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What are the main findings? * MODIS MCD43A3 daily albedo is in good agreement with in situ measurements at THAAO, in northwestern Greenland. * The agreement is excellent in snow-free days and worst for mixed and snow-covered conditions. MODIS MCD43A3 daily albedo is in good agreement with in situ measurements at THAAO, in northwestern Greenland. The agreement is excellent in snow-free days and worst for mixed and snow-covered conditions. What are the implications of the main findings * MODIS albedo product has limitations when fast changes in albedo are occurring. * The use of MODIS albedo values with best-quality flags is recommended. MODIS albedo product has limitations when fast changes in albedo are occurring. The use of MODIS albedo values with best-quality flags is recommended. The surface albedo, α, is one of the key climate parameters since it regulates the shortwave radiation absorbed by the Earth’s surface. An accurate determination of the albedo is crucial in the polar regions due to its variations associated with climate change and its role in the strong feedback mechanisms. In this work, satellite and in situ measurements of broadband surface albedo at the Thule High Arctic Atmospheric Observatory (THAAO) on the northwestern coast of Greenland (76.5°N, 68.8°W) are compared. Measurements of surface albedo were started at THAAO in 2016. They show a large variability mainly in the transition seasons, suggesting that THAAO is a very interesting site for verifying the satellite capabilities in challenging conditions. The comparison of daily ground-based and MODIS-derived albedo covers the period July 2016–October 2024. The analysis has been conducted for all-sky and cloud-free conditions. The mean bias and mean squared difference between the two datasets are −0.02 and 0.09, respectively, for all sky conditions and −0.03 and 0.06 for cloud-free conditions. Very good agreement is found in summer in snow-free conditions, when the mean albedo is 0.17 in both datasets under cloud-free conditions. On the contrary, the capability to determine the surface albedo from space is largely reduced in the transition seasons, when significant differences between ground- and satellite-based albedo estimates are found. Differences for all-sky conditions may be as large as 0.3 in spring and autumn. These maximum differences are significantly reduced for cloud-free conditions, although a negative bias of MODIS data with respect to measurements at THAAO is generally found in spring. The combined analysis of the albedo, cloudiness, air temperature, and precipitation characteristics during two periods in 2023 and 2024 shows that, although satellite observations provide a reasonable picture of the long-term albedo evolution, they are not capable of following fast changes in albedo values induced by precipitation of snow/rain or temperature variations. Moreover, as expected, cloudiness plays a large role in affecting the satellite capabilities. The use of MODIS albedo data with the best value of the quality assurance flag (equal to 0) is recommended for studies aimed at determining the daily evolution of the surface radiation and energy budget.

Examining the composition of aerosols in Antarctic ice cores can provide insights into past atmospheric circulation. However, interpreting this data requires an understanding of the characteristics and variability of present-day aerosols over time. In 2019, we performed the first year-round, multiparametric optical characterisation of atmospheric aerosols at Concordia Station in East Antarctica using OPTAIR, a novel instrument based on the Single Particle Extinction and Scattering (SPES) technique. We compared this data with the chemical composition of PM10 samples collected at the site and with meteorological data. We also compared it with synchronous data from a LIDAR and a ceilometer operating at Concordia Station. Significant temporal irregularities were observed in the atmospheric aerosol load, with more than one-third of the particles being dry-deposited during brief air mass subsidence events (‘spikes’), which mainly occurred in winter. The aerosol particles detected during these events were primarily composed of sea salt. Their optical properties differ significantly depending on whether they originate from frost flowers or the open ocean. Due to the intermittent nature of aerosol advection to Antarctica and its radiative effect, we estimate that glaciological, time-integrated samples may lead to an overestimation of light extinction by a factor of 3.5 or more.

Knowledge of the precipitation contribution to the Antarctic surface mass balance is essential for defining the ice-sheet contribution to sea-level rise. Observations of precipitation are sparse over Antarctica, due to harsh environmental conditions. Precipitation during the summer months (November–December–January) on four expeditions, 2015–16, 2016–17, 2017–18 and 2018–19, in the Terra Nova Bay area, were monitored using a vertically pointing radar, disdrometer, snow gauge, radiosounding and an automatic weather station installed at the Italian Mario Zucchelli Station. The relationship between radar reflectivity and precipitation rate at the site can be estimated using these instruments jointly. The error in calculated precipitation is up to 40%, mostly dependent on reflectivity variability and disdrometer inability to define the real particle fall velocity. Mean derived summer precipitation is ~55 mm water equivalent but with a large variability. During collocated measurements in 2018–19, corrected snow gauge amounts agree with those derived from the relationship, within the estimated errors. European Centre for the Medium-Range Weather Forecasts (ECMWF) and the Antarctic Mesoscale Prediction System (AMPS) analysis and operational outputs are able to forecast the precipitation timing but do not adequately reproduce quantities during the most intense events, with overestimation for ECMWF and underestimation for AMPS.

Boreal fires have increased during the last years and are projected to become more intense and frequent as a consequence of climate change. Wildfires produce a wide range of effects on the Arctic climate and ecosystem, and understanding these effects is crucial for predicting the future evolution of the Arctic region. This study focuses on the impact of the long-range transport of biomass-burning aerosol into the atmosphere and the corresponding radiative perturbation in the shortwave frequency range. As a case study, we investigate an intense biomass-burning (BB) event which took place in summer 2017 in Canada and subsequent northeastward transport of gases and particles in the plume leading to exceptionally high values (0.86) of Aerosol Optical Depth (AOD) at 500 nm measured in northwestern Greenland on 21 August 2017. This work characterizes the BB plume measured at the Thule High Arctic Atmospheric Observatory (THAAO; 76.53∘N, 68.74∘W) in August 2017 by assessing the associated shortwave aerosol direct radiative impact over the THAAO and extending this evaluation over the broader region (60∘N–80∘N, 110∘W–0∘E). The radiative transfer simulations with MODTRAN6.0 estimated an aerosol heating rate of up to 0.5 K/day in the upper aerosol layer (8–12 km). The direct aerosol radiative effect (ARE) vertical profile shows a maximum negative value of −45.4 Wm−2 for a 78∘ solar zenith angle above THAAO at 3 km altitude. A cumulative surface ARE of −127.5 TW is estimated to have occurred on 21 August 2017 over a portion (∼3.1×106 km2) of the considered domain (60∘N–80∘N, 110∘W–0∘E). ARE regional mean daily values over the same portion of the domain vary between −65 and −25 Wm−2. Although this is a limited temporal event, this effect can have significant influence on the Arctic radiative budget, especially in the anticipated scenario of increasing wildfires.

Snow plays a crucial role in the hydrological cycle and energy budget of the Earth, and remote sensing instruments with the necessary spatial coverage, resolution, and temporal sampling are essential for snowfall monitoring. Among such instruments, ground-radars have scanning capability and a resolution that make it possible to obtain a 3D structure of precipitating systems or vertical profiles when used in profiling mode. Radars from space have a lower spatial resolution, but they provide a global view. However, radar-based quantitative estimates of solid precipitation are still a challenge due to the variability of the microphysical, geometrical, and electrical features of snow particles. Estimations of snowfall rate are usually accomplished using empirical, long-term relationships between the equivalent radar reflectivity factor (Ze) and the liquid-equivalent snowfall rate (SR). Nevertheless, very few relationships take advantage of the direct estimation of the microphysical characteristics of snowflakes. In this work, we used a K-band vertically pointing radar collocated with a laser disdrometer to develop Ze-SR relationships as a function of snow classification. The two instruments were located at the Italian Antarctic Station Mario Zucchelli. The K-band radar probes the low-level atmospheric layers, recording power spectra at 32 vertical range gates. It was set at a high vertical resolution (35 m), with the first trusted range gate at a height of only 100 m. The disdrometer was able to provide information on the particle size distribution just below the trusted radar gate. Snow particles were classified into six categories (aggregate, dendrite aggregate, plate aggregate, pristine, dendrite pristine, plate pristine). The method was applied to the snowfall events of the Antarctic summer seasons of 2018–2019 and 2019–2020, with a total of 23,566 min of precipitation, 15.3% of which was recognized as showing aggregate features, 33.3% dendrite aggregate, 7.3% plates aggregate, 12.5% pristine, 24% dendrite pristine, and 7.6% plate pristine. Applying the appropriate Ze-SR relationship in each snow category, we calculated a total of 87 mm water equivalent, differing from the total found by applying a unique Ze-SR. Our estimates were also benchmarked against a colocated Alter-shielded weighing gauge, resulting in a difference of 3% in the analyzed periods.

Size-fractionated particulate mercury (PHg) measurements were performed from November 2017 to January 2018 at Terra Nova Bay (Antarctica) for the first time. Samples were collected every 10 days by a six-stage high-volume cascade impactor with size classes between 10 μm and 0.49 μm. Total PHg concentrations were maxima (87 ± 8 pg m−3) in November, then decreased to values ~40% lower and remained almost constant until the end of the sampling period (~30 pg m−3). The trimodal aerosol mass distribution reveals that from 30% to 90% of the total PHg came in the size > 1.0 μm. Hg in the two coarse fractions was probably produced by the adsorption of oxidized Hg species transported by air masses from the Antarctic plateau or produced locally by sea ice edges. PHg in accumulation mode seemed to be related to gas–particle partitioning with sea salt aerosol. Finally, average dry deposition fluxes of PHg were calculated to be 0.36 ± 0.21 ng m−2 d−1 in the accumulation mode, 47 ± 44 ng m−2 d−1 in the first coarse mode, and 37 ± 31 ng m−2 d−1 in the second coarse mode. The present work contributed to the comprehension of the Hg biogeochemical cycle, but further research studies are needed.

Numerical weather prediction models require an accurate parametrization of the energy budget at the air-ground interface, that can be obtained only through long-term atmospheric boundary layer measurements at different spatial and temporal scales. Despite their importance, such measurements are still scarce even in well-characterized areas. In this paper, a three-year dataset from four micrometeorological stations run by the Regional Agency for Environmental Protection of Lazio was analyzed to estimate albedo, zero-displacement height, roughness length and surface properties over Rome and its suburbs, characterizing differences and interconnections between urban, suburban and rural areas of the same municipality. The integral albedo coefficient at the zenith for the urban station was found to be almost twice that for suburban and rural stations. The zero-displacement height of the urban site was strongly dependent on wind direction, with values varying between 12.0 and 17.8 m, while the roughness length (≈1.5 m) was almost independent of upwind direction, but it was significantly higher than the typical values calculated for rural stations (≈0.4 m). The apparent thermal capacities and thermal conductivity at all the non-urban sites were in fair agreement with each other and typical of soils with relatively low water content, as expected for a relatively dry Mediterranean area like Rome, while the apparent thermal diffusivity reflected the presence of different soil types.

Here we present the first multi-year record of nitrate in the atmospheric aerosol (2005-2008) and surface snow (2006-08) from central Antarctica. PM10 and size-segregated aerosol, together with superficial snow, have been collected all year-round at high resolution (daily for all the snow samples and for most of aerosol samples) at Dome C since the 2004/05 field season and analysed for main and trace ionic markers. The suitability of the sampling location in terms of possible contamination from the base is shown in detail. In spite of the relevance of nitrate in Antarctic atmosphere, both for better understanding the chemistry of N cycle in the plateau boundary layer and for improving the interpretation of long-term nitrate records from deep ice core records, nitrate sources in Antarctica are not well constrained yet, neither in extent nor in timing. A recurring seasonal pattern was pointed out in both aerosol and snow records, showing summer maxima and winter minima, although aerosol maxima lead the snow ones of 1-2 months, possibly due to a higher acidity in the atmosphere in mid-summer, favouring the repartition of nitrate as nitric acid and thus its uptake by the surface snow layers. On the basis of a meteorological analysis of one major nitrate event, of data related to PSC I extent and of irradiance values, we propose that the high nitrate summer levels in aerosol and snow are likely due to a synergy of enhanced source of nitrate and/or its precursors (such as the stratospheric inputs), higher solar irradiance and higher oxidation rates in this season. Moreover, we show here a further evidence of the substantial contribution of HNO 3 /NOx re-emission from the snowpack, already shown in previous works, and which can explain a significant fraction of atmospheric nitrate, maintaining the same seasonal pattern in the snow. As concerning snow specifically, the presented data suggest that nitrate is likely to be controlled mainly by atmospheric processes, not on the daily timescale but rather on the seasonal one.

In this study, surface mass balance (SMB) is estimated from snow accumulation data collected in the nearby area of Concordia Station, Antarctica. Results from the Italian and French stake farms are jointly analysed. The Italian stake farm consists of 13 stakes; continuous observations started at the end of 2010 with near-monthly sampling. Some measurements are also available for the 2006–2010 period from a previous stake farm. The French stake farm consists of 50 stakes; observations started in 2004 with yearly sampling during austral summer. Snow buildup measurements at individual stakes show a strong variability caused by the interaction of wind-driven snow with surface micro-relief. In the common observation period, the present Italian stake farm generally underestimates the SMB with respect to the French one, except for 3 years in which an overestimation is observed. Over the 2011–2023 period, the mean yearly accumulation recorded by the Italian and French stake farms is 7.3 ± 0.2 cm and 8.4 ± 0.1 cm, respectively. Bootstrap simulation has been performed to: (i) assess the significance of the differences between the two datasets; (ii) evaluate the effect on the measurements of the different size of the stake farms and their distance to the Station. The comparison of the observations with reanalysis datasets (ERA5 and MERRA2) and regional models (RACMO2.4p1, MAR3.12) indicates the former more in agreement with the observations. The potential interaction effect of the Station has also been investigated by analysing wind direction during snowfall events, suggesting that buildings may influence accumulation. In fact, in the hyper-arid environment of Dome C, snow accumulation is largely governed by post-depositional processes such as wind redistribution and clear-sky precipitation. Buildings alter the wind field, enhancing erosion beneath them and forming snowdrifts leeward and laterally, which may explain accumulation differences between the ITA and FRA stake fields. Additionally, two more stake farms, located 25 km North and South of Concordia Station, are also analysed to study the SMB gradient across Dome C, confirming previous results. On average, yearly SMB increases northward by 8 %–9 % over the 50 km span between the southern and northern stake farms. At Concordia, for the 2004–2023 period, a mean SMB of 27.21 ± 0.60 kg m−2 has been estimated, taking into account the uncertainty of the observations and of the snow compaction effect. Results are valuable for validating SMB estimated from reanalysis, regional climate models and remote-sensing data.

Ground-based high resolution observations of downward longwave irradiance (DLI), surface air temperature, water vapor surface partial pressure and column amount, zenith sky infrared (IR) radiance in the atmospheric window, and all-sky camera images are regularly obtained at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5° N, 68.8° W), northwestern Greenland. The datasets for the years 2017 and 2018 have been used to assess the performance of different empirical formulas used to infer clear sky DLI. An algorithm to identify clear sky observations has been developed, based on value, variability, and persistence of zenith sky IR radiance. Seventeen different formulas to estimate DLI have been tested against the THAAO dataset, using the originally determined coefficients. The formulas that combine information on total column water vapor and surface air temperature appear to perform better than others, with a mean bias with respect to the measured DLI smaller than 1 W m−2 and a root mean squared error (RMSE) around 6 W m−2. Unexpectedly, some formulas specifically developed for the Arctic are found to produce poor statistical results. This is attributed partly to limitations in the originally used dataset, which does not cover a whole year or is relative to very specific condition (i.e., the presence of an ice sheet). As expected, the bias displays a significant improvement when the coefficients of the different formulas are calculated using the THAAO dataset. The presence of 2 full years of data allows the determination and the applicability of the coefficients for singular years and the evaluation of results. The smallest values of the bias and RMSE reach 0.1 and 5 W m−2, respectively. Overall, the best results are found for formulas that use both surface parameters and total water vapor column content, and have been developed from global datasets. Conversely, formulas that express the atmospheric emissivity as a linear function of the logarithm of the column integrated water vapor appear to reproduce poorly the observations at THAAO.