SEDAC
Home
Featured link and image: NASA Watches Arctic Ice, click to see full story

Home Page (MVA) > Integrated Assessment Models (IAMs) and Resources > IAMs Thematic Guide

 

Thematic Guide Icon

Thematic Guide to Integrated Assessment Modeling

[HOME] [PREVIOUS] [NEXT] [BOTTOM]

 

Atmosphere and Oceans

The rich and well-developed literature of physical and chemical modeling of the atmosphere and oceans encompasses large models and vast computer resources. For purposes of conducting integrated assessment, the crucial questions concerning representation of these systems focus on the degree of detail, size, and complexity that is appropriate, and the manner of treatment of those aspects where conflicting models exist (e.g., for clouds).

Any attempt at a detailed representation of the atmosphere-ocean system in an integrated assessment modeling project makes this component by far the most computationally demanding piece. No integrated assessment project now under way uses a full Global Circulation Model (GCM) for the atmosphere. The most detailed representation is the two-dimensional climate model with coupled ocean in the Massachusetts Institute of Technology project. Design decisions in this component limit the possible uses of an integrated assessment model, determining both what machines it can run on and how many repeated runs are possible for uncertainty analysis.

The simplest possible approach, used by several of the projects summarized in this guide, models only a globally averaged atmosphere. A future path of global-average temperature change is projected from a relatively simple specification of gases' atmospheric lifetimes and contribution to changes in radiative forcing, global energy balance, and the lag between changes in equilibrium temperature and realized temperature. In this approach, either the change in radiative forcing or the change in realized average global temperature is used to drive an extremely simple, illustrative damage function or response surface.

Approaches of intermediate complexity are also possible, using techniques of statistical downscaling to fit higher-dimensionality or finer-scale data to an average provided by a simpler model. One can, for example, proceed from a global-average temperature to grid-cell climate changes by fitting a prior result from a particular GCM run (or a blend of two or more runs) to the calculated global-average temperature. This of course requires choosing a particular GCM result or results from among those available and assumes consistency between the projected global temperature change and the prior GCM result. Similar downscaling techniques are needed to estimate longitudinal climate from a two-dimensional climate model, and are even required when running a full GCM to downscale climatic variables to the finer resolution required for ecosystem or agriculture models. In the latter case, GCM grid-cell averages are fitted to observed historical weather patterns at fine scale within the grid cell.

 

The next section is Ecological Impacts.

 

[SEDAC] [PREVIOUS] [NEXT] [TOP]

 

Sources

Parson, E.A. and K. Fisher-Vanden, Searching for Integrated Assessment: A Preliminary Investigation of Methods, Models, and Projects in the Integrated Assessment of Global Climatic Change. Consortium for International Earth Science Information Network (CIESIN). University Center, Mich. 1995.

 

Suggested Citation

Center for International Earth Science Information Network (CIESIN). 1995. Thematic Guide to Integrated Assessment Modeling of Climate Change [online]. Palisades, NY: CIESIN. Available at http://sedac.ciesin.columbia.edu/mva/iamcc.tg/TGHP.html [accessed DATE].

 

 

Our sponsors:

TM0=o`$JB [Fj P!+t;r& L> e"e7޳lv*1VLa T$D&F&-.nKO)Jq* j|^!|12b(l4^Бaa}KMlXȔP\3)HK x׸"k`TC '\/<3tf,CnLI}Ȏce!HSZBFX&󝝙T)qgg֊+{ah.hr ^ h8gO`w_NW;VX1s6t2 e) Fa릭**@B"V*kh $