Permafrost is undergoing rapid changes due to climate warming, potentially exposing a vast reservoir of carbon to be released to the atmosphere, causing a positive feedback cycle. Despite the importance of this feedback, its specifics remain poorly constrained, because representing permafrost dynamics still poses a significant challenge for Earth System Models (ESMs). This review assesses the current state of permafrost representation in land surface models (LSMs) used in ESMs and offline permafrost models, highlighting both the progress made and the remaining gaps.We identify several key physical processes crucial for permafrost dynamics, including soil thermal regimes, freeze-thaw cycles, and soil hydrology, which are underrepresented in many models. While some LSMs have advanced significantly in incorporating these processes, others lack fundamental elements such as latent heat of freeze-thaw, deep soil columns, and Arctic vegetation dynamics. Offline permafrost models provide valuable insights, offering detailed process testing and aiding the prioritization of improvements in coupled LSMs.Our analysis reveals that while significant progress has been made in incorporating permafrost-related processes into coupled LSMs, many small-scale processes crucial for permafrost dynamics remain underrepresented. This is particularly important for capturing the complex interactions between physical and biogeochemical processes required to model permafrost carbon dynamics. We recommend leveraging advancements from offline permafrost models and progressively integrating them into LSMs, while recognizing the computational and technical challenges that may arise in coupled simulations. We highlight the importance of enhancing the representation of physical processes, including through improvements in model resolution and complexity, as this is a fundamental precursor to accurately incorporate biogeochemical processes and capture the permafrost carbon feedback.

The global cryosphere is retreating under ongoing climate change. The Third Pole (TP) of the Earth, which serves as a critical water source for two billion people, is also experiencing this decline. However, the interplay between rising temperatures and increasing precipitation in the TP results in complex cryospheric responses, introducing uncertainties in the future budget of TP cryospheric water (including glacier and snow water equivalents and frozen soil moisture). Using a calibrated model that integrated multiple cryospheric-hydrological components and processes, we projected the TP cryospheric water budgets under both low and high climatic forcing scenarios for the period 2021-2100 and assessed the relative impact of temperature and precipitation. Results showed (1) that despite both scenarios involving simultaneous warming and wetting, under low climatic forcing, the total cryospheric budget exhibited positive dynamics (0.017 mm yr-1 with an average of 1.77 mm), primarily driven by increased precipitation. Glacier mass loss gradually declined with the rate of retreat slowing, accompanied by negligible declines in the budget of snow water equivalent and frozen soil moisture. (2) By contrast, high climatic forcing led to negative dynamics in the total cryospheric budget (-0.056 mm yr-1 with an average of -1.08 mm) dominated by warming, with accelerated decreases in the budget of all cryospheric components. These variations were most pronounced in higher-altitude regions, indicating elevation-dependent cryospheric budget dynamics. Overall, our findings present alternative futures for the TP cryosphere, and highlight novel evidence that optimistic cryospheric outcomes may be possible under specific climate scenarios.

Evapotranspiration (ET) is a critical component of the soil-plant-atmosphere continuum, significantly influencing the water and energy balance of ecosystems. However, existing studies on ET have primarily focused on the growing season or specific years, with limited long-term analyses spanning decades. This study aims to analyse the components of ET within the alpine ecosystem of the Heihe River Basin, specifically investigating the dynamics of vegetation transpiration (T) and soil evaporation (Ev). Utilizing the SPAC model and integrating meteorological observations and eddy covariance data from 2013 to 2022, we investigate the impact of solar radiation and vegetation dynamics on ET and its partitioning (T/ET). The agreement between measured and simulated energy fluxes (net radiation and latent energy flux) and soil temperature underscores the validity of the model's performance. Additionally, a comparison employing the underlying water use efficiency method reveals consistent T/ET values during the growing season, further confirming the model's accuracy. Results indicate that the annual average T/ET during the 10-year study period is 0.41 +/- 0.03, close to the global average but lower than in warmer, humid regions. Seasonal analysis reveals a significant increase in T/ET during the growing season (April to October), particularly in May and June, coinciding with the thawing of permafrost and increased soil moisture. In addition, the study finds that the leaf area index and canopy stomatal conductance exhibit a logarithmic relationship with T/ET, whereas soil temperature and downward longwave radiation show an exponential relationship with T/ET. This study highlights the importance of understanding the stomatal conductance dynamics and their controls of transpiration process within alpine ecosystems. By providing key insights into the hydrological processes of these environments, it offers guidance for adapting to climate change impacts.

Particulate matter (PM) is a vital pollutant that severely impacts human health, ecosystem well-being, and climate systems. In this review, the importance of vertical profiling is considered for understanding PM behavior between different layers of the atmosphere, and it includes modern techniques used such as meteorological towers and building methods, unmanned aerial vehicles (UAVs), aircraft, and satellite-based aerosol optical depth measurements. A systematic review was conducted, sourcing 150 articles published between 2000 and 2023, using relevant keywords such as Particulate Matter, Vertical Profiling, Environmental Impacts, and Climate Change from databases like Web of Science, Scopus, and Google Scholar. Key findings illustrate the vertical variations in PM levels associated with interactions among urban environments, meteorology, and specific atmospheric processes such as cloud formation, radiative forcing, and long-distance transport of pollutants. PM's effects on biodiversity, nutrient cycles, and ecosystem stability are also discussed. The environmental impacts of PM deposition, including biodiversity loss, nutrient cycling disruption, and ecosystem destabilization, elucidate widespread chronic anthropogenic particulate causes of long-term ecological damage around the globe. The study also examines relevant regulatory frameworks, specifically air quality standards, and policies, underpinning mitigation strategies. This review discusses how PM pollution is an increasingly alarming health risk. It reiterates the importance of demanding effective regulations on the local and global levels to counteract detrimental environmental and climatic consequences. This review clearly shows the immediate threats of PM. It should form a wake-up call to develop more effective monitoring tools and stringent regulatory measures against this omnipresent pollutant.

Atmospheric particulate matter (PM) as light-absorbing particles (LAPs) deposited to snow cover can result in early onset and rapid snow melting, challenging management of downstream water resources. We identified LAPs in 38 snow samples (water years 2013-2016) from the mountainous Upper Colorado River basin by comparing among laboratory-measured spectral reflectance, chemical, physical, and magnetic properties. Dust sample reflectance, averaged over the wavelength range of 0.35-2.50 mu m, varied by a factor of 1.9 (range, 0.2300-0.4444) and was suppressed mainly by three components: (a) carbonaceous matter measured as total organic carbon (1.6-22.5 wt. %) including inferred black carbon, natural organic matter, and carbon-based synthetic, black road-tire-wear particles, (b) dark rock and mineral particles, indicated by amounts of magnetite (0.11-0.37 wt. %) as their proxy, and (c) ferric oxide minerals identified by reflectance spectroscopy and magnetic properties. Fundamental compositional differences were associated with different iron oxide groups defined by dominant hematite, goethite, or magnetite. These differences in iron oxide mineralogy are attributed to temporally varying source-area contributions implying strong interannual changes in regional source behavior, dust-storm frequency, and (or) transport tracks. Observations of dust-storm activity in the western U.S. and particle-size averages for all samples (median, 25 mu m) indicated that regional dust from deserts dominated mineral-dust masses. Fugitive contaminants, nevertheless, contributed important amounts of LAPs from many types of anthropogenic sources.

We present an innovative approach to understanding permafrost degradation processes through the application of new environment-based particle image velocimetry (E-PIV) to time-lapse imagery and correlation with synchronous temperature and rainfall measurements. Our new approach to extracting quantitative vector movement from dynamic environmental conditions that can change both the position and the color balance of each image has optimized the trade-off between noise reduction and preserving the authenticity of movement data. Despite the dynamic polar environments and continuous landscape movements, the E-PIV provides the first quantitative real-time associations between environmental drivers and the responses of permafrost degradation mechanism. We analyze four event-based datasets from an island southwest of Tuktoyaktuk, named locally as Imnaqpaaluk or Peninsula Point near Tuktoyaktuk, NWT, Canada, spanning a 5-year period from 2017 to 2022. The 2017 dataset focuses on the interaction during a hot dry summer between slope movement and temperature changes, laying the foundation for subsequent analyses. In 2018, two datasets significantly expand our understanding of typical failure mechanisms in permafrost slopes: one investigates the relationship between slope movement and rainfall, while the other captures an overhang collapse, providing a rare quantitative observation of an acute landscape change event. The 2022 dataset revisits the combination of potential rain and air temperature-related forcing to explore the environment-slope response relationship around an ice wedge, a common feature of ice-rich permafrost coasts. These analyses reveal both a direct but muted association with air temperatures and a detectable delayed slope response to the occurrence of rainfall, potentially reflective of the time taken for the warm rainwater to infiltrate through the active layer and affect the frozen ground. Whilst these findings also indicate that other factors are likely to influence permafrost degradation processes, the associations have significant implications given the projections for a warmer, wetter Arctic. The ability to directly measure permafrost slope responses offers exciting new potential to quantitatively assess the sensitivity of different processes of degradation for the first time, improving the vulnerability components of hazard risk assessments, guiding mitigation efforts, and better constraining future projections of erosion rates and the mobilization of carbon-rich material.

In permafrost regions, vegetation growth is influenced by both climate conditions and the effects of permafrost degradation. Climate factors affect multiple aspects of the environment, while permafrost degradation has a significant impact on soil moisture and nutrient availability, both of which are crucial for ecosystem health and vegetation growth. However, the quantitative analysis of climate and permafrost remains largely unknown, hindering our ability to predict future vegetation changes in permafrost regions. Here, we used statistical methods to analyze the NDVI change in the permafrost region from 1982 to 2022. We employed correlation analysis, multiple regression residual analysis and partial least squares structural equation modeling (PLS-SEM) methods to examine the impacts of different environmental factors on NDVI changes. The results show that the average NDVI in the study area from 1982 to 2022 is 0.39, with NDVI values in 80% of the area remaining stable or exhibiting an increasing trend. NDVI had the highest correlation with air temperature, averaging 0.32, with active layer thickness coming in second at 0.25. Climate change plays a dominant role in NDVI variations, with a relative contribution rate of 89.6%. The changes in NDVI are positively influenced by air temperature, with correlation coefficients of 0.92. Although the active layer thickness accounted for only 7% of the NDVI changes, its influence demonstrated an increasing trend from 1982 to 2022. Overall, our results suggest that temperature is the primary factor influencing NDVI variations in this region.

Alpine meadows are vital ecosystems on the Qinghai-Tibet Plateau, significantly contributing to water conservation and climate regulation. This study examines the energy flux patterns and their driving factors in the alpine meadows of the Qilian Mountains, focusing on how the meteorological variables of net radiation (Rn), air temperature, vapor pressure deficit (VPD), wind speed (U), and soil water content (SWC) influence sensible heat flux (H) and latent heat flux (LE). Using the Bowen ratio energy balance method, we monitored energy changes during the growing and non-growing seasons from 2022 to 2023. The annual average daily Rn was 85.29 W m-2, with H, LE, and G accounting for 0.56, 0.71, and -0.32 of Rn, respectively. Results show that Rn is the main driver of both H and LE, highlighting its crucial role in turbulent flux variations. Additionally, a negative correlation was found between air temperature and H, suggesting that high temperatures may suppress H. A significant positive correlation was observed between soil moisture and LE, further indicating that moist soil conditions enhance LE. In conclusion, this study demonstrates the impact of climate change on energy distribution in alpine meadows and calls for further research on the ecosystem's dynamic responses to changing climate conditions.

The abrupt warming events punctuating the Termination 1 (about 11.7-18 ka Before Present, BP) were marked by sharp rises in the concentration of atmospheric methane (CH4). The role of permafrost organic carbon (OC) in these rises is still debated, with studies based on top-down measurements of radiocarbon (14C) content of CH(4 )trapped in ice cores suggesting minimum contributions from old and strongly C-14-depleted permafrost OC. However, organic matter from permafrost can exhibit a continuum of C-14 ages (contemporaneous to >50 ky). Here, we investigate the large-scale permafrost remobilization at the Younger Dryas-Preboreal transition (ca. 11.6 ka BP) using the sedimentary record deposited at the Lena River paleo-outlet (Arctic Ocean) to reflect permafrost destabilization in this vast drainage basin. Terrestrial OC was isolated from sediments and characterized geochemically measuring delta C-13, Delta C-14, and lignin phenol molecular fossils. Results indicate massive remobilization of relatively young (about 2,600 years) permafrost OC from inland Siberia after abrupt warming triggered severe active layer deepening. Methane emissions from this young fraction of permafrost OC contributed to the deglacial CH4 rise. This study stresses that underestimating permafrost complexities may affect our comprehension of the deglacial permafrost OC-climate feedback and helps understand how modern permafrost systems may react to rapid warming events, including enhanced CH4 emissions that would amplify anthropogenic climate change.

Deposition of ambient black carbon (BC) aerosols over snow-covered areas reduces surface albedo and accelerates snowmelt. Based on in-situ atmospheric BC data and the WRF-Chem model, we estimated the dry and wet deposition of BC over the Yala glacier of the central Himalayan region in Nepal during 2016-2018. The maximum and minimum BC dry deposition was reported in pre- and post-monsoon respectively. Approximately 50% of annual dry deposition occurred in the pre-monsoon season (March to May) and 27% of the annual dry deposition occurred in April. The total dry BC deposition rate was estimated as -4.6 mu g m- 2 day- 1 providing a total deposition of 531 mu g m- 2 during the pre-monsoon season. The contribution of biomass burning and fossil fuel sources to BC deposition on an annual basis was 28% and 72% respectively. The annual accumulated wet deposition of BC was 196 times higher than the annual dry deposition. The ten months of observed dry deposition of BC (October 1, 2016 to August 31, 2017 - except December 2016) was -39% lower than that of WRFChem's estimated annual dry deposition from September 1, 2016 to August 31, 2017 partially due to model bias. The deposited content of BC over the snow surface has an important role in albedo reduction, therefore snow samples were collected from the surface of the Yala Glacier and the surrounding region in April 2016, 2017, and 2018. Samples were analyzed for BC mass concentration through the thermal optical analysis and single particle soot photometer method. The BC calculated via the thermal optical method was in the range of 352-854 ng g- 1, higher than the BC calculated through the particle soot photometer method and estimated BC in 2 cm surface snow (imperial equation). The maximum surface snow albedo reduction due to BC was 8.8%, estimated by a widely used snow radiative transfer model and a linear regression equation.