Precipitation Water Vapour Variation in the East Java Region from Data CORS Using GIPSY

The Global Navigation Satellite System is being developed as an atmospheric remote sensing system through the calculation of Zenith Total Delay. The development of the Continous Operating Reference Station encourages research investigations into Zenith Tropospheric Delay with continuous data and good spatial resolution. This research studies the characteristics of spatial and temporal variations of the Zenith Wet Delay in East Jawa. The case study in East Jawa Province uses 16 Continous Operating Reference Stations. As a comparison, meteorological data from the Badan Meteorologi, Klimatologi, and Geofisika stations are used.The Zenith Total Delay and Zenith Wet Delay values from the Continous Operating Reference Station data are calculated using GIPSY 6.4 Software. The Zenith Wet Delay values are gridded using the kriging method with the size of the grids being 0,25 x 0,25. The ZWD value comparison from the Continous Operating Reference Station and meteorology data has a strong correlation with a coefficient value of 0,712. The mean of Zenith Wet Delay’s trend is increasing by about 0,712 mm/yr. The characteristics of the spatial and temporal variations of the ZWD value are influenced by the monsoon of Asia-Australian, which causes dry and rainy seasons, global phenomena such as El Nino and La Nina, rainfall, local meteorological conditions such as temperature and humidity, weather, and the topography of the stations.

Evaluation of Precipitable Water Vapor Retrieval from Homogeneously Reprocessed Long-Term GNSS Tropospheric Zenith Wet Delay and Multi-Technique

Water vapor is one of the most important greenhouse gases in the world. There are many techniques that can measure water vapor directly or remotely. In this work, we first study the Global Positioning System (GPS)- and the Global Navigation Satellite System (GLONASS)-derived Zenith Wet Delay (ZWD) time series based on 11 years of the second reprocessing campaign of International Global Navigation Satellite Systems (GNSS) Service (IGS) using 320 globally distributed stations. The amount of measurement, the local environment, and the antenna radome are shown to be the main factors that affect the GNSS ZWDs and the corresponding a posteriori formal errors. Furthermore, antenna radome is able to effectively reduce the systematic bias of ZWDs and a posteriori formal errors between the GPS- and GLONASS-based solutions. With the development of the GLONASS, the ZWD differences between the GPS- and the GLONASS-based solutions have gradually decreased to sub-mm-level after GLONASS was fully operated. As the GPS-based Precipitable Water Vapor (PWV) is usually used as the reference to evaluate the other PWV products, the PWV consistency among several common techniques is evaluated, including GNSSs, spaceborne sensors, and numerical products from the European Center for Medium-Range Weather Forecasts (ECMWF). As an example of the results from a detailed comparison analysis, the long-term global analysis shows that the PWV obtained from the GNSS and the ECMWF have great intra-agreements. Based on the global distribution of the magnitude of the PWV and the PWV drift, most of the techniques showed superior agreement and proved their ability to do climate research. With a detailed study performed for the ZWDs and PWV on a long-term global scale, this contribution provides a useful supplement for future research on the GNSS ZWD and PWV.

Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points

Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristics of water vapor pressure, temperature, and pressure, which are the basic components of the refractive index, a method for retrieving atmospheric refractivity profile based on GNSS (Global Navigation Satellite System) and meteorological sensor measurement is introduced and investigated in this study. The variation of the correlation between zenith wet delay and water vapor pressure is investigated and analyzed in detail. The partial pressure profiles of water vapor are retrieved with relevance vector machine method based on tropospheric zenith wet delay calculated by single ground-based GPS (Global Positioning System) receiver. The atmospheric temperature and pressure is calculated with the least square method, which is used to fit the coefficients of the polynomial model based on a large number of historical meteorological radiosonde data of local stations. By combining the water vapor pressure profile retrieving from single ground-based GPS and temperature and pressure profile from reference model, the refractivity profile can be obtained, which is compared to radiosonde measurements. The comparison results show that results of the proposed method are consistent with the results of radiosonde. By using over ten years’ (through 2008 to 2017) historical radiosonde meteorological data of different months at China Big-Triangle Points, i.e., Qingdao, Sanya, Kashi, and Jiamusi radiosonde stations, tropospheric radio refractivity profiles are retrieved and modeled. The comparison results present that the accuracies of refractivity profile of the proposed method at Qingdao, Sanya, Kashi, and Jiamusi are about 5.48, 5.63, 3.58, and 3.78 N-unit, respectively, and the annual average relative RMSE of refractivity at these stations are about 1.66, 1.53, 1.49, and 1.23%, respectively.

Monitoring and prediction of hurricane tracks using GPS tropospheric products

We have reconstructed integrated water vapor (IWV) using the zenith wet delays to track the properties of hurricanes and explore their spatial and temporal distributions estimated from 922 GPS stations. Our results show that a surge in GPS-derived IWV occurred at least six hours prior to the landfall of two major hurricanes (Harvey and Irma) that struck the Gulf and East Coasts of the USA in 2017. We observed enhanced IWV, in particular, for the two hurricanes landfall locations. The observed variations exhibit a correlation with the precipitation value constructed from GPM/IMERG satellite mission coinciding with hurricane storm front passage. We used GPS-IWV data as inputs for spaghetti line plots for our path predictions, helping us predict the paths of Hurricanes Harvey and Irma. Hence, a directly estimable zenith wet delay sourced from GPS that has not been previously reported can serve as an additional resource for improving the monitoring of hurricane paths.

Comparison of Tropospheric Zenith Wet Delay from VLBI and GNSS Estimations

<p>Tropospheric delay is one of the major error sources for space geodetic techniques such as Very Long Baseline Interferometry (VLBI) and Global Navigation Satellite System (GNSS). In this study, we compared the agreement of tropospheric zenith wet delay (ZWD) seasonal variations derived from VLBI and GNSS observations at 8 stations that are located at all around the globe. We have analysed time series of 8 years, starting in 2012 until end of 2019. Results show that VLBI_ZWD present clear seasonal variations which depend on the location of each station, in the tropics the variability is more pronounced than in mid-latitudes or polar regions. Furthermore, the VLBI_ZWD also shows a reasonably good agreement with seasonal fit model. When comparing zenith wet delays derived from co-located GNSS and VLBI stations at  cut-off elevation angle, they agree quite well, which is proved by the high correlation coefficients, varying from 0.6 up to 0.95. The biases between the techniques are in mm level and standard errors of the whole time series are in few centimetres.</p>

An ERA5-Based Hourly Global Pressure and Temperature (HGPT) Model

The Global Navigation Satellite System (GNSS) meteorology contribution to the comprehension of the Earth’s atmosphere’s global and regional variations is essential. In GNSS processing, the zenith wet delay is obtained using the difference between the zenith total delay and the zenith hydrostatic delay. The zenith wet delay can also be converted into precipitable water vapor by knowing the atmospheric weighted mean temperature profiles. Improving the accuracy of the zenith hydrostatic delay and the weighted mean temperature, normally obtained using modeled surface meteorological parameters at coarse scales, leads to a more accurate and precise zenith wet delay estimation, and consequently, to a better precipitable water vapor estimation. In this study, we developed an hourly global pressure and temperature (HGPT) model based on the full spatial and temporal resolution of the new ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The HGPT model provides information regarding the surface pressure, surface air temperature, zenith hydrostatic delay, and weighted mean temperature. It is based on the time-segmentation concept and uses the annual and semi-annual periodicities for surface pressure, and annual, semi-annual, and quarterly periodicities for surface air temperature. The amplitudes and initial phase variations are estimated as a periodic function. The weighted mean temperature is determined using a 20-year time series of monthly data to understand its seasonality and geographic variability. We also introduced a linear trend to account for a global climate change scenario. Data from the year 2018 acquired from 510 radiosonde stations downloaded from the National Oceanic and Atmospheric Administration (NOAA) Integrated Global Radiosonde Archive were used to assess the model coefficients. Results show that the GNSS meteorology, hydrological models, Interferometric Synthetic Aperture Radar (InSAR) meteorology, climate studies, and other topics can significantly benefit from an ERA5 full-resolution model.

Improving GNSS Zenith Wet Delay Interpolation by Utilizing Tropospheric Gradients: Results from the dense station network in Japan

<p>In a recent study we have shown how GNSS Zenith Wet Delay (ZWD) interpolation and therefore Integrated Water Vapor (IWV) maps can be improved by utilizing tropospheric gradients (Zus et al., 2019). For a station configuration with an average distance of 50 km in Germany and a period of two months in the summer 2013 we demonstrated an average improvement of 10% in interpolated ZWDs. We extended this work by a new study. It differs from the previous one in two respects: (1) we consider more than 1,200 stations with an average distance of 20 km in Japan and (2) ZWDs and tropospheric gradients are taken from the Nevada Geodetic Laboratory (NGL) (Blewitt et al., 2018). We present results and propose future directions. For example, we may consider a mixed approach where ZWDs and tropospheric gradients from a numerical weather prediction model are utilized as well.</p><p>Zus, F.; Douša, J.; Kačmařík, M.; Václavovic, P.; Balidakis, K.; Dick, G.; Wickert, J. Improving GNSS Zenith Wet Delay Interpolation by Utilizing Tropospheric Gradients: Experiments with a Dense Station Network in Central Europe in the Warm Season. Remote Sens. 2019, 11, 674. </p><p>Blewitt, G., W. C. Hammond, and C. Kreemer (2018), Harnessing the GPS data explosion for interdisciplinary science, EOS, 99, https://doi.org/10.1029/2018EO104623.</p>