Abstract
We analyze the control runs and 2 × CO2 projections (5-year lengths) of the CSIRO Mk 2 GCM and the RegCM2 regional climate model, which was nested in the CSIRO GCM, over the Southeastern U.S.; and we present the development of climate scenarios for use in an integrated assessment of agriculture. The RegCM exhibits smaller biases in both maximum and minimum temperature compared to the CSIRO. Domain average precipitation biases are generally negative and relatively small in winter, spring, and fall, but both models produce large positive biases in summer, that of the RegCM being the larger. Spatial pattern correlations of the model control runs and observations show that the RegCM reproduces better than the CSIRO the spatial patterns of precipitation, minimum and maximum temperature in all seasons. Under climate change conditions, the most salient feature from the point of view of scenarios for agriculture is the large decreases in summer precipitation, about 20% in the CSIRO and 30% in the RegCM. Increases in spring precipitation are found in both models, about 35% in the CSIRO and 25% in the RegCM. Precipitation decreases of about 20% dominate in winter in the CSIRO, while a more complex pattern of increases and decreases is exhibited by the regional model. Temperature increases by 3 to 5 °C in the CSIRO, the higher values dominating in winter and spring. In the RegCM, temperature increases are much more spatially and temporally variable, ranging from 1 to 7 °C across all months and grids. In summer large increases (up to 7 °C) in maximum temperature are found in the northeastern part of the domain where maximum drying occurs.
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References
Briegleb, B. P.: 1992, Delta-Eddington Approximation for Solar Radiation in the NCAR Community Climate Model’, J. Geoph. Res. 97, 7603–7612.
Carter, T. R., Parry, M. L., Harasawa, H., and Nishioka, S.: 1994, IPCC Technical Guidelines for Assessing Climate Change Impacts and Adaptations,WMO/UNEP, 59 pp.
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.
Dickinson, R. E., Henderson-Sellers, A., and Kennedy, P. J.: 1993, Biosphere-Atmosphere Transfer Scheme (BATS) Version lE as Coupled to the NCAR Community Climate Model, NCAR Technical Note, (NCAR/TN-387+STR) NCAR, Boulder, CO, 72 pp.
Gates, W. L.: 1985, ‘The Use of General Circulation Models in the Analysis of the Ecosystem Impacts of Climatic Change’, Clim. Change 7, 267–284.
Giorgi, F.: 1991, ‘Sensitivity of Summertime Precipitation over the Western United States to Model Physics Parameterizations’, Mon. Wea. Rev. 119, 2870–2888.
Giorgi, F., Hewitson, B., Christensen, J., Hulme, M., von Storch, H., Whetton, P., Jones, R., Meares, L., and Fu, C.: 2001, ‘Regional Climate Information: Evaluation and Projections’, Chapter 10, in Houghton, J. T., Ding, Y., Griggs, D. J. Noguer, M., van der Linden, P. J., Dai, X., Maskell, K., and Johnson C. A. (eds.), Climate Change 2001: The Scientific Basis, Contribution of Working Group I to the Third Assessment Report of the IPCC,Cambridge University Press, Cambridge, pp. 583–638, 739–768.
Giorgi, F., Huang, Y., Nishizawa K., and Fu, C.: 1999, ‘A Seasonal Cycle Simulation over Eastern Asia and its Sensitivity to Radiative Transfer and Surface Processes’, J. Geophys. Res. 104, 64036423.
Giorgi, F. and Marinucci, M. R.: 1996: ‘A Study of the Sensitivity of Simulated Precipitation to Model Resolution and its Implications for Climate Studies’, Mon. Weather Rev. 124, 148–166.
Giorgi, F., Marinucci, M. R., and Bates, G. T.: 1993a, ‘Development of a Second Generation Regional Climate Model (RegCM2): Boundary Layer and Radiative Transfer Processes’, Mon. Wea. Rev. 121, 2794–2813.
Giorgi, F., Marinucci, M. R., de Canio, G., and Bates, G. T.: 1993b, ‘Development of a Second Generation Regional Climate Model (RegCM2): Convective Processes and Assimilation of Lateral Boundary Conditions’, Mon. Wea. Rev. 121, 2814–2832.
Giorgi, F. and Mearns, L. 0.: 1999, ‘Introduction to Special Section: Regional Climate Modeling Revisited’, J. Geophys. Res. 104, 6335–6352.
Giorgi, F., Mearns, L., Shields, C., and McDaniel, L.: 1998, ‘Regional Nested Simulations of Present Day and 2 x 2 Climate over the Central Great Plains of the United States’, Clim. Change 40, 457–493.
Giorgi, F. and Shields, C.: 1999, ‘Tests of Precipitation Parameterizations Available in the Latest Version of the NCAR Regional Climate Model (RegCM) over the Continental United States’, J. Geophys. Res. 104, 6353–6375.
Giorgi, F., Shields Brodeur, C., and Bates, G. T.: 1994, ‘Regional Climate Change Scenarios over the United States Produced with a Nested Regional Climate Model’, J. Climate 7, 375–399.
Grell, G. A., Dudhia J., and Stauffer, D. R.: 1994, A Description of the Fifth Generation Penn State/CAR Mesoscale Model (MM5), NCAR Technical Note, NCAR/TN-398+STR, 121 pp. Henderson, K. G. and Vega, A. J.: 1996, ‘Regional Precipitation Variability in the Southern United States’, Phys. Geog. 17, 93–112.
Holtslag, A. A. M., de Bruijn, E. I. F., and Pan, H. L.: 1990, ‘A High Resolution Air Transformation Model for Short-Range Weather Forecasting’, Mon. Weather Rev. 118, 1561–1575.
Jones, R. G., Murphy, J. M., and Noguer, M.: 1995, ‘Simulation of Climate Change over Europe Using a Nested Regional Climate Model. I: Assessment of Control Climate, Including Sensitivity to Location of Lateral Boundary Conditions’, Quart. J. Roy. Meteorol. Soc. 121, 1413–1449.
Katz, R. W.: 1982, ‘Statistical Evaluation of Climate Experiments with General Circulation Models: A Parametric Time Series Approach’, J. Atmos. Sci. 39, 1446–1445.
Katz, R. W.: 1983, ‘Statistical Procedures for Making Inferences about Precipitation Changes Simulated by an Atmospheric General Circulation Model’, J. Atmos. Sci. 40, 2193–2201.
Kowalczyk, E. A., Garratt, J. R., and Krummel, P. B.: Implementation of a Soil-Canopy Scheme into the CSIRO GCM — Regional Aspects of the Model Response,CSIRO Division of Atmospheric Research Technical Paper No. 32, CSIRO, Australia, 59 pp.
Legates, D. R. and Willmott, C. J.: 1990a, ‘Mean Seasonal and Spatial Variability in Gauge-Corrected Global Precipitation’, Int. J. Clim. 10, 111–127.
Legates, D. R. and Willmott, C. J.: 1990b, ‘Mean Seasonal and Spatial Variability in Global Surface Air Temperature’, Theor. Appl. Climatol. 41, 11–21.
Loveland, T. R., Merchant, J. W., Ohlen, D. O., and Brown, J. F.: 1991, ‘Development of a Land Cover Characteristics Database for the Conterminous United States’, Photogrammetric Engineer. Remote Sens. 57, 1453–1463.
Mearns, L. 0.: 2003, ‘Issues in the Impacts of Climate Variability and Change on Agriculture. Applications to the southeastern United States’, Guest Editorial, Special Issue Clim. Change 60, 1–6.
Mearns, L. O., Giorgi, F., McDaniel, L., and Shields, C.: 1995a, ‘Analysis of the Diurnal Range and Variability of Daily Temperature in a Nested Modeling Experiment: Comparison with Observations and 2C0 Results’, Clim. Dyn. 11, 193–209.
Mearns, L. O., Giorgi, F., McDaniel, L., and Shields, C.: 1995b, ‘Analysis of the Variability of Daily Precipitation in a Nested Modeling Experiment: Comparison with Observations and 2C0 Results’, Global Plan. Change 10, 55–78.
Mearns, L. O., Hulme, M., Carter, T. R., Leemans, R., Lal, M., and Whetton, P.: 2001, ‘Climate Scenario Development’, Chapter 13, in Houghton, J. T., Ding, Y., Griggs, D. J., Noguer, M., van der Linden, P. J., Dai, X., Maskell, K., and Johnson, C. A. (eds.), Climate Change 2001: The Scientific Basis, Contribution of Working Group I to the Third Assessment Report of the IPCC, Cambridge University Press, Cambridge, pp. 739–768.
National Renewable Energy Laboratory (NREL): 1992, National Solar Radiation Data Base (19611990), Users Manual, Version 1.0, Ashville, N.C., NOAA, NCDC, 93 pp.
New, M., Hulme, M., and Jones, P. D.: 1999, ‘Representing Twentieth Century Space-Time Climate Variability. Part 1: Development of 1961–90 Mean Monthly Terrestrial Climatology’, J. Climate 12, 829–856.
New, M., Hulme, M., and Jones, P. D.: 2000, ‘Representing Twentieth Century Space-Time Climate Variability. Part 2: Development of 1901–96 Monthly Grids of Terrestrial Surface Climate’, J. Climate 13, 2217–2238.
Pal, J. S., Small E. E., and Eltahir, E. A. B.: 2000, ‘Simulation of Regional-Scale Water and Energy Budgets: Representation of Subgrid Cloud and Precipitation Processes within RegCM’, J. Geophys. Res. 105, 29579–29594.
Pan, Z., Christensen, J. H., Arritt, R. W., Gutowski, W. J. Jr., Takle, E. S., Otieno, F.: 2001, ‘Evaluation of Uncertainties in Regional Climate Change Simulations’, J. Geophys. Res. 106, 17735–17753.
Richardson, C. W. and Nicks, A. D.: 1990, ‘Weather Generator Description’, in EPIC — Erosion/Productivity Impact Calculator, 1, Model Documentation, Agricultural Research Service, United States Department of Agriculture, Washington, D.C., 93–104.
Robinson, P. J. and Henderson, K. G.: 1992, ‘Precipitation Events in the Southeast United States of America’, Int. J. Clim. 12, 701–720.
Takle, E. S., Gutowski, W. J., Arritt, R. W., Pan, Z., Anderson, C. J., Ramos da Silva, R., Caya, D., Chen, S.-C., Giorgi, F., Christensen, J. H., Hong, S.-Y., Juang, H.-M. H., Katzfey, J., Lapenta, W. M., Laprise, R., Liston, G. E., Lopez, P., McGregor, J., Pielke, R. A. Sr., and Roads, J. O.: 1999: ‘Project to Intercompare Regional Climate Simulations (PIRCS): Description and Initial Results’, J. Geophys. Res. 104, 19443–19461.
Watterson, I. G.: 1998, ‘An Analysis of the Global Water Cycle of Present and Doubled CO2 Climates Simulated by the CSIRO General Circulation Model’, J. Geophys. Res. 103, 2311–23129.
Watterson, I. G., Dix, M. R., and Colman, R. A.: 1999, ‘A Comparison of Present and Doubled 2 Climates and Feedbacks Simulated by Three General Circulation Models’, J. Geophys. Res. 104, 1943–1956.
Watterson, I. G., O’Farrell, S. P., and Dix, M. R.: 1997, ‘Energy and Water Transport in Climates Simulated by a General Circulation Model that Includes Dynamic Sea Ice’, J. Geophys. Res. 102, 11027–11037.
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Mearns, L.O., Giorgi, F., McDaniel, L., Shields, C. (2003). Climate Scenarios for the Southeastern U.S. Based on GCM and Regional Model Simulations. In: Mearns, L.O. (eds) Issues in the Impacts of Climate Variability and Change on Agriculture. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1984-1_2
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DOI: https://doi.org/10.1007/978-94-017-1984-1_2
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