000003193 001__ 3193
000003193 005__ 20170619102653.0
000003193 0247_ $$2DOI$$a10.5194/amt-10-2183-2017
000003193 037__ $$aSCART-2017-0031
000003193 100__ $$aMichal, Kačmařík 
000003193 245__ $$aInter-technique validation of tropospheric slant total delays
000003193 260__ $$c2017
000003193 520__ $$aAn 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.
000003193 594__ $$aSTCE
000003193 700__ $$aDouša, Jan
000003193 700__ $$aDick, Galina
000003193 700__ $$aZus, Florian
000003193 700__ $$aBrenot, Hugues 
000003193 700__ $$aMöller, Gregor 
000003193 700__ $$aPottiaux, Eric
000003193 700__ $$aKapłon, Jan 
000003193 700__ $$aHordyniec, Paweł 
000003193 700__ $$aVáclavovic, Pavel 
000003193 700__ $$aMorel, Laurent 
000003193 773__ $$c2183-2208$$pAtmos. Meas. Tech.$$v10$$y2017
000003193 8560_ $$feric.pottiaux@observatoire.be
000003193 85642 $$ahttp://www.atmos-meas-tech.net/10/2183/2017/
000003193 905__ $$apublished in
000003193 980__ $$aREFERD