To investigate a winter thundercloud structure, we have been acquiring data on the electrostatic field and the meteorological variables (atmospheric pressure and wind speed) over a full winter season. The obtained data were investigated by a wavelet transform method that is a mathematical technique introduced recently for analyzing seismic and acoustic signals. Microscopic variations in time series of the pressure and the wind speed are extracted from nonprocessed ones using a moving average method, then analyzed by a wavelet method. For each variable, wavelet transform coefficients (modulus) are displayed using gray scales as its grade. These figures provide a clearly interpretable visual representation of time series signals. Namely, it is easily understood what significant scales exist at the concerned time. Mutual correlation coefficients of modulus between the pressure and the wind speed variation are also calculated to clarify how these two variables are related to each other. A scale parameter and a phase shift in time are adopted as two-dimensional coordinates in the same manner as the wavelet transform. This figure shows whether there is a strong correlation between the two variables or not, and if so, its time and/or position. When thunderclouds pass near the observation station, characteristic oscillations are detected in a pressure variation. A strong correlation between the pressure and the wind speed has been proved by a method of a wavelet transform method. On the other hand, when the climate is quiet, there is no correlation. A correlation between the pressure variation and the electrostatic field at the ground has also been clarified. ¿ American Geophysical Union 1994