Soil Moisture (SM) is a key parameter in northern Arctic and sub-Arctic (A-SA) environments that are highly vulnerable to climate change. We evaluated six SM satellite passive microwave datasets using thirteen ground-based SM stations across Northwestern America. The best agreement was obtained with SMAP (Soil Moisture Active Passive) products with the lowest RMSD (Root Mean Square Difference) (0.07 m$3$3 m${-3}$-3) and the highest R (0.55). ESA CCI (European Space Agency Climate Change Initiative) also performed well in terms of correlation with a similar R (0.55) but showed a strong variation among sites. Weak results were obtained over sites with high water body fractions. This study also details and evaluates a dedicated retrieval of SM from SMOS (Soil Moisture and Ocean Salinity) brightness temperatures based on the $\tau -\omega$tau-omega model. Two soil dielectric models (Mironov and Bircher) and a dedicated soil roughness and single scattering albedo parameterization were tested. Water body correction in the retrieval shows limited improvement. The metrics of our retrievals (RMSD = 0.08 m$3$3 m${-3}$-3 and R = 0.41) are better than SMOS but outperformed by SMAP. Passive microwave satellite remote sensing is suitable for SM retrieval in the A-SA region, but a dedicated approach should be considered.

The tau -omega model is expanded to properly simulate L -band microwave emission of the soil-snow-vegetation continuum through a closed -form solution of Maxwell's equations, considering the intervening dry snow layer as a loss -less medium. The error standard deviations of a least -squared inversion are 0.1 and 3.5 for VOD and ground permittivity, over moderately dense vegetation and a snow density ranging from 100 to 400 kg m -3 , considering noisy brightness temperatures with a standard deviation of 1 kelvin. Using the Soil Moisture Active Passive (SMAP) satellite observations, new global estimates of VOD and ground permittivity are presented over the Arctic boreal forests and permafrost areas. In the absence of dense in situ observations of ground permittivity and VOD, the retrievals are causally validated using ancillary variables including ground temperature, above -ground biomass, tree height, and net ecosystem exchange of carbon dioxide. Time -series analyses promise that the new data set can expand our understanding of the land-atmosphere interactions and exchange of carbon fluxes over Arctic landscapes.

The optical properties of snow can be strongly modified by the presence of a variety of impurities including mineral dust and snow algae. We made use of measured concentration of snow algae and mineral dust to parameterize the BioSNICAR radiative transfer model. Surficial snow samples were gathered during a field campaign on 7th July 2020 at the Presena glacier (Rhaetian Alps). We collected 18 samples of surface snow containing different amount of snow algae and mineral dust. Through radiative transfer simulations we estimated an average broadband albedo reduction of 7.4 +/- 6.1 % and 35.3 +/- 7.4 % compared to clean snow, caused by snow algae and mineral dust presence, respectively. When we considered the combined effect of snow algae and dust, we estimated a broadband albedo reduction equal to 40.8 +/- 8.4 %. We estimated an average instantaneous radiative forcing induced by snow algae, mineral dust and both impurities equals to 42.3 (+/- 36.1) W/m(2), 203.7 (+/- 45.5) W/m(2), and 211.8 (+/- 45.9) W/m(2), respectively. Using BioSNICAR simulations, we also tested a series of narrowband spectral indices to determine the concentration of mineral dust and snow algae from multi- and hyper -spectral data. Results showed that most spectral indices used for snow algae mapping are correlated also with mineral dust concentration. We found that only an index correlates uniquely with snow algae: the scaled band integral at 680 nm. A new spectral index, namely the Green Blue Normalized Index, is therefore proposed to discriminate mineral dust from snow algae when both impurities are present. The high spectral resolution of current (e.g. PRISMA, EnMAP) and future (e.g. CHIME, SBG) hyperspectral satellite missions will be fundamental to decouple the effect of mineral dust and snow algae on the optical properties of snow. In fact, from those data it is possible to calculate all narrowband indices presented in this study.

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.

Accurate surface soil moisture (SM) data are crucial for agricultural management in Jiangsu Province, one of the major agricultural regions in China. However, the seasonal performance of different SM products in Jiangsu is still unknown. To address this, this study aims to evaluate the applicability of four L-band microwave remotely sensed SM products, namely, the Soil Moisture Active Passive Single-Channel Algorithm at Vertical Polarization Level 3 (SMAP SCA-V L3, hereafter SMAP-L3), SMOS-SMAP-INRAE-BORDEAUX (SMOSMAP-IB), Soil Moisture and Ocean Salinity in version IC (SMOS-IC), and SMAP-INRAE-BORDEAUX (SMAP-IB) in Jiangsu at the seasonal scale. In addition, the effects of dynamic environmental variables such as the leaf vegetation index (LAI), mean surface soil temperature (MSST), and mean surface soil wetness (MSSM) on the performance of the above products are investigated. The results indicate that all four SM products exhibit significant seasonal differences when evaluated against in situ observations between 2016 and 2022, with most products achieving their highest correlation (R) and unbiased root-mean-square difference (ubRMSD) scores during the autumn. Conversely, their performance significantly deteriorates in the summer, with ubRMSD values exceeding 0.06 m3/m3. SMOS-IC generally achieves better R values across all seasons but has limited temporal availability, while SMAP-IB typically has the lowest ubRMSD values, even reaching 0.03 m3/m3 during morning observation in the winter. Additionally, the sensitivity of different products' skill metrics to environmental factors varies across seasons. For ubRMSD, SMAP-L3 shows a general increase with LAI across all four seasons, while SMAP-IB exhibits a notable increase as the soil becomes wetter in the summer. Conversely, wet conditions notably reduce the R values during autumn for most products. These findings are expected to offer valuable insights for the appropriate selection of products and the enhancement of SM retrieval algorithms.

The risk of carbon emissions from permafrost is linked to an increase in ground temperature and thus in particular to thermal insulation by vegetation, soil layers and snow cover. Ground insulation can be influenced by the presence of large herbivores browsing for food in both winter and summer. In this study, we examine the potential impact of large herbivore presence on the soil carbon storage in a thermokarst landscape in northeastern Siberia. Our aim in this pilot study is to conduct a first analysis on whether intensive large herbivore grazing may slow or even reverse permafrost thaw by affecting thermal insulation through modifying ground cover properties. As permafrost soil temperatures are important for organic matter decomposition, we hypothesize that herbivory disturbances lead to differences in ground-stored carbon. Therefore, we analyzed five sites with a total of three different herbivore grazing intensities on two landscape forms (drained thermokarst basin, Yedoma upland) in Pleistocene Park near Chersky. We measured maximum thaw depth, total organic carbon content, delta C-13 isotopes, carbon-nitrogen ratios, and sediment grain-size composition as well as ice and water content for each site. We found the thaw depth to be shallower and carbon storage to be higher in intensively grazed areas compared to extensively and non-grazed sites in the same thermokarst basin. First data show that intensive grazing leads to a more stable thermal ground regime and thus to increased carbon storage in the thermokarst deposits and active layer. However, the high carbon content found within the upper 20 cm on intensively grazed sites could also indicate higher carbon input rather than reduced decomposition, which requires further studies including investigations of the hydrology and general ground conditions existing prior to grazing introduction. We explain our findings by intensive animal trampling in winter and vegetation changes, which overcompensate summer ground warming. We conclude that grazing intensity-along with soil substrate and hydrologic conditions-might have a measurable influence on the carbon storage in permafrost soils. Hence the grazing effect should be further investigated for its potential as an actively manageable instrument to reduce net carbon emission from permafrost.

The role of atmospheric aerosols in earth's radiative balance is crucial. A thorough knowledge about the spectral optical properties of various types of aerosols is necessary to quantify the net radiative forcing produced by aerosol-light interactions. In this study, we exploited an open-source inverse algorithm based on the Python-PyMieScatt survey iteration method, to retrieve the wavelength dependent Mie-equivalent complex refractive indices of ambient aerosols. This method was verified by obtaining the broadband complex refractive indices of monodisperse polystyrene latex spheres and polydisperse common salt aerosols, using laboratory data collected with a supercontinuum broadband cavity enhanced extinction spectrometer operating in the 420-540 nm wavelength range. Field measurements of ambient aerosol were conducted using a similar cavity enhanced extinction spectrometer (IBBCEES) operating in the wavelength range of 400-550 nm, a multi-wavelength aethalometer, and a scanning mobility particle sizer, in Changzhou city, People's Republic of China. The absorption coefficients for the entire wavelength range were retrieved using the absorption Angstrom exponents calculated from a pair of measured absorption coefficients at known wavelengths. The survey iteration method takes scattering and absorption coefficients, wavelength, and size distributions as inputs; and it calculates the Mie-equivalent wavelength dependent complex refractive index (RI = n +/- ik) and estimated errors. The retrieved field RI values ranged from 1.66 <= n <= 1.80 to 1.65 <= n <= 1.86 and from 0.036 <= k <= 0.038 to 0.062 <= k <= 0.067 in the wavelength range (400-550 nm), for low and high aerosol loading conditions, respectively. Additionally, we derived the spectral dependencies of scattering and absorption coefficients along with the n and k Angstrom exponents (AE). The nAE and kAE estimated values suggest a stronger wavelength dependence for aerosol light scattering compared to absorption, and a decreasing trend for the spectrally dependent single scattering albedo during both loading conditions. The extremum of errors in the retrieved n and k values were quantified by considering (a) uncertainties in input parameters in the broad spectral region (400-550 nm), (b) using CAPS extinction values at 530 nm and (c) an estimated size distribution incorporating the coarse particles (at 530 nm).

Portable aethalometers are commonly used for online measurements of light-absorbing carbonaceous particles (LAC). However, they require strict calibration. In this study, the performance of a micro-aethalometer (MA200 with polytetrafluoroethylene filter) in charactering brown carbon aerosol (BrC) absorption was evaluated in comparison with reference materials and techniques that included bulk solution absorbance and Mie-theory based particle extinction retrieval via broadband cavity enhanced spectrometer (BBCES). Continuous-wavelength resolved (300-650 nm) imaginary refractive index (k(BrC)) was derived with these methods for various BrC proxies and standard materials representing a wide range of sources and absorbing abilities, including the strongly absorbing nigrosin, pahokee peat fluvic acid (PPFA), tar aerosol from wood pyrolysis, humic-like substance (HULIS) separated from wood smoldering burning emissions, and secondary organic aerosols (SOA) from photochemical oxidation of indole and naphthalene in the presence of NOx. The BrC and nigrosin optical results by bulk solution absorption are comparable with the properties retrieved from BBCES. The MA200 raw measurements provide reliable absorption Angstrom exponent (AAE) but overestimate kBrC largely. The parameterized overestimates against reference methods depend on light absorption strength, so that the MA200 overestimates more for the less absorbing BrC. The correction factor for MA200 can be expressed well as an exponential function of kBrC or particle single scattering albedo (SSA), and also as a power-law function of the MA200 raw results derived BrC mass absorption efficiency (MAE). The ensemble correction factor regressed for all these BrC and nigrosin is 2.8 based on bulk absorption and 2.7 using BBCES result as reference. Simple radiative forcing (SRF) calculations for different scenarios using the correction for MA200, show consistent SRF when using the aethalometer results after the k(BrC)-dependent correction. (C) 2021 Elsevier B.V. All rights reserved.

For summer-accumulation-type glaciers, the glaciological literature is lacking studies on determining the snow line altitude (SLA) from optical images at the end of the summer as an indicator of the equilibrium line altitude (ELA). This paper presents a workflow for extracting the SLA from Landsat images based on the variation in the albedo with the altitude in the central line area of glaciers. The correlation of >0.8 at the 99% confidence level between the retrieved SLAs with ELAs derived from the interpolation of ground-based, mass balance measurements indicated that the workflow can be applied to derive the SLA from end-of-summer satellite data as an indicator of ELA. The ELA was under-estimated by the calculated SLA. The relationship between the end-of-summer SLA and the ELA depends on the intensity of glacier melting. Subsequently, the workflow was applied to the seven glaciers in the Eastern Tien Shan Mountains, and a time series of the SLA was obtained using 12 end-of-summer Landsat scenes from 1994 to 2016. Over the whole study period, a mean SLA of 4011.6 +/- 20.7 m above sea level (a.s.l.) was derived for the seven investigated glaciers, and an increasing SLA was demonstrated. The increase in SLAs was consistent for the seven glaciers from 1994 to 2016. Concerning the spatial variability, the east-west difference was prominent, and these differences exhibited a decreasing trend. The average SLA of each glacier is more influenced by its morpho-topographic variables. The interannual variations in the average SLA are mainly driven by the increasing summer air temperature, and the high correlation with the cumulative summer solid precipitation reflects the characteristics of the summer-accumulation-type glaciers.

Black carbon (BC) aerosol has a strong radiative forcing effect and significantly affects human beings and the environment. Therefore, it is important to quantitatively calculate its direct radiative effect (BC DRE) at the surface (SFC) and the top of the atmosphere (TOA). Current studies mainly use empirical formula methods or broadband methods to calculate BC DRE. However, these two methods do not consider the differences of sky diffuse light ratios in different wavelength bands. To overcome this problem, a new scheme named the multiband synthetic method is proposed to calculate blue sky albedo at MODIS narrow bands, and then, the blue sky albedo at the whole shortwave band is synthesized with these separate narrowband blue sky albedos. Based on BC concentration measured in Xuzhou over two years (from May 2014 to July 2016), aerosol optical depth (AOD) and microphysical parameters provided by AERONET, and the black sky albedo (BSA) and white sky albedo (WSA) provided by Google Earth Engine (GEE) products, shortwave BC DRE was calculated numerically with the use of the 6S radiative transfer model. The range of BC DRE computed by the multiband synthetic method at the TOA and SFC are 0.84 +/- 0.08 to 3.27 +/- 1.01W/m(2) and -14.57 +/- 4.53 to -4.31 +/- 0.36W/m(2). The shortwave BC DRE calculated by the multiband synthetic method was higher than that calculated with the broadband method and empirical formula method by 0.11% to 0.36% (at the SFC), 0.14% to 1.4% (at the SFC) and 3.4% to 10.1% (at the TOA), 5.5% to 15.8% (at the TOA), respectively. The BC DREs calculated by these three methods have small differences at the SFC. However, the difference was large at the TOA. The results of this study suggest that it is important to consider the differences between different narrow bands when calculating the broadband shortwave blue sky albedo. (C) 2020 Elsevier B.V. All rights reserved.