1999 Progress Report: Sensitivity Analysis of the Effect of Changes in Mean and Variability of Climate on Crop Production and Regional Economics in the Southeastern U.S.EPA Grant Number: R824997
Title: Sensitivity Analysis of the Effect of Changes in Mean and Variability of Climate on Crop Production and Regional Economics in the Southeastern U.S.
Investigators: Mearns, Linda , Adams, Richard , Carbone, Greg , Easterling, William Ewart , Katz, R. , McCarl, B.
Institution: National Center for Atmospheric Research , Oregon State University , Pennsylvania State University , Texas A & M University , University of South Carolina at Columbia
EPA Project Officer: Chung, Serena
Project Period: November 1, 1996 through October 31, 1999 (Extended to September 30, 2001)
Project Period Covered by this Report: November 1, 1998 through October 31, 1999
Project Amount: $1,200,901
RFA: Global Climate (1996) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Global Climate Change , Climate Change
We are investigating the effects of the spatial scale of: (1) climate change scenarios, and (2) changes in interannual (and daily) climatic variability compared to the effects of changes in mean climate, on crop production in the southeastern United States. We will determine differences in crop responses to several types of possible future climate: two from a control and doubled CO2 experiment of a high resolution (50 km) regional climate model, and two from the coarse resolution GCM that provided boundary conditions for the regional model. Two types of scenarios are being developed from these runs: one including only mean changes in the relevant climate variables, and another including both mean and variability changes. We are applying the scenarios to crop models (i.e., CERES, CROPGRO, COTTAM, and EPIC), which are being run for conditions of: (1) climate change only; (2) climate change and direct CO2 effects; and (3) climate change, direct CO2 effects, and management adaptations.
Resulting changes in mean and variability of simulated yield from the different scenarios will provide input to an agricultural sector economic model (ASM) for evaluation of economic sensitivity to the different sets of yield changes. The overarching goal is to establish the sensitivity of the regional economics to changes in crop yields resulting from a range of changes in mean and variability of climate at different spatial resolutions.
We also are analyzing the effect of large scale circulation features and indices on daily climatological characteristics of the region, features such as the El Ni?o Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Bermuda High Index.
We formed two different spatial scales of climate change scenarios from the regional climate model and coarse GCM. We then applied the baseline climatology and these scenarios to crop models for six different crops (CERES family of models and COTTAM): corn, cotton, sorghum, soybean, rice, and wheat. In addition, four EPIC crop models were used: corn, soybean, wheat, and clover. We also formed two different scale scenarios for the rest of the United States, using a less dense network of baseline climatology stations, using output from earlier climate model runs. We found that the two different scales of scenarios resulted in different responses of the crop models for most crops. On the whole, for the climate change only cases, yields decreased in both scenarios (except for cotton yields which increased), but the decreases were greater in the case of the high resolution scenario. In the case of climate change with direct CO2 effects, there are smaller decreases or even some increases in crop yields, but the effect of the spatial scale of the scenarios remains important.
We calculated changes in simulated yield for the two scenarios (climate change plus direct CO2 effects, CERES models) and used them as input to the agricultural sector economic model (ASM).
On a country-wide basis, both scales of climate change scenarios result in increased total surplus for the agricultural sector, but the coarse resolution scenario produces twice the surplus ($4.6 billion) compared to the fine-scale scenario ($2.3 billion). Such contrasts also were seen on the regional scale. For example, the southeast suffered decreased agricultural activity, but the decrease was much larger in the case of the high resolution scenario.
Our analysis so far indicates that the spatial scale of climate change scenarios substantially affects the simulation of changes in simulated crop yields on various levels of spatial aggregation. Moreover, we have demonstrated that these contrasts in changes in yield are substantial enough to affect the results of an agricultural economic model both on national and regional levels.
Future activities will be to:
- Complete the establishment of adaptations to the climate changes (e.g., changes in sowing dates, cultivars), rerun crop models with climate changes, direct CO2 effects plus adaptations, and then the ASM with the resultant new set of yield changes.
- Quantitatively examine, through detailed statistical techniques, the significance of mean changes in yield and contrasts in the spatial variability of simulated yields. We also will determine which aspects of the different climate change scenarios are most responsible for the contrasts in changes in yield.
- Complete the comparison between the results for climate change of the EPIC and CERES crop models.
- Complete the formation of variance change scenarios, apply to the crop models, and then apply resultant changes in yields to the ASM.
Journal Articles:No journal articles submitted with this report: View all 38 publications for this project
Supplemental Keywords:ecosystem, regionalization, integrated assessment, scaling, agriculture, southeast., RFA, Scientific Discipline, Air, Geographic Area, climate change, Economics, Southeast, Atmospheric Sciences, Ecological Risk Assessment, Agronomy, environmental monitoring, sensitivity analysis, economic models, green house gas concentrations, regional ecosystems, socioeconomic indicators, carbon dioxide, circulation model, climate models, CO2 concentrations, GENESIS climate model, environmental stressors, agriculture, ecosystem sustainability, climate variability, crop production
http://www.esig.ucar.edu/asr00 (click on Enhancing Productivity and Resilience of Natural Resources, then on Climate Variability and Agriculture in the Southeast). This site provides the project overview.
http://www.esig.ucar.edu/pi (this site about the Southeast Project is under construction)