An ERA5‐Based Model for Estimating Tropospheric Delay and Weighted Mean Temperature Over China With Improved Spatiotemporal Resolutions

Abstract

Tropospheric delay is an important error source in Global Navigation Satellite System (GNSS) positioning and can also be used in water vapor monitoring. Many models have been built to correct tropospheric delays or to convert zenith wet delays to precipitable water vapor. However, these models suffer from limited resolutions (spatial resolution lower than 1°and temporal resolution lower than 6 hr), which affects their performance. The release of European Centre for Medium-Range Weather Forecasts ReAnalysis 5 (ERA5) provides the opportunity to lift this limit. In this study, we use the ERA5 hourly 0.5°× 0.5°data to build a new model over China, which integrates tropospheric delay correction for GNSS positioning and weighted mean temperature calculation for GNSS meteorology. By modeling the diurnal variations of zenith hydrostatic delay, zenith wet delay, and weighted mean temperature and the seasonal variations in their lapse rates, this model has the state-of-the-art spatial resolution of 0.5°× 0.5°and temporal resolution of 1 hr. We validate this new model by the ERA5 data, the radiosonde data, and the GNSS data in comparison with the canonical GPT2w model. The results show that the new model has better accuracies in terms of root-mean-square than the GPT2w model in all parameters. Especially, the new model well captures the diurnal variations in tropospheric delay and weighted mean temperature. This new model provides accurate tropospheric delays and weighted mean temperature simultaneously, which enables GNSS receivers to measure precipitable water vapor directly and also benefits GNSS positioning.

A New Four-Layer Inverse Scale Height Grid Model of China for Zenith Tropospheric Delay Correction

“…In this study, ERA5 is used for the development and validation of the four-layer inverse scale height models, which is the latest European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis dataset, also the follow up of ERA-Interim that has been wildly utilized in the field of meteorology over the past decade [25]. Compared with ERA-Interim, ERA5 has incorporated a higher gridded spatial resolution of 0.25°× 0.25° and temporal resolution of 1 hour [26], which makes it possible to describe a more detailed spatial distribution of physical parameters and to analyze its diurnal and semidiurnal variations [14]. In this study, we adopted the gridded data from ERA5 over China, of which the scope is 0°-55°, 70°-135°.…”

“…For covering China, the parameters were estimated at more than 50 thousand grids with a spatial resolution of 0.25°× 0.25°. With the established four-layer inverse scale height grid model, the 1/ at any time and any grid points can be calculated with equation (14). Then, the inverse scale height at any location can be determined with 1/ at four surrounding grids with the bilinear interpolation method.…”

“…Recently, several empirical models without the need for meteorological parameters have been developed. These empirical models, including GPT [6][7][8], UNB [9,10], EGNOS [11], IGGtrop [12,13] and Ctrop [14], are developed with the reanalysis atmospheric dataset and are expressed as a function of location and time. Although these newly developed models can provide a good priori value in the estimation of the ZTD, their accuracy is still not good enough and an estimation of a correction to this priori value is still needed.…”

“…The height correction method can be categorized into the following two types: the physics-based approach [6][7][8] and the exponential decay function [13,14,21], Zhang et al [22] utilized real-time GNSS network stations and the IGGtrop model [12,13], which employs an exponential function to implement the height correction and generates the gridded tropospheric product (GTP) over China. Lou et al [23] developed a new inverse scale height model based on atmospheric reanalysis data to achieve the height correction.…”

A Regional Model for Predicting Tropospheric Delay and Weighted Mean Temperature in China Based on GRAPES_MESO Forecasting Products

“…[20,21]. The latter directly model the tropospheric delay according to its temporal characteristics, including the IGGtrop models [5,22], the GZTD models [23,24], the CTrop model [25], etc. [9,26].…”