PDO Modulated ENSO Variability Impacting Regional Missouri Crop Yields

An analysis of crop yields for the state of Missouri was completed to determine if an interannual or multidecadal variability existed as a result of the El Nińo Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). Four crops were of focus for this study over a period of up to 95 years. Corn, sorghum, soybean, and wheat yields were recorded in bushels per acre, from the USDA National Agricultural Statistics Service, for each of the six climate regions of Missouri, defined by NOAA. Annual temperature and precipitation data were obtained from the Midwestern Regional Climate Center (MRCC). An analysis using the Birk “method of cycles” demonstrated interannual, interdecadal, and multidecadal variations in crop yields. Cross-spectral analysis was then used to determine which region was impacted the greatest by ENSO and PDO influenced annual temperature and precipitation. Interannual variations represent a correlation to ENSO phase, interdecadal variations represent a possible “interaction harmonic” between ENSO and PDO, and multidecadal variations represent a correlation to PDO phase. A cross-spectral analysis was also completed using annual Southern Oscillation Index data and annual mean values for the PDO index, obtained from the Bureau of Meteorology and the Japan Meteorological Agency, respectively. The resultant power spectrum was analyzed in order to verify that an interdecadal variation exists between ENSO and PDO. Average crop yields were calculated for each combination of ENSO and PDO phase, resulting in sufficient evidence to suggest that an “interaction harmonic” exists and PDO modulates ENSO-related variability. Therefore, when ENSO and PDO are both in a positive phase, wheat will most likely have a greater decrease in yields and corn, sorghum, and soybean will have a more pronounced increase in yields. Final results show the two northern Missouri regions having the strongest variability related to ENSO and PDO, giving regions 1 and 2 the greater chance of having accurate crop yield predictions when long-range forecasts are created.