Evaluation of Precipitable Water Vapor from Five Reanalysis Products with Ground-Based GNSS Observations

Abstract

At present, the global reliability and accuracy of Precipitable Water Vapor (PWV) from different reanalysis products have not been comprehensively evaluated. In this study, PWV values derived by 268 Global Navigation Satellite Systems (GNSS) stations around the world covering the period from 2016 to 2018 are used to evaluate the accuracies of PWV values from five reanalysis products. The temporal and spatial evolution is not taken into account in this analysis, although the temporal and spatial evolution of atmospheric flows is one of the most important information elements available in numerical weather prediction products. The evaluation results present that five reanalysis products with PWV accuracy from high to low are in the order of the fifth generation of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5), ERA-Interim, Japanese 55-year Reanalysis (JRA-55), National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), and NCEP/DOE (Department of Energy) according to root mean square error (RMSE), bias and correlation coefficient. The ERA5 has the smallest RMSE value of 1.84 mm, while NCEP/NCAR and NCEP/DOE have bigger RMSE values of 3.34 mm and 3.51 mm, respectively. The findings demonstrate that ERA5 and two NCEP reanalysis products have the best and worst performance, respectively, among five reanalysis products. The differences in the accuracy of the five reanalysis products are mainly attributed to the differences in the spatial resolution of reanalysis products. There are some large absolute biases greater than 4 mm between GNSS PWV values and the PWV values of five reanalysis products in the southwest of South America and western China due to the limit of terrains and fewer observations. The accuracies of five reanalysis products are compared in different climatic zones. The results indicate that the absolute accuracies of five reanalysis products are highest in the polar regions and lowest in the tropics. Furthermore, the effects of different seasons on the accuracies of five reanalysis products are also analyzed, which indicates that RMSE values of five reanalysis products in summer and in winter are the largest and the smallest in the temperate regions. Evaluation results from five reanalysis products can help us to learn more about the advantages and disadvantages of the five released water vapor products and promote their applications.

Evaluation of Hourly PWV Products Derived From ERA5 and MERRA‐2 Over the Tibetan Plateau Using Ground‐Based GNSS Observations by Two Enhanced Models

“…Therefore, it is essential to unify the PWV values at different heights to reduce the impact of these height differences. Previous studies (Leckner et al., 1978; Li et al., 2020; Wang et al., 2020; H. Zhang et al., 2019; Zhao et al., 2020) have used the widely common empirical correction function of PWV (E‐PWVC model) to unify the PWV values of stations at different heights. However, due to the significant seasonal variations in PWV over the TP (Zhang et al., 2013), systematic errors are generated when using such a simple correction formula to adjust the PWV.…”

“…Similar investigations were later carried out over China and East Africa for ERA5 by Zhao et al (2019) and Ssenyunzi et al (2020), respectively. Wang et al (2020) evaluated the accuracies of PWV values from ERA5 and four other reanalysis products on a global scale with GNSS observations, but the temporal and spatial evolution of those values was not taken into account. In addition, Zhao and Zhou (2020) used radiosonde profiles to evaluate the MERRA2 and other PWV datasets over the TP in the context of the climatology, annual cycle and interannual variability.…”

“…A comprehensive assessment of ERA5 and MERRA‐2 PWV products has yet to be fully explored at the hourly scale over the TP with the help of numerous and reliable ground‐based GNSS observations. Moreover, in previous studies, several widely common T m models and a PWV vertical adjustment method are adopted in the comparison between reanalysis data and GNSS observations (Wang et al., 2020; H. Zhang et al., 2019; Zhao et al., 2020). However, due to the substantially undulating terrain and complex climate conditions of the TP, the uncertainties of reanalysis data set evaluation would increase when using such models in the TP.…”

Analysis of the Characteristics of Climate Change in the Ecologically Vulnerable Area of the Mu Us Dune Field under the Background of Global Warming

“…On the one hand, ERA5 has a high spatial and temporal resolution. On the other hand, ERA5 has improved its performance through more advanced assimilation methods, allowing it to absorb more recent satellite observations [24]. In this study, PWV data from 1978 to 2018 with a spatial resolution of 0.25 × 0.25 • listed in the monthly averaged dataset of ERA5 provided by ECMWF were used to analyze the overall spatial and temporal distribution of air water resources in the Mu Us dune field.…”

Evaluation of the ZWD/ZTD Values Derived from MERRA-2 Global Reanalysis Products Using GNSS Observations and Radiosonde Data

“…The results illuminated the accuracy and feasibility of computing the tropospheric delays and establishing the ZTD prediction model over Asia for navigation and positioning with ECMWF and NCEP data. Wang et al [ 30 ] evaluated the accuracies of precipitable water vapor (PWV) values from five reanalysis products. The evaluation results showed that the reanalysis products with the best PWV accuracy is the fifth generation ECMWF Reanalysis (ERA5).…”