Arctic Domain Awareness

Research Areas

Maritime Domain Awareness

Maritime Situational Awareness and Response Support

Maritime Technology Research

Integrated Education

About Us

University of Alaska Anchorage

3211 Providence Drive
Anchorage, AK 99508



ADAC Factsheet

Executive Leadership:

Dr. Douglas Causey, Principal Investigator

Dr. Larry Hinzman, Research Director

Randy "Church" Kee, Maj Gen USAF (Ret), Executive Director

Supporting Leadership:

Heather Paulsen, Finance Director

Malla Kukkonen, Education and Administrative Manager

Project Search

Arctic Domain Awareness Center

The Arctic Domain Awareness Center (ADAC), led by the University of Alaska Anchorage, develops and transitions technology solutions, innovative products, and educational programs to improve situational awareness and crisis response capabilities related to emerging maritime challenges posed by the dynamic Arctic environment.

Center Activity

ADAC supports US Coast Guard disaster response by mapping spills in Arctic maritime environment through development of propeller-driven long range autonomous vehicle


Responding to the challenges of Arctic resource development: how a propeller-driven Long Range Autonomous Underwater Vehicle (LRAUV) can support USCG disaster response:  

Scenario 2020:  In response to sharply rising oil prices, coupled with OPEC mandated production limitations, the U.S. President authorizes unprecedented oil exploration in the Exclusive Economic Zone regions in the eastern Chukchi and the Beaufort Seas.  A major oil producer establishes a new field 175 nautical miles north of the city formerly known as Barrow, and deploys new extraction technologies to initiate production of crude oil.  To the horror of producers, environmentalists, Native coastal populations and disaster responders, the new technology malfunctions, resulting in the release of an estimated 700,000 barrels of oil into the marine environment just as the autumn sea ice is starting to form.

USCG D-17 response forces swing into action to characterize, address and attempt to mitigate the disaster.  Initial on-scene coordinators deploy from Kodiak via rotary and fixed wing assets. The response package includes their new Long Range Autonomous Underwater Vehicle (LRAUV) developed by Woods Hole Oceanographic Institution (WHOI) via ADAC/DHS support.  The onset of sea ice prompts the USCG response team to deploy their HH-60 helicopter to find an open water zone for pitching the LRAUV into the sea. After successful LRAUV launch, the team places a long-range maritime antenna buoy to relay LRAUV mapping signals back to the on-shore coordination center.

The LRAUV guides itself to the oil plume and commences three-dimensional mapping of the site, sending details that characterize the spill to emergency responders, for both ice free areas and those covered by newly formed sea ice, none of which would be available via overhead imagery.  Armed with this comprehensive data, the response team forms its plan.  “To be continued.

While the above futuristic scenario benefits from ADAC’s scientific advances as funded by DHS, relatively recent oil spills in the real world created catastrophes that underlie the urgency to improve response capabilities. For instance, the massive oil spill from the Macondo Canyon well in the “Deepwater Horizon” event in 2010 was unprecedented for uncontrolled release of petroleum in the maritime domain. USCG’s response to Deepwater Horizon did benefit from early generation remotely-controlled underwater vehicles to characterize the nature of the well blow-out.  These early generation vehicles were both limited in range and time on-station, but proved useful to on-scene operators, and provided impetus to press forward with further scientific discovery and development.

While much smaller in scale, the grounding and breakup of the M/V Selendang Ayu in 2004 resulted in a substantial loss of oil in pristine fishing grounds in the Aleutian Islands.

Oil Spills from future well development or transport in the Arctic region could be exponentially complicated for USCG and other operators to respond to, particularly due to the presence of sea ice and the austerity of infrastructure, including very limited ports, expeditionary quality port structure, vast distances and remoteness of the Arctic. ADAC’s sponsored project, conducted by world-renowned underwater vehicle developers at the Woods Hole Oceanographic Institution, has developed the search algorithms, arrayed the right sensor packages and is joining the sensors to a newly developing LRAUV, using the “Tethys” platform, to achieve an unprecedented 600+ KM range at approximately two knots speed.  The Tethys platform can be deployed by two persons with relative ease, and requires no special handling equipment to deploy or recover.  LRAUV will fill a vital need in the USCG Arctic response capability kit.


EEZ: An area of coastal water and seabed prescribed by the United Nations Convention (within 200 nautical miles of the U.S. coastline) to which the country claims exclusive rights for fishing, drilling, and other economic activities.

THEME 1: Maritime Risk, Threat Analysis, and Resilience

PROJECT: High-Resolution Modeling of Arctic Sea Ice and Currents (HIOMAS)

This ADAC project is developing an accurate, High-resolution Ice-Ocean Modeling and Assimilation System (HIOMAS) to simulate and predict sea ice and currents in the Arctic Ocean. This system is to be calibrated and validated using a range of available sea ice and ocean observations and then used for (near) real-time hindcast and daily-to-seasonal forecast of Arctic Ocean currents, sea ice, and change.  The research pays particular attention to the prediction of spatial distribution of ice motion and thickness, the fraction of thick-ridged or multi-year ice, and to the retreat and advance of ice edge. These are the sea ice factors, which are most relevant to Arctic operators. 

Accurate, high-resolution prediction of ocean currents and sea ice conditions will enhance the Coast Guard’s ability to prepare for and respond to oil spills in the Arctic Ocean. The prediction data will also allow the Coast Guard to more safely and reliably conduct search and rescue missions.  The prediction data may also be useful for assisting other stakeholders in the planning and management of economic activities and for other modeling efforts, such as oil spill and wave modeling.   A strength of HIOMAS is its ability to generate high precision models of sea thickness and the movement of ice and ocean currents across the entire Arctic Ocean.   When focused on a particular region of concern, HIOMAS is able to generate even greater precision.  Through prior ADAC investigation, pan-Arctic resolution has reached the limits of computing ability.  Research focus is now on operationalizing HIOMAS for USCG users to predict Arctic sea ice and currents on daily to seasonal time scales.  Complementing research prediction for Arctic sea ice and ocean currents is assessing HIOMAS model predictability through skilled evaluation and uncertainty analysis, and identifying areas for further model improvement.

PROJECT: Developing Sea-Ice and Weather Forecasting Tools to Improve Situational Awareness and Crisis Response in the Arctic

This research project aims to improve USCG and other DHS Arctic maritime operator situational awareness and crisis response by enhancing support for planning and emergency response to meteorological and environmental marine hazards in the Arctic.   Researchers will develop a decision support tool, grounded in stakeholder interactions, to support weather and sea ice-sensitive decision making.  This includes facilitated and deliberate interactions among University of Alaska researchers, USCG emergency responders, NOAA forecasters, and marine operators in the Arctic.  Researchers will focus investigation on the waters surrounding Utqia?vik (Barrow), Alaska, a sub region of the North Slope located on the north coast of Alaska between the Chukchi and Beaufort Seas. The research project involves three phases: preliminary tool development; stakeholder feedback and tool optimization; and outreach, dissemination, and evaluation. 

Phase 1:  Prototype tool development involves three steps.  First, researchers assess the decision contexts of marine operators in the Arctic, including weather and sea ice-sensitive decisions, use of weather and climate information, factors influencing information use, thresholds, and uncertainties via a series of literature reviews and interviews. Second, the team identifies coastal hazards from historical gridded ice velocity data from the UAF Coastal Sea Ice Radar system (CSIRS). Third, researchers will collaborate with the National Weather Service (NWS) and Arctic Environmental Response Management Application (ERMA) to identify procedures for generating event notifications and formats suitable for communicating information.  Phase 2: Findings help to develop a prototype-forecasting module. Researchers leverage feedback obtained from marine stakeholders via an interactive webinar to improve the project-forecasting tool.  Phase 3: Researchers share project findings with a broader audience across Alaska and the Arctic via outreach and project evaluation.


THEME 2: Maritime Domain Awareness

PROJECT: Arctic Oil Spill Modeling

In support of the USCG marine oil spill response mission, the research team is developing analytical modeling to estimate the spread of oil released in an ocean environment under ice due to a well blowout or ruptured pipeline, or among ice due to a ship grounding.  For the under-ice oil release from an offshore well blowout or rupture of a marine transit oil pipeline, the approach will involve coupling output from the ocean oil plume model developed by TAMU with UAA derived analytical density current models to arrive at forecasts of oil spreading.  For oil released near the ocean surface, the project team will adopt approaches derived from the research literature compatible with NOAA’s GNOME oil spill model (General NOAA Operational Modeling Environment).

The research goal is to develop a tool to forecast the spreading of oil in an Arctic marine environment in the immediate aftermath of an oil spill event (i.e., within 24 or 48 hours of the spill).  Modeling will account for the character of the oil spill (e.g., well blowout or pipe rupture), the release rate or amount, and the environmental conditions (ice concentration, water depth, water velocity (drift), and salinity). Researchers will prioritize near-surface releases of oil (e.g., vessel source) as there is a greater risk of oil spills from a vessel source.

Specific research seeks to transition the Arctic-capable oil spill-forecasting tool to appropriate stakeholders by incorporating the tool, with associated training to operate, into NOAA’s oil spill model (the GNOME Suite, including both WebGNOME and PyGNOME). This approach improves NOAA modeling environment used by USCG decision makers in oil spill response. The team further advances the tool by incorporating improved environmental data on Arctic conditions and through increased amounts of pre-formatted input data for Arctic applications.  Planned research includes laboratory validation of elements of the oil spread forecasting model that are not amenable to field validation.

PROJECT: Ice Conditions Index for the Great Lakes Region (ICE-CON)

In collaboration with USCG and others, the project team develops an ice condition index (ICECON) for the Canada-U.S. Great Lakes.  ICECON is a USCG decision support tool combining vessel class with nowcast and forecast lake ice.  Researchers plan ICECON forecasts up to 120 hours into the future, making use of circulation and ice models developed by NOAA’s Great Lakes Environmental Research Laboratory (GLERL).  Researchers will account for Icebreaker activity and its impact on ICECON nowcasts and forecasts. In parallel with the development of ICECON, ADAC will identify and adopt a vessel classification system to define a number of vessel classes and the ice-capability of ships in those classes (in terms of ICECON).  The ICECON system will help the USCG provide guidance and appropriate decision support to Great Lakes marine vessels (for a given class) planning a given transit.

ICECON’s workplan consists of six tasks.  Collectively these tasks combine marine vessel size, gross tonnage and hull strength to contrast against now and forecast ice of the planned route of sail, to provide USCG and shipmasters improved safe passage insight.  In order to achieve effectiveness, ICECON for the Great Lakes needs to be an inclusive and iterative process principally with meteorological, marine traffic, and safety experts.  Accordingly, project researchers plan several workshops and seminars (using distant technologies as appropriate) in coordination with USCG D-9 to collaborate with ice and maritime transportation experts.   These experts are from a range of organizations including (but not exclusive to): NOAA, the National Ice Center, the US Army Corps of Engineers Cold Regions Lab, USCG RDC, USCG D-9, Transport Canada, the Canadian Ice Service, the Finish Meteorological Institute, and the University of Alaska.

PROJECT: Using Vessel Tracking Data to Prioritize Bathymetric Surveying in a Rapidly Changing Arctic

The Arctic Domain Awareness Center’s Arctic-related Incidents of National Significance (Arctic IoNS) workshop in June 2016 highlighted the need to improve awareness and understanding of nearshore bathymetry across the Arctic and, in particular, the North American Arctic.  Accordingly, this research project supplies critical data related to vessel tracking and bathymetry that is useful for existing and developing USCG mission databases.

The project team will create products that inform decision-making about vessel traffic and vessel safety in a rapidly changing Arctic environment.  The research effort will develop the capability to reduce execution time for handling and analyzing exceptionally large collections of Automated Information System (AIS) vessel tracking data.  This capability will enable the investigating team to produce AIS-derived data products to identify marine vessel risk areas, such as those with outdated bathymetry or insufficient coastal detail for safe passage of vessel traffic.  Using and optimizing a high capacity, parallel compute workflow will solve current data volume processing challenges by streamlining the workflow to deliver valuable summaries of vessel density patterns from massive quantities of data across multiple vessel types, environments, and locations.


THEME 3: Maritime Technology

PROJECT: Development of Propeller Driven Long Range Autonomous Underwater Vehicle (LRAUV) for Under-Ice Mapping of Oil Spills and Environmental Hazards (LRAUV)

The increasing level of commercial marine activity in high latitudes creates an ever growing risk of oil spills.  Even in logistically accessible, ice-clear oceans, characterizing the extent and nature of a spill can be difficult as the Deepwater Horizon incident highlighted.  We propose to develop an AUV-based approach leveraging a small, long-range system developed by the PI, called the Tethys Long-Range AUV (LRAUV).  The LRAUV is helicopter-portable, allowing rapid response to incidents to provide situational awareness for first responders. 

Outcomes of this project will be construction of a small long-range AUV (LRAUV) equipped with oil sensors and navigation systems, demonstration of the LRAUV survey capability, and creation of a simulator for gaming AUV deployments for oil spills.  The resulting capability to survey oil spills at high latitudes and under ice answers an unmet need for DHS and the USCG.

PROJECT: Arctic-Related Incidents of National Significance (Arctic IoNS) & Arctic-Focused Medium and Long Term Envrionment (Arctic MaLTE) Workshops

ADAC plans to conduct one Arctic-related Incidents of National Significance (IoNS) workshop for the upcoming program year.  ADAC plans the Arctic IoNS workshop in close coordination with USCG District 17.  Based on identified operator concerns, Arctic IoNS assembles assemble expert academic and industry research professionals to work with select Canada and U.S. Coast Guard Arctic operators, along with U.S. and Canada government security officials in a structured workshop to understand gaps and shortfalls in science and technology and to provide corresponding research questions to address.  ADAC publishes a corresponding workshop Rapporteurs report addressing research questions in a funded call for proposals.  

ADAC plans to conduct one Arctic focused Medium and Long Term Environment (MaLTE) workshop to understand and address the medium and long-term research needs specific to the Arctic environment.  ADAC plans Arctic MaLTE in close coordination with HQ USCG Future Concepts Division (HQ USCG DCO-X, “Evergreen”).    Arctic MaLTE is a structured workshop involving select academics, industry researchers, and government officials, who explore longer, range challenges comprehensively, from policy, governance, and science & technology.   Due to a broader focus than Arctic IoNS, Arctic MaLTE seeks to use advance Delphi research techniques to support workshop participation and associated topic investigation.


THEME 4: Integrated Education

PROJECT: DHS Career Development Grant (CDG) 

ADAC CDG scholars are part of the next generation of scientists and engineers devoted to the discovery, development and improvement of technologies and applications for Arctic Maritime Domain Awareness, Response, and Resilience.  

Funded via a DHS S&T OUP Supplemental Award, ADAC established CDG Scholars as the initial element of the overall ADAC Fellows Program in February 2016.   The DHS Supplemental award provides ADAC’s CDG Fellows a scholarship to support student studies, external to the main Cooperative Agreement.  Participation in the ADAC Fellows program provides CDG scholars student research opportunities and professional development to include access to DHS and USCG professional forums and networks.  DHS S&T OUP Supplemental award established eligibility, minimum grade average and student service obligation requirements.  ADAC leadership manages these requirements to ensure compliance.   Due to no additional DHS S&T OUP CDG Supplemental Awards, the Center does not plan to add any new participants to the project.  Center leadership manages CDG Scholars as part of the overall ADAC Student Fellows Program.  Continuing prior efforts, ADAC plans to mentor and develop CDG students to be capable of competing for future opportunities in DHS and/or DHS enterprise careers.

PROJECT: Minority Serving Institution (MSI) and Workforce Development (WFD)

The Workforce Development (WFD) and Minority Serving Institutions (MSI) program components of ADAC Fellows involve qualified University of Alaska students (WFD) and students of Minority Serving Institutions (MSI) who are seeking degrees from across academic disciplines related to: advanced data analysis and visualization; communications and interoperability; community, commerce, and infrastructure resilience; emergency preparedness and response; maritime and port security; natural disasters and related geophysical studies; and decision sciences. The specific aim of the WFD/MSI programs is for the DHS Enterprise to employ the students who have graduated, and the ideal end-state of the CDG grant program is to two-fold: 1) to contribute to the growth of highly skilled workforce for Homeland Security agencies; and 2) to contribute to the capability of the US Coast Guard operator, in support of USCG missions in the Arctic. ADAC’s WFD component is a research internship program that occurs during the academic year for undergraduate and graduate students. With DHS funding approval occurring in November, 2016, the first WFD cohort is currently under recruitment for Spring semester, 2017. ADAC’s MSI component is a summer internship program, whereby we recruit and select junior and senior undergraduate students from partnering Minority Serving Institutions to participate in a 10-week, hands-on research project within one of the ADAC projects. The first such program will run in the summer of 2017. The MSI summer internship program recruitment targets student participation from outside the University of Alaska System, and even from beyond the existing ADAC Research Network of existing partnerships to extend the impact of the ADAC scientific and educational work more broadly across the country.

In Program Year 4, ADAC will recruit five student summer interns from under-represented classifications, seeking to leverage established partnerships with designated MSI and SME institutions.   The ADAC Minority Summer Internship will integrate these five summer interns along with additional participating ADAC Fellows for a new 2018 ADAC Arctic Summer Intern Program. 

The ADAC Arctic Summer Intern Program (ASIP) is a comprehensive 10-week internship conducted at University of Anchorage.   ADAC’s ASIP will provide student visits across multiple U.S. Federal Agencies posted in Anchorage, participate in ADAC research conducted at UAA, and further participate in Arctic research at Utqia?vik (formally Barrow) Alaska.

PROJECT: Arctic Summer Intern Program (ASIP)

 In Program Year 4, ADAC will conduct the Arctic Summer Intern Program (ASIP).   ADAC’s ASIP will integrate visiting Minority Student Summer Interns with participating ADAC Fellows in a comprehensive orientation and mission focused education experience. ASIP includes visits to U.S. Federal agencies based in Anchorage that are concerned with Arctic issues, a maritime disaster response top-top exercise, focused time with ADAC researchers at UAA, individual research concept development to generate new approaches to addressing Science and Technology solutions to USCG Arctic mission needs and a 2-week Arctic Field work experience at Utqiagvik (Barrow) Alaska.

Included in the focus of this project is to establish a Summer Internship geared at recruiting for underrepresented classifications.  Project specifications of the Minority Student Internship are described associated (preceding project) and included in the DHS - ADAC Terms and Conditions for Workforce Development Plan.



PROJECT: Community Based Observer Networks for Situational Awareness (CBONS-SA)

This project will establish a community-based observing network and system (CBONS) to acquire fine scale, local data on a range of variables critical to USCG operations (Savo et al. 2016, Alessa et al. 2015).  Variables will include those associated with environmental change, subsistence activities/habitats and vessel transits (see Figure 6).  A systematic and quality assured CBONS will enhance the Coast Guard’s ability to successfully respond to Arctic-related Incidents of National Significance (Arctic IONS). CBONS data may be used to enhance the preparedness of communities on the ground which can greatly increase the effectiveness of USCG in the Arctic while potentially reducing costs in the long term. The data will also generate community maps consisting of areas critical to culture and subsistence which will allow the Coast Guard to operate in ways that protect livelihoods and traditional lifeways. The data will eventually be transmitted via the Arctic Information Fusion Capability (AIFC) in order to promote safer SAR/HADR operations. Finally, the data may be used to enhance the precision of data from other Arctic Observing Networks (AON) by placing them in their social contexts.

PROJECT: Real-time Storm Surge, Coastal Flooding, and Coastal Erosion Forecasting for Arctic Alaska

In this project, we will work in collaboration with NOAA’s National Weather Service (NWS) to develop a high (1 km) resolution storm surge forecasting model for the north coast of Alaska between Cape Lisburne and the US/Canadian Border (a distance of 1000 km). Currently, the NWS operates a ~ 5 km resolution forecasting model (ET-Surge). The storm surge modeling will be conducted with NWS-compatible software (either the SLOSH model or the ADCIRC model). Water level forcing data, applied on the ocean boundary, will come from National Weather Service’s Extra Tropical (ET)-Storm Surge model. Bathymetric and topographic data will be gathered from NOAA sources.

In addition to the storm surge forecasting, we will develop a preliminary coastal erosion forecasting model for the Barrow area. The coastal erosion model will be a semi-empirical model that computes erosion rate based on environmental data including surge height, wave condition, water temperature, and nearshore ice condition. Nearshore wave data for the erosion model will be estimated based on NOAA’s operational Wavewatch III model or the Nearshore Wave Prediction System (planned to be operational in September 2016).

The storm surge and coastal erosion models will be calibrated and validated using available data including NOAA water level data collected at Prudhoe Bay and shoreline change, wave and water level data available by Barrow. Co-PI Craig Tweedie will assist with the gathering of Barrow data for model calibration/validation. Time permitting, the team will include an Xbeach model to explicitly include the contribution of wave run-up to the coastal storm surge (following Erickson et al. 2015). The suite of models will forecast storm surge, coastal flooding, and erosion risk and they will be included in the Arctic Information Fusion Capability (AIFC).

PROJECT: Identifying, Tracking and communicated Sea-Ice Hazards in an Integrated Framework

The overarching objectives of this project are to identify, track and communicate hazards associated with ice in the ocean such as the entrapment of vessels; structural damage to vessels and infrastructure; risk to personnel and assets due to detachment of landfast ice; and the limitation of oil spill response. These objectives are directly motivated by input from USCG D-17 and review of USCG Arctic Information Needs workshop report. The proposed work addresses several of the 20 US MDA challenges identified by the USCG.

Our approach is two-pronged and involves 1) the development of technology to identify and track ice-related hazards; and 2) the creation of an Arctic MDA testbed located in Barrow, Alaska, to assess the value of available met-ice-ocean data streams and test strategies for effective communication in an Arctic emergency response setting.

The outcomes of this work will include i) the development of software products for deriving ice motion and deformation from land-based and ship-based radar platforms; ii) baseline coastal sea ice motion data for long-term hazard assessment and model validation; iii) assessment of a new satellite-based methodology for assessing ice stability and trafficability; iv) a leadership role in the development of an Arctic MDA testbed.

PROJECT: Arctic Information Fusion Capability (AIFC)

Arctic Information Fusion Capability (AIFC) seeks to support operational decision makers in the maritime domain ranging from operational commanders to tactical operators to community-based observers.  AIFC strives to gain two dimensional geographic orientation of precision mapping data, near-real-time and high resolution satellite imagery incorporated with available modeling, sensors, web based communications and appropriate social networking feeds to gain domain awareness in support of operational decision making and interface with humans and responders in the field. 

Further, AIFC will provide elements of domain awareness from a 3 dimensional “column view to gain insights vertically from seabed to surface and surface skyward.  AIFC seeks to achieve a near- real-time and forecast decision support that can transition to intelligent decision support in a follow-on phase.  AIFC near-real-time products will be delivered as rapidly as possible following capture and processing of the observation. In general, near-real-time is a qualitative descriptor.  In the AIFC context it refers to products delivered between a few seconds up to 30 minutes following capture.

In Phase 1, AIFC will leverage and fuse existing sources, capabilities, and models to provide operational decision support.  This includes visualization and mapping of sensor output, marine systems modeling, communications, appropriate social networking feeds, and other information required for Arctic maritime situational awareness.  This also includes a deployable/field capability to support USCG emergency on-scene coordinators and community-based observations. In Phase 2, AIFC will transition to provide intelligent decision support and prototype the automatic control of sensors and robotic systems.

PROJECT: Low Cost Wireless Remote Sensors for Arctic Monitoring and Lifecycle Assessment

The project goal is to develop low-cost wireless sensors for use in remote monitoring, asset management, surveillance, and security, particularly in Arctic and marine environments. We categorize a sensor’s functionality into three areas: detection of an input event, computation of the detected event, and communication of the data. We develop an inexpensive, self-organizing network of devices that can reliably compute and communicate detected events. The computing device for each sensor node is the MoteineoR4 RFM69W. An integrated RFM69 transceiver enables wireless ISM band communications. A software simulator and hardware proof-of-concept consisting of a 7x7 array of nodes has been constructed. Our initial target application is to utilize acoustic and electromagnetic signal detectors to classify human vs. animal traffic in a remote area. 

The concurrent phase of the project includes the evaluation of the lifecycle cost (LOC) for the deployed sensor array. The LOC framework will be applied to the monitoring of the US-Canada border for intrusions deployment scenario. Assessment will employ common techniques in life cycle assessment with focus on geospatial array structure associated with terrain and climate as well as overall power requirements, proximity to urban areas and the end-of-life considerations. 

ASRC Federal Mission Solutions (AFMS) will identify, from the mission perspective, the systems involved in the Command and Control and Situational Awareness missions for multiple DHS projects, including USCG and Customs and Border Patrol. Using its experience as the USCG’s National Security Cutter C2/S2 system developer, AFMS will develop an integration strategy that will incorporate data from these sensors into tactical mission components for use by multiple echelons.

The team will initially use its open system architecture (OSA)- based C4 system for prototype component development and initial sensor integration and fusion. After initial integration of sensor data from both simulated and fielded sensors, the AFMS team will fuse the data into a tactical track picture and situational awareness display in order to prove the usefulness of the low-cost remote sensor approach for C2 and SA. The team will develop a set of decision aids to support events detected by the sensor network, including new contacts, lost contacts, indeterminate contact information requiring human-in-the-loop interpretation, as well as network readiness information.

PROJECT: Arctic Education Implementing the Arctic Strategy in Training 

This project includes three courses developed and submitted over three years.  Years one and two have involved the construction of the Basic Ice Navigation course, which is complete and is currently being offered as a face-to-face class at Maine Maritime Academy.  The course has been submitted to the Coast Guard for approval for Standards of Training, Certification, and Watchkeeping (STCW) certification. 

Select Publications

Alessa, L., Kliskey, A., Drukenmiller, M., Griffin, D., McKann, H., Myers, B., Pulsifer, P., Washburn, E., Beaujean, G., Behe, C., Jackson, L. 2016. Best Practices fro Community-based Observing. Report of a National Workshop, Oct 5-6, 2015. Center for Resilinet Communities, University of Idaho.  

Alessa, L., Williams, P., Kliskey, A., Beaujean, G. 2016. Incorporating Community-based Observing Networks and Systems: Toward a Regional Early Warning System for Enhanced Responses to Arctic Critical Events. Washington Journal of Environmental Law and Policy 6(1): 1-27.

Audubon, February 2016: Arctic on the Edge-Special Issue. Aboard the Last Ship to Nowhere-M Funk and E Horvath. Featuring J. Welker and E. Kleins’s ADAC sea ice and oil detection program.

Brunswick, D., Ravens, T. M. "Development and validation of an Arctic oil spill model making use of the 2009 Barents Sea experimental spill," to be submitted to  Marine Pollution Bulletin.  Anticipated submission:  November 2017.

Dammann, D. O., H. Eicken, A. R. Mahoney, F. J. Meyer, J. Freymueller, and A. M. Kaufman (2017 (in review)), Assessing landfast sea ice stability and internal ice stress around ice roads using L-band SAR interferometry and inverse modeling, Cold Reg. Sci. and Tech.

Dammann, D. O., H. Eicken, E. Saiet, A. R. Mahoney, F. J. Meyer, and J. C. George (2017, in review), Traversing sea ice – linking surface roughness and ice trafficability through SAR polarimetry and interferometry, IEEE journal of selected topics in applied earth observations and remote sensing.

Dammann, D. O., H. Eicken, F. J. Meyer, and A. R. Mahoney (2016), Assessing small-scale deformation and stability of landfast sea ice on seasonal timescales through L-band SAR interferometry and inverse modeling, Remote Sensing of Environment, 187, 492-504

Dissanayake, A. L., Gros, J., and Socolofsky, S. A. “Integral models for bubble, droplet, and multiphase plume dynamics in stratification and crossflow,” for submission to Environmental Fluid Mechanics.  Anticipated submission:  September 2017.

Eicken, H., A. Mahoney, J. Jones, T. Heinrichs, H. Bader, D. Broderson, H. Statscewich, T. Ravens, M. Ivey, and A. Merten 2016. The Potential Contribution of Sustained, Integrated Observations to Arctic Maritime Domain Awareness and Common Operational Picture Development in a Hybrid Research-Operational Setting. Theme (s) 4.

Eicken, H., A. R. Mahoney, J. M. Jones, T. Heinrichs, D. Broderson, H. Statsweich, T. J. Weingartner, M. Stuefer, T. M. Ravens, M. Ivey, A. Merten, and J. Zhang (2017, in press), Sustained observations of changing Arctic coastal and marine environments and their potential contribution to Arctic maritime domain awareness: A case study in northern Alaska, Arctic.

Eicken, H., A. R. Mahoney, T. M. Ravens, M. Ivey, A. Merten (2017, submitted), Sustained, Integrated Observations for Arctic Maritime Domain Awareness in a Hybrid Research-Operational Setting in Northern Alaska, paper submitted to IEEE Marine Technology Society Oceans 17.

Griffith, D., Alessa, L., Kliskey, A. 2017. A Typology of Community-based observing. NIMIO Bulletin.12: 32-39.

Gros, J., Dissanayake, A. L., and Socolofsky, S. A. “Oil spill modeling in the ocean environment:  estimation of oil properties for traditional pseudo-component models,” to be submitted to Marine Pollution Bulletin.  Anticipated submission:  November 2017.

Jones, J., H. Eicken, A. Mahoney, M. Rohith, C. Kambhamettu, Y. Fukamachi, K. I. Ohshima, and J. C. George 2016. Landfast sea ice breakouts: Stabilizing ice features, oceanic and atmospheric forcing at Barrow, Alaska. Continental Shelf Research, 126, 50-63.

Klein, E. S., and J. M. Welker. 2016. Influence of sea ice on ocean water vapor isotopes and Greenland ice core records. Geophysical. Research. Letters. 43, 12, 475–12,483, doi:10.1002/2016GL071748.

Kukulya, A. L., J. G. Bellingham, J. W. Kaeli, C. M. Reddy, M. A. Godin and R. N. Conmy. 2016. Development of a propeller driven long range autonomous underwater vehicle (LRAUV) for under-ice mapping of oil spills and environmental hazards: An Arctic Domain Center of Awareness project (ADAC). 2016 IEEE/Oceanic Engineering Society (OES) Autonomous Underwater Vehicles (AUV), Tokyo, Japan, 2016, pp95-100.URL:

Mahoney, A. R., D. O. Dammann, F. J. Meyer, H. Eicken, and M. A. Johnson (2017), Monitoring smallscale sea ice motion with land-based and space-based radar, 32nd International Symposium on Okhotsk Sea & Polar Oceans, Mombetsu, Japan, 19-22 February, 2017.

Siewert S., V. Angoth, R. Krishnamurthy, K. Mani, K. Mock, S. B. Singh, S. Srivistava, C. Wagner, R. Claus, M. Vis. 2016. Software Defined Multi-Spectral Imaging for Arctic Sensor Networks, SPIE Proceedings, Volume 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII [program, h-index], Baltimore, Maryland, April 2016.

Siewert S., M. Vis, R. Claus, R. Krishnamurthy, S. B. Singh, A. K. Singh, S. Gunasekaran. 2017. Image and Information Fusion Experiments with a Software-Defined Multi-Spectral Imaging System for Aviation and Marine Sensor Networks. AIAA SciTech 2017 [program], Grapevine, Texas, January 2017.

Siewert S., J. Shihadeh, Randall Myers, Jay Khandhar, Vitaly Ivanov. 2014. Low Cost, High Performance and Efficiency Computational Photometer Design. SPIE Sensing Technology and Applications, SPIE Proceedings, Volume 9121, Baltimore, Maryland, May 2014.

Williams, P., Alessa, L., Beaujean, G., Kliskey, A., Witmer, F., Rieken, V., Trammell, E. In review. Community-based observing networks and systems: An assessment of correspondence between human perceptions of environmental change and instrument-derived data. Regional Environmental Change.

Zhang, J., Invariant sea ice properties in high-resolution sea ice models, Geophysical Research Letters, in prep., 2017.

ADAC Fellows

Our current ADAC fellows are students from the University of Alaska Anchorage (UAA) and University of Alaska Fairbanks (UAF).

Career Development Grant (CDG) Fellows:

Christina Hoy - Christina was admitted to the ADAC Program Fall 2015 as a first year undergrad. Currently studying Civil Engineering, she plans on concentrating on Environmental and Water Resource Engineering. With opportunities granted by ADAC, Christina spent eight weeks participating in the Maritime Security Center’s Summer Research Institute hosted by Stephens Institute of Technology in Hoboken, New Jersey. She worked on a multidisciplinary research team focused on underwater acoustics and increasing situational awareness in remote maritime locations. Upon completion of the program, Christina and her team designed a self-sustaining hydrophone system fitted with a satellite system to report data recordings remotely to an email address. Christina also studied port security and operations, hoping to focus on this field specifically later in her college career. In her time at the University of Alaska Anchorage, she has been an active member of the UAA Chapter of the Society of Women Engineers where she holds the president position.

Workforce Development (WFD) Fellows:

Jessica Faust - Jessica Faust joined the ADAC CDG Fellowship in January of 2017. She is a graduate student of the Department of Biological Sciences at UAA, where she is examining the population dynamics, distribution, and habitat association of Little Brown Bats. In 2015, Jessica spent 12 weeks collecting ultrasonic acoustic data throughout Southcentral Alaska and Prince William Sound, primarily based out of Cordova. Her master’s thesis analyzes the ultrasonic recordings to determine habitat preference and potential colony locations of bats. Jessica graduated from Willamette University, in 2012 with a Bachelor of Arts in Biology, and will begin pursuing her doctorate in the fall of 2017. She is interested in a teaching career in balance with research and community outreach.

Lonnie Young - Lonnie Young is currently studying Electrical Engineering at UAA. He has been a part of the International Brotherhood of Electrical Workers for thirteen years and plans on concentrating his studies on power and distribution to compliment his electrical knowledge. Lonnie is currently the chair of IEEE (The institute of electrical and Electronics Engineers) student branch. In his spare time, he likes to downhill ski, hike as well as travel the globe.

Seth Campbell - Seth Campbell is a graduate student at UAA pursuing a MS in Civil Engineering specializing in Water Resources. Seth graduated from UAA with a BS in Mechanical Engineering in 2014. Seth became interested in Water Resources engineering after working with the UAA chapter of Engineers Without Borders from 2010-2012. As an ADAC fellow, Seth has participated in the Arctic Incidences of National Significance conference and is working to develop an ice indexing system for the Great Lakes as part of ICECON. Seth is keenly interested in hydrology and the role of sea ice in climate change. In his spare time, he enjoys playing guitar, hiking, reading, and biking.

Kelsey Frazier - Seeking BS in Mechanical Engineering at UAA.

Alumni Fellows:

Matthew Ahlrichs, CDG Fellow, UAA

James Matthews, CDG Fellow, UAA

Leif Hammes, CDG Fellow, UAA

Kyle Alvarado, CDG Fellow, UAA

Patrick Steckman, WFD Fellow, UAF

Academic Institutions:

Maine Maritime Academy

University of Idaho

University of Washington

Woods Hole Oceanographic Institute

US Coast Guard Academy and their Center for Arctic Study and Policy

Texas A&M University

University of New Mexico *

University of Texas El Paso *

Industry Partners:

Axiom Data Science

Alaska Marine Exchange

Dubay Business Services

NOVA DINE-Kestrel **

ASRC Federal Solutions **

Collaborative Organizations:

NOAA & National Weather Service

Canadian DND and Canadian Academic Researchers

USCG Headquarters, USCG Pacific Area, USCG Research & Development Center, and District 9 and 17

DoD Alaska Command and Alaska NORAD Region

Alaska Ocean Observation

NASA-OSD Arctic Collaborative Environment

DHS Centers of Excellence at Rutgers University, Stevens Institute and University of Houston

National Ice Center

National Science Foundation

* Federally Designated Minority Serving Institutions (MSI)

** Federally Designated Tribal Organizations (FDTO)