Validation of low-cost receiver derived tropospheric products against ERA5 reanalysis

The aim of the study is to investigate the quality of the tropospheric estimates obtained with the use of the latest dual-frequency low-cost GNSS receivers. We aim to verify if the low-cost receivers may provide information on the parameters that describe the state of the troposphere with accuracy and reliability close to that of high-grade receivers. In this way, we address a scientific question on the potential usability of such receivers for climate applications. We investigate selected GNSS tropospheric estimates such as zenith tropospheric delays (ZTDs) and horizontal gradients. ZTD accuracy is validated in comparison to ERA5, which is the fifth generation reanalysis for the global climate and weather produced by European Centre for Medium-Range Weather Forecasts (ECMWF).

The experiment is based on GNSS data collected during two measurement campaigns. The 1^st campaign was carried out over three days in the winter 2020; the 2^nd one was held over three days in the summer 2021. Three collocated stations equipped with u-blox ZED F9P receivers and one station with a high-grade Trimble Alloy receiver were used. Receivers were connected to two different types of GNSS antennas: a surveying-grade Leica AR10 and a patch ANN-MB antenna. Collected GNSS data were processed using Bernese GNSS Software v.5.2 in Precise Point Positioning (PPP) mode based on dual-frequency ionosphere-free model.

The presented results confirm that the tropospheric solutions based on low-cost receivers data can achieve high accuracy. Low-cost equipment provides tropospheric parameters with precision and reliability only slightly lower than that of high-grade one. We also show that an application of a surveying-grade antenna to a low-cost receiver may noticeably enhance the accuracy of the tropospheric estimates derived with such receivers. Finally, validation against the ERA5 climate reanalysis confirms that both sets can provide high-quality, accurate tropospheric estimates, which can be further used in climate applications.