GROUND-BASED REMOTE SENSING SYSTEMS - Wind Resource Assessment: A Practical Guide to Developing a Wind Project - page 110

postprocessing the data. Failure to account for variations in temperature can result in
biases of up to 2-3% between a sodar and a nearby anemometer.
8.5.2 Vector to Scalar Wind Speed Conversion (Sodar and Lidar)
Sodars and lidars typically record a vector-average horizontal wind speed at the end of
each averaging period. 1 In turbulent conditions, the varying wind direction causes the
vector average to be less than the scalar average (the usual output from anemometers).
A correction to the vector average can be estimated if the standard deviation of the
wind direction is known. Unfortunately, it is not possible to rely on the sodar's or
lidar's own horizontal standard deviation readings to perform this correction because
they, too, are based on vector averages. One option is to use the direction standard
deviation recorded by an anemometer at a nearby mast. If this is not possible, then the
standard deviation of the vertical speed measured by the sodar or lidar can be used
instead. The vector-to-scalar bias correction is typically about 1-3%.
Some devices may apply a vector to scalar correction during data processing. This
should be confirmed with the manufacturer.
8.5.3 Environmental Conditions (Lidar)
For all lidar devices, data recovery depends on the number and size of aerosol particles
in the atmosphere. In especially clean air (e.g., high mountain air, and other environ-
ments after a rain storm), signal recovery at all monitoring heights is reduced, and
measuring speeds at over 150 m height may not be possible. Some lidar devices are
also sensitive to backscatter from clouds. Although corrective algorithms have been
created for these conditions, this is an ongoing area of development. Finally, data col-
lected during periods of precipitation should be excluded from certain analyses. While
the effects of rain and snow on horizontal wind speed measurements may be small,
the vertical wind measurements are almost always overwhelmed by the precipitation's
downward motion and should be ignored during these periods.
8.5.4 Turbulence Intensity and Anemometer Overspeeding
(Sodar and Lidar)
As noted in Chapter 4, cup anemometers tend to overestimate the mean wind speed
in turbulence because they speed up in a gust more quickly than they slow down
after the gust passes. This effect varies significantly by sensor model, and where the
anemometers are not IEC Class I models, it can produce an apparent negative bias
of as much as 1-3% in lidar or sodar readings compared to anemometer measure-
ments. In this case, it is appropriate to adjust the anemometer data to avoid possibly
overestimating power production by the turbine. This topic is addressed in Chapter 9.
1 In a vector average, the east-west and north-south components of the speed are averaged separately and
then converted to a magnitude. If the speed changes direction from, say, east to west within the averaging
interval, the vector average can be much smaller in magnitude than the scalar average speed.