Remote Sensing Measurement Height Verification

Introduction

Ground based remote sensing devices (RSD) like LiDAR and SODAR are able to measure vertical profiles of wind characteristics by measuring in different heights above ground. Using the correct measurement height is essential to this measurement task. Deutsche WindGuard (DWG) developed a new method to verify the accuracy of the instruments measurement height in comparison to a measurement mast. The same measurement data is used as in a verification of the wind speed measurement of an RSD according to the upcoming revision of the IEC 61400-12-1, ed. 2. Therefore the method requires no additional measurement effort.

Approach

Wind speed data is recorded as 10-minute averages both at the reference sensor and at the tested RSD. From the wind speed measurements at two different heights of the reference measurement, the wind shear exponent is calculated for every 10 minute interval. A time series of 10 minute wind speeds at any intermediate height can be constructed by assuming that the vertical profile of the wind speed follows the power law described by the derived exponents.
The key step of the method is to identify the height at which the constructed wind speed and the measurement of the RSD exhibit the highest correlation. This height is then interpreted as the measurement height of the RSD. Deviation of this height from the measurement height given by the RSD is interpreted as the measurement height error.


Main body of abstract

The described method was tested with the following measurement set ups. The first test was to apply the method to anemometers instead of an RSD. This has the advantage that the mounting height of anemometers can be directly measured. This was done at the met mast of DWG’s own RSD calibration site, which consists of 6 height levels between 40 m and 135 m with at least 2 anemometers at each level. In this case, the method reproduces the expected height difference within 1 m of accuracy. Drawback of this method is that the anemometers tested were almost on the same height as the reference anemometer. Therefore a second test was set up, where two LiDARs where used with a height difference of about 1 m to 2 m between two consecutive measurement heights. Thus an artificial height error of a few meters could be simulated. Again the method could detect the expected height error within 1 m accuracy.

Having gained some confidence in the method by the tests above, the method was applied on the data collected during a number of calibration measurements with DWG’s met mast. A height error of 3 m to 5 m is observed for a number of tested RSDs.


Conclusion

A new method to derive the measurement height error of a remote sensing device was successfully developed. In a control test on known height errors, these height errors could be reproduced by the method with a deviation less than 1 m. In a first test of RSDs against a met mast, height errors of 3 m to 5 m were detected.


Learning objectives
assess remote sensing measurement height errors