Monitoring Observing Modeling and Prediction

Integrating and improving monitoring, observing, modeling, and prediction efforts to advance Arctic research

Scope of activities

Monitoring is a subset of observing and generally refers to observing specific variables over time to detect change. Similarly, prediction is a subset of modeling and refers to using numerical models to estimate how the Arctic or a subsystem of it may change in the future. MOMP is critical for increasing understanding of the natural and human components of the Arctic system as well as the degree and direction of past and future changes. MOMP is also essential for providing actionable data, forecasts, and new research directions.

Sustained observations and widespread monitoring support research activities by providing information on the variability of the Arctic system. This information provides a necessary baseline for future studies and data for evaluating models and making both short-term predictions and longer-scale projections. Focused short-term observational efforts are important for improving fundamental understanding of Arctic processes, regions, and extreme events. A foundational Arctic observational capability requires a sustained, coordinated, and integrated network of satellites, other remote sensing, and in situ observing systems suitable for Arctic conditions; collection of physical and biological samples; resources to train instrument operators, support data quality, and analyze observations; and continued development of new technologies, such as low-cost and autonomous sensors, to fill observational gaps.

Many critical Arctic observational and monitoring efforts are conducted by non-federal partners. IARPC will improve coordination and integration of observations conducted or supported by federal agencies with those conducted or enabled by non-federal partners including the state of Alaska, Indigenous and Tribal organizations, Arctic communities, research institutions, and private sector.

Future development of Arctic observing capabilities should consider sustainability in field research, good practices to limit potential environmental impacts, coordination with other observational efforts, and meaningful engagement with Indigenous Peoples, including incorporation of Indigenous Knowledge through Indigenous leadership, participatory research, and co-production in the design and implementation of local, regional, and circumpolar observing systems.

Computational models combine findings from theory, observations, and process studies, providing a framework for understanding interactions among components of the Arctic and between the Arctic and the global system across a range of scales and complexity. Short-term predictions and longer-term projections of the Arctic system are essential for providing information to users and decision-makers to inform the design of climate adaptation and resilience plans and to support hazard mitigation actions. A foundational modeling capability for the Arctic requires a set of models of different complexities, integration of observing and modeling capabilities, and strong interactions with partners to understand their needs, communicate uncertainties, and provide information for decision-making.

The need to advance understanding of Arctic processes and system interactions drives the effort to improve synthesis of monitoring, observing, and modeling. Numerical models require observations for initialization, evaluation, and assimilation. Integrating observational and modeling output enables creation of value-added products and can help fill spatial and temporal gaps in analysis. Models can provide critical information to inform the design and optimization of observing networks. Advances in related fields such as AI and machine learning should be explored to improve analysis and integration of large volumes of observational and model data. Such integration will accelerate the advancement of knowledge of the dynamic Arctic system and lead to improved predictive capabilities. Working with the Monitoring and Observing communities of practice, this team seeks to identify current gaps in observational or modeling capabilities that hamper predictive skill of the Arctic system, barriers that hold back progress in filling these gaps, and key activities most critical to improving predictability, including the need to maintain critical existing MOMP capabilities.

In coordination with the Education, Training, and Capacity Building Foundational Activity, training the next generation in MOMP activities will be incorporated. IARPC will also promote international coordination and cooperation in Arctic system MOMP efforts. For example, through the U.S. Arctic Observing Network (US AON) Board, IARPC will support federal agencies’ efforts to improve the performance of Arctic-wide observing and data management activities. Lastly, IARPC will increase coordination and engagement with other federal efforts (including public-private partnerships) focused on improved observations, modeling, and predictability of the Earth system. This will include working with the U.S. Global Change Research Program (USGCRP) and the Interagency Council on Advancing Meteorological Services (ICAMS), and identifying and prioritizing actions to implement the Earth System Predictability Research and Development Strategic Framework and Roadmap.

Team leaders

Sally McFarlane
Atmospheric Radiation Measurement User Facility (Website)

David Allen
NOAA, Arctic Research Program (Website)


To be added in 2023.