Assessing predictability of cotton yields in the southeastern United States based on regional atmospheric circulation and surface temperatures

Journal of Applied Meteorology and Climatology

Volumn 47, Issue 1, 2008, Pages 76-91

  Baigorria, Guillermo A ^a   Hansen, James W ^b   Ward, Neil ^b   Jones, James W ^a   O'Brien, James J ^c  

^a J Crayton Pruitt Family Department of Biomedical Engineering   (United States)

^b Earth Institute   (United States)

^c FLORIDA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC HUMIDITY; ATMOSPHERIC MOVEMENTS; ATMOSPHERIC TEMPERATURE; CLIMATE CHANGE; COMPUTER SIMULATION; COTTON; HARVESTING; MATHEMATICAL MODELS; RAIN;

CLIMATE MODELS; COTTON YIELDS; GLOBAL CIRCULATION MODEL;

WEATHER FORECASTING;

ATMOSPHERIC CIRCULATION; CIRCULATION MODELING; COTTON; PREDICTION; SURFACE TEMPERATURE; WIND FIELD; YIELD;

ALABAMA; GEORGIA; NORTH AMERICA; UNITED STATES;

GOSSYPIUM HIRSUTUM;

EID: 40449134852     PISSN: 15588424     EISSN: None     Source Type: Journal    
DOI: 10.1175/2007JAMC1523.1     Document Type: Article

References (44)

1. Baigorria, G. A., 2007: Assessing the use of seasonal climate forecasts to support farmers in the Andean Highlands. Climate Prediction and Agriculture: Advances and Challenges, M. V. K. Sivakumar and J. W. Hansen, Eds., Springer-Verlag, 99-110.
2. Baigoria, G. A., J. W. Jones, and J. J. O'Brien, 2006: Predicting crop yields using an ensemble of forecasts from a regional climate model. Southeast Climate Consortium Tech. Rep. Series SECC-06-008, 14 pp.
3. Baigoria, G. A., J. W. Jones, and J. J. O'Brien, 2007a: Understanding rainfall spatial variability in the southeast USA at different time scales. Int. J. Climatol., 27, 749-760.
4. Baigoria, G. A., J. W. Jones, D. W. Shin, A. Mishra, and J. J. O'Brien, 2007b: Assessing uncertainties in crop model simulations using daily bias-corrected Regional Circulation Model outputs. Climate Res., 34, 211-222.
5. Cantelaube, P., and J. M. Terres, 2005: Seasonal weather forecasts for crop yield modelling in Europe. Tellus, 57A, 476-487.
6. Challinor, A. J., J. M. Slingo, T. R. Wheeler, P. Q. Craufurd, and D. I. F. Grimes, 2003: Toward a combined seasonal weather and crop production forecasting system: Determination of the working spatial scale. J. Appl. Meteor., 42, 175-192.
7. Challinor, A. J., J. M., and F. Doblas-Reyes, 2005: Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles. Tellus, 57A, 498-512.
8. Davis, R. E., B. P. Hyden, D. A. Gay, W. L. Phillips, and G. V. Jones, 1997: The North Atlantic subtropical anticyclone. J. Climate, 10, 728-744.
9. Efron, B., and G. Gong, 1983: A leisurely look at the bootstrap, the jackknife, and cross-validation. Amer. Stat., 37, 36-48.
10. Efron, B., and R. J. Tibshirani, 1993: An Introduction to the Bootstrap. Monogr. on Statistics and Applied Probability, No. 57, Chapman and Hall, 436 pp.
11. Fraisse, C. W., and Coauthors, 2006: AgClimate: A climate forecast information system for agricultural risk management in the southeastern USA. Comput. Electron. Agric., 53, 13-27.
12. Gong, G., 1986: Cross-validation, the jackknife, and the bootstrap: Excess error estimation in forward logistic regression. J. Amer. Stat. Assoc., 81, 108-113.
13. Goodman, B., 2004: 2004 cotton outlook. Southeastern Regional Outlook Conference, Alabama Cooperative Extension System and College of Agriculture, Auburn University, 6 pp.
14. Hair, J. F., Jr., R. E. Anderson, R. L. Tatham, and W. C. Black, 1998: Multivariate Data Analysis. 5th ed. Prentice Hall, 799 pp.
15. Hansen, J. W., 2002: Realizing the potential benefits of climate prediction to agriculture: Issues, approaches, challenges. Agric. Syst., 74, 309-330.
16. Hansen, J. W., 2005: Integrating seasonal climate prediction and agricultural models for insights into agricultural practice. Philos. Trans. Roy. Soc. London, 360B, 2037-2047.
17. Hansen, J. W., and M. Indeje, 2004: Linking dynamic seasonal climate forecasts with crop simulation for maize yield prediction in semi-arid Kenya. Agric. For. Meteor., 125, 143-157.
18. Hansen, J. W., A. W. Hodges, and J. W. Jones, 1998: ENSO influences on agriculture in the southeastern United States. J. Climate, 11, 404-411.
19. Higgins, R. W., K. C. Mo, and Y. Yao, 1998: Interannual variability of the U.S. summer precipitation regime with emphasis on the southwestern monsoon. J. Climate, 11, 2582-2606.
20. Hsieh, W. W., B. Y. Tang, and E. R. Garnett, 1999: Teleconnections between Pacific seas surface temperatures and Canadian prairie wheat yield. Agric. For. Meteor., 96, 209-217.
21. Ibarra, R., and T. Hewitt, 1999: Utilizing crop insurance to reduce production risk. Institute of Food and Agricultural Sciences Publication FE-198, Florida Cooperative Extension Service, 3 pp.
22. Ines, A. V. M., and J. W. Hansen, 2006: Bias correction of daily GCM rainfall for crop simulation studies. Agric. For. Meteor., 138, 44-53.
23. Ingram, K. T., M. C. Roncoli, and P. H. Kirshien, 2002: Opportunities and constraints for farmers of west Africa to use seasonal precipitation forecasts with Burkina Faso as a case study. Agric. Syst., 74, 331-349.
24. Jagtap, S. S., J. W. Jones, P. Hildebrand, D. Letson, J. J. O'Brien, G. Podestá, D. Zierden, and F. Zazueta, 2002: Responding to stakeholder's demands for climate information: From research to applications in Florida. Agric. Syst., 74, 415-430.
25. Jost, P. H., S. M. Brown, S. Culpepper, G. Harris, B. Kemerait, P. Roberts, D. Shurley, and J. Williams, 2005: 2005 Georgia cotton production guide. Cooperative Extension Service/The University of Georgia, College of Agricultural and Environmental Sciences Bulletin CSS-05-01, No. 1275, 39 pp.
26. Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437-471.
27. Klein, W. H., 1957: Principal tracks and mean frequencies of cyclones and anticyclones in the Northern Hemisphere. Weather Bureau Research Paper 40, 60 pp.
28. Krzanowski, W. J., 1987: Cross-validation in principal component analysis. Biometrics, 43, 575-584.
29. Mailhot, D., J. Marois, and D. Wright, 2005: Association of flower thrips with Fusarium verticillioides. Phytopathology, 95 (6).
30. Marletto, V., and Coauthors, 2005: Evaluation of downscaled DEMETER multi-model ensemble seasonal hindcasts in a northern Italy location by means of a model of wheat growth and soil water balance. Tellus, 57A, 488-497.
31. Marois, J. J., D. L. Wright, P. J. Wiatrak, and M. A. Vargas, 2002: Association of Fusarium sp. with Hardlock of cotton in the southeastern U.S. Proc. Beltwide Cotton Conf., Nashville, TN, National Cotton Council, C017.
32. Marois, J. J., D. L. Wright, P. J. Wiatrak, and M. A. Vargas, 2004: Effect of row width and nitrogen on cotton morphology and canopy microclimate. Crop Sci., 44, 870-877.
33. Marois, J. J., T. W. Katsvairo, D. L. Wright, and P. P. Wiatrak, 2005: Cotton Hardlock update. Proc. Management of Miscellaneous Crops, ASA-CSSA-SSSA Int. Meeting, Salt Lake City, UT, ASA, CSSA, and SSSA, 310.
34. Murphy, A. H., 1993: What is a good forecast? An essay on the nature of goodness in weather forecasting. Wea. Forecasting, 8, 281-293.
35. Nelson, R. A., D. P. Holzworth, G. L. Hammer, and P. T. Hayman, 2002: Infusing the use of seasonal climate forecasting into crop management practice in North East Australia using discussion support software. Agric. Syst., 74, 393-414.
36. Phillips, J. G., D. Deane, L. Unganai, and A. Chimeli, 2002: Implications of farm-level response to seasonal climate forecasts for aggregate grain production in Zimbabwe. Agric. Syst., 74, 351-369.
37. Podestá, G., and Coauthors, 2002: Use of ENSO-related climate information in agricultural decision making in Argentina: A pilot experience. Agric. Syst., 74, 371-392.
38. Press, W. H., B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling, 1989: Numerical Recipes: The Art of Scientific Computing. Cambridge University Press, 702 pp.
39. Roeckner, E., and Coauthors, 1996: The atmospheric general circulation model ECHAM4: Model description and simulation of present-day climate. Max Planck Institut für Meteorologie Rep. 218, 90 pp.
40. Sahsamanoglou, H. S., 1990: A contribution to the study of action centres in the North Atlantic. Int. J. Climatol., 10, 247-261.
41. Shin, D. W., J. G. Below, T. E. LaRow, S. Cocke, and J. J. O'Brien, 2006: The role of an advance land model in seasonal dynamical downscaling for crop model application. J. Appl. Meteor. Climatol., 45, 686-701.
42. Stahle, D. W., and M. K. Cleaveland, 1992: Reconstruction and analysis of spring rainfall over the southeastern U.S. for the past 1000 years. Bull. Amer. Meteor. Soc., 73, 1947-1961.
43. USDA National Agricultural Statistics Service, 2004: Crop values: Final estimates 1997-2002. Statistical Bulletin, No. 999a, 70 pp.
44. Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. 2nd ed. Academic Press, 627 pp.