Abstract
The white-backed planthopper, Sogatella furcifera, and the brown planthopper, Nilaparvata lugens, are pests of rice and migrate from south China to Japan in the rainy season of early summer. In order to achieve high-precision migration prediction, a real-time prediction system was developed. In this system, the latest meteorological data are supplied online to an advanced numerical weather prediction model, MM5. The model forecasts three-dimensional atmospheric fields at one-hour intervals. In these fields, a planthopper migration simulation model, GEARN, calculates movement of a number of modeled planthoppers and predicts their relative aerial density at three-hour intervals. The results are converted to maps and become available on the Internet. The maps of relative aerial density provide information about the timing and area of migrations over the next two days. During the main migration season in June and July 2003, the system achieved a prediction quality that was comparable to that of rainfall forecasts by the Japanese Meteorological Agency.