Date of this Version
Interannual climate variability poses the greatest risk that farmers face. Until recently, seasonal climate forecasts have been weak and therefore rarely observed by farmers in making management decisions. Farm management is generally based on long-term mean expectations of climate and crop responses to local edaphic conditions. Currently, significant progress is being made in the skill level of predictions of seasonal to interannual climate, primarily because of new understanding of the teleconnections between ocean circulation and atmospheric processes. The El Niño/Southern Oscillation (ENSO) refers to fluctuations in both sea-surface temperatures (SSTs) in the eastern equatorial Pacific and in sea-level pressures in the southern Pacific at a time scale of roughly 3 to 7 years. Using ocean circulation models, we are now able to forecast the SST anomaly up to a year in advance with an 80% level of accuracy (Latif et al., 1994). Thus, associated climate phenomena may be predicted with a high degree of skill using this tool.
Given the strong relationship between crop growth and climate, this predictability carries significant implications for improved efficiency of agricultural production (Adams et al., 1995; Sonka et al., 1986). In some regions, the teleconnection between climate and ENSO has been well established. In others, however, the relationship is only now being elucidated. Thus, the spatial extent of the potential for use of ENSO forecasts is not well defined. We are developing a methodology that uses analysis of historical climate and crop data as well as models of crop growth and farm management to explore the extent of ENSO impacts and implications for using forecasts in agricultural management.
Based on the few studies that have been done, there is indication of a significant link between ENSO and climate in the midwestern United States. Using reconstruction from white oak tree rings in Iowa going back to 1640, Cleveland and Duvick (1992) showed a strong correlation with the Southern Oscillation Index, one indicator of the ENSO phase. Handler (1984) used yield data from the major Corn Belt states going back to 1868 and a classification scheme ranking event intensity. He found a strong relationship, with El Niño years associated with positive maize yield anomalies and La Niña with negative anomalies. Our current work extends the analysis of the U.S. Corn Belt, with the objective of testing the potential for using long-range ENSO/climate forecasts to increase profit margins and decrease risk for maize farmers in the United States.