties. Simulation results demonstrated that with constant SMSD at 20% throughout the year, the thermal insulation effect was strengthened with increasing SOMC. A better insulating effect was judged by lower annual amplitudes and smaller depths of zero annual amplitude of ground temperatures. In case of low SMSD in summer (20%) and high SMSD in winter (60-80%), the HTCC effect of soil is enhanced with increasing SOMC. This enhancement was evidenced by increased thermal offsets and decreased maximum summer and average nearsurface soil temperatures. With constant SOMC and increasing SMSD, the rising HTCC effect gradually cools the ground. An integral analysis indicates that the higher the SOMC and SMSD in winter, the larger the thermal offset and the lower the ground temperature, i.e., the greater the HTCC effect of organic soil. This study may provide geocryological bases for engineering and environmental applications in cold regions.

Climate change has already made significant alterations to various elements of the hydrologic cycle. One relatively less attended hydrologic impact of climate change is on the landscape Freeze-Thaw (FT), which largely affects surface and sub-surface hydrology, phenology, and land-atmospheric interactions, particularly in cold regions. Understanding the impacts of climate change on FT patterns, however, is not trivial due to sparse networks of in-situ measurements as well as limitations in current physically-based modeling schemes, aiming at continuous simulations of FT states. Here, we propose shifting the focus of FT modeling from continuous simulations in time and space, and move toward statistical representations of FT characteristics at larger temporal and spatial scales. We accordingly suggest using copulas to formally describe the impacts of temperature alterations on FT characteristics using conditional probabilities. To showcase the application of this framework in practice, we pair datasets of satellite-based FT with gridded temperature over Quebec, Canada. The results show strong and rather unique dependencies between temperature and FT characteristics across different regions and/ or timeframes. Our findings demonstrate copulas as effective tools to capture such dependencies and to reconstruct marginal FT characteristics. Through a set of impact assessments, it is shown that a similar change in temperature conditions can result in different regional responses in landscape FT. These responses are often nonsymmetric, meaning that the magnitude of change in FT conditions can be different under warming and cooling conditions. In addition, we highlight intensifications in FT responses to a similar magnitude of change in temperature under more recent years, which is linked to alterations in dependencies between temperature and FT. This study provides another line of evidence for complex responses of landscape FT to climate change.

Long-term and high-quality surface soil moisture (SSM) and root-zone soil moisture (RZSM) data is crucial for understanding the land-atmosphere interactions of the Qinghai-Tibet Plateau (QTP). More than 40% of QTP is covered by permafrost, yet few studies have evaluated the accuracy of SSM and RZSM products derived from microwave satellite, land surface models (LSMs) and reanalysis over that region. This study tries to address this gap by evaluating a range of satellite and reanalysis estimates of SSM and RZSM in the thawed soil overlaying permafrost in the QTP, using in-situ measurements from sixteen stations. Here, seven SSM products were evaluated: Soil Moisture Active Passive L3 (SMAP L3) and L4 (SMAP-L4), Soil Moisture and Ocean Salinity in version IC (SMOS IC), Land Parameter Retrieval Model (LPRM) Advanced Microwave Scanning Radiometer 2 (AMSR2), European Space Agency Climate Change Initiative (ESA CCI), Advanced Scatterometer (ASCAT), and the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERAS-Land). We also evaluated three RZSM products from SMAP-L4, ERA5-Land, and the Noah land surface model driven by Global Land Data Assimilation System (GLDAS-Noah). The assessment was conducted using five statistical metrics, i. e. Pearson correlation coefficient (R), bias, slope, Root Mean Square Error (RMSE), and unbiased RMSE (ubRMSE) between SSM or RZSM products and in-situ measurements. Our results showed that the ESA CCI, SMAP-L4 and SMOS-IC SSM products outperformed the other SSM products, indicated by higher correlation coefficients (R) (with a median R value of 0.63, 0.44 and 0.57, respectively) and lower ubRMSE (with a median ubRMSE value of 0.05, 0.04 and 0.07 m(3)/m(3), respectively). Yet, SSM overestimation was found for all SSM products. This could be partly attributed to ancillary data used in the retrieval (e.g. overestimation of land surface temperature for SMAP-L3) and to the fact that the products (e.g. LPRM) more easily overestimate the in-situ SSM when the soil is very dry. As expected, SMAP-L3 SSM performed better in areas with sparse vegetation than with dense vegetation covers. For RZSM products, SMAP-L4 and GLDAS-Noah (R = 0.66 and 0.44, ubRMSE = 0.03 and 0.02 m(3)/m(3), respectively) performed better than ERAS-Land (R = 0.46; ubRMSE = 0.03 m(3)/m(3)). It is also found that all RZSM products were unable to capture the variations of in-situ RZSM during the freezing/thawing period over the permafrost regions of QTP, due to large deviation for the ice-water phase change simulation and the lack of consideration for unfrozen-water migration during freezing processes in the LSMs.

Long-term and high-resolution gridded products of precipitation and temperature data are highly important to study the changes in climate and environment under global warming. Considering the uncertainties of these products in mountainous areas, it is necessary to evaluate the data reliability. This study evaluates the performances of the CMFD (China Meteorological Forcing Dataset) and ERA5-Land in simulating precipitation and temperature in the Qilian Mountains over the period of 1980-2018. We use the observation data of 28 basic meteorological stations in the Qilian Mountains to compare with the reanalysis products. Error metrics (the correlation coefficient (CC), the root mean square error (RMSE), the mean absolute error (MAE), and the relative bias (BIAS)) are used to quantify the monthly differences in existence between the observed data and reanalysis data. Our findings indicate that both CMFD and ERA5-Land could well reproduce the spatial distribution of mean monthly precipitation and temperature in the region. A good correlation is found between CMFD and OBS under different amounts of monthly precipitation conditions. The monthly average temperatures of CMFD and ERA5-Land reveal a high correlation with the observed results. Moreover, the CC values of CMFD and ERA5-Land precipitation products are the highest in autumn and the lowest in winter, and the CC values of both CMFD and ERA5-Land temperature products are higher in spring and autumn. However, we find that both reanalysis products underestimate the temperature to varying degrees, and the amount of precipitation is overestimated by ERA5-Land. The results of the evaluation show that the errors in precipitation yielded by CMFD as a whole are distinctly fewer than those yielded by ERA5-Land, while the errors in air temperature yielded by both ERA5-Land and CMFD are nearly identical to each other. Overall, ERA5-Land is more suitable than CMFD for studying the trends of temperature changes in the Qilian Mountains. As for simulation of precipitation, CMFD performs better in the central and eastern parts of the Qilian Mountains, whereas ERA5-Land performs better in the western part of the Qilian Mountains.