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.

This paper investigates the spatiotemporal dynamics and their changes of the southern limit of latitudinal permafrost (SLLP) and the lower limit of mountain permafrost (LLMP) in Northeast China, emphasizing the roles of climate change and human activities. Permafrost in this region is primarily distributed in the northern parts of the Da and Xiao Xing'anling mountain ranges and in the upper parts of the Changbai Mountains and at the summits of the Huanggangliang Mountains in the southern part of the Da Xing'anling Mountain Range. Permafrost degradation, ongoing since at least the local Holocene Megathermal Period (8.5-6.0 ka BP), has intermittently reversed during cooler climatic intervals but continues to exert significant impacts on regional environments, infrastructure stability, and carbon storage. Notably, the northward retreats of the SLLP since the mid-19th century underscore the sustained nature of this degradation, especially in southern patchy permafrost zones increasingly sensitive to warming and anthropogenic influences. LLMP variability is similarly shaped by a combination of climatic, hydrometeorological, ecological, and topographic factors. The distributions of SLLP and LLMP are further complicated by the presence of relict and sporadic permafrost, as well as the hydrothermal effects of vegetation and snow cover. Addressing the challenges of mapping and modeling boreal permafrost in Northeast China requires comprehensive field investigations, long-term in situ monitoring via station networks, and advanced numerical modeling. Emerging technologies, including satellite and airborne remote sensing (RS), geographic information systems (GIS), unmanned aerial vehicles (UAVs), surface geophysical methods, and big data analytics, offer new possibilities for enhancing permafrost monitoring and mapping. Integrating these tools with conventional field studies can significantly improve our understanding of permafrost dynamics. Continued efforts in monitoring, technological innovation, multidisciplinary collaboration, and international cooperation are essential to meet the challenges posed by permafrost degradation in a changing climate.

In this study, we used satellite observations to identify 10 typical dust-loading events over the Indian Himalayas. Next, the aerosol microphysical and optical properties during these identified dust storms are characterized using cotemporal in situ measurements over Mukteshwar, a representative site in Indian Himalayas. Relative to the background values, the mass of coarse particles (size range between 2.5 and 10 mu m) and the extinction coefficient were found to be enhanced by 400% (from 24 +/- 15 to 98 +/- 40 mu g/m3) and 175% (from 89 +/- 57 Mm-1 to 156 +/- 79 Mm-1), respectively, during these premonsoonal dust-loading events. Moreover, based on the air mass trajectory, these dust storms can be categorized into two categories: (a) mineral dust events (MDEs), which involve long-range transported dust plumes traversing through the lower troposphere to reach the Himalayas and (b) polluted dust events (PDEs), which involve short-range transported dust plumes originating from the arid western regions of the Indian subcontinent and traveling within the heavily polluted boundary layer of the Gangetic plains before reaching the Himalayas. Interestingly, compared to the background, the SSA and AAE decrease during PDEs but increase during MDEs. More importantly, we observe a twofold increase in black carbon concentrations and the aerosol absorption coefficient (relative to the background values) during the PDEs with negligible changes during MDEs. Consequently, the aerosol-induced snow albedo reduction (SAR) also doubles during MDEs and PDEs relative to background conditions. Thus, our findings provide robust observational evidence of substantial dust-induced snow and glacier melting over the Himalayas.

The temporal variability of microphysical parameters of pyrolysis smoke, retrieved by inverting the characteristics of aerosol scattering and extinction, has been studied. The polarization scattering phase functions and spectral extinction coefficients were measured for 65 hours in smoke aerosols produced from thermal decomposition of pine wood during low-temperature pyrolysis in the Big Aerosol Chamber (BAC) of Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences. The microstructure parameters (volume concentration and mean radius of particles with division into fine and coarse fractions) and the complex refractive index of pyrolysis smoke are retrieved following the developed algorithm for inverting optical measurements. The real part of the refractive index is found to be in the vicinity of n = 1.55, and the imaginary part is in the range 0.007 < kappa < 0.009; the mean radius of fine particles varies in the narrow range 0.137-0.146 mu m. During smoke aging, the particle ensemble-mean radius monotonically increased from 0.19 to 0.6 mu m mainly due to a relative increase in the content of coarse aerosol. Results of this work are important for estimation of the radiative forcing of aerosol and improvement of climate models and algorithms of remote optical sounding.

The areas covered by permafrost in the polar regions are vulnerable to rapid changes in the current climate. The well-studied near-surface active layer and permafrost zone are in contrast to the unknown exact shape of the bottom permafrost boundary. Therefore, the entire shape of permafrost between the upper and lower boundaries is not identified with sufficient accuracy. Since most of the factors affecting deep cryotic structures are subsurface in nature, their evolution in deeper layers is also relatively unclear. Here, we propose a hypothesis based on the results of geophysical studies regarding the shape of the permafrost in the coastal area of Svalbard, Southern Spitsbergen. In the article, we emphasize the importance of recognizing not only the uppermost active layer but also the bottom boundary of permafrost along with its transition zone, due to the underestimated potential role of its continuity in observing climate change. The lower permafrost boundary is estimated to range from 70 m below the surface in areas close to the shore to 180 m inland, while a continuous layer of an entirely frozen matrix can be identified with a thickness between 40 m and 100 m. We also hypothesized the presence of the possible subsea permafrost in the Hornsund. The influence of seawater intrusions, isostatic uplift of deglaciated areas, and surface-related processes that affect permafrost evolution may lead to extensive changes in the hy-drology and geology of the polar regions in the future. For all these reasons, monitoring, geophysical imaging and understanding the characteristics and evolution of deep permafrost structures requires global attention and scientific efforts.

According to the monitoring data of the optical and microphysical characteristics of smoke aerosol at AERONET stations during forest fires in the summer of 2019 in Alaska, the anomalous selective absorption of smoke aerosol has been detected in the visible and near-infrared spectral range from 440 to 1020 nm. With anomalous selective absorption, the imaginary part of the refractive index of smoke aerosol reached 0.315 at a wavelength of 1020 nm. A power-law approximation of the spectral dependence of the imaginary part of the refractive index with an exponent from 0.26 to 2.35 is proposed. It is shown that, for anomalous selective absorption, power-law approximations of the spectral dependences of the aerosol optical extinction and absorption depths are applicable with an angstrom ngstrom exponent from 0.96 to 1.65 for the aerosol optical extinction depth and from 0.97 to -0.89 for the aerosol optical absorption depth, which reached 0.72. Single scattering albedo varied from 0.62 to 0.96. In the size distribution of smoke aerosol particles with anomalous selective absorption, the fine fraction of particles of condensation origin dominated. The similarity of the fraction of particles distinguished by anomalous selective absorption with the fraction of tar balls (TBs) detected by electron microscopy in smoke aerosol, which, apparently, arise during the condensation of terpenes and their oxygen-containing derivatives, is noted.

Shortcomings and uncertainties in the model representation of atmospheric transformations (the aging) of organic aerosol (OA) have long been identified as one of the potential sources of considerable uncertainty in OA simulations with both global and regional models. However, the impact of this uncertainty on predictions of radiative and climate effects of both anthropogenic and biomass burning (BB) aerosol yet needs to be understood. This study examines the importance of the model representation of OA for simulating the direct radiative effect (DRE) of Siberian BB aerosol in the eastern Arctic. We employ a regional coupled chemistry-meteorology model and a global fire emission database to simulate the optical properties and DRE of BB aerosol emitted from intense Siberian fires in July 2016 and compare the DRE estimates that were obtained using two alternative representations of Siberian BB OA. One of them is a default OA representation that predicts very little secondary OA (SOA), and another involves a simple original OA parameterization that has been developed previously within the volatility basis set (VBS) framework and features a strong production of SOA. The simulations of the aerosol optical properties are evaluated against satellite observations of the aerosol optical depth (AOD) in Siberia and the Arctic as well as against values of the single scattering albedo derived from in situ observations of the aerosol absorption and scattering coefficients at four Arctic sites. While the simulations with the default OA representation are found to strongly underestimate AOD both in Siberia and the eastern Arctic, the use of the VBS parameterization considerably improves the agreement between the AOD simulations and observations in both regions. Simulations of the single scattering albedo are found to be overall rather adequate with both representations. Differences in the OA representations are found to result in major differences in the estimates of the DRE of Siberian BB aerosol in the eastern Arctic. Specifically, although the simulations with both representations predict that the DRE is predominantly negative at the top of the atmosphere (TOA), the magnitude of the mean DRE is found to be more than twice as large (6.0 W m-2) with the VBS parameterization than with the default OA representation (2.8 W m-2). An even larger difference (by a factor of 3.5) is found between the estimates of the DRE over the snow-or ice-covered areas. The different treatments of the BB OA evolution are associated also with considerably different contributions of black and brown carbon to the DRE estimates. Overall, our results indicate that model estimates of the DRE of Siberian BB aerosol in the eastern Arctic are strongly sensitive to the assumptions regarding the evolution of OA in Siberian BB plumes and that the SOA formation in these plumes is one of the major factors determining the magnitude of the radiative effects of Siberian BB aerosol in the real atmosphere.

A comprehensive investigation of physical, optical, and chemical characteristics of columnar aerosols over two locations with distinct environmental settings in the Indo-Gangetic Plain (IGP) region, namely, Kanpur (urban and industrial area) and Gandhi College (rural area), is conducted using high-quality aerosol datasets obtained from ground-based Aerosol Robotic Network (AERONET) observations during the recent five year period (2015-2019). This study utilizes all the crucial columnar aerosol parameters necessary for accurately estimating aerosol radiative forcing. Quantification of contribution by different aerosol species originating from natural and anthropogenic sources to the total aerosol optical depth (AOD) and single scattering albedo (SSA) is important to understand the specific mechanisms that influence the aerosol composition, thereby reducing the uncertainty in aerosol radiative forcing. For the first time, two highly spatially resolved models' (Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS)) simulated absorbingspecies-wise (black carbon (BC), dust, and brown carbon (BrC)) AOD, and absorption AOD (AAOD) are compared and contrasted against the AERONET observations over the IGP region in a systematic manner. MERRA-2 AODs are mostly lower, whereas CAMS AODs are consistently higher than the AERONET AODs. A comparison of collocated time and space observations with models clearly suggests that improvements in emission inventories on a seasonal scale are essential. MERRA-2 SSA is noted lower than the AERONET SSA during the winter season due to overestimation in BC AOD. During winter in >70% of MERRA-2 simulated SSA the difference is higher than +/- 0.03 (the uncertainty range of AERONET SSA) whereas during pre-monsoon and monsoon seasons >60% of MERRA-2 SSA lies within the uncertainty range of AERONET SSA. Both models show a gradient in AODDust decreasing from west to east in the IGP. However, observations do not often exhibit the gradient in dust, which is validated by air mass back trajectory analyses as air masses travel through different pathways to IGP and reverse the west to east gradient in AODDust. This quantitative and comparative collocated analysis of observed aerosol characteristics with models on a seasonal scale will enable a better estimation of aerosol radiative forcing, and can help improve aerosol processes and parameterizations in models.

In this work, we report the ongoing implementation of online-coupled aerosol-cloud microphysical-radiation interactions in the Brazilian global atmospheric model (BAM) and evaluate the initial results, using remote-sensing data for JFM 2014 and JAS 2019. Rather than developing a new aerosol model, which incurs significant overheads in terms of fundamental research and workforce, a simplified aerosol module from a preexisting global aerosol-chemistry-climate model is adopted. The aerosol module is based on a modal representation and comprises a suite of aerosol microphysical processes. Mass and number mixing ratios, along with dry and wet radii, are predicted for black carbon, particulate organic matter, secondary organic aerosols, sulfate, dust, and sea salt aerosols. The module is extended further to include physically based parameterization for aerosol activation, vertical mixing, ice nucleation, and radiative optical properties computations. The simulated spatial patterns of surface mass and number concentrations are similar to those of other studies. The global means of simulated shortwave and longwave cloud radiative forcing are comparable with observations with normalized mean biases <= 11% and <= 30%, respectively. Large positive bias in BAM control simulation is enhanced with the inclusion of aerosols, resulting in strong overprediction of cloud optical properties. Simulated aerosol optical depths over biomass burning regions are moderately comparable. A case study simulating an intense biomass burning episode in the Amazon is able to reproduce the transport of smoke plumes towards the southeast, thus showing a potential for improved forecasts subject to using near-real-time remote-sensing fire products and a fire emission model. Here, we rely completely on remote-sensing data for the present evaluation and restrain from comparing our results with previous results until a complete representation of the aerosol lifecycle is implemented. A further step is to incorporate dry deposition, in-cloud and below-cloud scavenging, sedimentation, the sulfur cycle, and the treatment of fires.

As the amplifier of global climate change, climate warming exerts an important impact on the freezing/thawing cycles of soil over the Tibetan Plateau, and it shapes the trend of permafrost degradation. Intensified frozen soil collapse causes severe effects on ecosystem water and energy balance as well as on carbon cycle. Previous studies have focused on the direct effects of climate change on permafrost degradation. However, there is also growing evidence showing vegetation growth can affect regional climate system, and consequently we hypothesize that vegetation autumn phenology (i.e., the end of the growing season, EOS) may influence the start date of frozen (SOF) through feedbacks to regional climates. Using satellite greenness data derived EOS and the microwave remote sensing generated SOFESDR (freeze-thaw Earth system data record) over 2001-2018, we showed a dominant-negative (13.1% vs. 0.9%) relationship between SOFESDR and EOS, suggesting an earlier SOFESDR with a delayed EOS. We found that biogeophysical indicators served as potential connections, including surface al-bedo, soil temperature, soil water content, and evapotranspiration, for the observed relationship. We therefore proposed a new site-level SOFf(EOS)xESDR algorithm based on the EOS-SOF relationship. With ground SOFALT observed from the active layer thickness at 63 sites over Tibetan Plateau, the new model provided significantly improved estimates of SOF with Pearson's correlation coefficient (R) of 0.84 and root mean square error (RMSE) of 7.63 days, comapred with current remote sensing-based SOF product (R = 0.26, RMSE = 22.60 days). We further proposed a look-up table approach to map the SOF over TP and found an overall earlier SOF (24.0 +/- 15.8) than current SOFESDR products. Therefore, our results identified a significant correlation between the autumn phenology and the SOF variability, highlighting the importance of feedbacks of autumn phenology on climate change.