  The short-term rapid CR flux depressions, generally referred to as Forbush
decreases (FDs), are the most spectacular time-intensity CR variation. The need
for analytical transformation of the observational CR time series data, to
account for FDs and other recurrence tendencies such as periodicities and
cycles, was noted since the 1930s'. Nevertheless, it has been recently observed
that harmonic analysis, which is capable of transforming raw CR data into
different frequencies, is rarely exploited. Predominant in the literature are
the ordinary Fourier and power spectral analyses, generally used to calculate
the positive vectors (amplitude and phase) of the periodic diurnal CR
anisotropy. In the two approaches, the days immediately connected with FDs are
frequently removed to minimize unusual changes in the amplitude of the vectors
as well as a spurious time of maximum. However, there is a paucity of
publications that adjust for the influence of enhanced CR diurnal anisotropy on
the magnitude and timing of FDs. Recently, in an attempt to test the global FD
event simultaneity, a combination of numerical filtering and fast Fourier
transform techniques was deployed to account for these superposition tendencies
in daily CR data, including the intractable CR diurnal anisotropy. However, an
extremely sensitive version of the software would be required to analyze
high-resolution CR hourly averages. As a way of achieving accurate detection
and precise timing of FD signals, the computer algorithms were technically
improved and employed in a long-term statistical investigation. To appreciate
the implemented extremely sensitive statistical technique, several validation
analyses, including FD-based solar-terrestrial correlation, comparison of FD
catalogues, and Frobush event simultaneity test were conducted.
