The potential impacts of the use of Southern Oscillation information on the Texas aggregate sorghum production

Journal of Climate

Volumn 12, Issue 2, 1999, Pages 519-530

  Hill, Harvey S J ^a   Mjelde, James W ^a   Rosenthal, Wesley ^b   Lamb, Peter J ^c  

^a TEXAS A AND M UNIVERSITY   (United States)

^b BLACKLAND RESEARCH AND EXTENSION CENTER   (United States)

^c UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURE; ENVIRONMENTAL IMPACT; MATHEMATICAL MODELS;

SORGHUM PRODUCTION; SOUTHERN OSCILLATION INFORMATION;

CLIMATE CHANGE;

CLIMATE CHANGE; CROP PRODUCTION; PREDICTION; SOUTHERN OSCILLATION;

TEXAS; UNITED STATES;

EID: 0033079848     PISSN: 08948755     EISSN: None     Source Type: Journal    
DOI: 10.1175/1520-0442(1999)012<0519:TPIOTU>2.0.CO;2     Document Type: Article

References (46)

1. Adams, R. M., K. J. Bryant, B. A. McCarl, D. M. Legler, J. J. O'Brien, A. Solow, and R. Weiher, 1995: Value of long-range weather information. Contemp. Econ. Policy, 13, 10-19.
2. Australian Bureau of Meteorology, 1991: Seasonal climate outlook. National Climate Centre Rep. 28, Melbourne, Australia, 18 pp. [Available from Director of Meteorology, Bureau of Meteorology, G.P.O. Box 1289K, Melbourne, Victoria 3001, Australia.]
3. _, cited 1998: Australian Rainman 2.0. [Available online from http: //amdisa.ho.bom.gov.au/climate/how/rainman/rainman.shtml.]
4. Babcock, B. A., 1990: The value of weather information and market equilibrium. Amer. J. Agric Econ., 72, 63-72.
5. Cane, M. A., 1983: Oceanographic events during El Niño. Science, 222, 1189-1194.
6. _, G. Eshel, and R. W. Buckland, 1994: Forecasting Zimbabwean maize using eastern equatorial pacific sea surface temperature. Nature, 370, 204-205.
7. GCOS Working Group, 1995: Socio-economic value of climate forecasts literature review and recommendations. GCOS-12 WMO/ TD-No. 674, World Meteorological Organization, Geneva, Switzerland, 34 pp. [Available from GCOS Joint Planning Office, CP2300, CH-1211 Geneva 2, Switzerland.]
8. Glantz, M. H., 1994: Forecasting El Niño: Science's gift to the 21st century. Ecodecision, 4, 78-81.
9. _, 1996: Currents of Change: El Niño's Impact On Climate and Society. Cambridge University Press, 194 pp.
10. Godfrey, C. L., G. S. McKee, and H. Oaks, comps., 1973: General soil map of Texas. Texas A&M University and Soil Conservation Service. [Available from Sterling C. Evans Library, Texas A&M University, College Station, TX 77483-5000.]
11. Greenberg, J., 1976: Economic benefits of improved meteorological forecasts. Weather Forecasting and Weather Forecasts: Models Systems and User, Vol. 2, National Center for Atmospheric Research, 608-629.
12. Hill, S. J. H., 1995: Improved climate forecast accuracy: Implications for the aggregate sorghum supply curve. M.S. thesis, Department of Agricultural Economics, Texas A&M University, College Station, TX, 195 pp. [Available from Sterling C. Evans Library, Texas A&M University, College Station, TX 77483-5000.]
13. Kiladis, G. N., and H. F. Diaz, 1989: Global climatic anomalies associated with extremes of the Southern Oscillation. J. Climate, 2, 1069-1090.
14. Kissel, D. E., J. T. Ritchie, and C. W. Richardson, 1975: A stress day concept to improve nitrogen fertilizer utilization: Dryland grain sorghum in the Texas blackland prairie. Texas A&M Agricultural Experiment Station Rep. MP 1201, 15 pp. [Available from Sterling C. Evans Library, Texas A&M University, College Station, TX 77483-5000.]
15. Lagus, P., and J. Buzier, 1992: El Niño and Peru: A nation's response to interannual climate variability. Natural and Technological Disasters: Causes, Effects, and Preventive Measures, S. K. Majumdar, Ed., Pennsylvania Academy of Sciences, 223-239.
16. Lamb, P. J., 1979: Some perspectives on climate and climate dynamics. Progr. Phys. Geogr., 3, 215.
17. _, 1981: Do we know what we should be trying to forecast -Climatically? Bull. Amer. Meteor. Soc., 62, 1000-1001.
18. Lave, L. B., 1963: The value of better weather information to the raisin industry. Econometrica, 31, 151-164.
19. Livezey, R. E., 1990: Variability of skill of long-range forecasts and implications for their use and value. Bull. Amer. Meteor. Soc., 71, 300-309.
20. Mjelde, J. W., and K. Keplinger, 1998: Using the Southern Oscillation to forecast Texas winter wheat and sorghum crop yields. J. Climate, 11, 54-60.
21. _, S. T. Sonka, and D. S. Peel, 1989: The socioeconomic value of climate and weather forecasting: A review. Research Rep. 89-01, 21 pp. [Available from Midwestern Climate Center, Climate and Meteorology Section, Illinois State Water Survey, 2204 Griffith Drive, Champaign, IL 61820-7495.]
22. _, D. S. Peel, S. T. Sonka, and P. J. Lamb, 1993: Characteristics of climate forecasts quality: Implications for economic value to Midwestern corn producers. J. Climate, 6, 2175-2187.
23. _, T. N. Thompson, and C. J. Nixon, 1995: Government institutional effects on the value of seasonal climate forecasts. Rep. to United States Department of Commerce/National Oceanic and Atmospheric Administration, 65 pp.
24. _, J. B. Penson Jr., and C. J. Nixon, 1997: Dynamic aspects of the impact of the use of improved climate forecasts in the corn belt region. NOAA Final Rep. NA56GP0266, 45 pp.
25. National Oceanic and Atmospheric Administration, 1995: The ENSO signal international forum on forecasting El Niño: Launching an international research institute. Office of Global Programs Rep., Issues 1-3, Silver Spring, MD, 67 pp.
26. Nicholls, J. M., 1996: Economic and social benefits of climatological information and services: A review of existing assessments. WMO/TD-No. 780, World Meteorological Organization, Geneva, Switzerland, 38 pp.
27. Nicholls, N., 1986: Use of the Southern Oscillation to predict Australian sorghum yield. Agric. For. Meteor., 38, 9-15.
28. Nicholson, W., 1992: Microeconomic Theory: Basic Principles and Extensions. 5th ed. Dryden Press, 825 pp.
29. Rasmussen, E. M., and J. M. Wallace, 1983: Meteorological aspects of the El Niño/Southern Oscillation. Science, 222, 1195-1202.
30. Richardson, C. W., and D. A. Wright, 1984: WGEN: A model for generating daily weather variable. USDA/ARS-8, 83 pp. [Available from National Technical Research Service, U.S. Department of Agriculture, Agricultural Research Service, Springfield, VA 22161.]
31. Ropelewski, C. F., and M. S. Halpert, 1986: North American precipitation and temperature patterns associated with the El Niño/ Southern Oscillation (ENSO). Mon. Wea. Rev., 114, 2352-2362.
32. _, and _, 1987: Global and regional scale precipitation and temperature patterns associated with the El Niño/Southern Oscillation. Mon. Wea. Rev., 115, 1606-1626.
33. _, and _, 1989: Precipitation patterns associated with the high index phase of the Southern Oscillation. J. Climate, 2, 268-284.
34. Rosenthal, W. D., and T. J. Gerik, 1990: Application of a crop model to evaluate cultural practices and optimal dryland grain sorghum yield. J. Prod. Agric., 3, 124-131.
35. _, R. L. Vanderlip, B. S. Jackson, and G. F. Arkin, 1989: SORKAM: A grain sorghum crop growth model. Texas Agricultural Experiment Station Computer Documentation Series, MP 1689, Rep. 94-2, 205 pp. [Available from Texas A&M University, College Station, TX 77843.]
36. Sittle, M., 1994: Differences in means of ENSO extremes for maximum temperatures and precipitation in the U.S. Florida State University COAPS Rep., 50 pp. [Available from Center for Ocean-Atmosphere Prediction Studies, The Florida State University, Tallahassee, FL 32306.]
37. Sonka, S. T., J. L. Lamb, S. A. Changnon, and A. Wiboonpongse, 1982: Can climate forecasts for the growing season be valuable to crop producers: Some general considerations and an Illinois pilot study. J. Appl. Meteor., 21, 471-476.
38. _, S. A. Changnon, and S. Hofing, 1988: Assessing climate information use in agribusiness. Part II: Decision experiments to estimate economic value. J. Climate, 1, 766-773.
39. Stone, R. C., and A. Auliciems, 1992: SOI phase relationships with rainfall in eastern Australia. Int. J. Climatol., 12, 625-636.
40. _, G. L. Hammer, and T. Marcussen, 1996: Prediction of global rainfall probabilities using phases of the Southern Oscillation index. Nature, 384, 252-255.
41. Texas Agricultural Statistics Service, 1991: 1990 Texas crop statistics. Bull. 249, No. 1, 128 pp. [Available from Texas Agricultural Statistics Service, P.O. Box 70, Austin, TX 78767.]
42. _, 1993: 1992 Texas crop statistics. Bull. 251, No. 4, 136 pp. [Available from Texas Agricultural Statistics Service, P.O. Box 70, Austin, TX 78767.]
43. Texas Department of Agriculture-USDA, 1993: Texas agriculture cash receipts and price statistics. Texas Agriculture Statistics Service. Bull. 252, No. 3, Austin, TX, 32 pp.
44. Trenberth, K. E., and J. T. Kiehl, 1997: Earth's annual global mean energy budget. Bull. Amer. Meteor. Soc., 78, 197-208.
45. U.S. Department of Agriculture, 1993: Agriculture statistics 1993. National Agriculture Statistics Service, U.S. Government Printing Office, Washington, DC, 517 pp.
46. Webster, P. J., and R. Lukas, 1992: TOGA COARE: The Coupled Ocean-Atmosphere Response Experiment. Bull. Amer. Meteor. Soc., 73, 1377-1416.