Calibrating Water Vapour Lidars with Radiosonde Trajectories

Water vapour trends are difficult to calculate due to water vapour’s inherent high variability in the atmosphere. Highly accurate instruments with high vertical and temporal resolution are required to produce statistically significant trends. To that end, atmospheric lidars are highly suited for trend measurements. However, water vapour Raman lidars produce a relative measurement and require calibration to transform them into absolute physical units. Typically, the calibration is done using a reference instrument such as a radiosonde. Calibrations can be affected by a lack of co-location with the reference instrument, particularly when the water vapour field changes rapidly over the calibration period. We have minimized this effect by tracking the air parcels measured by the radiosonde through the field-of-view of the lidar. We present an improved trajectory technique to calibrate water vapour Raman lidars based on the previous work of Whiteman et al. (2006), Leblanc et al. (2008), and Adam et al. (2010) and compare this technique to traditional radiosonde-lidar calibration techniques which do not track the radiosonde position.

We use GCOS Reference Upper Air Network (GRUAN) Vaisala RS92 radiosonde measurements and lidar measurements from the RAman Lidar for Meteorological Observation (RALMO), located in Payerne, Switzerland to demonstrate this improved calibration technique. The results shows that the "trajectory method" more accurately reproduces the radiosonde profile, particularly when the water vapour field is not homogeneous over a 30 min calibration period. Using GRUAN radiosondes allows us to calculate a calibration uncertainty budget that can be performed on a nightly basis. We include the contribution of the radiosonde measurement uncertainties to the total calibration uncertainty, and show that on average the uncertainty contribution from the radiosonde is 4% of the water vapour mixing ratio uncertainty. We also calculate the uncertainty in the lidar's counting system dead time in the calibration uncertainty and found it to be an average of 0.3% for a system with 5% uncertainty in dead time. This trajectory method allows a more accurate calibration with non-co-located radiosondes, and allows additional nights to be used for calibration that would otherwise be discarded.