Development of time-varying global gridded <i>T</i><sub>s</sub>–<i>T</i><sub>m</sub> model for precise GPS–PWV retrieval

Abstract

Abstract. Water-vapor-weighted mean temperature, Tm, is the key variable for estimating the mapping factor between GPS zenith wet delay (ZWD) and precipitable water vapor (PWV). For the near-real-time GPS–PWV retrieval, estimating Tm from surface air temperature Ts is a widely used method because of its high temporal resolution and fair degree of accuracy. Based on the estimations of Tm and Ts at each reanalysis grid node of the ERA-Interim data, we analyzed the relationship between Tm and Ts without data smoothing. The analyses demonstrate that the Ts–Tm relationship has significant spatial and temporal variations. Static and time-varying global gridded Ts–Tm models were established and evaluated by comparisons with the radiosonde data at 723 radiosonde stations in the Integrated Global Radiosonde Archive (IGRA). Results show that our global gridded Ts–Tm equations have prominent advantages over the other globally applied models. At over 17 % of the stations, errors larger than 5 K exist in the Bevis equation (Bevis et al., 1992) and in the latitude-related linear model (Y. B. Yao et al., 2014), while these large errors are removed in our time-varying Ts–Tm models. Multiple statistical tests at the 5 % significance level show that the time-varying global gridded model is superior to the other models at 60.03 % of the radiosonde sites. The second-best model is the 1∘ × 1∘ GPT2w model, which is superior at only 12.86 % of the sites. More accurate Tm can reduce the contribution of the uncertainty associated with Tm to the total uncertainty in GPS–PWV, and the reduction augments with the growth of GPS–PWV. Our theoretical analyses with high PWV and small uncertainty in surface pressure indicate that the uncertainty associated with Tm can contribute more than 50 % of the total GPS–PWV uncertainty when using the Bevis equation, and it can decline to less than 25 % when using our time-varying Ts–Tm model. However, the uncertainty associated with surface pressure dominates the error budget of PWV (more than 75 %) when the surface pressure has an error larger than 5 hPa. GPS–PWV retrievals using different Tm estimates were compared at 74 International GNSS Service (IGS) stations. At 74.32 % of the IGS sites, the relative differences of GPS–PWV are within 1 % by applying the static or the time-varying global gridded Ts–Tm equations, while the Bevis model, the latitude-related model and the GPT2w model perform the same at 37.84 %, 41.89 % and 29.73 % of the sites. Compared with the radiosonde PWV, the error reduction in the GPS–PWV retrieval can be around 1–2 mm when using a more accurate Tm parameterization, which accounts for around 30 % of the total GPS–PWV error.