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At least 253 records · Page 14

Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81°N. Excellent agreement (difference less than 1%) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45% and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73°N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.

54 ENVIRONMENTAL SCIENCES↗

Impacts of active satellite sensors' low-level cloud detection limitations on cloud radiative forcing in the Arctic

Previous studies revealed that satellites sensors with the best detection capability identify 25 %–40 % and 0 %–25 % fewer clouds below 0.5 and between 0.5–1.0 km, respectively, over the Arctic. Quantifying the impacts of cloud detection limitations on the radiation flux are critical especially over the Arctic Ocean considering the dramatic changes in Arctic sea ice. In this study, the proxies of the space-based radar, CloudSat, and lidar, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations), cloud masks are derived based on simulated radar reflectivity with QuickBeam and cloud optical thickness using retrieved cloud properties from surface-based radar and lidar during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. Limitations in low-level cloud detection by the space-based active sensors, and the impact of these limitations on the radiation fluxes at the surface and the top of the atmosphere (TOA), are estimated with radiative transfer model Streamer. The results show that the combined CloudSat and CALIPSO product generally detects all clouds above 1 km, while detecting 25 % (9 %) fewer in absolute values below 600 m (600 m to 1 km) than surface observations. These detection limitations lead to uncertainties in the monthly mean cloud radiative forcing (CRF), with maximum absolute monthly mean values of 2.5 and 3.4 Wm –2 at the surface and TOA, respectively. Cloud information from only CALIPSO or CloudSat lead to larger cloud detection differences compared to the surface observations and larger CRF uncertainties with absolute monthly means larger than 10.0 Wm –2 at the surface and TOA. The uncertainties for individual cases are larger – up to 30 Wm –2 . These uncertainties need to be considered when radiation flux products from CloudSat and CALIPSO are used in climate and weather studies.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of methods to determine the surface mixing layer height of the atmospheric boundary layer in the central Arctic during polar night and transition to polar day in cloudless and cloudy conditions

This study evaluates methods to derive the surface mixing layer (SML) height of the Arctic atmospheric boundary layer (ABL) using in situ measurements inside the Arctic ABL during winter and the transition period to spring. An instrumental payload carried by a tethered balloon was used for the measurements between December 2019 and May 2020 during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Vertically highly resolved (centimeter scale) in situ profile measurements of mean and turbulent parameters were obtained, reaching from the sea ice to several hundred meters above ground. Two typical conditions of the Arctic ABL over sea ice were identified: cloudless situations with a shallow surface-based inversion and cloudy conditions with an elevated inversion. Both conditions are associated with significantly different SML heights whose determination as accurately as possible is of great importance for many applications. We used the measured turbulence profile data to define a reference of the SML height. With this reference, a more precise critical bulk Richardson number of 0.12 was derived, which allows an extension of the SML height determination to regular radiosoundings. Furthermore, we have tested the applicability of the Monin–Obukhov similarity theory to derive SML heights based on measured turbulent surface fluxes. The application of the different approaches and their advantages and disadvantages are discussed.

54 ENVIRONMENTAL SCIENCES↗

Bioaerosols as indicators of central Arctic ice nucleating particle sources

The Arctic is warming at a rapid rate, with implications for microbial communities as the ecosystems change. Some microbes and biogenic materials can affect the persistence of long-lived mixed-phase clouds by serving as ice nucleating particles (INPs). The presence of INPs modulates the cloud phase, and long-term measurements are important to elucidate their seasonal sources and to predict future change. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020 provided the first year-long measurements of bioaerosols and INPs in the central Arctic, with 3 d filters for amplicon sequencing and cumulative INP concentrations from −5 to −30 °C. Here, we investigated the INP seasonal cycle and its relation to the seasonal cycle of bacteria and eukaryotes. INPs were greatly elevated and compositionally similar in summer, aligning with a greater prevalence of local bioaerosol sources, but, despite this, a diverse mixture of sources (marine and terrestrial) was present all times. A common broader Arctic INP population is hypothesized for much of the year by comparable coincident data collected in Svalbard and a sensitivity of both the INPs and bioaerosols to large-scale events.

Barry, Kevin R. [Colorado State Univ., Fort Collin↗

MOSAiC studies of long-lasting mixed-phase cloud events and analysis of the liquid-phase properties of Arctic clouds

Vertically resolved observations of the temporal evolution of mixed-phase clouds (MPCs) were performed over the central Arctic during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, which lasted from October 2019 to September 2020. The research icebreaker Polarstern , drifting with the pack ice for more than 7 months, mostly at latitudes > 85° N, served as a platform for state-of-the-art remote sensing of aerosols and clouds. The use of the recently introduced dual field-of-view (FOV) polarization lidar technique in combination with the well-established lidar-radar retrieval technique provided, for the first time, a robust instrumental basis to monitor the evolution of the liquid and the ice phase of MPCs and the interplay between the two phases. Two long-lasting Arctic MPC events observed close to the North Pole in mid-winter (December 2019) and late summer (September 2020) are discussed to provide new insight into Arctic MPC evolution processes. In the second part of the article, cloud statistics, covering all seasons of a year, are presented. The focus is on the optical and microphysical properties of the liquid phase. These results are solely derived from the dual-FOV lidar observations. The key findings of the study can be summarized as follows: persistent activation of aerosol particles to form water droplets is of great importance for the longevity of MPCs. The observations confirm that ice formation occurs predominantly via immersion freezing. The field studies suggest that the free tropospheric reservoirs of cloud condensation nuclei (CCN) and of ice-nucleating particles (INPs) were always well filled, i.e., the clouds did not exhaust their supply of activatable and activated particles. The observation of long-lasting MPC events, low ice production rates, and a sufficiently large INP reservoir leads to the recommendation to use a time-dependent immersion freezing parameterization in MPC modeling efforts.

Jimenez, Cristofer [Leibniz Inst. for Tropospheric↗

Occurrence of seeding multi-layer clouds in the Arctic from ground-based observations

Studies of Arctic clouds often focus on low-level single-layer clouds (SLCs). Here, we use combined observations of soundings and cloud radar during the MOSAiC, ACSE, and AO2018 research cruises as well as from long-term observations at Ny-Ålesund, Svalbard and Utqiagvik, Alaska to investigate the occurrence of SLCs and multi-layer clouds (MLCs) in the Arctic and to assess the rate of ice-crystal seeding in cold MLCs. MOSAiC observations show cloudy conditions in between 70 % and 90 % of sounding-radar cases. SLCs show occurrence rates of 30 % to 40 % with the highest value of 45 % during October. Cold MLCs are most abundant from November to June (40 % to 55 % of cases). Seeding occurs in about half to two thirds of the identified cold MLCs during MOSAiC for which the sub-saturated layer extends between 100 and 1000 m. The seeding rate increases by as much as 20 percentage points as the assumed size of the falling ice crystals is increased from 100 to 400 µm. The observations reveal a stable rate of cloud-free conditions of around 20 % over the covered latitude range. Cloud occurrence during MOSAiC and at Ny-Ålesund in July, when the geographical distance between observations was minimal, shows reasonable agreement. Comparisons of MOSAiC and other research cruises to the central Arctic also indicate consistent occurrence rates of different cloud types despite the likely effect of year-to-year variability. The comparison of data from ship campaigns and land sites suggests that the latter are not necessarily a good indicator of cloud occurrence in the high Arctic.

Achtert, Peggy [Leipzig Univ. (Germany); Meteorolo↗

Measurement report: Role of organic coating and chemical composition on ice nucleation potential of atmospheric particles in European Arctic

Understanding the ice nucleation (IN) potential of Arctic aerosols is critical for predicting their influence on cloud formation and water cycles in this vulnerable region. This study investigates the role of particle composition, organic coatings, and aerosol sources in modulating ice nucleating particle (INPs) abundance across five aerosol samples collected at the Gruvebadet Observatory Station in Ny-Ålesund, Svalbard. The IN potential of Arctic aerosol particles was studied by investigating chemical, morphological, and INP abundance measurements. Single-particle analyses revealed distinct differences in mixing state, organic volume fraction (OVF), and organic coating morphology across samples. OVF distributions were linked to particle origin, with marine-influenced Na-rich particles often exhibiting thin organic coatings, while long-range transported particles showed thicker organic coatings. Biogenic contributions, though variable, were linked to heat-sensitive INPs, suggesting a role for labile biological macromolecules under certain meteorological conditions. Spearman rank correlation analysis between particle composition and immersion-mode INP concentrations at two freezing temperatures indicated that organic-rich and Na-rich particles were positively associated with enhanced INP abundance. However, discrepancies in INP abundance were observed for particles with thicker organic coatings, where the morphological configuration of the organic material may play a role. The results highlight that Arctic INP variability is governed not only by chemical composition but also by the morphological configuration of organic material, which can either enhance or inhibit ice nucleation depending on its abundance, distribution, thickness, and mixing state. These findings underscore the combined influence of source regions, atmospheric processing, and organic–inorganic interactions in shaping Arctic aerosol freezing behavior.

Lata, Nurun Nahar [Pacific Northwest National Labo↗

Environmental controls on ecosystem-scale cold-season methane and carbon dioxide fluxes in an Arctic tundra ecosystem

Abstract. Understanding the processes that influence and control carbon cycling in Arctic tundra ecosystems is essential for making accurate predictions about what role these ecosystems will play in potential future climate change scenarios. Particularly, air–surface fluxes of methane and carbon dioxide are of interest as recent observations suggest that the vast stores of soil carbon found in the Arctic tundra are becoming more available to release to the atmosphere in the form of these greenhouse gases. Further, harsh wintertime conditions and complex logistics have limited the number of year-round and cold-season studies and hence too our understanding of carbon cycle processes during these periods. We present here a two-year micrometeorological data set of methane and carbon dioxide fluxes, along with supporting soil pore gas profiles, that provide near-continuous data throughout the active summer and cold winter seasons. Net emission of methane and carbon dioxide in one of the study years totalled 3.7 and 89 g C m−2 a−1 respectively, with cold-season methane emission representing 54 % of the annual total. In the other year, net emission totals of methane and carbon dioxide were 4.9 and 485 g C m−2 a−1 respectively, with cold-season methane emission here representing 82 % of the annual total – a larger proportion than has been previously reported in the Arctic tundra. Regression tree analysis suggests that, due to relatively warmer air temperatures and deeper snow depths, deeper soil horizons – where most microbial methanogenic activity takes place – remained warm enough to maintain efficient methane production whilst surface soil temperatures were simultaneously cold enough to limit microbial methanotrophic activity. These results provide valuable insight into how a changing Arctic climate may impact methane emission, and highlight a need to focus on soil temperatures throughout the entire active soil profile, rather than rely on air temperature as a proxy for modelling temperature–methane flux dynamics.

54 ENVIRONMENTAL SCIENCES↗

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

54 ENVIRONMENTAL SCIENCES↗

Formation and fate of freshwater on an ice floe in the Central Arctic

The melt of snow and sea ice during the Arctic summer is a significant source of relatively fresh meltwater. The fate of this freshwater, whether in surface melt ponds or thin layers underneath the ice and in leads, impacts atmosphere–ice–ocean interactions and their subsequent coupled evolution. Here, we combine analyses of datasets from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (June–July 2020) for a process study on the formation and fate of sea ice freshwater on ice floes in the Central Arctic. Our freshwater budget analyses suggest that a relatively high fraction (58 %) is derived from surface melt. Additionally, the contribution from stored precipitation (snowmelt) outweighs by 5 times the input from in situ summer precipitation (rain). The magnitude and rate of local meltwater production are remarkably similar to those observed on the prior Surface Heat Budget of the Arctic Ocean (SHEBA) campaign, where the cumulative summer freshwater production totaled around 1 m during both. A relatively small fraction (10 %) of freshwater from melt remains in ponds, which is higher on more deformed second-year ice (SYI) compared to first-year ice (FYI) later in the summer. Most meltwater drains laterally and vertically, with vertical drainage enabling storage of freshwater internally in the ice by freshening brine channels. In the upper ocean, freshwater can accumulate in transient meltwater layers on the order of 0.1 to 1 m thick in leads and under the ice. The presence of such layers substantially impacts the coupled system by reducing bottom melt and allowing false bottom growth; reducing heat, nutrient, and gas exchange; and influencing ecosystem productivity. Regardless, the majority fraction of freshwater from melt is inferred to be ultimately incorporated into the upper ocean (75 %) or stored internally in the ice (14 %). Terms such as the annual sea ice freshwater production and meltwater storage in ponds could be used in future work as diagnostics for global climate and process models. For example, the range of values from the CESM2 climate model roughly encapsulate the observed total freshwater production, while storage in melt ponds is underestimated by about 50 %, suggesting pond drainage terms as a key process for investigation.

54 ENVIRONMENTAL SCIENCES↗

Chemical Composition and Mixing State of Wintertime Aerosol from the European Arctic Site of Ny-Ålesund, Svalbard

The Arctic is rapidly warming, and aerosols play an increasingly important role by scattering and absorbing sunlight and by participating in cloud formation. Their optical and cloud-forming properties depend on the mixing state and chemical composition, but observations of these features remain limited. This study comprehensively characterizes 25,254 individual particles collected at Ny-Ålesund, Svalbard (November −December 2020), using microspectroscopy techniques to investigate their size, morphology, mixing state, and chemical composition. Fresh sea salt aerosols (SSA) were identified as the most abundant (∼85%), of the total observed aerosol population, with potential sources from sea spray and blowing snow. Air masses originating from the Arctic Ocean surrounding Svalbard likely contribute to increased concentrations of sub-micrometer “Fresh SSA” particles. “Aged SSA” particles (7.4%) are enriched in sulfur and nitrogen, compared to “Fresh SSA”. These elevated ratios may result from various atmospheric aging processes including the uptake of sulfuric and nitric acids. Here, our results suggest that aged SSA, with sizes larger than 300 nm, likely underwent chlorine depletion by sulfuric and nitric acids during transport. Additionally, elemental analysis reveals that both fresh and aged SSA can mix with dust particles, regardless of the SSA size (49.9% in sub-micrometer size and 50.1% in super-micrometer size, respectively). Dust particles are efficient ice-nucleating particles (INPs), and SSA is known to act as cloud condensation nuclei (CCN), and therefore, their mixtures may inherit both properties. The non-negligible number (4.4%) of SSA-dust mixtures underscores the importance of these particles as potential sources of CCN and INP in the Arctic atmosphere.

Arctic↗

Insights into the year-round vertical distribution of chlorophyll concentration in high-latitude Arctic Ocean: implications for primary production

Climate-induced rapid changes in the Arctic Ocean, such as decreasing sea ice extent and increasing water temperature, are altering nutrient and light availability, profoundly impacting primary producer growth. However, access to the high-latitude Arctic Ocean is limited, and satellite data are primarily available only during summer, making continuous in-situ data collection challenging. We collected year-round chlorophyll-a (Chl-a) concentration data in high-latitude regions using a mooring system and performed a comparative analysis with reanalysis data. Unlike previous satellite-based studies, which typically rely on surface measurements, we used the annual vertical distribution of Chl-a. These data were applied to the vertically generalized production model to accurately estimate annual primary production. The moored Chl-a concentration data showed that phytoplankton exhibited a typical subsurface chlorophyll maximum (SCM) layer as sea ice retreated in June. Contrary to the gradually deepening SCM distribution predicted by model-based reanalysis data, the SCM layer persisted for approximately 4 months. This indicates that light and nutrient conditions within the SCM layer remained stable, sustaining continuous phytoplankton growth. Annual primary production, reflecting this vertical distribution of Chl-a concentration, was 6.85 gC m −2 yr −1 . This exceeded satellite-based estimates by at least two-fold, highlighting the significant underestimation of primary production by satellite approaches. Estimating primary production while accounting for the vertical distribution of phytoplankton and light is essential for improving ecological models to better understand carbon cycle and food web changes in the Arctic Ocean, with important implications for climate change predictions.

Arctic Ocean↗

Mapping wall-to-wall fractional cover of Arctic tundra plant functional types in Alaska using 20-m spatial resolution satellite imagery and harmonized plot observations

Estimates of fractional cover (fCover) across given land surfaces are used to assess, and often model, vegetation composition and diversity, which are crucial for understanding the health and functioning of terrestrial ecosystems. Remote sensing provides a useful means for scaling local, plot-measured fCover estimates to regional scales. Leveraging a recently synthesized and harmonized plot database, this study generated wall-to-wall maps of fCover for six Alaskan-Arctic plant functional types (PFT), including non-vascular plants, forbs, graminoids, and deciduous and evergreen shrubs, using 20-m satellite data (Sentinel-1, Sentinel-2, ArcticDEM) using a machine learning regression approach, specifically the random forest (RF) algorithm, which is well-suited for handling nonlinear relationships and high-dimensional satellite datasets. This study additionally addressed the spatio-temporal inconsistencies e.g., sampling scale, plot size, and collection year in plot measured fCover by adopting a multivariate outlier detection approach—Cook’s distance—to identify high-quality plots for model training and validation. Our approach achieves high accuracy (R 2 = 0.59–0.93, root mean squared errors = 0.02–0.10 for all PFTs) between plot-observed and satellite-derived fCover when using high-quality plot samples. The mapped fCover characterizes the spatial patterns of different PFTs across the tundra biome at a 20-m resolution, providing key information needed for improved representation of Arctic tundra vegetation in terrestrial biosphere models to better understand climate-vegetation feedback across the Arctic tundra.

Arctic tundra↗

Spatial variability of aerosol iron mineralogy and oxidation states over the Arctic Ocean

The mineralogy and oxidation state of aerosol iron (Fe) play important roles in controlling aerosol Fe solubility and consequent bioavailability in seawater. In this study, the spatial variability of Fe mineralogy and oxidation states in aerosols collected during the US GEOTRACES Western Arctic cruise (GN01) were determined using synchrotronbased X-ray absorption near edge structure (XANES) spectroscopy. Both Fe(II) minerals (biotite, ilmenite) and Fe (III) minerals (ferrihydrite, hematite, Fe(III) phosphate) were found in these samples. However, aerosol Fe mineralogy and solubility observed during this cruise varied spatially and can be grouped into three clusters based on the air masses that affected aerosols collected in different regions: (1) biotite-enriched particles (87 % biotite, 13 % hematite) with the air masses passing over Alaska, showing relatively low Fe solubility (4.0 +/- 1.7 %); (2) ferrihydrite-enriched particles (82 % ferrihydrite, 18 % ilmenite) collected in the remote Arctic air, showing relatively high Fe solubility (9.6 +/- 3.3 %); (3) the fresh dust derived from North America and Siberia, primarily dominated by hematite (41 % hematite, 25 % Fe(III) phosphate, 20 % biotite, 13 % ferrihydrite), showing relatively low Fe solubility (5.1 +/- 3.5). A significant positive correlation was found between Fe oxidation state and Fe fractional solubility, suggesting that long-range transport could modify iron (hydr) oxide such as ferrihydrite through atmospheric processing, influencing aerosol Fe solubility and consequently Fe bioavailability in the remote Arctic Ocean.

54 ENVIRONMENTAL SCIENCES↗

Long-Term Trends for Marine Sulfur Aerosol in the Alaskan Arctic and Relationships With Temperature

Marine aerosol plays a vital role in cloud-aerosol interactions during summer in the Arctic. The recent rise in temperature and decrease in sea ice extent have the potential to impact marine biogenic sources. Compounds like methanesulfonic acid (MSA) and non-sea-salt sulfate (nss-SO 4 2- ), oxidation products of dimethyl sulfide (DMS) emitted by marine primary producers, are likely to increase in concentration. Long-term studies are vital to understand these changes in marine sulfur aerosol and potential interactions with Arctic climate. Samples were collected over three summers at two coastal sites on the North Slope of Alaska (Utqiagvik and Oliktok Point). MSA concentrations followed previously reported seasonal trends, with evidence of high marine primary productivity influencing both sites. When added to an additional data set collected at Utqiagvik, an increase in MSA concentration of + 2.5% per year and an increase in nss-SO 4 2- of + 2.1% per year are observed for the summer season over the 20-year record (1998–2017). This study identifies ambient air temperature as a strong factor for MSA, likely related to a combination of interrelated factors including warmer sea surface temperature, reduced sea ice, and temperature-dependent chemical reactions. Analysis of individual particles at Oliktok Point, within the North Slope of Alaska oil fields, showed evidence of condensation of MSA onto anthropogenic particles, highlighting the connection between marine and oil field emissions and secondary organic aerosol. Finally, this study shows the continued importance of understanding MSA in the Arctic while highlighting the need for further research into its seasonal relationship with organic carbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diel Redox Cycle of Manganese in the Surface Arctic Ocean

Knowledge of the chemical speciation of particulate manganese (pMn) is important for understanding the biogeochemical cycling of Mn and other particle-reactive elements. Here, in this work, we present the synchrotron-based X-ray spectroscopy-derived average oxidation state (AOS) of pMn in the surface Arctic Ocean collected during the United States GEOTRACES Arctic cruise (GN01) in 2015. We show that the pMn AOS is <2.4 when sampled during the day and more than ~3.0 when sampled at night. We hypothesize that an active light-dependent redox cycle between dissolved Mn and particulate Mn(III/IV) exists during the day-night cycle in the surface Arctic Ocean, which occurs on the timescale of hours. The magnitude of observed pMn AOS is likely determined by the net effect of the length of the previous night and integrated light level before the end of pMn sampling.

58 GEOSCIENCES↗

Modeling Terrestrial Dissolved Organic Carbon Loading to Western Arctic Rivers

The mobilization and land-to-ocean transfer of dissolved organic carbon (DOC) in Arctic watersheds is intricately linked with the region's climate and water cycle, and furthermore at risk of changes from climate warming and associated impacts. This study quantifies model-simulated estimates of runoff, surface and active layer leachate DOC concentrations and loadings to western Arctic rivers, specifically for basins that drain into coastal waters between and including the Yukon and Mackenzie Rivers. Model validation leverages data from other field measurements, synthesis studies, and modeling efforts. The simulations effectively quantify DOC leaching in surface and subsurface runoff and broadly capture the seasonal cycle in DOC concentration and mass loadings reported from other studies that use river-based measurements. A marked east-west gradient in simulated spring and summer DOC concentrations of 24 drainage basins on the North Slope of Alaska is captured by the modeling, consistent with independent data derived from river sampling. Simulated loadings for the Mackenzie and Yukon show reasonable agreement with estimates of DOC export for annual totals and four of the six seasonal comparisons. Nearly equivalent loading occurs to rivers which drain north to the Beaufort Sea and west to the Bering and Chukchi Seas. The modeling framework provides a basis for understanding carbon export to coastal waters and for assessing impacts of hydrological cycle intensification and permafrost thaw with ongoing warming in the Arctic.

54 ENVIRONMENTAL SCIENCES↗

Consistent Timing of Arctic Permafrost Loss Across the CESM1 Large Ensemble

Abstract The Arctic is especially vulnerable to climate change and is warming faster than the global average. Changes in this region pose a heightened threat due to the immense amount of carbon frozen as organic material in the soil. When permafrost thaws, organic material decays and releases as greenhouse gases into the atmosphere, contributing to further warming. A better understanding of the processes that influence permafrost degradation is needed to inform climate adaptation and mitigation planning. This study assesses changes to Arctic permafrost across 35 ensemble member simulations from the Community Earth System Model 1 Large Ensemble Project, under the Representative Concentration Pathway 8.5 21st century scenario. Most Arctic near‐surface permafrost is lost by 2100, but timing varies across regions and with soil depth. Internal climate variability, represented by differences between ensemble members, has a constrained influence on degradation timing due to relative consistency of summer temperature increases and insulation by winter snow cover.

54 ENVIRONMENTAL SCIENCES↗