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A physically based short‐term rainfall prediction method, which uses a volume scanning radar, is extended so that it utilizes grid point values from a numerical weather prediction model as supplementary information. The original short‐term prediction method mainly consists of a conceptual rainfall model that can predict rainfall distribution, particularly over mountainous regions, in a qualitative sense. On the other hand, the grid point values from the numerical weather prediction model, the Japan Spectral Model developed by the Japan Meteorological Agency, are operationally distributed as the grid point value (GPV) data. In the original short‐term prediction method the three‐dimensional wind field as well as initial distributions of the air temperature and water vapor were identified using topography and upper air observations. In the extended method, however, in identifying those initial values, the information from the GPV data is used instead of the upper air observations in order to accommodate large differences in temporal and spatial resolution between radar information and upper air observations. It is noted that this extended method does not use predicted GPV rainfall data. The conceptual rainfall model plays the role of bridging the gap between radar information and numerical weather prediction scales. This extended method is applied to a rainfall event which occurred in the bai‐u season (one of the rainy seasons of Japan) in July 1994. Results show that for the extended lead time of three and four hours, prediction of the expanding rainfall area was improved.

A physically-based short-term rainfall prediction method, which uses a volume scanning radar, is extended so that it utilizes grid point values from a numerical weather prediction, namely GPV data, as supplementary information. It is noted that this extended method does not use predicted GPV rainfall data The conceptual rainfall model in the prediction method plays the role of bridging a gap between radar information and the numerical -weather prediction.This extended method is applied to a rainfall event which occurred in the Baiu season, , in July of 1994. Results shows that for extended lead time of three and four hours, the prediction of expanding rainfall area was greatly improved.

Chronologies of tree-ring width and stable carbon isotope composition of Japanese cypress were developed to help reconstruct a 300-year record of past hydrologic and climatic environments in the Lake Biwa area, central Japan. Site chronologies were built with 37 trees for ring width and four trees for carbon isotope composition, respectively. Correlation analysis with monthly climatic data revealed that radial growth of the trees is related to temperature in early spring, precipitation (or number of precipitation days) in early summer and precipitation in previous-year summer to autumn. Tree-ring cellulose carbon isotopic composition is correlated most significantly with the number of precipitation days in early summer months. Consequently, a chronology of the number of precipitation days in May was reconstructed by multiple regression analysis with ring-width and carbon-isotope predictors and was validated by comparison with the recent observed record.