Statistical Analysis of Subsurface Diffusion of Solar Energy with Implications for Urban Heat Stress ()
ABSTRACT
Analysis
of hourly underground temperature measurements at a medium-size (by population)
US city as a function of depth and extending over 5+ years revealed a positive
trend exceeding the rate of regional and global warming by an order of magnitude.
Measurements at depths greater than ~2 m are unaffected by daily fluctuations
and sense only seasonal variability. A comparable trend also emerged from the
surface temperature record of the largest US city (New York). Power spectral
analysis of deep and shallow subsurface temperature records showed respectively
two kinds of power-law behavior: 1) a quasi-continuum of power amplitudes
indicative of Brownian noise, superposed (in the shallow record) by 2) a
discrete spectrum of diurnal harmonics attributable to the unequal heat flux
between daylight and darkness. Spectral amplitudes of the deepest temperature
time series (2.4 m) conformed to a log-hyperbolic distribution. Upon removal of
seasonal variability from the temperature record, the resulting spectral
amplitudes followed a log-exponential distribution. Dynamical analysis showed
that relative amplitudes and phases of temperature records at different depths
were in excellent accord with a 1-dimensional heat diffusion model.
Share and Cite:
Silverman, M. (2014) Statistical Analysis of Subsurface Diffusion of Solar Energy with Implications for Urban Heat Stress.
Journal of Modern Physics,
5, 751-762. doi:
10.4236/jmp.2014.59085.