Scope of activities

The Environmental Intelligence Collaboration Team is a new team created as part of Arctic Research Plan 2017-2021. The team's scope of activities will include implementation of Research Objectives and Performance Elements listed under Research Goal 9, which is described as follows in the Plan:

To adequately support decision-making in the face of unprecedented change in the Arctic, the United States and its international partners need improved scientific data collection and stewardship, understanding, and environmental predictions. This challenge requires frameworks for generating Environmental Intelligence: integrated environmental knowledge that is timely, reliable and suitable for the decisions at hand.

Developing suitable Environmental Intelligence frameworks requires the integration of two distinct aspects of research. The first concerns the end-to-end integration of research across the linked and iterative steps of problem identification, environmental observing, understanding, prediction, and decision support. For example, safe marine transit through Arctic waters requires engagement with operators to understand the details of their information needs, such as high resolution sea ice forecasts. To produce these forecasts, sparse yet detailed observations of sea ice from drifting ice buoys, community-based observers, and other in situ observations must be synthesized with broad, low- resolution satellite observations. Synthesized observations must then be assimilated into forecast models, which subsequently must be tested and validated through efforts like observational process studies—feeding back into an iterative cycle of improved observing and modeling capabilities.

The second aspect of Environmental Intelligence requires integration of research across the components of the Arctic System, as most decision-making contexts require a holistic view. Building on the example in the previous paragraph, research is needed to inform how gridded estimates of sea ice thickness are interdependent with weather systems and ocean currents. With its emphasis on understanding the interconnected nature of the Arctic, IK presents a model for Arctic System integration.

Interagency collaboration is ideal for making progress on both end-to-end and Arctic System integration, because capacities and mission mandates to provide decision support tend to be distributed across many institutions and independently sponsored work. For example, NOAA and the Department of the Interior (DOI) sponsor many Alaska-based programs directly concerned with research for stakeholder engagement and decision support, such as ACCAP, AOOS and FWS’s LCCs. These agencies and others like NSF, DOE, and NASA also support sustained observing of the Arctic environments; DOE, NSF, NASA, ONR, and NOAA all contribute to models for improved predictions and projections, and many agencies support data centers that contribute comprehensive data stewardship for valuable Arctic data products. The Arctic Domain Awareness Center (ADAC), sponsored by DHS, bridges between research and operations to improve maritime domain awareness in support of the U.S. Coast Guard’s (USGC) mission. IARPC Collaborations will serve as a valuable forum for sharing practices and linking capabilities across IARPC agencies and outside collaborators.

While these efforts in the Arctic provide a solid foundation of knowledge and expertise, the Environmental Intelligence Goal addresses key areas for interagency progress. The sparseness of observational coverage and limited year-round environmental intelligence gathering have hobbled efforts to fully understand the impacts of changing environmental conditions on global processes as well as weather patterns, ecosystems, economic development, and safety. Interagency collaboration can leverage sparse observing assets and propel enhancements through the development of autonomous technologies (Research Objective 9.1). Modeling is a vital tool to advance system integration, to capture feedbacks within the systems, and to extend current understanding into the future. Progress is needed on how Arctic-specific processes and feedbacks are represented in models (Research Objective 9.2). Further, Arctic modeling can benefit from global and regional improvements to things like model resolution, as well as from comparative assessments, including quantified uncertainties among models (Research Objective 9.3). Arctic data stewardship, sharing, and access is evolving from systems where data are discovered in data catalogues and downloaded to the local machines of users, to a system of distributed data nodes with visualization and collaboration platform capabilities made to enable interoperability. Interagency collaboration is needed to understand the connection between these distributed nodes and work toward common visions (Research Objective 9.4) for exchanging and integrating data, in particular across disciplines. Finally, the practices of and frameworks for exchanging knowledge between researchers and stakeholders are in an exciting and dynamic growth period, yet few organizations have the capacity or mandate to adequately address the needs. IARPC Collaborations can serve as a valuable forum for advancing dialog on engagement research, decision support, and science communications (Research Objective 9.5) and feedback critical areas for progress (e.g. specific data needs) to the other Research Objectives in this Goal.

Improvements within and across each of these areas will improve the ability to understand, communicate about, and support decisions in response to the impacts of Arctic change. These efforts, across the scales from community to global at which IARPC agencies engage, support each policy driver of this plan (Well-being, Stewardship, Security, Arctic-Global Systems).

References


Team leaders

Jeremy T. Mathis
NOAA (Website)

Anjuli Bamzai
Office of Polar Programs


Performance elements from the Arctic research plan

9.1 Enhance multi-agency participation in new and existing activities to improve best practices, coordination, and synthesis of Arctic observations toward a fully integrated interagency "U.S. Arctic Observing Network" (U.S. AON).

  • 9.1.1 Coordinate U.S. agency and outside collaborators support for and participation in the international Sustaining Arctic Observing Networks (SAON) process.
  • 9.1.2 Work with the research community and other stakeholders to develop the concept of multi-agency research coordination networks to advance observational science and promote broad synthesis within thematic research communities.

9.2 Advance understanding of the Arctic System by using global and regional models with detailed Arctic processes to understand feedbacks and interactions within the components of the Arctic system and with the climate system as a whole.

  • 9.2.1 Support and coordinate research to advance understanding of the connections between the Arctic and mid-latitude weather patterns and vice-versa.
  • 9.2.2 Support and coordinate research to enhance the understanding of connections between Arctic and global ocean circulation.
  • 9.2.3 Enhance understanding of processes and their interactions and feedbacks within the Arctic System itself, including the complex relationships between the ocean, sea ice, land, and atmosphere; impacts of snow on ice; interactions between Arctic clouds and aerosols; effects of thermal forcing of sea ice; changes in ocean stratification; stratosphere-troposphere interactions; and radiative exchanges of energy throughout the system.
  • 9.2.4 Conduct a survey and identify investigator-driven modeling projects designed to understand important local and global Arctic System feedbacks.

9.3 Enhance climate prediction capabilities for the Arctic system from sub-seasonal to decadal timescales and climate projection capabilities up to centennial timescales by focusing on improving earth system models and their interactions, and assessing the strengths and weaknesses of the various coupled regional arctic and earth system models by conducting intercomparison and model evaluations.

  • 9.3.1. Support the configuration and the initial development of a global variable resolution model with very high resolution in the Arctic that will allow high-resolution interactions within the Arctic System and interactions between the Arctic and mid-latitudes
  • 9.3.2 Support model development activities in global earth system models focusing on increased resolution, better coupling techniques, and inclusion of new process models in the Arctic for improved predictions, projections, and better representation of extreme events. In addition to developing models for CMIP6, this will include routine global ocean data assimilation capabilities linked to Global Ocean Observing System observations.
  • 9.3.3 Foster interactions between the Arctic Testbed and Environmental Modeling Center’s weather modeling efforts to facilitate the improvement of model guidance at higher latitudes.
  • 9.3.4 Support model development of Regional Arctic System Models focusing on improved resolution, better coupling, inclusion of new process models, and better assimilation techniques for improved seasonal predictions.
  • 9.3.5 Support Systematic Improvements to Reanalyses of the Arctic (SIRTA) to address the need for improved models of Arctic weather, sea ice, glaciers, ecosystems, and other components of the Arctic System.
  • 9.3.6 Coordinate and support the ISMIP6 efforts in the U.S. by integrating ice- sheet models into coupled climate and earth system models to both: (1) improve sea level projections due to changes in the cryosphere; and (2) enhance scientific understanding of the cryosphere in a changing climate.

9.4 Enhance discoverability, understanding, and interoperability of Arctic data and tools across Federal data centers.

  • 9.4.1 Advance system models of U.S. observing inventories and data centers to further understanding of these capacities so that informed, optimal, strategic decisions and design, and spending plans can be made.
  • 9.4.2 Promote a nationally and internationally interoperable Arctic data sharing system that will facilitate data discovery, access, usage in many contexts, and long-term preservation, building off the efforts of NSF’s Arctic Data Center, the AOOS Regional Data Assembly Center and the Alaska Data Integration Working Group (ADIWG).
  • 9.4.3 Enhance the timely availability, diversity of content, and inclusion of international contributions to the Arctic data sets and resilience tools within the Arctic Theme for the Climate Data Initiative (CDI) and CRT.
  • 9.4.4 Advance agile situational awareness and decision support for Arctic operators through efforts like ADAC's Arctic Information Fusion Capability28, ERMA, and NASA ACE project.
  • 9.4.5 Update baseline mapping and charting across the Arctic, including additional charting in Arctic waters, updates to baseline topographic mapping and supporting data, and updating high resolution imagery-derived elevation data repeated coverage. Multiagency partners include Alaska Mapping Executive Committee, Alaska Geospatial Council, and Arctic-related LCCs.

9.5 Advance research, tools and strategies to improve the accessibility and usability of Arctic science for decision support.

  • 9.5.1 Advance coordination among Federally-funded research programs that provide decision support to Arctic stakeholders.
  • 9.5.2 Advance policy-relevant science communication through efforts like the annual Arctic Report Card, the Arctic Research Consortium of the United States (ARCUS), and the Study of Environmental Arctic Change (SEARCH).

Accomplishments

The EICT is tasked with integrating across three sub-teams: Arctic Observing Systems, Arctic Data, and Modeling. Undertaking in-situ system-wide measurements in the Arctic region is difficult, given the logistical challenges of working in extreme environments. The urgent need for environmental knowledge in the Arctic highlights the need for a new and responsive approach to Arctic observing. The Environmental Intelligence (EI) framework aims to achieve an end-to-end integration of linking the results of scientific research and decision support. By integrating across Arctic system observing, data and modeling efforts, scientific results can be more easily translated in a holistic way into stakeholder needs and policy-relevant contexts. The EI approach aims to produce environmental knowledge that is timely, reliable, and suitable for decision support at the local, state, national and pan-Arctic levels.

The EICT team leaders and the sub-team leaders used the IARPC annual planning meeting in Anchorage (March 2017) to identify cross-cutting themes that emerged from the new IARPC FY2017-FY2021 plan. Team leaders carefully identified research foci to incorporate the network analysis and expertise of the eight other IARPC collaboration teams. Topics that emerged include the carbon budget/cycling, the energy budget, food security, maritime safety and shipping, and national security. The team leaders identified the carbon budget focus as an action-ready topic and have woven this topic through sub-team meetings and IARPC group meetings. Progress has been made with the EI carbon focus following the performance element 9.5.1 (advance coordination among federally-funding research programs that provide decision support to Arctic stakeholders) through the hosting of joint collaborative meetings as well as the EI Carbon Forum hosted in July. Examples of collaborative meetings held by the EI sub-teams include carbon data interoperability (ADST-AOSST), terrestrial carbon observations: a carbon case study (AOSST), and regional Arctic models: a focus on carbon (MST). The first of the EICT scheduled forums took place in late July to introduce the EI carbon focus and to solicit valuable feedback from the community. Progress has also been made on performance element 9.5.2 (advance policy-relevant science communication) via the inclusion of an essay to NOAA’s Arctic report card (Collecting Environmental Intelligence in the New Arctic). The EICT is also hosting a poster session at the American Geophysical Union Fall Meeting (December 2017) to make further progress on the carbon focus (Science to Decision Making: Using the Environmental Intelligence Framework to Constrain the Arctic Carbon Budget).

The following three reports outline the achievements and goals of the EI sub-teams.

  1. Arctic Observing Systems Sub-team

  2. Modeling Sub-Team

  3. Arctic Data Sub-Team

2017 Performance Element Reporting Log

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