106
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
we observe is the broad spectral peak punctuated by multiple distinct minor peaks
beginning at about 0.09–0.4. This region is the energy-containing range, where the
dominant portion of the turbulent energy produced is from buoyancy and shear
stresses. The inertial subrange is characterized by substantial turbulent variability,
indicating strongly unstable surface conditions. The subinertial range is the region
where energy is neither produced nor dissipated but rather energy is transferred
down to ever-decreasing scales. Distinct oscillations in the turbulent flow indicate
a range of eddy motions responsible for the dominant transport of heat. The intensity of the turbulence perturbations is noted for this condition of strong winds and
surface instability as observed by the magnitude of the cospectral energy of the
turbulence and is actually equivalent and at times greater than the energy of larger
low-frequency eddies. The significance of this response is presently undetermined.
Figure 5.11b shows the cospectral plot wρ v (LE). The spectral gap observed for the
heat flux is clearly absent for the water vapor flux. Beginning at 0.01, the cospectral
shape and slope of the subinertial range is nearly identical with the heat flux. During
this period, the conditions for EC measurements were nearly ideal, and the results
were consistent with those reported by Goulden et al. (1996) and McNaughton and
Laubach (2000). There is more power in the cospectra for LE compared to H, which
is expected given the large LE fluxes shown in Figure 5.9b.
The spectral (power and cospectra) results show that turbulence will affect heat
and water vapor transport in different ways. Although it is not shown in this chapter,
calm periods limit the turbulent exchange for scalar and mass fluxes. During more
turbulent periods, that is, higher winds, turbulence does affect the exchange of heat
and water vapor through the boundary layer.
5.7 CONCLUSIONS
Preliminary data and results from an experiment in Bushland, TX, have been analyzed in this study. This experiment focused on estimating ET over irrigated cotton
surfaces in a heterogeneous landscape using remotely sensed thermal measurements
from an aircraft platform. Multiple EC systems were deployed over the heterogeneous landscapes to provide validation points for the remotely sensed estimates
based on satellite images. Agricultural production in a semiarid climate inherently
produces a patchwork heterogeneous surface characterized by multiple wet and dry
surfaces, producing large gradients in saturation deficit (advection) that would result
in variations in the transport of warm dry air originating from nonirrigated surfaces
and transporting to the irrigated surfaces. This results in enhancing ET and modifying the SEB and has obvious implications for energy balance and ET studies and
for computing and interpreting reliable ET fluxes to provide validation points to
compare with remotely sensed ET estimates. Examination of raw EC high-frequency
data revealed distinct eddy structures that were spatially variable in time and space
and readily observable in the horizontal component of the mean wind. The vertical
velocity was less clear, but still, distinct structures could be seen. Temperature and
water vapor concentrations over the irrigated cotton were well coupled through most
portions of the day that included stable and unstable conditions. Latent and sensible
heat flux time traces computed as 5- and 30-min averages suggest the presence of
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
we observe is the broad spectral peak punctuated by multiple distinct minor peaks
beginning at about 0.09–0.4. This region is the energy-containing range, where the
dominant portion of the turbulent energy produced is from buoyancy and shear
stresses. The inertial subrange is characterized by substantial turbulent variability,
indicating strongly unstable surface conditions. The subinertial range is the region
where energy is neither produced nor dissipated but rather energy is transferred
down to ever-decreasing scales. Distinct oscillations in the turbulent flow indicate
a range of eddy motions responsible for the dominant transport of heat. The intensity of the turbulence perturbations is noted for this condition of strong winds and
surface instability as observed by the magnitude of the cospectral energy of the
turbulence and is actually equivalent and at times greater than the energy of larger
low-frequency eddies. The significance of this response is presently undetermined.
Figure 5.11b shows the cospectral plot wρ v (LE). The spectral gap observed for the
heat flux is clearly absent for the water vapor flux. Beginning at 0.01, the cospectral
shape and slope of the subinertial range is nearly identical with the heat flux. During
this period, the conditions for EC measurements were nearly ideal, and the results
were consistent with those reported by Goulden et al. (1996) and McNaughton and
Laubach (2000). There is more power in the cospectra for LE compared to H, which
is expected given the large LE fluxes shown in Figure 5.9b.
The spectral (power and cospectra) results show that turbulence will affect heat
and water vapor transport in different ways. Although it is not shown in this chapter,
calm periods limit the turbulent exchange for scalar and mass fluxes. During more
turbulent periods, that is, higher winds, turbulence does affect the exchange of heat
and water vapor through the boundary layer.
5.7 CONCLUSIONS
Preliminary data and results from an experiment in Bushland, TX, have been analyzed in this study. This experiment focused on estimating ET over irrigated cotton
surfaces in a heterogeneous landscape using remotely sensed thermal measurements
from an aircraft platform. Multiple EC systems were deployed over the heterogeneous landscapes to provide validation points for the remotely sensed estimates
based on satellite images. Agricultural production in a semiarid climate inherently
produces a patchwork heterogeneous surface characterized by multiple wet and dry
surfaces, producing large gradients in saturation deficit (advection) that would result
in variations in the transport of warm dry air originating from nonirrigated surfaces
and transporting to the irrigated surfaces. This results in enhancing ET and modifying the SEB and has obvious implications for energy balance and ET studies and
for computing and interpreting reliable ET fluxes to provide validation points to
compare with remotely sensed ET estimates. Examination of raw EC high-frequency
data revealed distinct eddy structures that were spatially variable in time and space
and readily observable in the horizontal component of the mean wind. The vertical
velocity was less clear, but still, distinct structures could be seen. Temperature and
water vapor concentrations over the irrigated cotton were well coupled through most
portions of the day that included stable and unstable conditions. Latent and sensible
heat flux time traces computed as 5- and 30-min averages suggest the presence of