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It is well-known that short-term weather conditions have significant relationships with Fusarium head blight (FHB) epidemics and forecast models have been developed that use weather conditions near flowering to predict the risk of disease. However, we have also identified longer time-scales during the wheat-growing season where environmental variables are associated with FHB intensity, which may be in response to larger-scale climate patterns. Climate patterns that affect the Midwest Region include the Oceanic Niño Index (ONI), the El Niño Southern Oscillation (ENSO), the Pacific-North American pattern and the North Atlantic Oscillation. These climate patterns and the time-series of FHB disease intensity observations over more than 45 years were investigated through wavelet and spectral analysis methods. These analytical methods identify the frequency at which a temporal signal occurs and clusters of years within the overall patterns where relationships are strongest. Results suggest that global climate indices and models could be used to identify years with high (or low) risk for FHB development, although the most accurate risk predictions will also require use of local weather data during key time periods. Research on new analyses methods to investigate climate/disease relationships, other plant pathogens that exhibit relationships with the climate, and integration of climate into current or new weather forecasting models is ongoing.