Abstract
Rainfall is the most essential for investigating hydrological processes and water balance. However, because it is difficult to get spatial and daily rainfall data using equipments at many observation sites in the field, especially in developing countries, different useful methodologies have been required. Geostationary Meteorological Satellite-Infrared (GMS-IR) data has an excellent characteristic that the data can be collected 8 times every day, and is, therefore, available to obtain spatially-averaged data in a large-scale area. In this study, a regression model for estimating daily rainfall using GMS-IR data is proposed. The model is applied to daily rainfall data obtained in the regions of an area of 0.25°×0.25° in the Shikoku island, and can give satisfactory estimations.
