TY - JOUR
T1 - The importance of seasonal climate prediction lead time in agricultural decision making
AU - Easterling, William E.
AU - Mjelde, James W.
N1 - Funding Information:
This research was sponsored by NSF grant ATM82-13734, contract NA79-RAC-00104 of the National Climate Program Office, and the Andrew W. Mellon Foundation in association with the Fellowship Office of the National Academy of Sciences/National Research Council. The authors acknowledge Purdue University and Doanes Publishing Company for use of corn production and soil moisture models. Lastly, the authors wish to thank Peter J. Lamb, Steven T. Sonka, Steve Hollinger and John S. Perry for advice on this effort.
Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 1987/6
Y1 - 1987/6
N2 - Monthly and seasonal climate predictions are of potential value in agricultural decision making. Most studies evaluating the usefulness of climate predictions to various economic sectors have focused primarily on accuracy levels as the primary impediment to wider use of the predictions in decision making. It is argued here, however, that prediction lead time is also an important factor in the usefulness of the predictions. It is shown that lead time (or lack thereof) is the most important variable distinguishing between subscribers to a National Oceanic and Atmospheric Administration (NOAA) prediction who use the prediction in decision making from those who do not. Indeed, the lack of lead time is a major deterrent to the use of the prediction. Detailed decision analysis of east-central Illinois corn production reveals that a prediction of early summer conditions available in early spring has significantly more value than the same prediction available in late spring. The increased value of the early summer prediction that is available in early spring stems primarily from added flexibility in nitrogen application. Further, economic trade-offs are found between lead time and predictive accuracy. These findings are likely to have relevance beyond agriculture to other dynamic decision-making activities.
AB - Monthly and seasonal climate predictions are of potential value in agricultural decision making. Most studies evaluating the usefulness of climate predictions to various economic sectors have focused primarily on accuracy levels as the primary impediment to wider use of the predictions in decision making. It is argued here, however, that prediction lead time is also an important factor in the usefulness of the predictions. It is shown that lead time (or lack thereof) is the most important variable distinguishing between subscribers to a National Oceanic and Atmospheric Administration (NOAA) prediction who use the prediction in decision making from those who do not. Indeed, the lack of lead time is a major deterrent to the use of the prediction. Detailed decision analysis of east-central Illinois corn production reveals that a prediction of early summer conditions available in early spring has significantly more value than the same prediction available in late spring. The increased value of the early summer prediction that is available in early spring stems primarily from added flexibility in nitrogen application. Further, economic trade-offs are found between lead time and predictive accuracy. These findings are likely to have relevance beyond agriculture to other dynamic decision-making activities.
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U2 - 10.1016/0168-1923(87)90053-0
DO - 10.1016/0168-1923(87)90053-0
M3 - Article
AN - SCOPUS:0023470268
SN - 0168-1923
VL - 40
SP - 37
EP - 50
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
IS - 1
ER -