The quantum spin Hall effect and topological insulators Physics Today 63, 33 (2010); https://doi

No abstract

Abstract. Surface pressure is a necessary meteorological variable for the accurate determination of integrated water vapor (IWV) using Global Navigation Satellite System (GNSS). The lack of pressure observations is a big issue for the conversion of historical GNSS observations, which is a relatively new area of GNSS applications in climatology. Hence the use of the surface pressure derived from either a blind model (e.g., Global Pressure and Temperature 2 wet, GPT2w) or a global atmospheric reanalysis (e.g., ERAInterim) becomes an important alternative solution. In this study, pressure derived from these two methods is compared against the pressure observed at 108 global GNSS stations at four epochs (00:00, 06:00, 12:00 and 18:00 UTC) each day for the period 2000-2013. Results show that a good accuracy is achieved from the GPT2w-derived pressure in the latitude band between −30 and 30 • and the average value of 6 h root-mean-square errors (RMSEs) across all the stations in this region is 2.5 hPa. Correspondingly, an error of 5.8 mm and 0.9 kg m −2 in its resultant zenith hydrostatic delay (ZHD) and IWV is expected. However, for the stations located in the mid-latitude bands between −30 and −60 • and between 30 and 60 • , the mean value of the RMSEs is 7.3 hPa, and for the stations located in the high-latitude bands from −60 to −90 • and from 60 to 90 • , the mean value of the RMSEs is 9.9 hPa. The mean of the RMSEs of the ERAInterim-derived pressure across at the selected 100 stations is 0.9 hPa, which will lead to an equivalent error of 2.1 mm and 0.3 kg m −2 in the ZHD and IWV, respectively, determined from this ERA-Interim-derived pressure. Results also show that the monthly IWV determined using pressure from ERAInterim has a good accuracy − with a relative error of better than 3 % on a global scale; thus, the monthly IWV resulting from ERA-Interim-derived pressure has the potential to be used for climate studies, whilst the monthly IWV resulting from GPT2w-derived pressure has a relative error of 6.7 % in the mid-latitude regions and even reaches 20.8 % in the highlatitude regions. The comparison between GPT2w and seasonal models of pressure-ZHD derived from ERA-Interim and pressure observations indicates that GPT2w captures the seasonal variations in pressure-ZHD very well.

Abstract. The Global Positioning System (GPS) is a powerful atmospheric observing system for determining precipitable water vapour (PWV). In the detection of PWV using GPS, the atmospheric weighted mean temperature (T m ) is a crucial parameter for the conversion of zenith tropospheric delay (ZTD) to PWV since the quality of PWV is affected by the accuracy of T m . In this study, an improved voxel-based T m model, named GWMT-D, was developed using global reanalysis data over a 4-year period from 2010 to 2013 provided by the United States National Centers for Environmental Prediction (NCEP). The performance of GWMT-D was assessed against three existing empirical T m models -GTm-III, GWMT-IV, and GTm_N -using different data sources in 2014 -the NCEP reanalysis data, surface T m data provided by Global Geodetic Observing System and radiosonde measurements. The results show that the new GWMT-D model outperforms all the other three models with a root-meansquare error of less than 5.0 K at different altitudes over the globe. The new GWMT-D model can provide a practical alternative T m determination method in real-time GPS-PWV remote sensing systems.