Abstract
Future climate changes, as well as differences in climates from one location to another, may involve changes in climatic variability as well as changes in means. In this study, a synthetic weather generator is used to systematically change the within-year variability of temperature and precipitation (and therefore also the interannual variability), without altering long-term mean values. For precipitation, both the magnitude and the qualitative nature of the variability are manipulated. The synthetic daily weather series serve as input to four crop simulation models. Crop growth is simulated for two locations and three soil types. Results indicate that average predicted yield decreases with increasing temperature variability where growing-season temperatures are below the optimum specified in the crop model for photosynethsis or biomass accumulation. However, increasing within-year variability of temperature has little impact on year-to-year variability of yield. The influence of changed precipitation variability on yield was mediated by the nature of the soil. The response on a droughtier soil was greatest when precipitation amounts were altered while keeping occurrence patterns unchanged. When increasing variability of precipitation was achieved through fewer but larger rain events, average yield on a soil with a large plant-available water capacity was more affected. This second difference is attributed to the manner in which plant water uptake is simulated. Failure to account for within-season changes in temperature and precipitation variability may cause serious errors in predicting crop-yield responses to future climate change when air temperatures deviate from crop optima and when soil water is likely to be depleted at depth.
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References
Austin, M. E.: 1972, ‘Land Resource Regions and Major Land Resource Areas of the United States’, Agricultural Handbook 296, USDA/SCS, 82 pp.
Berry, J. A. and Bjorkman, O.: 1980, ‘Photosynthetic Response and Adaptation to Temperature in Higher Plants’, Annu. Rev. Plant Phys. 31, 491–543.
Bonan, G.: 1993, ‘Do Biophysics and Physiology Matter in Ecosystem Models?’ Climatic Change 24, 281–285.
Buttler, I. W. and Riha, S. J.: 1992, ‘Water Fluxes in Oxisols: A Comparison of Approaches’, Water Resources Res. 28, 221–229.
Cohen, S. J.: 1990, ‘Bringing the Global Warming Issue Closer to Home: The Challenge of Regional Impact Studies’, Bull. Amer. Meteorol. Soc. 71, 520–526.
Gordon, H. B., Whetton, P. H., Pittock, A. B., Fowler, A. M., and Haylock, M. R.: 1992, ‘Simulated Changes in Daily Rainfall Intensity Due to the Enhanced Greenhouse Effect: Implications for Extreme Rainfall Events’, Climate Dynamics 7, 83–102.
Hanks, R. J.: 1983, ‘Yield and Water-Use Relationships: An Overview’, in Taylor, H. M., Jordan, W. R., and Sinclair, T. R. (eds.), Limitations to Efficient Water Use in Crop Production, Am. Soc. of Agron., Madison, WI, pp. 393–411.
Jones, C. A. and Kiniry, J. R. (eds.): 1986, CERES - Maize: A Simulation Model of Maize Growth and Development, Texas A&M Univ. Press, College Station, 194 pp.
Katz, R. W.: 1996, ‘Use of Stochastic Models to Generate Climate Change Scenarios’, Climatic Change 32, 237–255 (this issue).
Katz, R. W. and Brown, B. G.: 1992, ‘Extreme Events in a Changing Climate: Variability is More Important than Averages’, Climatic Change 21, 289–302.
Mearns, L. O., Schneider, S. H., Thompson, S. L., and McDaniel, L. R.: 1990, ‘Analysis of Climatic Variability of General Circulation Models: Comparison with Observations and Changes in Variability of 2X-CO2 Experiments’, J. Geophys. Res. D95, 20469–20490.
Mearns, L. O., Rosenzweig, C., and Goldberg, R.: 1992, ‘Effects of Change in Interannual Climatic Variability on CERES - Wheat Yields: Sensitivity and 2XCO2 General Circulation Model Scenarios’, Ag. For. Meteorol. 62, 159–189.
Mearns, L. O., Rosenzweig, C., and Goldberg, R.: 1996, ‘The Effect of Changes in Daily and Interannual Variability on CERES - Wheat: A Sensitivity Study’, Climatic Change 32, 257–292 (this issue).
Moen, T. N., Kaiser, H. M., and Riha, S. J.: 1994, ‘Regional Yield Estimation Using a Crop Simulation Model: Concepts, Methods and Validation’, Agricul. Systems 46, 79–92.
Neild, R. E., Richman, H. N., and Seeley, M. W.: 1979, ‘Impacts of Different Types of Temperature Change on the Growing-Season for Maize’, Agr. Meteorol. 20, 367–374.
Nonhebel, S.: 1993, ‘Effects of Change in Temperature and CO2 Concentration on Simulated Spring Wheat Yields in The Netherlands’, Climatic Change 24, 311–329.
Nonhebel, S.: 1994, ‘The Effects of Use of Average Instead of Daily Weather Data in Crop Growth Simulation Models’, Agricul. Systems 44, 377–396.
Priestley, C. H. B. and Taylor, R. J.: 1972, ‘On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters’, Monthly Weather Rev. 100, 81–92.
Reed, D. N.: 1986, ‘Simulation of Time Series of Temperature and Precipitation over Eastern England by an Atmospheric General Circulation Model’, J. Climatol. 6, 233–253.
Richardson, C. W.: 1981, ‘Stochastic Simulation of Daily Precipitation, Temperature, and Solar Radiation’, Water Resources Res. 17, 182–190.
Rind, D., Goldberg, R., and Ruedy, R.: 1989, ‘Change in Climate Variability of the 21st Century’, Climatic Change 14, 5–37.
Semenov, M. A. and Porter, J. R.: 1995, ‘Climatic Variability and the Modelling of Crop Yields’, Agricult. Forest Meteorol. 73, 265–283.
Sharpley, A. N. and Williams, J. R. (eds.): 1990a, EPIC - Erosion/Productivity Impact Calculator: 1. Model Documentation, U.S. Dept. of Agric., AgricResearch Serv. Tech. Bull. No. 1768.
Sharpley, A. N. and Williams, J. R. (eds.): 1990b, EPIC - Erosion/Productivity Impact Calculator: 2. User Manual, U.S. Dept. of Agric., Agric. Research Serv. Tech. Bull. No. 1768.
Simane, B., van Keulen, H., and Stol, W.: 1994, ‘Application of a Crop Growth Model (SUCROS-87) to Assess the Effect of Moisture Stress on Yield Potential of Durum Wheat in Ethiopia’, Agricul. Systems 44, 337–352.
Stockle, C. O. and Campbell, G. S.: 1985, ‘A Simulation Model for Predicting Effect of Water Stress on Yield: An Example Using Corn’, Advan. Irrigation 3, 283–323.
Stockle, C. O. and Campbell, G. S.: 1989, ‘Simulation of Crop Response to Water and Nitrogen: An Example Using Spring Wheat’, Trans. ASAE 32, 66–74.
Waggoner, P. E.: 1989, ‘Anticipating the Frequency Distributions of Precipitation if Climate Change Alters Its Mean’, Agricul. Forest Meteorol. 47, 321–337.
Wilks, D. S.: 1992, ‘Adapting Stochastic Weather Generation Algorithms for Climate Change Studies’, Climatic Change 22, 67–84.
Williams, J. R.: 1995, ‘The EPIC Model’, in V. P. Singh (ed.), Computer Models of Watershed Hydrology, 909–1000.
Wilson, C. A. and Mitchell, J. F. B.: 1987, ‘Simulated Climate and CO2-Induced Climate Change over Western Europe’, Climatic Change 10, 11–42.
deWit, C. T.: 1958, Transpiration and Crop Yields, Agric. Research Paper 64.6 Pudoc, Wageningen, 88 pp.
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Riha, S.J., Wilks, D.S. & Simoens, P. Impact of temperature and precipitation variability on crop model predictions. Climatic Change 32, 293–311 (1996). https://doi.org/10.1007/BF00142466
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DOI: https://doi.org/10.1007/BF00142466