TITLE:
On the Variability of Charleston South Carolina Winds, Atmospheric Temperatures, Water Levels, Waves and Precipitation
AUTHORS:
L. J. Pietrafesa, P. T. Gayes, S. Bao, T. Yan, D. A. Dickey, D. D. Carpenter, T. G. Carver
KEYWORDS:
Charleston Atmospheric Temperature, Winds, Water Level, Precipitation, Oceanic Waves, Temporal Scales of Variability, Kinematics of the Winds, Winds Predict Waves
JOURNAL NAME:
International Journal of Geosciences,
Vol.12 No.5,
May
28,
2021
ABSTRACT: Atmospheric winds, air
temperatures, water levels, precipitation and oceanic waves in the Charleston
South Carolina (SC) coastal zone are evaluated for their intrinsic, internal
variability over temporal scales ranging from hours to multi-decades. The
purpose of this study was to bring together a plethora of atmospheric and
coastal ocean state variable data in a specific locale, to assess temporal
variabilities and possible relationships between variables. The questions
addressed relate to the concepts of weather and climate. Data comprise the
basis of this study. The overall distributions of atmospheric and coastal
oceanic state variable variability, including wind speed, direction and
kinematic distributions and state variable amplitudes over a variety of time
scales are assessed. Annual variability is shown to be highly variable from
year to year, making arithmetic means mathematically tractable but physically
meaningless. Employing empirical and statistical methodologies, data analyses
indicate the same number of intrinsic, internal modes of temporal variability
in atmospheric temperatures, coastal wind and coastal water level time series,
ranging from hours to days to weeks to seasons, sub-seasons, annual,
multi-year, decades, and centennial time scales. This finding demonstrates that
the atmosphere and coastal ocean in a southeastern U.S. coastal city are
characterized by a set of similar frequency and amplitude modulated phenomena.
Kinematic hodograph descriptors of atmospheric winds reveal coherent rotating and rectilinear particle motions. A
mathematical statistics-based wind to wave-to-wave algorithm is
developed and applied to offshore marine buoy data to create an hour-by-hour
forecast capability from 1 to 24 hours; with confidence levels put forward.
This affects a different approach to the conventional
deterministic model forecasting of waves.