9634290 Edmonds Battelle, Pacific Northwest Laboratories (BNW), Texas A&M University and the University Corporation for Atmospheric Research will develop techniques for modeling the interactive impacts of climate on agriculture, water resources and the economy and techniques for estimating the economic value to the agricultural sector of early identification of climate change. These techniques will be developed in two sequential tasks: Task 1: Develop techniques for modeling the interactive impacts of climate on agriculture, water resources and the economy; and Task 2: Develop techniques for estimating the economic consequences to the agricultural sector of varying modes of reaction to climatic change. The techniques to be developed address two of the major weaknesses in current integrated assessment frameworks, i.e., the treatment of individual economic sectors as though insulated and isolated from the economy as a whole and the treatment of impacts as 'snapshots' fixed in time rather than as transient or 'moving-pictures' of events occurring over decadal and century-length time spans in which not only climate changes but demographic, technological, political, social and economic conditions change, as well. Under Task 1, the HUMUS model that simulates the hydrologic cycle and the EPIC model of that simulates crop productivity and water requirement will be employed in BNW's Global Change Assessment Model (GCAM) for integrated assessment of the effects of climate change. In the research project these models will be linked interactively with one another and with a computable general equilibrium model. Regional distributions of climate change in the 48 contiguous United States will be drawn from a set of General Circulation Model equilibrium and transient experiments by means of the MAGICC/SCENGEN model. These models will be modified to include the regional implications of sulfur aerosols on climate, and the SCENGEN GCM library will be updated. Under Task 2, methods will be developed to assess the economic consequences and the value of early detection of climate change. These methods will utilize the tools developed in Task 1.
