Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack

The broadband albedo of surface snow is determined both by the near-surface profile of the physical and chemical properties of the snowpack and by the spectral and angular characteristics of the incident solar radiation. Simultaneous measurements of the physical and chemical properties of snow were carried out at Summit Camp, Greenland (72°36´ N, 38°25´ W, 3210 m a.s.l.) in May and June 2011, along with spectral albedo measurements. One of the main objectives of the field campaign was to test our ability to predict snow spectral albedo by comparing the measured albedo to the albedo calculated with a radiative transfer model, using measured snow physical and chemical properties. To achieve this goal, we made daily measurements of the snow spectral albedo in the range 350–2200 nm and recorded snow stratigraphic information down to roughly 80 cm. The snow specific surface area (SSA) was measured using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement, Gallet et al., 2009). Samples were also collected for chemical analyses including black carbon (BC) and dust, to evaluate the impact of light absorbing particulate matter in snow. This is one of the most comprehensive albedo-related data sets combining chemical analysis, snow physical properties and spectral albedo measurements obtained in a polar environment. The surface albedo was calculated from density, SSA, BC and dust profiles using the DISORT model (DIScrete Ordinate Radiative Transfer, Stamnes et al., 1988) and compared to the measured values. Results indicate that the energy absorbed by the snowpack through the whole spectrum considered can be inferred within 1.10%. This accuracy is only slightly better than that which can be obtained considering pure snow, meaning that the impact of impurities on the snow albedo is small at Summit. In the near infrared, minor deviations in albedo up to 0.014 can be due to the accuracy of radiation and SSA measurements and to the surface roughness, whereas deviations up to 0.05 can be explained by the spatial heterogeneity of the snowpack at small scales, the assumption of spherical snow grains made for DISORT simulations and the vertical resolution of measurements of surface layer physical properties. At 1430 and around 1800 nm the discrepancies are larger and independent of the snow properties; we propose that they are due to errors in the ice refractive index at these wavelengths. This work contributes to the development of physically based albedo schemes in detailed snowpack models, and to the improvement of retrieval algorithms for estimating snow properties from remote sensing data

Overview paper: New insights into aerosol and climate in the Arctic

Motivated by the need to predict how the Arctic atmosphere will change in a warming world, this article summarizes recent advances made by the research consortium NETCARE (Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments) that contribute to our fundamental understanding of Arctic aerosol particles as they relate to climate forcing. The overall goal of NETCARE research has been to use an interdisciplinary approach encompassing extensive field observations and a range of chemical transport, earth system, and biogeochemical models. Several major findings and advances have emerged from NETCARE since its formation in 2013. (1) Unexpectedly high summertime dimethyl sulfide (DMS) levels were identified in ocean water (up to 75&thinsp;nM) and the overlying atmosphere (up to 1&thinsp;ppbv) in the Canadian Arctic Archipelago (CAA). Furthermore, melt ponds, which are widely prevalent, were identified as an important DMS source (with DMS concentrations of up to 6&thinsp;nM and a potential contribution to atmospheric DMS of 20&thinsp;% in the study area). (2) Evidence of widespread particle nucleation and growth in the marine boundary layer was found in the CAA in the summertime, with these events observed on 41&thinsp;% of days in a 2016 cruise. As well, at Alert, Nunavut, particles that are newly formed and grown under conditions of minimal anthropogenic influence during the months of July and August are estimated to contribute 20&thinsp;% to 80&thinsp;% of the 30–50&thinsp;nm particle number density. DMS-oxidation-driven nucleation is facilitated by the presence of atmospheric ammonia arising from seabird-colony emissions, and potentially also from coastal regions, tundra, and biomass burning. Via accumulation of secondary organic aerosol (SOA), a significant fraction of the new particles grow to sizes that are active in cloud droplet formation. Although the gaseous precursors to Arctic marine SOA remain poorly defined, the measured levels of common continental SOA precursors (isoprene and monoterpenes) were low, whereas elevated mixing ratios of oxygenated volatile organic compounds (OVOCs) were inferred to arise via processes involving the sea surface microlayer. (3) The variability in the vertical distribution of black carbon (BC) under both springtime Arctic haze and more pristine summertime aerosol conditions was observed. Measured particle size distributions and mixing states were used to constrain, for the first time, calculations of aerosol–climate interactions under Arctic conditions. Aircraft- and ground-based measurements were used to better establish the BC source regions that supply the Arctic via long-range transport mechanisms, with evidence for a dominant springtime contribution from eastern and southern Asia to the middle troposphere, and a major contribution from northern Asia to the surface. (4) Measurements of ice nucleating particles (INPs) in the Arctic indicate that a major source of these particles is mineral dust, likely derived from local sources in the summer and long-range transport in the spring. In addition, INPs are abundant in the sea surface microlayer in the Arctic, and possibly play a role in ice nucleation in the atmosphere when mineral dust concentrations are low. (5) Amongst multiple aerosol components, BC was observed to have the smallest effective deposition velocities to high Arctic snow (0.03&thinsp;cm&thinsp;s−1).</p

Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study

Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe

Summertime evolution of snow specific surface area close to the surface on the Antarctic Plateau

On the Antarctic Plateau, snow specific surface area (SSA) close to the surface shows complex variations at daily to seasonal scales which affect the surface albedo and in turn the surface energy budget of the ice sheet. While snow metamorphism, precipitation and strong wind events are known to drive SSA variations, usually in opposite ways, their relative contributions remain unclear. Here, a comprehensive set of SSA observations at Dome C is analysed with respect to meteorological conditions to assess the respective roles of these factors. The results show an average 2-to-3-fold SSA decrease from October to February in the topmost 10 cm in response to the increase of air temperature and absorption of solar radiation in the snowpack during spring and summer. Surface SSA is also characterized by significant daily to weekly variations due to the deposition of small crystals with SSA up to 100 m² kg⁻¹ onto the surface during snowfall and blowing snow events. To complement these field observations, the detailed snowpack model Crocus is used to simulate SSA, with the intent to further investigate the previously found correlation between interannual variability of summer SSA decrease and summer precipitation amount. To this end, some Crocus parameterizations have been adapted to Dome C conditions, and the model was forced by ERA-Interim reanalysis. It successfully matches the observations at daily to seasonal timescales, except for the few cases when snowfalls are not captured by the reanalysis. On the contrary, the interannual variability of summer SSA decrease is poorly simulated when compared to 14 years of microwave satellite data sensitive to the near-surface SSA. A simulation with disabled summer precipitation confirms the weak influence in the model of the precipitation on metamorphism, with only 6 % enhancement. However, we found that disabling strong wind events in the model is sufficient to reconciliate the simulations with the observations. This suggests that Crocus reproduces well the contributions of metamorphism and precipitation on surface SSA, but snow compaction by the wind might be overestimated in the model

Simulating snow redistribution and its effect on ground surface temperature at a high‐Arctic site on Svalbard

In high‐latitude and mountain regions, local processes such as redistribution by wind, snow metamorphism and percolation of water, produce a complex spatial distribution of snow depths and snow densities. With its strong control on the ground thermal regime, this snow distribution has pronounced effects on ground temperatures at small spatial scales which are typically not resolved by land surface models (LSMs). This limits our ability to simulate the local impacts of climate change on for example vegetation and permafrost. Here, we present a tiling approach combining the CryoGrid permafrost model with snow microphysics parametrizations from the CROCUS snow scheme to account for sub‐grid lateral exchange of snow and water in a process‐based way. We demonstrate that a simple setup with three coupled tiles, each representing a different snow accumulation class with a specific topographic setting, can reproduce the observed spread of winter‐time ground surface temperatures (GST) and end‐of‐season snow distribution for a high‐Arctic site on Svalbard. For the three‐year study period, the three‐tile simulations showed substantial improvement compared to traditional single‐tile simulations which naturally cannot account for sub‐grid variability. Amongst others, the representation of the warmest and coldest 5% of the observed GST distribution was improved by 1‐2°C, while still capturing the average of the distribution. The simulations also reveal positive mean annual GSTs at the locations receiving the greatest snow cover. This could be an indication for the onset of localized permafrost degradation which would be obscured in single‐tile simulations

Influence of grain shape on light penetration in snow

The energy budget and the photochemistry of a snowpack depend greatly on the penetration of solar radiation in snow. Below the snow surface, spectral irradiance decreases exponentially with depth with a decay constant called the asymptotic flux extinction coefficient. As with the albedo of the snowpack, the asymptotic flux extinction coefficient depends on snow grain shape. While representing snow by a collection of spherical particles has been successful in the numerical computation of albedo, such a description poorly explains the decrease of irradiance in snow with depth. Here we explore the limits of the spherical representation. Under the assumption of geometric optics and weak absorption by snow, the grain shape can be simply described by two parameters: the absorption enhancement parameter <i>B</i> and the geometric asymmetry factor <i>g</i>^G. Theoretical calculations show that the albedo depends on the ratio <i>B</i>/(1-<i>g</i>^G) and the asymptotic flux extinction coefficient depends on the product <i>B</i>(1-<i>g</i>^G). To understand the influence of grain shape, the values of <i>B</i> and <i>g</i>^G are calculated for a variety of simple geometric shapes using ray tracing simulations. The results show that <i>B</i> and (1-<i>g</i>^G) generally covary so that the asymptotic flux extinction coefficient exhibits larger sensitivity to the grain shape than albedo. In particular it is found that spherical grains propagate light deeper than any other investigated shape. In a second step, we developed a method to estimate <i>B</i> from optical measurements in snow. A multi-layer, two-stream, radiative transfer model, with explicit grain shape dependence, is used to retrieve values of the <i>B</i> parameter of snow by comparing the model to joint measurements of reflectance and irradiance profiles. Such measurements were performed in Antarctica and in the Alps yielding estimates of <i>B</i> between 0.8 and 2.0. In addition, values of <i>B</i> were estimated from various measurements found in the literature, leading to a wider range of values (1.0–9.9) which may be partially explained by the limited accuracy of the data. This work highlights the large variety of snow microstructure and experimentally demonstrates that spherical grains, with <i>B</i> = 1.25, are inappropriate to model irradiance profiles in snow, an important result that should be considered in further studies dedicated to subsurface absorption of short-wave radiation and snow photochemistry

Airborne observations of far-infrared upwelling radiance in the Arctic

The first airborne measurements of the Far-InfraRed Radiometer (FIRR) were performed in April 2015 during the panarctic NETCARE campaign. Vertical profiles of spectral upwelling radiance in the range 8–50 µm were measured in clear and cloudy conditions from the surface up to 6 km. The clear sky profiles highlight the strong dependence of radiative fluxes to the temperature inversion typical of the Arctic. Measurements acquired for total column water vapour from 1.5 to 10.5 mm also underline the sensitivity of the far-infrared greenhouse effect to specific humidity. The cloudy cases show that optically thin ice clouds increase the cooling rate of the atmosphere, making them important pieces of the Arctic energy balance. One such cloud exhibited a very complex spatial structure, characterized by large horizontal heterogeneities at the kilometre scale. This emphasizes the difficulty of obtaining representative cloud observations with airborne measurements but also points out how challenging it is to model polar clouds radiative effects. These radiance measurements were successfully compared to simulations, suggesting that state-of-the-art radiative transfer models are suited to study the cold and dry Arctic atmosphere. Although FIRR in situ performances compare well to its laboratory performances, complementary simulations show that upgrading the FIRR radiometric resolution would greatly increase its sensitivity to atmospheric and cloud properties. Improved instrument temperature stability in flight and expected technological progress should help meet this objective. The campaign overall highlights the potential for airborne far-infrared radiometry and constitutes a relevant reference for future similar studies dedicated to the Arctic and for the development of spaceborne instruments

On the relationship between <i>δ</i>O₂∕N₂ variability and ice sheet surface conditions in Antarctica

International audienceWhile the processes controlling pore closure are broadly understood, the physical mechanisms driving the associated elemental fractionation remains ambiguous. Previous studies have shown that the pore closure process leads to a depletion in small-sized molecules (e.g. H 2 , O 2 , Ar, Ne, He) in ice core bubbles relative to larger-sized molecules like N 2 . This size-dependent fractionation, identified using ice core δ(O 2 /N 2 ) records, exhibits a clear anti-correlation with local summer solstice insolation, making δ(O 2 /N 2 ) a valuable ice core dating tool. Mechanisms controlling this relationship are attributed to the physical properties of deep firn. In this study, we compile δ(O 2 /N 2 ) records from 15 polar ice cores and show a new additional link between δ(O 2 /N 2 ) and local surface temperature and/or accumulation rate. Using the Crocus snowpack model, we perform sensitivity tests to identify the response of near-surface snow properties to changes in insolation intensity, accumulation rate, and air temperature. These tests support a mechanism linked to firn grain size, such that the larger the grain size for a given density, the stronger the pore closure fractionation and, hence, the lower the δ(O 2 /N 2 ) values archived in the ice. Based on both snowpack model outputs and data compilation, our findings suggest that local accumulation rate and temperature should be considered when interpreting δ(O 2 /N 2 ) as a local insolation proxy.</div