Optimizing the Arctic Social Observation System With an Arctic System Model
Tracking well-being of arctic residents as they confront environmental and social change can best be accomplished with an integrated international system of social observations. The Arctic Human Development Report (AHDR) identified three social indicator domains important to arctic people–control of destiny, cultural identity, and ties to nature–that complement the three United Nations' human development domains of material well-being, human health, and education. The Arctic Observation Network Social Indicators Project (AON-SIP) assembled relevant data and identified logistical, financial, and potential political challenges to closing gaps in the existing observation system. Given the identified challenges, and recognizing the contribution of data assimilation and observing system simulation experiments (OSSEs) to optimizing atmospheric and ocean observing systems, we develop a prototype arctic social system model for synthesis and optimization of the social observing system.
The objectives of the model are as follows: 1. determine highest priorities for integrated observations to track response of the arctic system to global change; 2. improve understanding of social system dynamics, including interaction of different indicator domains and links beyond the arctic; and 3. provide policy-relevant information about potential emerging social problems before they are observed. To meet these objectives, we
Bring all six AHDR social indicator domains together to create a true system model;
Model community dynamics based on current understanding of key system processes;
Identify and quantify external "forcing mechanisms" such as global market forces, government policies, and climate change;
Address the spatial complexity of the arctic human system, noting barriers created by political and geographic boundaries;
Keep the system structure simple and transparent;
Utilize observations from AON-SIP and other public sources to the extent feasible; and
Explore use of data assimilation techniques and OSSEs to quantify the contribution of potential new observations to improving the model's explanatory and predictive power.
The initial prototype version models dynamics of arctic Alaska. The goal is to extend the model to the entire Circumpolar North.
