Michal, Kačmařík ; Douša, Jan ; Dick, Galina ; Zus, Florian ; Brenot, Hugues ; Möller, Gregor ; Pottiaux, Eric ; Kapłon, Jan ; Hordyniec, Paweł ; Václavovic, Pavel ; Morel, Laurent

published in Atmos. Meas. Tech., 10, pp. 2183-2208 (2017)

Abstract: An extensive validation of line-of-sight tropospheric slant total delays (STD) from Global Navigation Satellite Systems (GNSS), ray tracing in numerical weather prediction model (NWM) fields and microwave water vapour radiometer (WVR) is presented. Ten GNSS reference stations, including collocated sites, and almost 2 months of data from 2013, including severe weather events were used for comparison. Seven institutions delivered their STDs based on GNSS observations processed using 5 software programs and 11 strategies enabling to compare rather different solutions and to assess the impact of several aspects of the processing strategy. STDs from NWM ray tracing came from three institutions using three different NWMs and ray-tracing software. Inter-techniques evaluations demonstrated a good mutual agreement of various GNSS STD solutions compared to NWM and WVR STDs. The mean bias among GNSS solutions not considering post-fit residuals in STDs was −0.6 mm for STDs scaled in the zenith direction and the mean standard deviation was 3.7 mm. Standard deviations of comparisons between GNSS and NWM ray-tracing solutions were typically 10 mm ± 2 mm (scaled in the zenith direction), depending on the NWM model and the GNSS station. Comparing GNSS versus WVR STDs reached standard deviations of 12 mm ± 2 mm also scaled in the zenith direction. Impacts of raw GNSS post-fit residuals and cleaned residuals on optimal reconstructing of GNSS STDs were evaluated at inter-technique comparison and for GNSS at collocated sites. The use of raw post-fit residuals is not generally recommended as they might contain strong systematic effects, as demonstrated in the case of station LDB0. Simplified STDs reconstructed only from estimated GNSS tropospheric parameters, i.e. without applying post-fit residuals, performed the best in all the comparisons; however, it obviously missed part of tropospheric signals due to non-linear temporal and spatial variations in the troposphere. Although the post-fit residuals cleaned of visible systematic errors generally showed a slightly worse performance, they contained significant tropospheric signal on top of the simplified model. They are thus recommended for the reconstruction of STDs, particularly during high variability in the troposphere. Cleaned residuals also showed a stable performance during ordinary days while containing promising information about the troposphere at low-elevation angles.

DOI: 10.5194/amt-10-2183-2017
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