The study team examined detailed impacts of a changed climate on agriculture, forests, water resources, energy, and the aggregate economy of the MINK region. To simulate future climate under global climate change, they used an "analog climate," drawn from actual weather records of the 1930s. Daily records of temperature and precipitation for the 1930s were available at 17 weather stations in the region, while measures of solar radiation, wind, and other climatic variables were available at lower resolution and interpolated. Relative to the climate of 1951-1980, which was used as a "control climate," the analog climate was on average 1 degree C warmer, with annual average precipitation lower by 3 percent to 15 percent in the four states. Single years in single states in the analog period were as much as 3 to 4 degrees C warmer than in the control climate. When particular components of the study required long-run equilibria, years from the analog climate were run repeatedly until equilibrium was reached (Easterling et al. 1993).
For each sector, the study examined impacts through the use of existing highly detailed sectoral models. Each sector's study proceeded in two major stages: First, the sector today was characterized in detail, and the analog climate imposed on it; second, the sector's characteristics were projected for the year 2030, and the analog climate imposed on this changed sector. Sector-specific impacts and adaptations were estimated, and effects were aggregated across the economy using an input-output model.
The agriculture study was conducted at the level of individual farms, using a set of 50 representative farms across the region, each specified in great detail by soil type, local weather, and kind of production. The effect of the analog climate was simulated using EPIC, a crop model that estimates yield, evapotranspiration, and water-use efficiency of particular crops as functions of soil, daily climate, and farm management. Effects of increased CO2 concentration on both yield and water use were also simulated, as were a set of adjustments in farm management judgmentally selected to mitigate yield loss. This approach was used both for each representative farm today and for the same farm in 2030 under projected market changes and improvements in five technological parameters. Results for these 50 farms were aggregated to give regional total agricultural impacts. For regional agriculture in 2030, the simulations showed that while changed climate alone reduced the value of crop production by 22 percent, increased CO2 reduced this loss to 8 percent while changing farm management changed the effect to a 3-percent gain.
Parallel studies estimated regional economic effects from the analog climate on forests, water, and energy. The water study was perhaps the most problematic, because the regional economic significance of climate-induced flow reductions was highly dependent on major policy choices regarding flow management in the Missouri, and because agricultural output losses depended strongly on the availability of irrigation water, which in turn depended on these management decisions. Results for all sectors studied were combined in a regional input-output model to estimate aggregate losses due to climate change (Frederick 1993).
The study authors identify four important methodological innovations in their work. First, they imposed a changed climate on a region that reflected their projections of demographics, economics, and technology in the year 2030 rather than on the region of today. Second, they included the impacts of small-scale climate variability and extreme events by using past weather data rather than Global Circulation Model (GCM) runs, though some critics have argued that the 1930s' climate was too close to today's to give a useful measure of likely impacts of projected climate change. Third, they considered inter-regional linkages in effects, though acknowledging that their treatment of these is necessarily limited. And fourth, they assumed that people do not simply suffer climatic impacts passively but do what they can to adapt and to mitigate their losses. The adaptations proposed are selected judgmentally for their effectiveness in reducing yield losses and are not claimed to reflect any optimizing behavior. The analysis is comparative-static, and so includes no adjustment costs or other dynamic effects.
The next section is The McKenzie Basin Impacts Study.
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