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The modified logarithmic wind profile accounting for the atmospheric startification is defined
in Equation 352. u is the wind speed at height z, z0 is the sea roughness length, u∗
is the friction velocity, κ is the von Kármán constant (0.4) and ΨM the stability correction.
The ENW is computed using u∗ and z0 consistent with the actual stratification and setting
the ΨM function to zero.
Wind observations from buoys, models or other satellite winds are used to estimate the
friction velocity using the observed stability. The friction velocity is then used to estimate the
10 m wind assuming a neutral atmosphere. Finally, this neutral 10 m wind is related to the
observed σ0. The GMF resulting from the SASS scatterometer (Ku band) are tuned to ENW.
The GMF of the CMOD family were tuned to non-neutral winds until CMOD5.N which is
currently being used for the ASCAT scatterometer (Hersbach , 2010).
Figure 198: Example of the difference between ENW and true wind depending on the atmospheric
stratification. Image taken from Bourassa (2013)
The atmospheric stability is not always neutral. Figure 198 shows how the stability can
influence the difference between the ENW and the true wind. When the stratification is neutral
(green line), the difference between the ENW and the true wind is negligible. When the
stratification is stable (blue lines) the true wind is higher than the ENW. When the stratification
is unstable (red lines) the ENW is higher than the true wind but the differences are
much smaller compared to the stable cases. Brown et al. (2006) found that the globally averaged
10 m neutral winds from the European Centre for Medium Range Weather Forecasting
(ECMWF) were 0.19 m s −1 stronger than the ECMWF standard 10 m winds and concluded
that the marine boundary layer is overall slightly unstable.
16.4 Sources of error
The backscattered signal is affected by rain, currents, the sea surface temperature and the
atmospheric stratification. Hilburn et al. (2006) stated that rain changes the ocean surface
roughness, backscatters the radar pulse and reduces its transmission through the atmosphere.
Ku-band instruments operate at shorter wavelengths than C-band ones which makes them
more sensitive to raindrops either in the atmospheric path or because of the rougher sea
surface.
The sea surface temperature (SST) influences the viscosity of the surface oceanic layer
where the wind stress is applied. Higher SST results in lower viscosity. For a given wind
speed, lower viscosity causes more surface roughness and thus, more backscattering. In such
a case, the scatterometer will record higher σ0 values and the derived wind speed will be
higher. The overall effect is that over warm water the scatterometer-derived wind speed may
be higher than from in situ measurements.
DTU Wind Energy-E-Report-0029(EN) 299