G2.08     Reducing water vapour lidar calibration uncertainties using a common reference standard

Gap detailed description

One of the paramount needs for developing a long-term data set for monitoring atmospheric water vapour using lidar techniques is represented by the calibration of Raman lidar water vapour profiles that vary randomly around some mean value (often addressed as a calibration constant that depends only on the instrument setup) and does not involve step jumps of unknown magnitude.

These step jumps in calibration increase the time required to detect atmospheric trends, which is already typically measured in decades [Weatherhead et. al., 1998; Boers and Meijgaard, 2009]. For this reason, it is important to carefully examine any calibration technique developed for ensuring stable and long-term calibrations. Absolute and relative, but also hybrid calibration methods have been developed. More recently, reference calibration lamps, tools traceable to NMIs standards, have proven to be robust for absolute calibration of water vapour Raman lidar to reduce systematic uncertainties and may represent a common reference for all the available systems.  

Activities within GAIA-CLIM related to this gap

GAIA-CLIM will address this gap as part of WP2.

Gap remedy(s)

Remedy #1

Specific remedy proposed

GAIA-CLIM WP2 deals with this technique in cooperation with ACTRIS-2 WP2. At a few stations a comparison among different methods (absolute and relative) will be investigated in order to provide a set of specific recommendations for the solutions how to implement in a systematic way, and about the uncertainties these solutions may imply in regard to the monitoring of water vapour in the whole troposphere and in the UT/LS.

Measurable outcome of success

Success would be, for example, if long term comparison between Raman lidar water vapour measurements and another traceable reference measurement technique (e.g. GRUAN radiosondes) would be compared over long term showing a reduction in the lidar calibration uncertainty using absolute techniques.  Evidences of this improvement have been reported in literature but comparison over longer time period have been not yet reported.

Achievable outcomes

Implementation of the best calibration standard identified within GAIA-CLIM WP2 in GRUAN and NDACC.

Technological / organizational viability: high. 

Indicative cost estimate: low (<1 million).  The cost of this lamp and of their operational use on a systematic basis is limited and affordable (less than 10k Euros per year), and therefore its implementation and use on a large scale is sustainable.


The proposed remedy will dramatically improve the traceability of water vapour Raman lidar measurements and data consistency at the global scale, and will help to manage any change in the system.


This is not clear yet. The time frame depends on the adoption of the approach and effort required by the networks to operate Raman lidars for measuring water vapour.

Gap risks to non-resolution

Identified future risk / impact

Probability of occurrence if gap not remedied

Downstream impacts on ability to deliver high quality services to science / industry / society

Lack of harmonization between water vapor Raman lidar collected at the global scale.


Inhomogeneities affecting water CDR in the troposphere and stratosphere to detect a signal of climate change.

Bias in the intercomparison or in the retrieval of the site atmospheric state best estimate.


Biased site atmospheric state best estimate; partially compensated by potential sensor intercalibration.

Bias affecting dataset used for satellite validation.


Misinterpretation of satellite CDRs assuming the ground based measurement of water vapour lidar as the reference; partially compensated using satellite intercalibration based on GPS-RO.


Work package: