Abstract Tropospheric lag is an important factor affecting the high-precision positioning of the Global Navigation Satellite System (GNSS) and also the basic data for GNSS atmospheric research. However, existing tropospheric delay models have some problems, such as the use of a single function for the whole atmosphere.
In this paper, a global model based on ERA5 (the fifth generation of the European Center for the Reanalysis of Medium-Range Weather Forecasts) is developed for vertical adjustment of zenith tropospheric delay (ZTD) using a piecewise function. ZTD data at 611 radiosonde stations and MERRA-2 (Second Modern Retrospective Analysis for Research and Applications) Atmospheric Reanalysis data were used to validate the reliability of the model. The Global Zenith Tropospheric Delay Piecewise (GZTD-P) model has excellent performance compared to the Global Pressure and Temperature (GPT3) model. Validated at radiosonde stations, the performance of the GZTD-P model improved by 0.96 cm (23%) relative to the GPT3 model. Validated with MERRA-2 data, the quality of the GZTD-P model improves by 1.8 cm (50%) compared to the GPT3 model, showing greater accuracy and stability. The ZTD vertical fit model with different resolutions was established to enrich the applicability of the model and speed up the tropospheric delay calculation process. By providing model parameters with different resolutions, users can choose the suitable model according to their applications.
Introduction Tropospheric lag is an important factor affecting the high precision of space technologies and also the key aspect of atmospheric scientific research (Ding, 2020; Huang et al., 2012; Li Therefore, a high-precision tropospheric delay model is beneficial for Global Navigation Satellite System (GNSS) positioning and atmospheric water vapor detection (Huang et al., 2021b; Jin & Su, 2020; Mohammed et Existing tropospheric delay models can be classified into three categories. The first is numerical weather modelling, for example the Vienna Mapping Functions (VMF) (Böhm et al., 2006) and the Potsdam Mapping Factors (PMF) (Zus et al., 2014). The second is analytical modeling with in situ meteorological observations, such as the Hopfield (1969) model, the Saastamoinen (1972) model, and the Black (1978) model. The third category includes empirical models, such as the University of New Brunswick (UNB) series models (Leandro et al., 2006, 2008), the European Geostationary Navigation Overlay Service (EGNOS) model (Penna et al. ., 2001), the TropGrid series (Krueger et al., 2004; Schüler et al., 2014), models of the Global Pressure and Temperature (GPT) series (Böhm et al., 2007, 2015; Lagler et al., 2013; Landskron et al., 2018), and the Saastamoinen + GPT3 model. and the quality of the TropGrid model is superior to that of the EGNOS model. Schuler et al. (2014) added the diurnal variation of tropospheric delay to the TropGrid model and built the TropGrid2 model. This model improves the temporal resolution of the model but ignores the semi-annual variation of the tropospheric delay. GPT3 is the latest generation model of the GPT series, which is an improved version of GPT2w, and has long been recognized as the high-precision tropospheric delay model (Ding and Chen, 2020; Sun et al., 2019). . Song and others. (2011) He built the Shao Astronomical Observatory model based on the European Center for medium -range weather forecast (ECMWF), which was improved by 60.5 % compared to the EGNOS model. To me and others. (2018) Provide a new method for simulating ZTD and building a ZTD model from non -metmatic parameters called Iggtrop_SH. This new model has improved the ZTD correction performance, especially in the northern hemisphere. Yao and others. (2016) recommended the delay form in the Zenith Troposperic (GZTD2), taking into account the daytime contrast in the delay of the troposphier. This model is validated using the International GNSS service (IGS) with the 3.9 cm Root Root box (RMS) box. Based on the atmosphere of the global geodes monitoring (GGOS), Sun et al. (2017) I developed the Zenith Toposphere Deing Sumpiped (GZTDS) with the assumption that the troposphler is a non -linear system. The average RMS of the GZTDS model, as verified with IGS data, is 3.46 cm, equivalent to the GPT2W. In recent years, the data provided by the products of reusing in the atmosphere such as Era-Interim, Era5 (the fifth generation of the European Center for Medium-range weather forecast), NCEP, or Merra-2 (retroactively analysis in the second modern era of research and applications , It was widely used to get the Tropessi delay information (Li et al., 2012, 2015; yang et al It is necessary to rely on the highly accurate and tightly spatial and temporal delay form for the Toprosfiri delay in the GNSS user site by forming information on the network to GNSS (Li et al., 2016, 2017; MA et al., 2021; et al., 2020). LI and He (2021) have achieved methods of extracting troposphere from the surface of the era. Based on realistic assumptions on the structure of the atmosphere, the complex formulas of vertical modification of pressure and PWV (equal water vapor) were proposed. Since the troposphere delay depends on the height, it differs in the heights of the different atmosphere. However, the vertical profile form for delaying a commonly used troposphere uses only a single function for the entire troposphere. Moreover, it is difficult to reflect the change in troposphere delay in terms of altitudes. Treating these restrictions in previous models, this paper has developed an ERA5 on the ERA5 vertical modification of Tropospheric Zenith using a gradual function.
Data
Radio information
Radiosonde information gives estimating meteorological boundaries in excess of 500 stations all over the planet. Radio information is acquired from the genuine estimations of meteorological sensors on sound inflatables, which have high exactness and dependability, and are generally used to really take a look at the consequences of estimation (Gui et al., 2017; Sun et al., 2019).
Air Packaging Item Information
ERA5 has included barometrical substitution information starting around 1979, which can be free. Its tension layer is partitioned into 37 sub - layers, which can give major troxavirus boundaries like temperature, strain and explicit dampness. Contrasted with information re - investigation information for the past item, Era5 can give appropriate surface boundaries and vertical profile information, and the precision of time has expanded from two hours to 60 minutes.
Merra-2 has included barometrical substitution information starting around 1980, which can be openly downloaded. The tension layer is partitioned into 42 sub - layers. (Randles et al., 2017; Molod et al., 2015).
Improvement of the GZTD-P model
To get a superior articulation of the upward side appearance of the Pinnacle postpone on the planet, the negative extravagance capabilities are frequently used to recreate the upward difference in delay (Chen et al., 2020; Yao et al., 2013, 2016). For more check of the upward change in the postponement, two focuses for network information were picked for re - examination in the environment at 0:00 UTC (Time Ponstrivation) on January 1, 2014, haphazardly. ZTD was acquired by the strategy for incorporation on various strain layers. The alleviation capability was utilized to suit the upward difference in delay and the outcomes are introduced in Figure 1. The moderation capability is communicated, as well as the strategy for coordination (Thayer, 1974), as follows. The saastamoinen model is introduced to get ZHD (Peak Hydrostatic) at the highest point of the upper tension level (Saastamoinen, 1972).
