Overview & Relevance:
Several phenomena of critical importance to the ultimate impacts of anthropogenic greenhouse gas emissions, the costs of emission reductions measures, or the effectiveness of such measures depend on feedbacks between small scales and larger scales. Much of the data collected and/or analysis performed with respect to various components of the global warming issue have been at relatively small scales, often at the scale of an individual measurement site. However, even the highest resolution global simulation models - whether of the atmosphere, oceans, biosphere, or the economic system - have a grid spacing (or spatial resolution) which can be several orders of magnitude larger than the scale at which observations are made and at which many observationally or theoretically derived relationships apply. Small scale observations and relationships must therefore be extrapolated to the model resolution scale. In many cases, the relationships amongst variables at larger scales can be, or have the potential to be, quite different from those found at smaller scales. Example of such up-scaling problems include:
• the scaling of parameters used in the computation of surface-air fluxes of heat, moisture, and momentum in coupled atmosphere-surface climate models, in which values appropriate at the scale of most field measurements are inappropriate at the typical grid scale of such models;
• the scaling of hydrologic parameters (rainfall intensity, antecedent soil moisture, soil properties) from the site scale to the climate model grid scale in computing grid-mean runoff and soil moisture amounts;
• the scaling of the direct physiological effects of higher CO2 on photosynthesis and water loss from the leaf to the plant to the forest canopy or ecosystem;
• scaling the relationship between ambient atmospheric conditions and a single cumulus cloud to that between ambient atmospheric conditions and the ensemble of clouds which occupy a global model grid cell;
• the scaling of the properties of sea ice from that of an individual block of ice to that of an ocean model grid, in which the physical properties of an aggregation of ice floes are different from those of the constituent components;
• the scaling of energy use savings due to energy efficiency measures at the scale of the individual energy user to national and possibly global energy use;
• the scaling of the driving factors for greenhouse gas emissions from the local to the regional and global scales.
This session of the Aspen Global Change Institute (AGCI) examined the problem of upscaling in global change research. The term "global environmental change" was meant to mean changes that are global by virtue of the fact that they involve systemic changes in the properties of the atmosphere or ocean, or changes that, although local or regional in scale, are so widespread in their occurrence that they can be regarded as global-scale problems. The term "upscaling" was taken to mean the process of extrapolating from the site-specific scale at which observations are usually made or at which theoretical relationships apply, to the grid cell size found in global models used to study global environmental change. Upscaling is concerned with the development of relationships that are applicable at the grid-cell scale of models, so that they can be implemented in such models as part of the process of developing projections for the future. It is distinct from the problem of downscaling, which also arises in global change research. The latter is concerned with taking the output of global change models and deducing the changes that would occur at finer scales than resolved by the model. The two problems are not entirely independent, however, in that common processes underlie both scaling problems. Upscaling is a process-oriented problem, but there are other issues involving scale that do not constitute upscaling (or downscaling). For example, predictability generally depends on scale, but the determination and description of how predictability varies with scale is not a scaling problem.
A number of important questions of relevance to upscaling were identified at the beginning of the meeting, and answers or partial answers to some of the questions emerged and are presented in this overview. The key questions raised were:
1. When is upscaling possible?
2. For cases where upscaling is possible, how should it be done?
3. For cases in which a given phenomenon has been (largely) independently examined at two or more scales by workers within the same discipline, how can results be properly intercompared?
4. What are the implications of scaling issues for such things as predictability, parameterization, and the response and vulnerability of ecosystems and human societies to global and local environmental change?
5. What are the relationships between upscaling and downscaling problems?
6. How does the relationship between changes in variability and changes in the mean change as the scale changes?
7. How does variability change with scale?
8. How does predictability change with scale?
9. How do errors propagate with scale?
10. What is the fundamental reason for a scaling problem in the first place? Examples of fundamental reasons include the existence of important feedbacks between large and small scales, the existence of spatial heterogeneity, underlying nonlinearities in the system of interest, or the development of "emergent properties" at larger scales.
11. How significant is the upscaling problem, and does or could its significance depend on other circumstances - circumstances which might themselves change?
12. How is the upscaling problem treated in global simulation models?
13. How have solutions to the scaling problem been validated, and to what extent is validation possible?
14. Is the upscaling problem a significant source of uncertainty in global change projections, compared to other sources of uncertainty?
15. What is the relationship between the particular problem of upscaling and the more general problem of parameterization of subgrid scale phenomena in the associated models?
16. How can a better understanding of the nature of the upscaling problem lead to the development of better parameterizations in global scale models? These questions will be addressed both in the context of specific disciplines relevant to global change, and as cross-cutting issues spanning the disciplines represented at the meeting.
To achieve insights in the problem of upscaling that can (1) lead to improved parameterizations in global scale models as used in a wide variety of disciplines; and (2) lead to a better appreciation of the strengths and weaknesses of global models.
Workshop Topic (s):
- Climate Variability and Change (including Climate Modeling)
- Land-Use/Land-Cover Change