Search

Sea ice forms a thin but horizontally extensive boundary between the ocean and the atmosphere and has complex, crust-like dynamics characterized by intermittent sea ice deformations. The heterogeneity and localization of these sea ice deformations are important characteristics of the sea ice cover that can be used to evaluate the performance of dynamical sea ice models against observations across multiple spatial and temporal scales. Here, we present a new pan-Arctic sea ice deformation and rotation rate (SIDRR; https://doi.org/10.5281/zenodo.13936609, Plante et al., 2024a) dataset derived from the RADARSAT Constellation Mission (RCM) and Sentinel-1 (S1) synthetic aperture radar (SAR) imagery from 1 September 2017 to 31 August 2023. The SIDRR estimates are derived from contour integrals of triangulated ice motion data, obtained from the Environment and Climate Change Canada automated sea ice tracking system (ECCC-ASITS). The SIDRR dataset is not regularized and consists of stacked data from multiple SAR images computed on a range of spatial (4–10 km) and temporal (0.5–6 d) scales. It covers the entire Arctic Ocean and all peripheral seas except the Okhotsk Sea. Uncertainties associated with the propagation of tracking errors on the deformation values are included. We show that rectangular patterns of deformation features are visible when the sampled deformation rates are lower than the propagation error. This limits the meaningful information that can be extracted in areas with low SIDRR values but allows for the study of linear kinematic features with a high SIDRR signal-to-noise ratio. The spatial coverage and range of resolutions of the SIDRR dataset provide an interesting opportunity to investigate regional and seasonal variability in sea ice deformation statistics across scales, and these data can also be used to determine metrics for model evaluation.

Objetivo: Examinar el uso y los resultados de la anticoagulación perioperatoria en pacientes bariátricos con antecedentes de tromboembolia venosa (TEV). Método: Revisión retrospectiva (base de datos prospectiva) de pacientes sometidos a cirugía general y bariátrica (1/2008-12/2017). Se evaluaron datos demográficos, detalles quirúrgicos y resultados. Resultados: Sesenta y cinco pacientes se sometieron a 76 procedimientos: 46 mujeres (71%), edad media 51 años (rango: 26-73), peso medio 284 libras (rango: 110-558), índice de masa corporal medio 45 (rango: 19-87). Comorbilidad: hipertensión (60%), enfermedad por reflujo gastroesofágico (54%), osteoartritis (49%), apnea obstructiva del sueño (45%), diabetes (37%). Operaciones: 22 cirugía general (29%), 20 gastrectomías en manga (26%), 12 revisiones/conversiones (16%), 12 Y-de-Roux (16%), 10 bandas gástricas (13%). Modalidades: 67% laparoscópica, 28% robótica, 5% abierta. A 22 pacientes (34%) se les colocó un filtro de vena cava inferior preoperatorio sin complicaciones. La estancia media fue de 4.4 días (rango: 1-31). Complicaciones: 7 reingresos a los 30 días (9%), 1 reoperación a los 30 días (1%), 2 TEV a los 90 días (3%). Reingresos a los 30 días: 4 por incapacidad para tolerar la vía oral, 2 obstrucciones de intestino delgado y 1 úlcera anastomótica sintomática. Conclusiones: En nuestros casos, la anticoagulación posoperatoria pudo iniciarse sin aumento del riesgo de sangrado en pacientes con antecedentes de TVE sometidos a cirugía bariátrica.

We present JWST Near Infrared Spectrograph (NIRSpec) measurements of the three largest low-albedo main-belt asteroids: (1) Ceres, (2) Pallas, and (10) Hygiea. Their reflectance spectra all have very similar absorptions centered near 2.72 μ m attributed to Mg–OH in minerals. Within this band, Pallas also shows evidence of a sharper, deeper band, also centered near 2.72 μ m. These band positions are similar to those seen in the most aqueously altered carbonaceous chondrites and samples from Ryugu and Bennu. Absorptions in the 2.7–2.9 μ m region due to other cation–OH combinations are weak, if present. The NIRSpec spectrum of Ceres is consistent with the global average spectrum of Dawn, and the similarity between Ceres and Hygiea seen in other wavelength regions continues into the 2.5–2.8 μ m region. This similarity in spectral properties, and thus in interpretations of surface composition, implies that the two bodies may have had similar processes occur and similar histories. This suggests that Hygiea, similar to Ceres, may be associated with the “ocean worlds” despite its relatively small mass. Quantitative estimates of the hydrogen concentrations on the surfaces suggest hydrogen concentrations of roughly 0.5–1 wt%, consistent with CM chondrites. Additional absorptions attributed to ammoniated minerals are seen in Ceres’s and Hygiea’s spectra, as has been reported by others, but are not seen in Pallas’s spectrum. Absorptions are also seen in the 2.5–2.7 μ m region in all three asteroids, likely due to OH combination bands, and from roughly 3.9 to 4.3 μ m in Hygiea, which could be due to carbonates plus an unidentified constituent.

Data are presented from intercomparisons between two research aircraft, the FAAM BAe-146 and the NASA Lockheed P3, and between the BAe-146 and the surface-based DOE (Department of Energy) ARM (Atmospheric Radiation Measurement) Mobile Facility at Ascension Island (8∘ S, 14.5∘ W; a remote island in the mid-Atlantic). These took place from 17 August to 5 September 2017, during the African biomass burning (BB) season. The primary motivation was to give confidence in the use of data from multiple platforms with which to evaluate numerical climate models. The three platforms were involved in the CLouds–Aerosol–Radiation Interaction and Forcing for Year 2017 (CLARIFY-2017), ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), and Layered Atlantic Smoke and Interactions with Clouds (LASIC) field experiments. Comparisons from flight segments on 6 d where the BAe-146 flew alongside the ARM facility on Ascension Island are presented, along with comparisons from the wing-tip-to-wing-tip flight of the P3 and BAe-146 on 18 August 2017. The intercomparison flight sampled a relatively clean atmosphere overlying a moderately polluted boundary layer, while the six fly-bys of the ARM site sampled both clean and polluted conditions 2–4 km upwind. We compare and validate characterisations of aerosol physical, chemical and optical properties as well as atmospheric radiation and cloud microphysics between platforms. We assess the performance of measurement instrumentation in the field, under conditions where sampling conditions are not as tightly controlled as in laboratory measurements where calibrations are performed. Solar radiation measurements compared well enough to permit radiative closure studies. Optical absorption coefficient measurements from all three platforms were within uncertainty limits, although absolute magnitudes were too low ( Mm−1) to fully support a comparison of the absorption Ångström exponents. Aerosol optical absorption measurements from airborne platforms were more comparable than aircraft-to-ground observations. Scattering coefficient observations compared adequately between airborne platforms, but agreement with ground-based measurements was worse, potentially caused by small differences in sampling conditions or actual aerosol population differences over land. Chemical composition measurements followed a similar pattern, with better comparisons between the airborne platforms. Thermodynamics, aerosol and cloud microphysical properties generally agreed given uncertainties.

This study characterizes single-particle aerosol composition from filters collected during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) and CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017) campaigns. In particular the study describes aged biomass burning aerosol (BBA), its interaction with the marine boundary layer and the influence of biomass burning (BB) air on marine aerosol. The study finds evidence of BBA influenced by marine boundary layer processing as well as sea salt influenced by BB air. Secondary chloride aerosols were observed in clean marine air as well as in BB-influenced air in the free troposphere. Higher-volatility organic aerosol appears to be associated with increased age of biomass burning plumes, and photolysis or oxidation may be a mechanism for the apparent increased volatility. Aqueous processing and interaction with the marine boundary layer air may be a mechanism for the presence of sodium on many aged potassium salts. By number, biomass burning potassium salts and modified sea salts are the most observed particles on filter samples. The most commonly observed BC coatings are inorganic salts. These results suggest that atmospheric processes such as photolysis, oxidation and cloud processing are key drivers in the elemental composition and morphology of aged BBA. Fresh BBA inorganic salt content, as it has an important role in the particles' ability to uptake water, may be a key driver in how aqueous processing and atmospheric aging proceed.

The radar circular polarization ratio (CPR) is an indicator of near-surface, wavelength-scale complexity. Interestingly, previous surveys also noted an association between near-Earth asteroid (NEA) disk-integrated CPR and spectral taxonomic class, potentially reflecting differences in regolith mechanical properties and/or surface histories. Here, using Arecibo S -band radar measurements, we revisit this relationship, as well as associations with orbital and physical parameters, to test the impact of compositional class and surface processes on CPR. We found that the X complex, and potentially V-type NEAs, follow a bimodal CPR distribution, while the other studied taxonomies are unimodal. Considering S, C, Q, L, V, and X types, a CPR ≳ 1 is diagnostic of the high-CPR X complex, which includes all Xe types, while a CPR ≲ 0.4 is shared by S, C, Q, and L types. V types are not reliably identified by CPR alone. The high CPR tied to some X types may be reflective of significant roughness over multiple scales, but further analysis, including experimental insights, is needed to understand this signature. Furthermore, we found strong evidence that Aten NEAs have both a broader distribution and a higher median CPR than objects outside of Earth’s orbit. This may suggest that these Earth-crossing asteroids have their surficial physical properties altered by planetary encounters, indicating that such processes act over centimeter-to-decimeter scales. The 2029 close approach of NEA (99942) Apophis presents a unique opportunity to integrate ground-based radar observations with spacecraft measurements, such as by the Apophis Explorer (OSIRIS-APEX) mission, to reveal how resurfacing events alter NEA radar properties.

Understanding the properties of near-Earth asteroids (NEAs) is key for many aspects of planetary science, particularly planetary defense. Our current knowledge of NEA sizes and regolith properties is heavily dependent on simple thermal models. These models are often used to analyze data from missions such as NEOWISE because they are well suited to deal with large volumes of data. However, simple model results based on NEOWISE data may be inconsistent with results based on other types of observation in some cases. In this work, we seek to better understand these potential inconsistencies, as well as the situations for which they are most prevalent. We do this by comparing simple model results based on Infrared Telescope Facility SpeX data to similar results based on NEOWISE data. This is carried out for six NEAs that represent a range of spectral types, shapes, and rotation states. We find that models based on SpeX and NEOWISE data for these six objects are inconsistent in some cases, even though the SpeX results are consistent with other methods and observations. We find that objects observed at fainter magnitudes and objects with more primitive compositions are more likely to produce inconsistent fits. These results highlight the importance of better understanding the limitations of simple models as applied to large survey data sets like NEOWISE. This is particularly true as we move into an era where our understanding of the NEA population will be dominated by future large surveys such as NEO Surveyor.

We report physical and mutual orbit characteristics of near-Earth binary asteroid (163693) Atira. Using S -band (2380 MHz, 12.6 cm) radar observations from the Arecibo Observatory and several epochs of lightcurve observations from 2003 to 2019 with SHAPE modeling software, we determine the shape, size, rotational period, and mutual orbit of the primary and secondary components and the density of the primary component. We confirm the primary’s sidereal rotation period to be 3.398521 ± 0.000003 hr, and we find a likely spin axis orientation of ecliptic longitude and latitude (187°, −53°) ± 12°. We find the primary’s volume-equivalent diameter to be 4.92 ± 0.95 km and the secondary’s volume-equivalent diameter to be 0.80 ± 0.30 km. We find the primary component’s density to be 1.43 ± 0.87 g cm ^−3 . We also find that the secondary has a semimajor axis of 7.8 ± 0.5 km and a sidereal orbital period of 15.577 ± 0.003 hr based on orbital calculations using delay and Doppler offsets between the primary and secondary and the timing of mutual events observed in lightcurve data. This work represents the first detailed analysis of the shape of an Atira-class asteroid.

In this paper, we use observations from the NASA ORACLES (ObseRvations of CLouds above Aerosols and their intEractionS) aircraft campaign to develop a framework by way of two parameterizations that establishes regionally representative relationships between aerosol-cloud properties and their radiative effects. These relationships rely on new spectral aerosol property retrievals of the single scattering albedo (SSA) and asymmetry parameter (ASY). The retrievals capture the natural variability of the study region as sampled, and both were found to be fairly narrowly constrained (SSA: 0.83 ± 0.03 in the mid-visible, 532 nm; ASY: 0.54 ± 0.06 at 532 nm). The spectral retrievals are well suited for calculating the direct aerosol radiative effect (DARE) since SSA and ASY are tied directly to the irradiance measured in the presence of aerosols – one of the inputs to the spectral DARE. The framework allows for entire campaigns to be generalized into a set of parameterizations. For a range of solar zenith angles, it links the broadband DARE to the mid-visible aerosol optical depth (AOD) and the albedo (α) of the underlying scene (either clouds or clear sky) by way of the first parameterization: P(AOD, α). For ORACLES, the majority of the case-to-case variability of the broadband DARE is attributable to the dependence on the two driving parameters of P(AOD, α). A second, extended, parameterization PX(AOD, α, SSA) explains even more of the case-to-case variability by introducing the mid-visible SSA as a third parameter. These parameterizations establish a direct link from two or three mid-visible (narrowband) parameters to the broadband DARE, implicitly accounting for the underlying spectral dependencies of its drivers. They circumvent some of the assumptions when calculating DARE from satellite products or in a modeling context. For example, the DARE dependence on aerosol microphysical properties is not explicit in P or PX because the asymmetry parameter varies too little from case to case to translate into appreciable DARE variability. While these particular DARE parameterizations only represent the ORACLES data, they raise the prospect of generalizing the framework to other regions.

Local-scale variations in snow density and layering on Arctic sea ice were characterized using a combination of traditional snow pit and SnowMicroPen (SMP) measurements. In total, 14 sites were evaluated within the Canadian Arctic Archipelago and Arctic Ocean on both first-year (FYI) and multi-year (MYI) sea ice. Sites contained multiple snow pits with coincident SMP profiles as well as unidirectional SMP transects. An existing SMP density model was recalibrated using manual density cutter measurements (n=186) to identify best-fit parameters for the observed conditions. Cross-validation of the revised SMP model showed errors comparable to the expected baseline for manual density measurements (RMSE = 34 kg m−3 or 10.9 %) and strong retrieval skill (R2=0.78). The density model was then applied to SMP transect measurements to characterize variations at spatial scales of up to 100 m. A supervised classification trained on snow pit stratigraphy allowed separation of the SMP density estimates by layer type. The resulting dataset contains 58 882 layer-classified estimates of snow density on sea ice representing 147 m of vertical variation and equivalent to more than 600 individual snow pits. An average bulk density of 310 kg m−3 was estimated with clear separation between FYI and MYI environments. Lower densities on MYI (277 kg m−3) corresponded with increased depth hoar composition (49.2 %), in strong contrast to composition of the thin FYI snowpack (19.8 %). Spatial auto-correlation analysis showed layered composition on FYI snowpack to persist over long distances while composition on MYI rapidly decorrelated at distances less than 16 m. Application of the SMP profiles to determine propagation bias in radar altimetry showed the potential errors of 0.5 cm when climatology is used over known snow density.

The surface of active asteroid (3200) Phaethon, parent body of the Geminid meteor shower, reaches temperatures sufficient to destabilize hydrated materials. Here, the authors show that the northern hemisphere and the equatorial region of this asteroid reveal no evidence of hydration in the near-infrared spectra.

Near-Earth asteroids (NEAs) are a key test bed for investigations into planet formation, asteroid dynamics, and planetary defense initiatives. These studies rely on understanding NEA sizes, albedo distributions, and regolith properties. Simple thermal models are a commonly used method for determining these properties; however, they have inherent limitations owing to the simplifying assumptions they make about asteroid shapes and properties. With the recent collapse of the Arecibo Telescope and a decrease of direct size measurements, as well as future facilities such as LSST and NEO Surveyor coming online soon, these models will play an increasingly important role in our knowledge of the NEA population. Therefore, it is key to understand the limits of these models. In this work we constrain the limitations of simple thermal models by comparing model results to more complex thermophysical models, radar data, and other existing analyses. Furthermore, we present a method for placing tighter constraints on inferred NEA properties using simple thermal models. These comparisons and constraints are explored using the NEA (285263) 1998 QE2 as a case study. We analyze QE2 with a simple thermal model and data from both the NASA IRTF SpeX instrument and NEOWISE mission. We determine an albedo between 0.05 and 0.10 and thermal inertia between 0 and 425J m ^−2 s ^−1/2 K ^−1 . We find that overall the simple thermal model is able to well constrain the properties of QE2; however, we find that model uncertainties can be influenced by topography, viewing geometry, and the wavelength range of data used.

Determining the direct aerosol radiative effect (DARE) of absorbing aerosols above clouds from satellite observations alone is a challenging task, in part because the radiative signal of the aerosol layer is not easily untangled from that of the clouds below. In this study, we use aircraft measurements from the NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) project in the southeastern Atlantic to derive it with as few assumptions as possible. This is accomplished by using spectral irradiance measurements (Solar Spectral Flux Radiometer, SSFR) and aerosol optical depth (AOD) retrievals (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research, 4STAR) during vertical profiles (spirals) that minimize the albedo variability of the underlying cloud field – thus isolating aerosol radiative effects from those of the cloud field below. For two representative cases, we retrieve spectral aerosol single scattering albedo (SSA) and the asymmetry parameter (g) from these profile measurements and calculate DARE given the albedo range measured by SSFR on horizontal legs above clouds. For mid-visible wavelengths, we find SSA values from 0.80 to 0.85 and a significant spectral dependence of g. As the cloud albedo increases, the aerosol increasingly warms the column. The transition from a cooling to a warming top-of-aerosol radiative effect occurs at an albedo value (critical albedo) just above 0.2 in the mid-visible wavelength range. In a companion paper, we use the techniques introduced here to generalize our findings to all 2016 and 2017 measurements and parameterize aerosol radiative effects.

Vicinity of small bodies might be dangerous to the spacecrafts and to their instrumentation. Here the authors show the operational environment of asteroid Bennu, validate its photometric phase function and demonstrate the accelerating rotational rate due to YORP effect using the data acquired during the approach phase of OSIRIS-REx mission.

ABSTRACT The flavors of fermented plant foods and beverages are formed by microorganisms, and in the case of wine, the location and environmental features of the vineyard site also imprint the wine with distinctive aromas and flavors. Microbial growth and metabolism play an integral role in wine production, by influencing grapevine health, wine fermentation, and the flavor, aroma, and quality of finished wines. The contributions by which microbial distribution patterns drive wine metabolites are unclear, and while flavor has been correlated with fungal and bacterial composition for wine, bacterial activity provides fewer sensorially active biochemical conversions than fungi in wine fermentation. Here, we collected samples across six distinct wine-growing areas in southern Australia to investigate regional distribution patterns of fungi and bacteria and the association with wine chemical composition. Results show that both soil and must microbiota distinguish wine-growing regions. We found a relationship between microbial and wine metabolic profiles under different environmental conditions, in particular measures of soil properties and weather. Fungal communities are associated with wine regional distinctiveness. We found that the soil microbiome is a source of grape- and must-associated fungi and suggest that weather and soil could influence wine characteristics via the soil fungal community. Our report describes a comprehensive scenario of wine microbial biogeography where microbial diversity responds to the surrounding environment and correlates with wine composition and regional characteristics. These findings provide perspectives for thoughtful human practices to optimize food composition through understanding fungal activity and abundance. IMPORTANCE The composition of soil has long been thought to provide wine with characteristic regional flavors. Here, we show that for vineyards in southern Australia, the soil fungal communities are of primary importance for the aromas found in wines. We propose a mechanism by which fungi can move from the soil through the vine.

Abstract We observed the near‐Earth asteroid (101955) Bennu from the ground in 1999 and 2005, and with the Hubble Space Telescope (HST) in 2012, to constrain its rotation rate. The data reveal an acceleration of 2.64 ± 1.05 × 10−6 deg/day2, which could be due to a change in the moment of inertia of Bennu or to spin up from the Yarkovsky‐O'Keefe‐Radzievskii‐Paddack effect or other source of angular momentum. The best solution is within 1 σ of the period determined by Nolan et al. (2013, https://doi.org/10.1016/j.icarus.2013.05.028). The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS‐REx) mission will determine the rotation state independently in 2019. Those measurements should show whether the change in rotation rate is a steady increase (due, e.g., to the Yarkovsky‐O'Keefe‐Radzievskii‐Paddack effect) or some other phenomenon. The precise shape and surface properties measured by the OSIRIS‐REx science team will allow for a better understanding of variations in rotation rate of small asteroids.

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state of the art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020–2050 period shows reductions in fall and spring snow cover fraction and sea ice concentration of 5–10 % per decade (or 15–30 % in total), with similar reductions in winter sea ice concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10 % per decade (30 % in total) are projected across southern Canada.

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.

Dietary phytochemicals promote health and reduce the risk of chronic disease. The Phytochemical Absorption Prediction Model (PCAP) predicts the time required for phytochemicals to reach maximal plasma concentrations (Tmax) in humans based on their lipophilicity and molecular mass. Cell-based transport models have been used to quantify transport rate and efficiency of pharmaceuticals and phytochemicals, however these parameters have not previously been related to the human absorption Tmax. Caco-2/HT29-MTX-E12 monolayers were used to characterise transport of phytochemical standards and extracts and to establish a relationship between the in vitro permeability (Papp) of standards and their in vivo Tmax predicted from the PCAP model. Lipophilic compounds transported through the cell monolayer at relatively faster rates (higher Papp) than hydrophilic compounds, whilst having slower predicted in vivo absorption rates (longer Tmax). The results infer differences between in vitro (cell monolayer) and in vivo (human gastrointestinal tract) absorption kinetics of phytochemicals.

Since 2009, the ultra-wideband snow radar on Operation IceBridge (OIB; a NASA airborne mission to survey the polar ice covers) has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Progressive improvements in radar hardware and data processing methodologies have led to improved data quality for subsequent retrieval of snow depth. Existing retrieval algorithms differ in the way the air–snow (a–s) and snow–ice (s–i) interfaces are detected and localized in the radar returns and in how the system limitations are addressed (e.g., noise, resolution). In 2014, the Snow Thickness On Sea Ice Working Group (STOSIWG) was formed and tasked with investigating how radar data quality affects snow depth retrievals and how retrievals from the various algorithms differ. The goal is to understand the limitations of the estimates and to produce a well-documented, long-term record that can be used for understanding broader changes in the Arctic climate system. Here, we assess five retrieval algorithms by comparisons with field measurements from two ground-based campaigns, including the BRomine, Ozone, and Mercury EXperiment (BROMEX) at Barrow, Alaska; a field program by Environment and Climate Change Canada at Eureka, Nunavut; and available climatology and snowfall from ERA-Interim reanalysis. The aim is to examine available algorithms and to use the assessment results to inform the development of future approaches. We present results from these assessments and highlight key considerations for the production of a long-term, calibrated geophysical record of springtime snow thickness over Arctic sea ice.

Abstract In the absence of widespread snowfall observations over the Arctic Ocean, reanalysis products provide a wide range of estimates of time‐evolving snowfall rates over Arctic sea ice, and it can be difficult to determine which product is most representative. In this work, Arctic snowfall rates retrieved from 2006 to 2016 CloudSat observations and snowfall products from three reanalyses are assessed. The products can be brought into encouraging agreement over the region on interannual time scales once differences in spatial representativeness and temporal sampling are accounted for. This motivates the use of CloudSat's snowfall product to calibrate reanalysis snowfall. The calibration is carried out for four Arctic quadrants and combined to produce regionally resolved and consistent estimates of interannually varying snowfall. Calibrated reanalysis snowfall inputs are then used to drive the NASA Eulerian Snow On Sea Ice Model, reducing the interproduct spread in the resulting simulated snow depths across the Arctic.