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At least 613 records · Page 34

Large-Scale Surveys of Snow Depth on Arctic Sea Ice from Operation IceBridge

We show the first results of a large ]scale survey of snow depth on Arctic sea ice from NASA fs Operation IceBridge snow radar system for the 2009 season and compare the data to climatological snow depth values established over the 1954.1991 time period. For multiyear ice, the mean radar derived snow depth is 33.1 cm and the corresponding mean climatological snow depth is 33.4 cm. The small mean difference suggests consistency between contemporary estimates of snow depth with the historical climatology for the multiyear ice region of the Arctic. A 16.5 cm mean difference (climatology minus radar) is observed for first year ice areas suggesting that the increasingly seasonal sea ice cover of the Arctic Ocean has led to an overall loss of snow as the region has transitioned away from a dominantly multiyear ice cover.

Kurtz, Nathan T.↗

A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes

Observations of long-lived mixed-phase Arctic boundary layer clouds on 7 May 1998 during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)Arctic Cloud Experiment (ACE)Surface Heat Budget of the Arctic Ocean (SHEBA) campaign provide a unique opportunity to test understanding of cloud ice formation. Under the microphysically simple conditions observed (apparently negligible ice aggregation, sublimation, and multiplication), the only expected source of new ice crystals is activation of heterogeneous ice nuclei (IN) and the only sink is sedimentation. Large-eddy simulations with size-resolved microphysics are initialized with IN number concentration N(sub IN) measured above cloud top, but details of IN activation behavior are unknown. If activated rapidly (in deposition, condensation, or immersion modes), as commonly assumed, IN are depleted from the well-mixed boundary layer within minutes. Quasi-equilibrium ice number concentration N(sub i) is then limited to a small fraction of overlying N(sub IN) that is determined by the cloud-top entrainment rate w(sub e) divided by the number-weighted ice fall speed at the surface v(sub f). Because w(sub c)< 1 cm/s and v(sub f)> 10 cm/s, N(sub i)/N(sub IN)<< 1. Such conditions may be common for this cloud type, which has implications for modeling IN diagnostically, interpreting measurements, and quantifying sensitivity to increasing N(sub IN) (when w(sub e)/v(sub f)< 1, entrainment rate limitations serve to buffer cloud system response). To reproduce observed ice crystal size distributions and cloud radar reflectivities with rapidly consumed IN in this case, the measured above-cloud N(sub IN) must be multiplied by approximately 30. However, results are sensitive to assumed ice crystal properties not constrained by measurements. In addition, simulations do not reproduce the pronounced mesoscale heterogeneity in radar reflectivity that is observed.

Fridlin, Ann↗

The Arctic Regional Communications Small SATellite (ARCSAT)

Traditional satellite missions are extremely complex and expensive to design, build, test, launch and operate. Consequently many complementary operational, exploration and research satellite missions are being formulated as a growing part of the future space community capabilities using formations of small, distributed, simple to launch and inexpensive highly capable small scale satellites. The Arctic Regional Communications small SATellite (ARCSAT) initiative would launch a Mini-Satellite "Mothership" into Polar or Sun Sync low-earth-orbit (LEO). Once on orbit, the Mothership would perform orbital insertion of four internally stored independently maneuverable nanosatellites, each containing electronically steerable antennas and reconfigurable software-defined radios. Unlike the traditional geostationary larger complex satellite communication systems, this LEO communications system will be comprised of initially a five small satellite formation that can be later incrementally increased in the total number of satellites for additional data coverage. ARCSAT will provide significant enabling capabilities in the Arctic for autonomous voice and data communications relay, Maritime Domain Awareness (MDA), data-extraction from unattended sensors, and terrestrial Search & Rescue (SAR) beacon detection missions throughout the "data starved desert" of the Arctic Region.

Casas, Joseph↗

Source Attributions of Pollution to the Western Arctic During the NASA ARCTAS Field Campaign

We use the NASA GEOS-5 transport model with tagged tracers to investigate the contributions of different regional sources of CO and black carbon (BC) to their concentrations in the Western Arctic (i.e., 50-90 deg N and 190- 320 deg E) in spring and summer 2008. The model is evaluated by comparing the results with airborne measurements of CO and BC from the NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaigns to demonstrate the strengths and limitations of our simulations. We also examine the reliability of tagged CO tracers in characterizing air mass origins using the measured fossil fuel tracer of dichloromethane and the biomass burning tracer of acetonitrile. Our tagged CO simulations suggest that most of the enhanced CO concentrations (above background level from CH4 production) observed during April originate from Asian anthropogenic emissions. Boreal biomass burning emissions and Asian anthropogenic emissions are of similar importance in July domain wise, although the biomass burning CO fraction is much larger in the area of the ARCTAS field experiments. The fraction of CO from Asian anthropogenic emissions is larger in spring than in summer. European sources make up no more than 10% of CO levels in the campaign domain during either period. Comparisons of CO concentrations along the flight tracks with regional averages from GEOS-5 show that the alongtrack measurements are representative of the concentrations within the large domain of the Western Arctic in April but not in July.

Black Carbon↗

Analysis of the Warmest Arctic Winter, 2015-2016

December through February 2015-2016 defines the warmest winter season over the Arctic in the observational record. Positive 2m temperature anomalies were focused over regions of reduced sea ice cover in the Kara and Barents Seas and southwestern Alaska. A third region is found over the ice-covered central Arctic Ocean. The period is marked by a strong synoptic pattern which produced melting temperatures in close proximity to the North Pole in late December and anomalous high pressure near the Taymyr Peninsula. Atmospheric teleconnections from the Atlantic contributed to warming over Eurasian high-latitude land surfaces, and El Niño-related teleconnections explain warming over southwestern Alaska and British Columbia, while warm anomalies over the central Arctic are associated with physical processes including the presence of enhanced atmospheric water vapor and an increased downwelling longwave radiative flux. Preconditioning of sea ice conditions by warm temperatures affected the ensuing spring extent.

Barents and Kara Seas↗

A Probabilistic Method of Assessing Carbon Accumulation Rate at Imnavait Creek Peatland, Arctic Long Term Ecological Research Station, Alaska

Arctic peatlands are an important part of the global carbon cycle, accumulating atmospheric carbon as organic matter since the Late glacial. Current methods for understanding the changing efficiency of the peatland carbon sink rely on peatlands with an undisturbed stratigraphy. Here we present a method of estimating primary carbon accumulation rate from a site where permafrost processes have either vertically or horizontally translocated nearby carbon-rich sediment out of stratigraphic order. Briefly, our new algorithm estimates the probability of the age of deposition of a random increment of sediment in the core. The method assumes that if sediment age is measured at even depth increments, dates are more likely to occur during intervals of higher accumulation rate and vice versa. Multiplying estimated sedimentation rate by measured carbon density yields carbon accumulation rate. We perform this analysis at the Imnavait Creek Peatland, near the Arctic Long Term Ecological Research network site at Toolik Lake, Alaska. Using classical radiocarbon age modeling, we find unreasonably high rates of carbon accumulation at various Holocene intervals. With our new method, we find accumulation rate changes that are in improved agreement within the context of other sites throughout Alaska and the rest of the Circum-Arctic region.

carbon accumulation;Imnavait;peatlands;permafrost;↗

Inter-relationship Between Subtropical Pacific Sea Surface Temperature, Arctic Sea Ice Concentration, and North Atlantic Oscillation in Recent Summers

The inter-relationship between subtropical western–central Pacific sea surface temperatures (STWCPSST), sea ice concentrations in the Beaufort Sea (SICBS), and the North Atlantic Oscillation (NAO) in summer are investigated over the period 1980–2016. It is shown that the Arctic response to the remote impact of the Pacific SST is more dominant in recent summers, leading to a frequent occurrence of the negative phase of the NAO following the STWCPSST increase. Lag–correlations of STWCPSST positive (negative) anomalies in spring with the negative (positive) NAO and SICBS loss (recovery) in summer have increased over the last two decades, reaching r = 0.4–0.5 with significance at the 5 percent level. Both observations and the atmospheric general circulation model experiments suggest that the positive STWCPSST anomaly and subsequent planetary-scale wave propagation act to increase the Arctic upper-level geopotential heights and temperatures in the following season. This response extends to Greenland, providing favorable conditions for developing the negative phase of the NAO. Connected with this atmospheric response, SIC and surface albedo decrease with an increase in the surface net shortwave flux over the Beaufort Sea. Examination of the surface energy balance (radiative and turbulent fluxes) reveals that surplus energy that can heat the surface increases over the Arctic, enhancing the SIC reduction.

SST↗

Radiative Impacts of Future Arctic Sea Ice Melt

The dramatic retreat in Arctic sea ice in recent decades has reduced the top-of-atmosphere albedo over this region and added more solar energy to the climate system. Here we use two satellite datasets--17 years of CERES top-of-atmosphere albedo and 38 years of microwave sea ice concentration measurements-- to estimate the radiative impact of the loss of Arctic sea ice. We then use these observations to estimate the potential impact of a future complete loss of the Arctic sea ice. This presentation will also discuss the seasonal variation in the estimated warming, the dependence of the results on the potential cloud response to ice loss, and a comparison with CMIP5 model results.

Pistone, Kristina↗

The Role of Cyclone Activity in Snow Accumulation on Arctic Sea Ice

Identifying the mechanisms controlling the timing and magnitude of snow accumulation on sea ice is crucial for understanding snow’s net effect on the surface energy budget and sea-ice mass balance. Here, we analyze the role of cyclone activity on the seasonal buildup of snow on Arctic sea ice using model, satellite, and in situ data over 1979–2016. On average, 44% of the variability in monthly snow accumulation was controlled by cyclone snowfall and 29% by sea-ice freeze-up. However, there were strong spatio-temporal differences. Cyclone snowfall comprised ~50% of total snowfall in the Pacific compared to 83% in the Atlantic. While cyclones are stronger in the Atlantic, Pacific snow accumulation is more sensitive to cyclone strength. These findings highlight the heterogeneity in atmosphere-snow-ice interactions across the Arctic, and emphasize the need to scrutinize mechanisms governing cyclone activity to better understand their effects on the Arctic snow-ice system with anthropogenic warming.

Webster, M. A.↗

Utilization of Airborne Observations to Assess Model Parametrizations of Critical RH Profiles in the Arctic Ocean

Observational paucity is a reality in the Arctic Ocean. This is especially true for near-surface variables such as temperature, moisture, heat fluxes and BL clouds. As a result, modeling has become one of the major avenues for understanding current and future Arctic trends. Reanalyses are frequently used to force global ocean circulation and sea-ice models. But in northern high latitudes, model integrations and reanalyses are known to have large uncertainties in temperature and humidity profiles, and in boundary layer cloudiness. These are common sources of error in the surface radiative budget terms.An important way to diagnose these biases spatially and temporally is by using satellite remote sensing data. However, remotely-sensed observations also have large uncertainties, especially in near-surface temperature and relative humidity profiles.In situ observational studies are important in bridging our knowledge gap in regions such as the Arctic Ocean. Here, we utilize airborne and ship observations from the ARISE, ACME-IV, and ASCOS campaigns to construct critical relative humidity (RH) profiles over the Beaufort Sea. Such profiles are used as parameterization inputs in the NASA GOES global model to derive the total water condensate in a model grid-box, which determines the cloud fraction. Currently, the critical RH profiles are derived by global AIRS data, relaying mostly on mid-latitude regions, which are not necessarily relevant to the Arctic.We derive campaign-wide mean, standard deviation, and critical RH values, for grid size of 50x50 km and altitude bins between 50 to 400 m, covering both open-ocean and sea-ice covered regions. We compare profiles over open ocean and sea-ice, and look at correlations between the observed critical RH values and water condensate (by cloud number concentration) from observations versus the modeled ones. We then input our calculated values of minimal critical RH values into a set of GEOS single column model (SCM) simulations over the ARISE and ASCOS regions and compare the differences between the predicted values of cloud liquid water path (LWP), ice water path (IWP) and surface fluxes with the observed ones under the range of input parameterizations. Finally, we discuss the implications on surface radiative budget predictions in this region.

Segal-Rozenhaimer, Michal↗

Winter Arctic Sea Ice Thickness from ICESat-2 Freeboards

NASA’s ICESat-2 mission was launched in September 2018 with the primary goal of monitoring our rapidly changing polar regions. The sole instrument onboard, the Advanced Topographic Laser Altimeter System (ATLAS), is now providing routine, very high-resolution, surface elevation data across the globe, including the Arctic and Southern Oceans. In this study we demonstrate our new processing chain for converting the along-track ICESat-2 sea ice freeboard product (ATL10) into sea ice thickness, focusing our initial efforts on the Arctic Ocean. For this conversion we primarily make use of snow depth and density data from the NASA Eulerian Snow on Sea Ice Model (NESOSIM). The coarse resolution (~100 km) snow data are redistributed onto the high resolution (~30 - 100 m) ATL10 freeboards using relationships obtained from snow depth and freeboard data collected by NASA’s Operation IceBridge mission. We present regional sea ice thickness distributions and highlight their seasonal evolution through our first winter-season of data collection. We include ice thickness uncertainty estimates, while also acknowledging the limitations of these estimates. We generate a gridded monthly thickness product and compare this with various monthly sea ice thickness estimates obtained from ESA’s CryoSat-2 satellite mission, with ICE 33 Sat-2 showing consistently lower thicknesses. Finally, we compare our February/March 2019 thickness estimates to ICESat February/March (19th February – 21st March) 2008 ice thickness estimates using the same input assumptions, which show a ~0.40 m or ~21% thinning across an inner Arctic Ocean domain in this 11-year time period.

Alek A Petty↗

A Community for Polar Early Career Researchers Engaging With the Interagency Arctic Research Policy Committee

The Interagency Arctic Research Policy Committee (IARPC) is tasked with implementation of the Arctic Research Plan (ARP) by coordinating representatives from federal and state agencies, academic, industry, and Indigenous partners with interests in Arctic research. IARPC is organized into several collaboration teams and discipline-specific communities of practice that interface on the IARPC Collaborations website. The Early Career Community of Practice (ECCoP) is one such community that was established to promote the research of early career researchers (ECR) and increase ECR engagement with the ARP, program managers, collaboration teams, and communities of practice. The ECCoP has grown to develop regular newsletters promoting recent ECR research publications ad sharing training, job, funding, and collaboration opportunities relevant to community members at all life stages that self-identify as ECRs. Within IARPC, the ECCoP continues to promote ECR participation in monthly community of practice meetings and webinars and to report on ECR efforts that contribute to deliverables of the ARP Biennial Implementation Plan. Recent activity of the ECCoP includes developing an annual survey of the ECR cohort on IARPC to follow change in demographics over time and to identify community needs to improve diversity and inclusion in the polar research space and to address gaps in training needs for ECRs.

Katy Smith↗

Passive Microwave Arctic Sea Ice Melt Onset Dates From the Advanced Horizontal Range Algorithm 1979 - 2022

The onset of the summer melt season is a key stage of the Arctic sea ice seasonal cycle and is an indicator of climate change. Surface melting of the bare or snow-covered sea ice is detected using passive microwave satellite observations. The data set presented here is a 44 year record of Arctic sea ice annual melt onset (MO) dates for 1979–2022 produced using an updated version of the Advanced Horizontal Range Algorithm (AHRA). This data product contains annual maps of the sea ice MO date and a set of descriptive statistics summarizing the data. This paper describes a new update of the AHRA methodology, now AHRA V5, including key changes to the algorithm starting date and sea ice mask methodology to improve estimates of early-season MO dates especially near the sea ice periphery. AHRA V5 data are suitable for monitoring trends in Arctic and regional sea ice MO dates and for process studies of atmosphere-sea ice interactions during the early spring and summer months.

Angela C. Bliss↗

Next-Generation Ecosystem Experiments–Arctic Flyer

An important challenge for Earth system models (ESMs) is to accurately represent land surface and subsurface processes and their complex interactions. This is true for all regions of the world, but is especially important for high-latitude Arctic ecosystems that are characterized by ice-rich landscapes where topography, hydrology, vegetation, and biogeochemistry are inexplicitly linked. To address this challenge, the Terrestrial Ecosystem Science (TES) program within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) is supporting a next-generation ecosystem experiments project in the Arctic (NGEE–Arctic).

54 ENVIRONMENTAL SCIENCES↗

Nuclear Explosion Monitoring in the Changing Arctic

As the Arctic warms and loses its perennial ice cover, it attracts new attention as a locus for resource extraction, commerce, communication, and defense. The region previously had a relatively low priority in global geopolitics due to operational challenges but is quickly attracting interest for economic growth, competition, and potential conflict. Future years and decades will see a transformation of the Arctic’s place in global geopolitics. In this context, monitoring both human and natural activity in the Arctic is increasingly critical.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Arctic tundra shrubification: a review of mechanisms and impacts on ecosystem carbon balance

Abstract Vegetation composition shifts, and in particular, shrub expansion across the Arctic tundra are some of the most important and widely observed responses of high-latitude ecosystems to rapid climate warming. These changes in vegetation potentially alter ecosystem carbon balances by affecting a complex set of soil–plant–atmosphere interactions. In this review, we synthesize the literature on (a) observed shrub expansion, (b) key climatic and environmental controls and mechanisms that affect shrub expansion, (c) impacts of shrub expansion on ecosystem carbon balance, and (d) research gaps and future directions to improve process representations in land models. A broad range of evidence, including in-situ observations, warming experiments, and remotely sensed vegetation indices have shown increases in growth and abundance of woody plants, particularly tall deciduous shrubs, and advancing shrublines across the circumpolar Arctic. This recent shrub expansion is affected by several interacting factors including climate warming, accelerated nutrient cycling, changing disturbance regimes, and local variation in topography and hydrology. Under warmer conditions, tall deciduous shrubs can be more competitive than other plant functional types in tundra ecosystems because of their taller maximum canopy heights and often dense canopy structure. Competitive abilities of tall deciduous shrubs vs herbaceous plants are also controlled by variation in traits that affect carbon and nutrient investments and retention strategies in leaves, stems, and roots. Overall, shrub expansion may affect tundra carbon balances by enhancing ecosystem carbon uptake and altering ecosystem respiration, and through complex feedback mechanisms that affect snowpack dynamics, permafrost degradation, surface energy balance, and litter inputs. Observed and projected tall deciduous shrub expansion and the subsequent effects on surface energy and carbon balances may alter feedbacks to the climate system. Land models, including those integrated in Earth System Models, need to account for differences in plant traits that control competitive interactions to accurately predict decadal- to centennial-scale tundra vegetation and carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

Using the MicroASAR on the NASA SIERRA UAS in the Characterization of Arctic Sea Ice Experiment

The MicroASAR is a flexible, robust SAR system built on the successful legacy of the BYU microSAR. It is a compact LFM-CW SAR system designed for low-power operation on small, manned aircraft or UAS. The NASA SIERRA UAS was designed to test new instruments and support flight experiments. NASA used the MicroASAR on the SIERRA during a science field campaign in 2009 to study sea ice roughness and break-up in the Arctic and high northern latitudes. This mission is known as CASIE-09 (Characterization of Arctic Sea Ice Experiment 2009). This paper describes the MicroASAR and its role flying on the SIERRA UAS platform as part of CASIE-09.

CASIE-09(CHARACTERIZATION OF ARCTIC SEA ICE EXPERI↗

Explicitly determined sea ice emissivity and emission temperature over the Arctic for surface–sensitive microwave channels

Data assimilation of satellite microwave measurements is one of the important keys to improving weather forecasting over the Arctic region. However, the use of surface-sensitive microwave-sounding channel measurements for data assimilation or retrieval has been limited, especially during winter, due to the poorly constrained sea ice emissivity. In this study, aiming at more use of those channel measurements in the data assimilation, we propose an explicit method for specifying the surface radiative boundary conditions (namely emissivity and emitting layer temperature of snow and ice). These were explicitly determined with a radiative transfer model for snow and ice and with snow/ice physical parameters (i.e., snow/ice depths and vertical distributions of temperature, density, salinity, and grain size) simulated from the thermodynamically-driven snow/ice growth model. Here we conducted 1-D Var experiments in order to examine whether this approach can help to use the surface-sensitive microwave temperature channel measurements over the Arctic sea ice region for data assimilation. Results show that (1) the surface-sensitive microwave channels can be used in the 1-D Var retrieval, and (2) the specification of the radiative boundary condition at the surface using the snow/sea ice emission model can significantly improve the atmospheric temperature retrieval, especially in the lower troposphere (500 hPa to surface). The successful retrieval suggests that useful information can be extracted from surface-sensitive microwave-sounding channel radiances over sea ice surfaces through the explicit determination of snow/ice emissivity and emitting layer temperature.

1-D Var retrieval↗