Tibetan zenith wet delay model with refined vertical correction

Abstract

Tibet presents significant elevation changes, thus leading to extraordinary tropospheric conditions. This eventually forms complicated and diverse delays in satellite data (such as global navigation satellite system (GNSS) observations), particularly for the wet component. Such delays cause non-negligible errors in microwave-dependent techniques. As infrastructure development progresses, GNSS applications (such as real-time kinematic and unmanned aerial vehicles) require a reliable tropospheric model that works not only on the surface but also over broader operating heights to pre-correct delays. However, the existing models, even the widely used global pressure and temperature 3 (GPT3) model, exhibit low performance in Tibet due to insufficient spatiotemporal resolution and limited vertical correction capability. We thereby proposed a refined Tibetan zenith wet delay (ZWD) model (TZ) established using pressure-level ERA5 datasets with a horizontal resolution of 0.25° released by the European Centre for Medium-Range Weather Forecasts. The core of the TZ is the optimized vertical correction, i.e., the cubic polynomial with two more parameters than the commonly used exponential function, whose underlying parameters are determined by a least-squares function refined up to semidiurnal harmonics. TZ achieves ZWD estimates for an arbitrary time and height in the Tibetan region with the above structure. ERA5- and radiosonde-derived ZWDs validated the TZ performance. Validation results show that the TZ model achieved a lower bias and root-mean-square error than the GPT3 model, regardless of the surface or other height layers. It demonstrates that the TZ performs better in Tibet than the widely adopted GPT3. The required MATLAB scripts and coefficient matrix of the TZ are available at https://zenodo.org/record/7063960.