Using long range seasonal forecasts to improve prediction of Oklahoma wheat yield

Accurately predicted crop yield is economically valuable for farmers and for the government, who can better prepare for high or low yields given a crop forecast. The CERES-Wheat model provides a forecast of wheat yield given environmental variables, typically using climatological means of temperature and precipitation data. This model excludes anomalous weather regimes, leading to possible error in the forecasted yield. In Oklahoma, long-term records of daily weather are available for each county in the state. For this study, three-month seasonal forecasts have been obtained from NOAA's Climate Prediction Center. To match the forecast information and to better model weather for an upcoming growing season, the climate history is divided into above normal, normal, and below normal temperature and precipitation regimes. The weights assigned to each of these categories are adjusted using probabilities from the long-range forecasts to generate a weighted climate history. Coupling this enhanced forecast with observed weather data creates a better model of potential weather in years that depart from the normal. This model of weather is used in conjunction with the CERES model to predict wheat yield using forecast information. Results indicate that enhanced weather forecasts can improve the prediction of wheat yield. Monthly charts illustrate how to use updated weather and forecast information, and the enhanced wheat yield forecasts show spatial shifts in comparison with the previous forecasting method.