• 2016 Snow Melt in the NGEE-Arctic Teller Research Watershed

      Busey, Robert; Wilson, Cathy; Iwahana, Go; Bolton, W. Robert; Cohen, Lily (2016-12)
      In April 2016, daily transects were made across the Teller Road Basin to begin the several year process of characterizing the largest event in the northern hydrologic year: snow melt. This year was an experiment to see how much could be accomplished (a full suite of time intensive measurements) during this interval.
    • Arctic Ecosystem Changes from Gloal Community Earthc System Model (CESM) and Regional Arctic System Model (RASM)

      Jin, Meibing; Deal, Clara; Maslowski, Wieslaw; Roberts, Andrew; Marina, Frants; Robert, Osinski; Craig, Anthony (2016-02)
      The Arctic Ocean is currently experiencing rapid and large environmental changes related to global warming. Many small scale physical processes, such as mesoscale eddies, mixed layer dynamics, ocean boundary and coastal currents, varying sea ice edges, upwelling can influence nutrient transport, light availability and ocean stratification, thus are critical for understanding marine primary production and carbon cycling in the Arctic Ocean. A high-resolution pan-Arctic regional earth system model (RASM) was developed to investigate the ecosystem response to climate changes in seasonal to decadal scales. Here we show some initial results from the high resolution ecosystem model and comparison with results from coarse resolution global community earth system model. Both models include coupled ice algal submodel at the bottom of sea ice and intermediate NPZD pelagic ecosystem submodel in water column.
    • Arctic Storm Activities in Ensemble Simulations by the HIRHAM-NAOISM Regional Coupled Climate Model

      Yang, Yang; Zhang, Xiangdong; Rinke, Annette (2016-12)
      Arctic storm activities have shown intensification during recent decades, which may have contributed to or caused extreme climate events. We examined Arctic storm activities in 10 ensemble simulations by using the Arctic regional coupled climate model HIRHAM-NAOSIM. Storm identification and tracking algorithm (Zhanget al., 2004) were employed to derive intensity, location and duration of each storm. Arctic regional storm climatology and variability were constructed and compared with the same statistics derived from the ERA-interim reanalysis data.
    • Assimilation of High-Frequency Radar Data in the East Chukchi Sea

      Stroh, J.; Panteleev, G. G.; Yaremchuk, M.; Weingartner, T. (2014-03)
      The maximum-likelihood ensemble filter (MLEF) is an eficient technique of data assimilation related to both 3D-variational (3Dvar) and Ensemble Kalman Filter (EnKF) methods. We demonstrate the utility of MLEF by assimilating high-frequency radar (HFR) data into a realistic model of the east Chukchi Sea. A set of three radar stations in Wainwright, Point Lay, and Barrow provide two-dimensional resolution of the sea-surface velocity. We use MLEF to incorporate this HFR data into a numerical model constructed using the Regional Ocean Modelling System (ROMS) for the ice-free months of 2012. The resulting analysis can be used as a benchmark for future operational forecasting, allowing for better real-time monitoring and decision-making as this biologically rich region is influenced by industry and commerce.
    • Carbon exchange rates in Polytrichum juniperinum moss of burned black spruce forest in interior Alaska

      Kim, Yongwon; Kodama, Y.; Iwata, H.; Kim, S.-D.; Shim, C.; Kushida, K.; Harazono, Y. (2013-01)
      Boreal black spruce forest is highly susceptible to wildfire, and postfire changes in soil temperature and substrates have the potential to shift large areas of such ecosystem from a net sink to a net source of carbon. In this paper, we examine CO2 exchange rates (e.g., NPP and Re) in juniper haircap moss (Polytrichum juniperinum) and microbial respiration in no-vegetation conditions using an automated chamber system at 5-year burned black spruce forest in interior Alaska during the fall season of 2009. Mean microbial respiration and NEP (net ecosystem productivity) of juniper haircap moss were 0.73 ± 0.36 and 0.75 ± 1.04 mgC/m2/min, respectively. CO2 exchange rates and microbial respiration showed temporal variations with fluctuation in air temperature during the fall season, suggesting the temperature sensitivity of juniper haircap moss and soil microbes after fire. During the 45-day fall period, mean NEP of P. juniperinum moss was 0.49 ± 0.28 MgC/ha after 5-year-old forest fire. On the other hand, simulated microbial respiration normalized to a 10 °C temperature might be stimulated by as much as 0.40 ± 0.23 MgC/ha. These findings demonstrate that fire-pioneer species juniper haircap moss is a net C sink in burned black spruce forest of interior Alaska.
    • A “CASE” Study on Developing Science Communication and Outreach Skills of University Graduate Student Researchers in Alaska

      Tedesche, Molly E.; Conner, Laura; Danielson, Jennifer (2015-12)
      Well rounded scientific researchers are not only experts in their field, but can also communicate their work to a multitude of various audiences, including the general public and undergraduate university students. Training in these areas should ideally start during graduate school, but many programs are not preparing students to effectively communicate their work. Here, we present results from the NSF-funded CASE (Changing Alaska Science Education) program, which was funded by NSF under the auspices of the GK-12 program. CASE placed science graduate students (fellows) in K-12 classrooms to teach alongside of K-12 teachers with the goal of enhancing communication and teaching skills among graduate students. CASE trained fellows in inquiry-based and experiential techniques and emphasized the integration of art, writing, and traditional Alaska Native knowledge in the classroom. Such techniques are especially effective in engaging students from groups that are underrepresented in science.
    • Chukchi-Beaufort Seas High-Resolution Atmospheric Reanalysis (CBHAR): Data Verification and Climate Analysis

      Zhang, Xiangdong; Zhang, Jing; Krieger, Jeremy; Shulski, Martha; Liu, Fushong; Stegall, Steve T.; Tao, Wei (2016-03)
      Global models are the most widely used tools to generate various reanalysis data. However, coarse resolution limits their capability to capture detailed synoptic and mesoscale weather systems and the associated heterogeneous distribution of weather elements. Regional models are commonly utilized to better represent local weather systems, benefiting from higher- resolution grids and regionally-optimized model configurations. In this study, the state-of-the-art regional model Weather Research and Forecasting (WRF) and its three dimensional variational (3DVAR) data assimilation system WRF-3DVAR was applied to the Arctic marginal ice zone along the northern Alaska Coast for producing high-resolution regional reanalysis. Potential oil development exists in the study area, thus the high-resolution reanalyzed surface winds will provide a better understanding of regional and local surface circulation patterns, which are the primary driver of oil spill movement should the spill disasters happen.
    • Climate Divisions for Alaska Based on Objective Methods

      Bieniek, Peter A.; Bhatt, Uma S.; Thoman, Richard L.; Angeloff, Heather; Partain, James; Papineau, John; Fritsch, Frederick; Holloway, Eric; Walsh, John E.; Daly, Chris; et al. (2012-12)
      Alaska climate regions first drawn by Fitton (1930) [Fitton]. Divisions outlined by Searby (1968) currently used by the National Climatic Data Center [NCDC]. Climate regions updated by Shulski and Wendler (2007) [ACRC]. None are based on primarily objective methods. Useful for seasonal forecasting and many other research applications.
    • CO2 Flux from Tundra Lichen, Moss, and Tussock, Council, Alaska: Assessment of Spatial Representativeness

      Kim, Yongwon; Chae, Namyi; Lee, Bangyong (2012-12)
      CO2 flux-measurement in dominant tundra vegetation on the Seward Peninsula of Alaska was examined for spatial representativeness, using a manual chamber system. In order to assess the representativeness of CO2 flux, a 40 m × 40 m (5-m interval; 81 total points) plot was used in June, August, and September of 2011. Average CO2 fluxes in lichen, moss, and tussock tundra were 3.4 ± 2.7, 4.5 ± 2.9, and 7.2 ± 5.7 mgCO2/m2/m during growing season, respectively, suggesting that tussock tundra is a significant CO2 source, especially considering the wide distribution of tussock tundra in the circumpolar region. Further, soil temperature, rather than soil moisture, held the key role in regulating CO2 flux at the study site: CO2 flux from tussock increased linearly as soil temperature increased, while the flux from lichen and moss followed soil temperature nearly exponentially, reflecting differences in surface area covered by the chamber system. Regarding sample size, the 81 total sampling points over June, August, and September satisfy an experimental average that falls within ±10% of full sample average, with a 95% confidence level. However, the number of sampling points for each variety of vegetation during each month must provide at least ±20%, with an 80% confidence level. In order to overcome the logistical constraints, we were required to identify the site’s characteristics with a manual chamber system over a 40 m × 40 m plot and to subsequently employ an automated chamber for spatiotemporal representativeness.
    • Conceptualization and Application of Arctic Tundra Landscape Evolution Using the Alaska Thermokarst Model

      Bolton, W. Robert; Romanovsky, Vladimir; McGuire, A. David; Lara, Mark (2015-05)
      Thermokarst topography forms whenever ice-rich permafrost thaws and the ground subsides due to the volume loss when excess ice transitions to water. The Alaska Thermokarst Model (ATM) is a large-scale, state-and-transition model designed to simulate transitions between [non-]thermokarst landscape units, or cohorts. The ATM uses a frame-based methodology to track transitions and proportion of cohorts within a 1- km2 grid cell. In the arctic tundra environment, the ATM tracks thermokarst related transitions between wetland tundra, graminoid tundra, shrub tundra, and thermokarst lakes. The transition from one cohort to another due to thermokarst processes can take place if seasonal thaw of the ground reaches ice-rich soil layers either due to pulse disturbance events such as a large precipitation event, wildfire, or due to gradual active layer deepening that eventually reaches ice-rich soil. The protective layer is the distance between the ground surface and ice-rich soil. The protective layer buffers the ice-rich soils from energy processes that take place at the ground surface and is critical to determining how susceptible an area is to thermokarst degradation. The rate of terrain transition in our model is determined by the soil ice-content, the drainage efficiency (or ability of the landscape to store or transport water), and the probability of thermokarst initiation. Tundra types are allowed to transition from one type to another (i.e. a wetland tundra to a graminoid tundra) under favorable climatic conditions. In this study, we present our conceptualization and initial simulation results of the ATM for an 1792 km2 area on the Barrow Peninsula, Alaska. The area selected for simulation is located in a polygonal tundra landscape under varying degrees of thermokarst degradation. The goal of this modeling study is to simulate landscape evolution in response to thermokarst disturbance as a result of climate change.
    • Conceptualization and Application of the Alaska Thermokarst Model

      Bolton, W. Robert; Lara, Mark; Genet, Helene; Romanovsky, Vladimir; McGuire, A. David (2016-06)
      Thermokarst topography forms whenever ice-rich permafrost thaws and the ground subsides due to the volume loss when ground ice transitions to water. The Alaska Thermokarst Model (ATM) is a large- scale, state-and-transition model designed to simulate transitions between landscape units affected by thermokarst disturbance. The ATM uses a frame-based methodology to track transitions and proportion of cohorts within a 1-km2 grid cell. In the arctic tundra environment, the ATM tracks thermokarst-related transitions among wetland tundra, graminoid tundra, shrub tundra, and thermokarst lakes. In the boreal forest environment, the ATM tracks transitions among forested permafrost plateau, thermokarst lakes, collapse scar fens and bogs. The spatial distribution of cohorts [landcover] is required to initialize and run the ATM. The initial landcover distribution is based upon analysis of compiled remote sensing data sets (SPOT-5, Inferometric Synthetic Aperture Radar, and LandSat8 OLI) at 30-m resolution. Remote sensing analysis and field measurements from previous and ongoing studies are used to determine the ice-content of the soil, the drainage efficiency (or the ability of the landscape to store or transport water), the cumulative probability of thermokarst initiation, distance from rivers, lake dynamics (increasing, decreasing, or stable), and other factors which help determine landscape transition rates. Tundra types are allowed to transition from one type to another (for example, wetland tundra to graminoid tundra) under favorable climatic conditions.
    • Conceptualization of Arctic Tundra Landscape Transitions Using the Alaska Thermokarst Model

      Bolton, W. Robert; Romanovsky, Vladimir; McGuire, A. David; Lara, Mark (2015-09)
      Thermokarst topography forms whenever ice-rich permafrost thaws and the ground subsides due to the volume loss when excess ice transitions to water. The Alaska Thermokarst Model (ATM) is a large-scale, state-and-transition model designed to simulate landscape transitions between landscape units, or cohorts, due to thermokarst. The ATM uses a frame-based methodology to track transitions and proportion of cohorts within a 1-km2 grid cell. In the arctic tundra environment, the ATM tracks landscape transitions between non-polygonal ground (meadows), low center polygons, coalescent low center polygons, flat center polygons, high center polygons, ponds and lakes. The transition from one terrestrial landscape type to another can take place if the seasonal ground thaw penetrates underlying ice-rich soil layers either due to pulse disturbance events such as a large precipitation event, wildfire, or due to gradual active layer deepening. The protective layer is the distance between the ground surface and ice-rich soil. The protective layer buffers the ice-rich soils from energy processes that take place at the ground surface and is critical to determining how susceptible an area is to thermokarst degradation. The rate of terrain transition in our model is determined by the soil ice-content, the drainage efficiency (or ability of the landscape to store or transport water), and the probability of thermokarst initiation. Using parameterizations derived from small-scale numerical experiments, functional responses of landscape transitions will be developed and integrated into NGEE-Arctic climate-scale (CLM) modeling efforts.
    • Continuous monitoring of soil gas efflux with Forced Diffusion (FD) chamber technique in a tundra ecosystem, Alaska

      Kim, Yongwon; Park, Sang-Jong; Lee, Bang-Yong (2015-11)
      We deployed the FD chamber system in a tundra ecosystem over the discontinuous permafrost regime of Council, Alaska. The representative understory plants are tussock (17 %), lichen (32 %), and moss (51 %), within a 40 × 40 m plot at an interval of five meters (81 points total) for efflux-measurement by dynamic chamber. The FD chamber monitored soil CO2 effluxes from moss, lichen, and tussock regimes at an interval of 30 min during the growing season of 2015. As the results, mean soil CO2 effluxes in intact and infected sphagnum moss, lichen, and tussock were 0.42 ± 0.17, 0.39 ± 0.22, 0.76 ± 0.21, and 0.87 ± 0.41 μmol/m2/s during June 25 to September 21 2015, respectively. Mean simulated soil CO2 efflux normalized by air temperature of 10°C were 0.40 ± 0.17, 0.36 ± 0.16, 0.77 ± 0.13, and 0.85 ± 0.30 μmol/m2/s from four plants, respectively, suggesting there are not significant differences between measured and simulated CO2 effluxes.
    • Dynamic Interactions of Snow and Plants in the Boreal Forest, Winter 2011-2012 Revealed by Time-Lapse Photography and LiDAR

      Filhol, Simon; Sturm, Matthew (2012-12)
      As winter progresses, snow accumulates on the ground and plants of the boreal forest. On their passage to the ground, the falling snowflakes encounter physical obstacles like the complex structure of tree branches and shrubs. These cause the fall trajectories to deviate, and in some cases even stop, before a snowflake reaches the forest floor. After deposition, wind and gravitational settlement further affect the snow distribution. Because of these snow-vegetation interactions, snow gets distributed in the forest along vertical and the horizontal directions in a complex way. To better understand these interactions between snow and plants, we designed an experiment, in the boreal forest near Fairbanks, Alaska (see panorama below) where we used a ground-based LiDAR (Light Detection And Ranging) to record the 3D geometrical evolution of the snowpack, the flexure of vegetation under snow loads, and the snow deposition on the ground during the winter of 2011-2012. In parallel, we set up a time-lapse camera to record loading and unloading of tree branches, and a weather station to record atmospheric conditions.
    • Ebullition-Driven Fluxes of Methane from Shallow Hot Spots in the East Siberian Arctic Shelf

      Shakhova, Natalia; Semiletov, Igor; Salyuk, Anatoly; Stubbs, Chris; Kosmach, Denis (2011-12)
      The maximum concentration of atmospheric methane (CH4) occurs over the Arctic: the value of CH4 over Greenland exceeds that over Antarctica by 8-10%; an absolute maximum is measured during wintertime (Steel et. al., 1987; Fung et. al., 1991). Geologic evidence provides insight into possible climate change effects from a warmer Arctic, suggesting that enhanced Arctic CH4 emissions during warm periods played a key role in past rapid climate change.
    • Education, Resilience, and Scenarios: Creating Capacity for Community- Based Observations through Youth Engagement

      Cost, Douglas; Lovecraft, A. L. (2016)
      Education and learning possess powerful potential in affecting future resilience and community-based monitoring. This research focuses on examining the connections and feedbacks between social-environmental systems (SESs), resilience, and compulsory education. We suggest scenarios development as a way to link local-scale interest in change to education and monitoring of key variables for resilience. SESs have been problematized as frequently having a poor fit between environmental change and policy solutions. This has led to discussion and debate over the role of schools in addressing local knowledge, environmental changes, and community priorities. In Alaska and other Arctic countries, the role of public schools in improving this fit has been largely overlooked. This research explains that as extensions of governments, public schools offer an opportunity to create better linkages between societies and environments through governance. Secondarily, at the individual level, education is a vital component of resilience, but such education must embrace multiple perspectives in its curriculum in order to honor and access the diversity offered by local, traditional ecological knowledge and Western methods. Scenarios are inherently transdisciplinary processes that integrate different knowledge perspectives as participants consider what matters the most and what is most uncertain in the long-range future. We report research results from two linked scenarios projects. The Northern Alaska Scenarios Project (NASP) drew resident expert participants from the North Slope and Northwest Arctic Boroughs and the Arctic Future Makers project (AFM) that completed a scenarios exercise with high school students from across the Northwest Arctic Borough.
    • Effect of thaw depth on fluxes of CO2 and CH4 in manipulated Arctic coastal tundra of Barrow, Alaska

      Kim, Yongwon; Oechel, Walter C. (2015-04)
      The manipulation treatment consisted of draining, controlling, and flooding treated sections by adjusting standing water. Inundation increased CH4 emission by a factor of 4.3 compared to non-flooded sections. This may be due to the decomposition of organic matter under a limited oxygen environment by saturated standing water. On the other hand, CO2 emission in the dry section was 3.9-fold higher than in others. CH4 emission tends to increase with deeper thaw depth, which strongly depends on the water table; however, CO2 emission is not related to thaw depth. Quotients of global warming potential (GWPCO2) (dry/control) and GWPCH4 (wet/control) increased by 464 and 148 %, respectively, and GWPCH4 (dry/control) declined by 66 %. This suggests that CO2 emission in a drained section is enhanced by soil and ecosystem respiration, and CH4 emission in a flooded area is likely stimulated under an anoxic environment by inundated standing water. The findings of this manipulation experiment during the autumn period demonstrate the different production processes of CO2 and CH4, as well as different global warming potentials, coupled with change in thaw depth. Thus the outcomes imply that the expansion of tundra lakes leads the enhancement of CH4 release, and the disappearance of the lakes causes the stimulated CO2 production in response to the Arctic climate change.
    • Historical Climatology of the Alaska Climate Divisions

      Bieniek, Peter A.; Walsh, John E.; Thoman, Richard L.; Bhatt, Uma S. (2013-04)
      Complex topography and proximity to coasts results in multiple climate types in Alaska. Climate variability is regional in Alaska. Understanding regional climate variability can further evaluation of climate change, seasonal climate prediction, and teleconnection impacts. Novel climate divisions for Alaska present new avenues for climate products and services.
    • Historical Climatology of the Alaska Climate Divisions

      Bieniek, Peter A.; Walsh, John E.; Thoman, Richard L.; Bhatt, Uma S. (2013-04)
      Complex topography and proximity to coasts results in multiple climate types in Alaska. Climate variability is regional in Alaska. Understanding regional climate variability can further evaluation of climate change, seasonal climate prediction, and teleconnection impacts. Novel climate divisions for Alaska present new avenues for climate products and services.
    • Improve ocean mixing caused by subgrid-scale brine rejection using multi-column ocean grid in a climate model

      Jin, Meibing; Hutchings, Jennifer; Kawaguchi, Yusuke; Kikuchi, Takashi (2012-12)
      Heterogeneous ice pack with sporadic narrow but long leads in the polar oceans was unresolved in typical climate model grid. Although multi-category sea ice thickness distribution was used in one sea ice model grid to calculate separate heat, salt and tracer fluxes through each category, the ocean models use only single-column grid to communicate with the averaged fluxes from all categories. When the lead is resolved by the grid, the added salt at the sea surface will sink to the base of the mixed layer and then spread horizontally. When averaged at a climate-model grid size, this vertical distribution of added salt is lead-fraction dependent. When the lead is unresolved, the model errors were systematic leading to greater surface salinity and deeper mixed-layer depth (MLD). An empirical function was developed to revise the added-salt-related parameter n from being fixed to lead-fraction dependent. Application of this new scheme in climate model showed significant improvement in modeled wintertime salinity and MLD as compared to series of CTD data sets in 1997/1998 and 2006/2007. The results showed the most evident improvement in modeled MLD in the Arctic Basin, similar to that using a fixed n = 5, as recommended by the previous Arctic regional model study, in which the parameter n obtained is close to 5 due to the small lead fraction in the Arctic Basin in winter.