Steady progress has been made in the understanding of Arctic sea ice cover and its role in the Arctic and global systems. In the committee’s view increased understanding of the Arctic sea ice cover is linked to steady improvements in our ability to predict sea ice conditions over seasonal to decadal timescales. These gains are marked by important advances in numerical models, instrumentation, methodologies, analysis, data assimilation, and observational techniques. However, recent dramatic change in the ice cover, accompanied by increased demand for access to this heretofore remote region, has created an urgent and escalated level of need for Arctic sea ice predictions to serve a broad stakeholder community. Added pressure comes with the reality of the limited resources (i.e., funding and infrastructure) available to support timely progress and the likelihood that, in the face of continued warming, the Arctic will remain a dynamic environment for the foreseeable future.
This report outlines key challenges and high-priority strategies to facilitate a transformative change in our predictive capability of sea ice conditions on the seasonal to decadal timescale (Box 4.1). Chief among the strategies is a deliberately integrative approach, founded on a sustained and coordinated conversation among the user, modeling, and observation communities. In fact, to be successfully implemented, many of the strategies will require the use of an integrative approach. In some ways, the strategies would also serve as a mechanism for sustained conversation and collaboration among the three communities.
This committed approach is necessary to reveal and address key challenges to our fundamental understanding of the Arctic environment and its connection to the global climate system; to balance high-priority user needs against realistic predictive capabilities; to foster coordinated support of this work within the private and public sectors; and to provide guidance in allocation of resources to support the most promising avenues in addressing the most pressing needs. It is an approach that moves beyond the status quo, which relies heavily on a largely disjointed set of research initiatives that often fail to produce a clear set of priorities. Fortunately, there are a number of precedents that exist to inform the design and implementation of this comprehensive communication network. The more daunting challenges are to
determine (1) the entity responsible for coordinating and facilitating this exchange and (2) the approach to ensure its sustained support.
Although the report suggests specific advancement strategies related to the models used to formulate seasonal and decadal sea ice prediction, the same level of specificity is not provided for observations (e.g., types and locations or frequencies of observations). Rather, it is the committee’s view that systematically identifying obstacles that prevent models from producing more accurate sea ice predictions at seasonal to decadal timescales will aid in (1) directing and prioritizing process studies, (2) designing observing networks, and (3) focusing model development. This perspective takes into account that the modeling infrastructure has advanced sufficiently to support a series of sensitivity studies designed to strategically inform research investments related to key observational needs. In addition, the committee has identified steps that will advance the modeling capabilities that are essential to sea ice prediction over seasonal to decadal timescales. These steps involve sustained interactions with the observational and user communities, reinforcing the importance of integration across the three communities. The extent to which such integration can be achieved will likely determine the rate at which sea ice prediction capabilities advance.
Compilation of Key Challenges and Strategies
GAPS IN OUR UNDERSTANDING
• Overarching Challenges
o Treating Sea Ice as Part of a Global System. - A key to advancing our understanding and predictive capabilities is the treatment of the sea ice cover as an integral part of the complex Arctic system which, in turn, is an integral element of the global system. Adding to this complexity is the broad range of human activities that not only influence the Arctic system, but are also influenced by it.
o Impacts of the Regime Shift of Arctic Sea Ice. - Understanding how the recent regime shift in the Arctic sea ice cover, resulting in a significant reduction in the amount of multiyear ice compared with first-year ice, affects the processes governing the atmosphere-sea ice-ocean system and the models and observations used to study and predict Arctic sea ice dynamics.
o Identifying Diverse and Emerging Stakeholder Requirements. - As the Arctic is being transformed by globalization and climate change, new stakeholders with additional and more sophisticated requirements are emerging. Clearly defining these diverse needs as they relate to seasonal to decadal sea ice prediction is crucial to inform the future directions of modeling, observations, and overall research.
• Challenges in Advancing Predictive Capability
o Competing Approaches to Seasonal Sea Ice Prediction. - Although limitations in the various approaches used to generate seasonal forecasts are generally acknowledged, there is a lack of quantitative information about their relative strengths and weaknesses.
o Observational Requirements for Seasonal Sea Ice Prediction. - Seasonal sea ice prediction capability depends on adequate knowledge of initial ice-ocean conditions, even though the specific requirements associated with “adequate knowledge” have yet to be established. This challenge is compounded by the need for a fast turnaround in acquiring and accessing observational data.
o Projecting Realistic Forcings and Feedbacks for Decadal Sea Ice Predictions. - A key challenge in coupled climate models is the capability to realistically simulate atmospheric and oceanic conditions of relevance to sea ice variability, including the identification of model processes that contribute to unrealistic forcings and feedbacks.
STRATEGIES FOR THE FUTURE
• Overarching Strategy
o A Deliberately Integrated Approach for Sustained and Coordinated Collaboration Among User, Modeling, and Observation Communities. - A deliberately integrated approach is needed to facilitate coordinated and sustained discussions and collaborations among the user, modeling, and observation communities to inform effective research activities and to set realistic expectations for predictions. Such an approach would need to take full advantage of existing infrastructure and draw from comparable efforts in other fields.
• Strategies to Improve Sea Ice Predictive Capabilities: Seasonal to Decadal Timescales
o Evaluation of Existing Seasonal Prediction Methods. - A coordinated and detailed comparison of the different approaches used to generate seasonal sea ice forecasts could establish baseline expectations for predictive skill and identify priority needs, setting the stage for advances in predictive capability.
o Process-Based Studies Targeted at Increasingly Prevalent First-Year Ice Cover. - Questions surrounding the impact of the trend toward an increasingly seasonal Arctic sea ice cover could be addressed with the development of a highly coordinated and integrated process-based study, analogous to Surface Heat Budget of the Arctic Ocean (SHEBA) project, focused on understanding oceanic, atmospheric, and terrestrial contributions to seasonal sea ice predictions.
o Model Sensitivity Studies to Determine Key, First-Order Observational Needs. - There is a particular need at this time for a coordinated effort to design and implement a set of model sensitivity studies that will provide quantitative metrics to assess the impact of various observation types, locations, and densities on seasonal sea ice forecasts.
o Enhanced Numerical Model Capabilities. - Enhancement of model-based predictive capabilities will require coordinated experiments to (a) identify which variables and processes are critical to simulating a realistic ice cover, (b) investigate the source of climate model drift, and (c) guide decisions regarding high-priority model development needs and the expansion of models to include capabilities and additional variables of interest to stakeholders.
• Knowledge Management
o Improved Information and Data Management. - Given the vast amounts of disparate data on Arctic sea ice and the numerous stakeholders who use these data, there is a need for a coordinated and centralized information hub for Arctic datasets that facilitates the timely access to observational and modeling results, and encourages sustained communication among stakeholders.