Key Uncertainties and Next Steps: Current ARCSS Research

The Process
The Arctic climate system is tightly coupled, rich in its complexity. ARCSS-funded Arctic research is similarly rich, but it is also somewhat fragmented. To understand the Arctic climate system, we face the challenging task of integrating and coordinating our science both within the U.S. and across the global community. The five 'ARCSS Themes' from the 1998 ARCSS science plan, Toward Prediction of the Arctic Systemmay be one path to achieve this integration; coordination of existing component-driven research, and new interdisciplinary initiatives are others. To focus the discussion, we should consider the following questions associated with each theme:

1. What are the key uncertainties?
For each key uncertainty:
2. What is the impact of this uncertainty on our understanding of the Arctic system?
3. What is our level of confidence in the above assessment?
4. What is our level of readiness to deal with this uncertainty?
Choosing critical focus areas for immediate attention should be driven by a high level of importance, confidence and readiness.
5. Finally, should this focus area be addressed by a new or existing initiative, by one or a combination of existing ARCSS components, or by some other means?
Here is an example:
Key uncertainty in projecting Arctic climate change (theme 1): Interactions between snow/ice and cloud feedback processes

Four cloud-radiation feedback mechanisms have been characterized: the cloud fraction feedback, the cloud liquid water content feedback, the cloud dropsize feedback, and the cloud temperature feedback. The impact of clouds on the surface radiation flux and thus the state of the surface means that the cloud-radiation feedback processes in the Arctic are inextricably linked with albedo feedback processes.

Because of the different thermodynamic and radiative environment in the polar regions, conclusions drawn for the globe regarding these cloud feedback processes may be inappropriate over the Arctic. A perturbation to the polar radiation balance may arise from increased greenhouse gas concentrations and/or increasing amounts of aerosol. A perturbation in the surface radiation balance of the snow/ice results in a change in snow/ice characteristics (i.e. snow/ice thickness and areal distribution, surface temperature and surface albedo). These changes in surface characteristics, particularly the surface temperature and, over ocean, fraction of open water, will modify fluxes of radiation and surface sensible and latent heat, which will modify the atmospheric temperature, humidity and dynamics. Modifications to the atmospheric thermodynamic and dynamic structure will modify cloud properties (e.g. cloud fraction, cloud optical depth), which will in turn modify the radiative fluxes. An understanding and correct simulation of the cloud-radiation feedback mechanism requires understanding of changes in: cloud fractional coverage and vertical distribution as the vertical temperature and humidity profiles change; and changes in cloud water content, phase and particle size as atmospheric temperature and composition changes. The largest uncertainty in assessing the cloudñclimate feedback mechanism is the change in cloud cover in response to a change in atmospheric temperature, and thus the sign of the cloudñclimate feedback over the Arctic is unknown.

Assessment: Potential contribution of this feedback to uncertainty is high.
Confidence in assessment: high
Readiness of the community to address this uncertainty: excellent


The Five Themes from the ARCSS Science Plan

1. How will the Arctic climate change over the next 10-100 years?

A primary goal of ARCSS research is the integration of contemporary and paleoenvironmental observational, process and modeling studies to assess future near term change in the Arctic. The importance of paleoenvironmental studies is highlighted when studies of Arctic change are placed in the context of multi-decadal modes of variability in the Arctic system.
Paramount for the assessment of change in the near term future are:
  • An integrated understanding of land, ocean, shelf and atmospheric feedbacks.
  • An understanding of the ways in which change is manifested as secular trends, and as projections onto preferred existing modes of variability or new modes of variability.
  • A clear goal as to the applications for which change is being projected, through recognition that models are developed not 'of a system' but 'for an application.'
2. How will human activities interact with future global change to affect the sustainability of natural ecosystems and human societies?

The primary objective for projections of change over the near term future is to arrive at an assessment of the impacts of these changes on natural ecosystems and human societies, and the responses and adaptations of those systems to change. Developing models to project pathways of change, be they numerical formulations or theoretical constructs, must be pursued with particular applications in mind, and often in close collaboration with affected communities.

Since most of the arctic regions people live on the coast, land-shelf-ocean interactions are critical to this theme, including sea level, erosion, and transport of constituents, including contaminants.

3. How will changes in arctic biogeochemical and hydrologic cycles and feedbacks affect arctic and global systems?


The magnitude and even the sign of some of the feedback processes are associated with significant uncertainties. A major source of uncertainty is associated with the cloud-radiation feedbacks, and how polar cloud characteristics will be altered in a changing climate. Because of the impact of clouds on the surface radiation flux and thus the state of the ocean and land surface, the cloud-radiation feedback processes in the polar regions are inextricably linked with sea ice and snow feedback processes. Our best estimate at present is that most, if not all, of the individual feedbacks in the polar regions are positive, with the possible exceptions of the aerosol/dehydration feedback and, on longer timescales, the vegetation carbon uptake feedback. It remains a major task to explain the relative stability of the polar climate in the presence of these positive feedbacks. Possibilities include unforeseen negative feedbacks associated with clouds, the biosphere, or between the sea ice and ocean. Specific strategies for resolving these issues need to consider not just processes, but linkages between them and the relationships between these processes and interannual variability.

4. Are predicted changes in the arctic system detectable?

The climate system exhibits natural modes of spatial and temporal variability that are important in assessing our ability to understand and model the climate system. Important modes of variability are forced by the daily and annual variations of insolation. Changes in the magnitude and structure of these modes may be among the most important features of anthropogenic climate change.

Furthermore, the climate system exhibits modes of variability that appear to have no external forcing, but are rather natural internal modes of variability of the climate system. These modes are thus pure expressions of feedback mechanisms internal to the climate system. Modes that affect the Arctic climate system include the North Atlantic Oscillation (NAO), the annular mode (AO) and the Pacific Decadal Oscillation (PDO). Some of these modes of variability have shown temporal trends in the past 30-50 years that may be associated with anthropogenic climate change. Understanding natural modes of variability is a promising means of assessing how climate change may express itself in regional shifts of temperature and precipitation.

In the context of these natural and forced modes of variability, the problem of detection leads to requirements that include the development of long term, detailed in situ observations, integration of the paleoenvironmental record, development of long term records utilizing satellite-derived products, and detailed regional reanalysis efforts.