The effect of data sources on calculating mean temperature and integrated water vapor in Iran

Abstract

The weighted mean temperature ($T_m$) plays a crucial role in calculating Precipitable Water Vapor (PWV) and integrated water vapor (IWV) using Global Navigation Satellite Systems (GNSS) techniques. Currently, the primary sources for meteorological parameters are radiosonde measurements and Numerical Weather Models (NWMs). This study focuses on assessing the influence of different data sources on the computation of $T_m$ and IWV in Iran. The investigation involved comparing several datasets: ERA5 numerical data with spatial resolutions of 0.125° and 2.5° (ERA5 0.125, ERA5 2.5), ERA-Interim, NCEP numerical data and $T_m$ results derived from the GPT3 model. Validation of the results utilized data from 12 radiosonde stations situated across Iran. In addition, the precision of the IWV parameter was evaluated by utilizing measurements from the only available IGS station in the region, situated in Tehran. The results revealed that ERA5 0.125 exhibited superior accuracy in $T_m$ estimation compared with the other datasets, showing a discrepancy of approximately 1–2 K. In contrast, the GPT3 model displayed an accuracy of about 3 K. Analysing the results across different months of the year revealed elevated root mean square error (RMSE) values during warmer months, with little variability based on station height in the region for the four datasets. Regarding IWV, the ERA5 0.125 dataset outperformed the other three datasets, demonstrating an accuracy of about 0.07 kg m⁻². Notably, RMSE values during summer were approximately 50% higher compared with the annual RMSE.