Winter-forest processes affect global and local climates. The interception-sublimation fraction (F) of snowfall in forests is a substantial part of the winter water budget (up to 40%). Climate, weather-forecast and hydrological modellers incorporate increasingly realistic surface schemes into their models, and algorithms describing snow accumulation and snow-interception sublimation are now finding their way into these schemes. Spatially variable data for calibration and verification of wintertime dynamics therefore are needed for such modelling schemes. The value of F was determined from snow courses in open and forested areas in Hokkaido, Japan. The value of F was related to species and canopystructure measures such as closure, sky-view fraction (SVF ) and leaf-area index (LAI ). Forest structure was deduced from fish-eye photographs. The value of F showed a strong linear correlation to structure: F D 0Γ44 0Γ6 Γ° SVF for SVF < 0Γ72 and F D 0 for SVF > 0Γ72, and F D 0Γ11 LAI. These relationships seemed valid for evergreen conifers, larch trees, alder, birch and mixed deciduous stands. Forest snow accumulation S F could be estimated from snowfall in open fields S o and to LAI according to S F D S o (1 0Γ11 LAI ) as well as from SVF according to S F D S o (0Γ56 C 0Γ6 SVF) for SVF < 0Γ72. The value of S F was equal to S o for SVF values above 0Γ72. The value of sky-view fraction was correlated to the normalized difference snow index (NDSI ) using a Landsat-TM image for observation plots exceeding 1 ha. Variables F and S F were related to NDSI for these plots according to: F D 0Γ37NDSI C 0Γ29 and S F D S o 0Γ81 C 0Γ37NDSI . These relationships are somewhat hypothetical because plot-size limitation only allowed one sparse-forest observation of NDSI to be used. There is, therefore, a need to confirm these relationships with further studies.