Articles | Volume 9, issue 1
Research article
18 Jan 2016
Research article |  | 18 Jan 2016

The uncertainty of the atmospheric integrated water vapour estimated from GNSS observations

T. Ning, J. Wang, G. Elgered, G. Dick, J. Wickert, M. Bradke, M. Sommer, R. Querel, and D. Smale

Abstract. Within the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) there is a need for an assessment of the uncertainty in the integrated water vapour (IWV) in the atmosphere estimated from ground-based global navigation satellite system (GNSS) observations. All relevant error sources in GNSS-derived IWV are therefore essential to be investigated. We present two approaches, a statistical and a theoretical analysis, for the assessment of the uncertainty of the IWV. The method is valuable for all applications of GNSS IWV data in atmospheric research and weather forecast. It will be implemented to the GNSS IWV data stream for GRUAN in order to assign a specific uncertainty to each data point. In addition, specific recommendations are made to GRUAN on hardware, software, and data processing practices to minimise the IWV uncertainty. By combining the uncertainties associated with the input variables in the estimations of the IWV, we calculated the IWV uncertainties for several GRUAN sites with different weather conditions. The results show a similar relative importance of all uncertainty contributions where the uncertainties in the zenith total delay (ZTD) dominate the error budget of the IWV, contributing over 75 % of the total IWV uncertainty. The impact of the uncertainty associated with the conversion factor between the IWV and the zenith wet delay (ZWD) is proportional to the amount of water vapour and increases slightly for moist weather conditions. The GRUAN GNSS IWV uncertainty data will provide a quantified confidence to be used for the validation of other measurement techniques.

Short summary
Integrated water vapour (IWV) obtained from GNSS is to be developed into a GRUAN data product. In addition to the actual measurement, this data product needs to provide an estimate of the measurement uncertainty at the same time resolution as the actual measurement. The method developed in the paper fulfils the requirement by assigning a specific uncertainty to each data point. The method is also valuable for all applications of GNSS IWV data in atmospheric research and weather forecast.