Developing Iran's empirical zenith wet delay model (IR-ZWD)

The presence of water vapor in the lower atmosphere can introduce errors in satellite-based geodetic observations. Accurate modeling of this part of atmospheric delay is particularly challenging due to the considerable variations of water vapor. Therefore, constructing a reasonable model to predict Zenith Wet Delay (ZWD) can improve the accuracy of geodetic observations and positioning techniques. In this study, we aim at constructing a regional ZWD model for Iran and nearby regions (called the IR-ZWD model) using base functions with local support. The mode is based on the five-year outputs of the Empirical Reanalysis Fifth generation (ERA5) data with the spatial resolution of about 0.25° from 2017 to 2021. The B-spline base functions are used to effectively represent local spatial changes in the spectral domain and to decrease the number of unknown parameters. A B-spline model with the order and surface resolution of about 3 and 5 (scalar values) is found to be efficient, which has an equivalent spatial resolution of ∼0.5°. Temporal variations are accounted for by applying a constant term, along with periodic components with annual, semi-annual, 3-, and 4-monthly periods. Our results demonstrate that the proposed model has a mean Root Mean Squared Error (RMSE) of about 0.035 m within Iran, which represents an improvement of approximately 12.5% compared to the commonly used global empirical models such as GPT3w, GTrop, and HGPT2. The correlation coefficient value of 0.55 is found between IR-ZWD and ERA5 data, which is about 10% higher than that of, e.g., GPT3w and GTrop. The IR-ZWD model is also evaluated against five radiosonde stations and ZWD from the Jason-3 satellite mission. In both cases, the results indicate that IR-ZWD can reduce the RMSE and MAE values of about 10%, and it improves the correlation coefficient value about 9%.