Arctic permafrost soils contain a vast reservoir of soil organic carbon (SOC) vulnerable to increasing mobilization and decomposition from polar warming and permafrost thaw. How these SOC stocks are responding to global warming is uncertain, partly due to a lack of information on the distribution and status of SOC over vast Arctic landscapes. Soil moisture and organic matter vary substantially over the short vertical distance of the permafrost active layer. The hydrological properties of this seasonally thawed soil layer provide insights for understanding the dielectric behavior of water inside the soil matrix, which is key for developing more effective physics-based radar remote sensing retrieval algorithms for large-scale mapping of SOC. This study provides a coupled hydrologic-electromagnetic framework to model the frequency-dependent dielectric behavior of active layer organic soil. For the first time, we present joint measurement and modeling of the water matric potential, dielectric permittivity, and basic physical properties of 66 soil samples collected across the Alaskan Arctic tundra. The matric potential measurement allows for estimating the soil water retention curve, which helps determine the relaxation time through the Eyring equation. The estimated relaxation time of water molecules in soil is then used in the Debye model to predict the water dielectric behavior in soil. A multi-phase dielectric mixing model is applied to incorporate the contribution of various soil components. The resulting organic soil dielectric model accepts saturation water fraction, organic matter content, mineral texture, temperature, and microwave frequency as inputs to calculate the effective soil dielectric characteristic. The developed dielectric model was validated against lab-measured dielectric data for all soil samples and exhibited robust accuracy. We further validated the dielectric model against field-measured dielectric profiles acquired from five sites on the Alaskan North Slope. Model behavior was also compared against other existing dielectric models, and an indepth discussion on their validity and limitations in permafrost soils is given. The resulting organic soil dielectric model was then integrated with a multi-layer electromagnetic scattering forward model to simulate radar backscatter under a range of soil profile conditions and model parameters. The results indicate that low frequency (P-,L-band) polarimetric synthetic aperture radars (SARs) have the potential to map water and carbon characteristics in permafrost active layer soils using physics-based radar retrieval algorithms.

The freeze-thaw cycle of near-surface soils significantly affects energy and water exchanges between the atmosphere and land surface. Passive microwave remote sensing is commonly used to observe the freeze-thaw state. However, existing algorithms face challenges in accurately monitoring near-surface soil freeze/thaw in alpine zones. This article proposes a framework for enhancing freeze/thaw detection capability in alpine zones, focusing on band combination selection and parameterization. The proposed framework was tested in the three river source region (TRSR) of the Qinghai-Tibetan Plateau. Results indicate that the framework effectively monitors the freeze/thaw state, identifying horizontal polarization brightness temperature at 18.7 GHz (TB18.7H) and 23.8 GHz (TB23.8H) as the optimal band combinations for freeze/thaw discrimination in the TRSR. The framework enhances the accuracy of the freeze/thaw discrimination for both 0 and 5-cm soil depths. In particular, the monitoring accuracy for 0-cm soil shows a more significant improvement, with an overall discrimination accuracy of 90.02%, and discrimination accuracies of 93.52% for frozen soil and 84.68% for thawed soil, respectively. Furthermore, the framework outperformed traditional methods in monitoring the freeze-thaw cycle, reducing root mean square errors for the number of freezing days, initial freezing date, and thawing date by 16.75, 6.35, and 12.56 days, respectively. The estimated frozen days correlate well with both the permafrost distribution map and the annual mean ground temperature distribution map. This study offers a practical solution for monitoring the freeze/thaw cycle in alpine zones, providing crucial technical support for studies on regional climate change and land surface processes.

Estimating the landscape and soil freeze-thaw (FT) dynamics in the Northern Hemisphere (NH) is crucial for understanding permafrost response to global warming and changes in regional and global carbon budgets. A new framework for surface FT-cycle retrievals using L-band microwave radiometry based on a deep convolutional autoencoder neural network is presented. This framework defines the landscape FT-cycle retrieval as a time-series anomaly detection problem, considering the frozen states as normal and the thawed states as anomalies. The autoencoder retrieves the FT-cycle probabilistically through supervised reconstruction of the brightness temperature (TB) time series using a contrastive loss function that minimizes (maximizes) the reconstruction error for the peak winter (summer). Using the data provided by the Soil Moisture Active Passive (SMAP) satellite, it is demonstrated that the framework learns to isolate the landscape FT states over different land surface types with varying complexities related to the radiometric characteristics of snow cover, lake-ice phenology, and vegetation canopy. The consistency of the retrievals is assessed over Alaska using in situ observations, demonstrating an 11% improvement in accuracy and reduced uncertainties compared to traditional methods that rely on thresholding the normalized polarization ratio (NPR).

Knowledge of aerosol radiative effects in the Tibetan Plateau (TP) is limited due to the lack of reliable aerosol optical properties, especially the single scattering albedo (SSA). We firstly reported in situ measurement of SSA in Lhasa using a cavity enhanced albedometer (CEA) at lambda = 532 nm from 22nd May to 11th June 2021. Unexpected strong aerosol absorbing ability was observed with an average SSA of 0.69. Based on spectral absorptions measured by Aethalometer (AE33), black carbon (BC) was found to be the dominated absorbing species, accounting for about 83% at lambda = 370 nm, followed by primary and secondary brown carbon (BrCpri and BrCsec). The average direct aerosol radiative forcing at the top of atmosphere (DARFTOA) was 2.83 W/m2, indicating aerosol warming effect on the Earth-atmosphere system. Even though aerosol loading is low, aerosol heating effect plays a significant role on TP warming due to strong absorbing ability. The Tibetan Plateau (TP) has experienced rapid warming over the past decades, but the key factors affecting TP climate change haven't yet been clearly understood. Aerosol single scattering albedo (SSA) is a key optical parameter determining aerosol warming or cooling effect; however, reliable SSA measurement is scarce in TP. This study firstly reported in situ measurement of SSA in Lhasa and explored the direct radiative effect of aerosol on TP warming. Strong aerosol absorption, mainly contributed by black carbon (BC), was observed with an average SSA value of 0.69 in this city. Besides Lhasa, other sites over TP were also reported with low SSA (<= 0.77) from surface measurement. The strong aerosol absorption could cause heating effect on the Earth-atmosphere system. To relieve TP warming, reasonable pollutant emission control strategies should be taken urgently to weaken aerosol absorbing ability. Unexpected low aerosol single scattering albedo was observed in Lhasa via in situ measurement of multiple optical parameters simultaneously Black carbon was the dominant contributor (similar to 83%) to aerosol absorption at 370 nm, followed by primary and secondary brown carbon The strong absorption in Lhasa exerted positive direct aerosol radiative forcing (warming effect) at the top of atmosphere

Purpose of ReviewCalculating atmospheric aerosol radiative forcing is a crucial aspect of climate change research. The aerosol scattering phase function stands out as a vital parameter for radiative forcing computations and holds significant importance in the remote sensing retrievals of aerosols. Despite its significance, research on aerosol scattering phase function measurements has been limited over the years. This review article provides a comprehensive summary of relevant studies on the measurements of aerosol scattering phase functions.Recent FindingsIn recent times, the application of imaging detection techniques in the measurement of aerosol scattering phase functions has emerged, highlighting advantages such as portability and high temporal-angular resolution. In addition, the development of aerosol retrieval algorithms facilitates a broader application of the results obtained from aerosol scattering phase function measurements in estimating aerosol physical properties and satellite retrievals.SummaryThis review introduces the measurement techniques, instruments, and retrieval algorithms associated with aerosol scattering phase functions, encompassing laboratory experiments, in situ field measurements, and remote sensing retrieval. The measurement results and related research on aerosol morphological effects and physical property retrievals have been summarized. Finally, it outlines future research prospects, suggesting improvements in instruments, experimental expansion, and enhanced data analysis and application, providing feasible suggestions for further studies.

Black carbon aerosol has received much more attention as the most light-absorbing aerosol in recent years. The accuracy, traceability and comparability of its optical measurements, which could be realized by unified and comprehensive calibration and correction system, are essential for the estimation of emission factor, radiative forcing, and the resulting international regulations such as the United Nations Framework Convention on Climate Change. This manuscript summarizes the current optical-based methods applied in China including in-situ and filter-based methods. We detail the metrological traceability of BC optical measurement by comparing the calibration and correction methods in China, as well as BC metrology in other countries. We provide some insight into existed challenges of BC optical measurements in China and potential future direction. The significance of traceability of BC optical measurements in radiative forcing and emission estimation is emphasized. This review will improve our understanding of the traceability of BC measurement based on optical methods.

The present investigation outlines the crucial factors that influence the black carbon (BC) concentrations over a polluted metropolis, Kolkata (22.57 & DEG; N, 88.37 & DEG; E), India. Located in the eastern part of the Indo Gangetic Plain (IGP) outflow region and close to the land-ocean boundary, Kolkata is subject to contrasting seasonal maritime airflow from the Bay of Bengal and continental air mass from the IGP and Tibetan plateau region, which modulates the local concentration of BC. The origin of aerosol transport and associated atmospheric dynamics with high and low BC activities over Kolkata are examined during 2012-2015 using data from multi-technique sources which include measurements of ground-based instruments of aethalometer and multi-frequency microwave radiometer, reanalysis data from ERA-5 and MEERA-2, and model outputs from HYPSLIT back trajectory model simulations. The study highlights the control of IGP wind inflow on the occurrence of anomalous enhancements in BC concentration during weekends and holidays when local emissions are low. High BC events are associated with enhanced atmospheric heating below the boundary layer (2000 m) and significant negative surface radiative forcing. The response of the boundary layer to high and low BC episodes, shown in the diurnal variation in comparison with the seasonal mean, is investigated. Dominant suppression of morning and night-time boundary layer height is observed on high BC days. During the daytime in pre-monsoon, post-monsoon, and winter seasons, boundary layer height peaks are found to be strongly controlled by high BC episode occurrences as obtained from the hourly data of ERA-5.

Accurate estimates of regional and global glacier mass require many field-based sample measurements that are widely distributed across an area of interest. The Sawir Mountains are an isolated mountain system in Central Asia and changes in glacier mass balance from this region have rarely been reported. In this study, we provide a comprehensive analysis of mass changes of the Muz Taw Glacier in the Sawir Mountains based on glaciological and geodetic measurements. The glaciological mass balance exhibited a strong variability during the period 2016-2020, with a range of values between - 1.29 and - 0.31 m water equivalent (w.e.) and a mean value of - 0.86 +/- 0.16 m w.e. Differences in the surface elevation of the Muz Taw Glacier were determined from analysis of a topographic map (1:100,000 scale) and terrestrial laser scanning (TLS) point-cloud data, with these data sources indicating an average surface elevation change of approximately - 33.36 +/- 9.39 m or - 0.54 +/- 0.15 m a(-1) during 1959-2021. This thickness is roughly equivalent to half of the mean thickness of the glacier terminus, which has contributed to the negative geodetic mass balance of - 28.36 +/- 8.23 m w.e. or - 0.46 +/- 0.13 m w.e. a(-1). Approximately twice as much mass has been lost from the Muz Taw Glacier during the past 5 years (2016-2020) than estimated by geodetic data, indicating that the mass loss of Muz Taw Glacier has continued unabated.

The freezing front depth (z(ff)) of annual freeze-thaw cycles is critical for monitoring the dynamics of the cryosphere under climate change because z(ff) is a sensitive indicator of the heat balance over the atmosphere-cryosphere interface. Meanwhile, although it is very promising for acquiring global soil moisture distribution, the L-band microwave remote sensing products over seasonally frozen grounds and permafrost is much less than in wet soil. This study develops an algorithm, i.e., the brightness temperature inferred freezing front (BT-FF) model, for retrieving the interannual z(ff) with the diurnal amplitude variation of L-band brightness temperature (?T-B) during the freezing period. The new algorithm assumes first, the daily-scale solar radiation heating/cooling effect causes the daily surface thawing depth (z(tf)) variation, which leads further to ?T-B; second, ?T-B can be captured by an L-band radiometer; third, z(tf) and z(ff) are negatively linear correlated and their relation can be quantified using the Stefan equation. In this study, the modeled soil temperature profiles from the land surface model (STEMMUS-FT, i.e., simultaneous transfer of energy, mass, and momentum in unsaturated soil with freeze and thaw) and T-B observations from a tower-based L-band radiometer (ELBARA-III) at Maqu are used to validate the BT-FF model. It shows that, first, ?T-B can be precisely estimated from z(tf) during the daytime; second, the decreasing of z(tf) is linearly related to the increase of z(ff) with the Stefan equation; third, the accuracy of retrieved z(ff) is about 5-25 cm; fourth, the proposed model is applicable during the freezing period. The study is expected to extend the application of L-band T-B data in cryosphere/meteorology and construct global freezing depth dataset in the future.

The permafrost degradation can cause long-term ground surface subsidence, and the surface undergoes frost heave and thaw settlement due to the ice-water phase change in the active layer. The multi-year surveys by leveling observations and Interferometric Synthetic Aperture Radar monitoring (InSAR) are helpful to understand the characteristics of seasonal deformation and to model the permafrost terrain surface deformation. In this paper, we studied the characteristics of seasonal deformation over permafrost terrain in Xidatan, obtained by leveling measurements from 2010 to 2018, Sentinel-1 data from 2014 to 2020, and hydrothermal-data-based simulation. The results consistently showed a four-stage pattern of seasonal deformation characteristics: Summer thaw subsiding, warm-season stable-standing, winter freeze heaving and stable-standing. The leveling measurements proved that spatial heterogeneity also exists on a small spatial scale (400 m(2)). The deformation amplitude obtained by leveling data is the largest, and the InSAR data is the smallest.